5,020 results on '"*AMBIGUITY"'
Search Results
2. eWOM Information Richness and Online User Review Behavior: Evidence from TripAdvisor
- Author
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Xueyu Liu, Jie Lin, Xiaoyan Jiang, Tingzhen Chang, and Haowen Lin
- Subjects
information richness ,cross–cultural ,interactive knowledge innovation ,online eWOM platform ,information ambiguity ,Business ,HF5001-6182 - Abstract
The growing number of online users commenting on review platforms has fueled the development of electronic word–of–mouth (eWOM). At the same time, merchants have improved their requirements for the length and frequency of online reviews. However, few studies have examined the updating mechanism of online reviews length and frequency from the perspective of businesses. This study explores the relationship between online commenting platform users and eWOM and examines how eWOM information richness affects online user review behavior. We used media richness theory (MRT) to quantify the information richness of eWOM content (linguistic, textual, and photographical) to build an empirical framework. For the research data, we used advanced big data analytics to retrieve and analyze TripAdvisor data on restaurant services in nine major tourist destinations, the United States, Mexico, and mainland Europe (including UK, Spain, Netherlands, etc.), over a long period of time. Based on >10 million eWOM, this study used multiple regression to examine the impact of eWOM information richness on online user review behavior, considering the moderating effect of information ambiguity. Our research results show that content information richness positively affects online user review behavior, increasing their frequency and length. Information ambiguity play a moderating role that strengthens this relationship. This supports our theoretical hypothesis. Finally, for greater applicability and reliability, we conducted a comparative study on the degree of differences in the relationship between eWOM and users based on different cultural backgrounds across countries.
- Published
- 2024
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3. Mediating role of work stressors between auditor knowledge-sharing activities and job satisfaction in Indonesian small audit firms
- Author
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Muhammad Subhan and Suyanto Suyanto
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hindrance stressor ,job satisfaction ,knowledge sharing ,work ambiguity ,work overload ,Business ,HF5001-6182 - Abstract
Audit businesses encourage their auditors to conduct remote audits during the COVID-19 pandemic. Therefore, auditors from small audit firms exchange their skills, viewpoints, and experiences through internet forums. The purpose of this study is to investigate how auditors’ knowledge-sharing activities through a social media community based on the reciprocity standard can prevent stress caused by work stressors, which affect their job satisfaction. The relationship between knowledge-sharing activities, work stressors, and job satisfaction was examined using the partial least squares structural equation modelling (PLS-SEM) method. This survey includes 151 auditors from 27 Indonesian small audit firms. The findings revealed that active involvement in knowledge sharing activities through social media groups boosts auditor motivation by raising good feelings when confronted with work conflict (β = 0.334, p < 0.001) and lowering negative emotions when confronted with work ambiguity (β = –0.407, p < 0.001) and work overload (β = –0.372, p < 0.001). However, only minimizing the negative feelings of work ambiguity (β = –0.331, p < 0.001) and work overload (β = –0.277, p < 0.001) can improve job satisfaction. Furthermore, work ambiguity (β = 0.135, p < 0.001) and overload (β = 0.103, p < 0.01) totally mediate the association between knowledge–sharing activities and auditor job satisfaction. Auditors set the norm for social media reciprocity by sharing their knowledge and expertise with others. As a result, the auditor can reduce negative emotions when facing hindrance stressors, thereby increasing job satisfaction. AcknowledgmentThis research was sponsored by Lembaga Pengelola Dana Pendidikan (LPDP).
- Published
- 2023
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4. Stress management intervention program for teaching staff at private engineering colleges in Tamil Nadu to improve their job performance and well-being
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R. Dhaneesh and V.S. Iswarya
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Workload ,Role ambiguity ,Salary ,Social support ,Intervention programs ,Business ,HF5001-6182 ,Finance ,HG1-9999 - Abstract
Purpose – Stress at workplace is quite common in all sorts of environment. It can be occurring when the demand in the job does not match with the requirements; thereby, it affects their performance. The study was conducted with the aim to identify the major factors that induce stress for teaching professionals in private engineering colleges and its impact towards job performance. From the observation and discussion, it was found that Workload, Working Hour, Salary, Role Ambiguity and Lack of Social Support are the major factors for stress. Design/methodology/approach – A structured questionnaire was framed with the help of stress-causing factors and their effect on job performance. In addition to this, a few questions were asked related to stress management intervention program. The survey was conducted with 370 respondents, while further analysis was carried out with the filled 260 respondent’s data using descriptive statistics, correlation, regression, ANOVA and SEM. Findings – The study reveals that workload plays a significant role in stress whereas other factors are consequently lower than that. Also, the primary-level intervention programs are more effective than secondary-level intervention programs to reduce the stress level of stressors. Originality/value – The paper was originally done by collecting data from the staff.
- Published
- 2023
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5. New Ways of Working in Academia: Maneuvering in and with Ambiguity in Workspace Design Processes
- Author
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Grégory Jemine, François Pichault, and Christophe Dubois
- Subjects
new ways of working ,ambiguity ,academic workspaces ,organizational change ,workspace design ,Management. Industrial management ,HD28-70 ,Business ,HF5001-6182 - Abstract
As a result of growing financial pressures and changing space demands, universities are increasingly looking to modernize and rationalize their workspaces through projects of New Ways of Working (NWoW). So far, extant research has mostly investigated the managerial construct of NWoW and its outcomes on organizational members, leaving the design process leading NWoW to be implemented in local contexts understudied. By contrast, the present study sets out to redefine NWoW as open-ended projects of organizational change that are unavoidably ambiguous and conflictual, hence seeking to overcome the tendency to conceal tensions arising at early stages of the change process under the abstract black-box of ‘resistance to change’. It is shown that ambiguity, simultaneously understood as an organizational problem causing tensions and as a rhetorical resource enabling collective action, plays a major role in the design process of such equivocal projects. This paper further advances our understanding of ambiguity as a multifaceted concept to bridge between individual rationalities and collective decision-making in the course of complex design processes.
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- 2022
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6. The impulsive online shopper: effects of COVID-19 burnout, uncertainty, self-control, and online shopping trust
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Shunying Zhao, Qiang Yang, Hohjin Im, Baojuan Ye, Yadi Zeng, Zhinan Chen, Lu Liu, and Dawu Huang
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Impulse buying ,COVID-19 burnout ,Self-control ,Uncertainty ,Ambiguity ,Trust ,Business ,HF5001-6182 ,Finance ,HG1-9999 - Abstract
Abstract Consumerism during the COVID-19 pandemic has been characterized by impulsive buying. Using the theoretical lens of uncertainty avoidance and ego-depletion to identify the mediating mechanisms and moderating factors for online impulse buying, we surveyed young consumers across two relevant periods for high consumerism—the week preceding the 2021 Chinese Spring Festival (Study 1; February 4–9, 2021, n = 1495) and the weeks during and after the festival (Study 2; February 12 to March 2, 2021, n = 923). Perception of COVID-19 variant uncertainty was both directly and indirectly (via online shopping trust) positively associated with online impulse buying. COVID-19 burnout was consistently indirectly associated with online impulse buying via self-regulation and self-appraised impulsivity but inconsistently directly associated. Self-regulation was surprisingly positively associated with online impulse buying, possibly reflecting evidence of already depleted resources from prolonged regulatory exertion among high self-regulators. Self-appraised impulsivity negatively interacted with perception of COVID-19 variant uncertainty, suggesting that as trait impulsivity increases, individuals are less incentivized by peripheral drivers of online impulse buying.
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- 2022
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7. Safety Stock Optimization under Lead Time Ambiguity
- Author
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Chong Keun Kim, Pansoo Kim, and Joon Yeop Kwon
- Subjects
ambiguity ,safety stock ,stochastic lead time ,Business ,HF5001-6182 ,Finance ,HG1-9999 - Abstract
Purpose: The purpose of this study is to investigate how ambiguity faced by the risk-neutral manager affects the firm’s optimal level of safety stock. Design/methodology/approach: This study adopts the traditional model of Arrow et al. (1951) and employ a manager who has multiple prior beliefs about the probability distribution of the lead time. Findings: This study finds that facing lead time ambiguity, the manager becomes more conservative when choosing the optimal stock level to hold and the amount of safety stock. Research limitations/implications: The future research would consider a risk-averse manager who could be compensated or punished as a result of stock management. Then the future research would examine the interactive effects of the manager’s risk aversion and lead time ambiguity on the optimal safety stock level. Originality/value: This would be the first study that investigates the effects of ambiguity on the level of safety stock.
- Published
- 2022
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8. Goal clarity on the relationship between government ownership and financial performance of the listed companies in Kenya and Tanzania
- Author
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Musa P. Ngilisho, Neema G. Mori, and Ernest G. Kitindi
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financial performance ,goal ambiguity ,goal clarity ,goal-setting ,government ownership ,Business ,HF5001-6182 ,Management. Industrial management ,HD28-70 - Abstract
This study investigates the moderating effect of company goal clarity on the relationship between government ownership and financial performance of the listed companies in Kenya and Tanzania. The results show that government ownership holds an average of 6% of the ownership stakes and a maximum of 74% in the selected listed companies. Furthermore, it is found that, listed companies that engage in goal-setting, pursue an average of 5 company goals concurrently, and a maximum of 13. Moreover, government ownership is found to be negatively related to financial performance, while a decrease in company goal clarity is both positively and negatively related to financial performance, for the Tobin’s q and the risk-adjusted ROA models, respectively. The implication is that, as government ownership in emerging economies is endowed with relatively more skills and resources compared to other owners in listed companies, it can effectively pursue a relatively higher number of company goals. The results also suggest that a decrease in goal clarity has a negative moderating effect on the relationship between government ownership and financial performance, whereby the moderating effect reduces the magnitude of the negative effects of government ownership on financial performance, up to an optimal point of seven company goals. The decrease of company goal clarity, which mainly emanates from the concurrent pursuit of all company goals plus the social welfare ones, reduces the negative effects of the ownership on financial performances, contrary to the assertions made in the goal-setting theory.
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- 2022
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9. Examining employees creativity in commercial bank of Ethiopia Woldia branches
- Author
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Erstu Tarko Kassa
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Employees’ creativity ,Autonomy ,Supervisors support ,Job complexity ,Role ambiguity ,Self-efficacy ,Business ,HF5001-6182 ,Commercial geography. Economic geography ,HF1021-1027 - Abstract
Abstract Creativity is the ability to combine unique ideas, identifying new ways, systems and products in the organization. Creative workers in the organization can transform their organization to higher level by inventing new systems. This study tried to examine employees’ creativity in the bank at commercial bank of Ethiopia Woldia branches. The researcher used an institutional-based cross-sectional design and followed a mixed research approach. The researcher applied a census method to participate in respondents from four branches, which were on duty 182 employees in commercial bank of Ethiopia. The collected data were analyzed by using multiple regression method after proving the quality of the data. The study finding revealed that autonomy, supervisors’ support and role ambiguity significantly affects the creativity of employees in the workplace. The remaining variables self-efficacy and job complexity have no statistically significant effect on employees’ creativity in the bank.
- Published
- 2021
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10. Peran Ambideksteritas Pembelajaran Sebagai Pemediasi Pada Hubungan Kapabilitas Berpikir Desain Terhadap Kapabilitas Inovasi: Studi Pada Perusahaan Startup
- Author
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Muhammad Nur Fietroh and Ika Fitriyani
- Subjects
design thinking capability ,learning ambiguity ,corporate innovation capability ,Business ,HF5001-6182 - Abstract
Penelitian ini bertujuan untuk menguji pengaruh kapabilitas berpikir desain terhadap ambideksteritas pembelajaran, kemudian menguji pengaruh ambideksteritas pembelajaran terhadap kapabilitas inovasi perusahaan. Penelitian ini juga bertujuan untuk menguji pengaruh ambideksteritas pembelajaran pada kapabilitas berpikir desain dan kapabilitas inovasi perusahaan. Penelitian ini dilakukan pada 164 perusahaan start-up di Yogyakarta, Provinsi Daerah Istimewa Yogyakarta (DIY) dan Kota lainnya. Hasil temuan penelitian mengkonfirmasi teori pandangan berbasis pengetahuan dan teori pembelajaran organisasi. Secara empiris menunjukkan bahwa kapabilitas berpikir desain berpengaruh positif signifikan pada ambideksteritas pembelajaran, ambideksteritas pembelajaran berpengaruh positif signifikan pada kapabilitas inovasi perusahaan. Hasil penelitian menunjukkan juga bahwa ambideksteritas pembelajaran memiliki pengaruh mediasi parsial pada kapabilitas berpikir desain dan kapabilitas inovasi perusahaan.
- Published
- 2021
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11. Why fuel economy fraud happened in the Japanese automotive industry?
- Author
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Ayako Aizawa
- Subjects
fuel economy ,organizational corruption ,competition index ,ambiguity ,Business ,HF5001-6182 ,Management. Industrial management ,HD28-70 - Abstract
Fuel economy competition has heated up as a result of the oil crises of the 1970s, the environmental issues occurring since the 1990s, and the Japanese government’s economic policies, so that fuel economy has become a key competition index. However, for engineers who measure fuel economy, it is (i) a vague and unstable metric that fluctuates because of a number of factors and (ii) a quality that does not affect safety and so is not subject to recall. Competitive pressure regarding fuel economy led to arbitrary measurements. This eventually became normalized, and since 2016, cases of organizational corruption in the Japanese automotive industry have been uncovered one after another.
- Published
- 2020
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12. Kepuasan Kerja sebagai Variabel Mediasi pada Pengaruh Ketidakjelasan Peran terhadap Kinerja Pegawai
- Author
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Riska Susanti and Rahmi Fahmy
- Subjects
individual performance ,job satisfaction ,role ambiguity ,Business ,HF5001-6182 - Abstract
The purpose of this research is to analyze the effect of role ambiguity on employee performance mediated by job satisfaction. The population in this research is ASN employees (State Civil Servants) at the Puskesmas located in Padang Panjang City. Samples of this research are 108 people that have taken with a purposive sampling technique. The results of this research show: 1) Role ambiguity has a negative and significant effect on employee performance. 2) Role Ambiguity has a negative and significant effect on job satisfaction felt by employees, and 3) Job satisfaction has a positive and significant effect on employee performance, and 4) Job satisfaction acts as a mediating variable of the unclear role on employee performance
- Published
- 2020
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13. On the (In)Security of ElGamal in OpenPGP
- Author
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Bertram Poettering, Luca De Feo, and Alessandro Sorniotti
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Modular exponentiation ,General Computer Science ,business.industry ,Computer science ,media_common.quotation_subject ,Interoperability ,Ambiguity ,Computer security ,computer.software_genre ,Public-key cryptography ,Cipher ,Side channel attack ,Simplicity ,business ,computer ,ElGamal encryption ,media_common - Abstract
Roughly four decades ago, Taher ElGamal put forward what is today one of the most widely known and best understood public key encryption schemes. ElGamal encryption has been used in many different contexts, chiefly among them by the OpenPGP email encryption standard. Despite its simplicity, or perhaps because of it, in reality there is a large degree of ambiguity on several key aspects of the cipher. Each library in the OpenPGP ecosystem seems to have implemented a slightly different "flavor" of ElGamal encryption. While-taken in isolation-each implementation may be secure, we reveal that in the interoperable world of OpenPGP, unforeseen cross-configuration attacks become possible. Concretely, we propose different such attacks and show their practical efficacy by recovering plaintexts and even secret keys.
- Published
- 2023
14. Confirmation bias in social networks
- Author
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Marcos Fernandes
- Subjects
FOS: Computer and information sciences ,History ,Physics - Physics and Society ,Polymers and Plastics ,Sociology and Political Science ,media_common.quotation_subject ,FOS: Physical sciences ,Context (language use) ,Physics and Society (physics.soc-ph) ,Public opinion ,Industrial and Manufacturing Engineering ,FOS: Economics and business ,Econometrics ,Economics - Theoretical Economics ,Business and International Management ,Social learning theory ,General Psychology ,media_common ,Social and Information Networks (cs.SI) ,Social network ,business.industry ,General Social Sciences ,Computer Science - Social and Information Networks ,Ambiguity ,Social learning ,Harm ,Confirmation bias ,Theoretical Economics (econ.TH) ,Statistics, Probability and Uncertainty ,business ,Psychology - Abstract
In this study, I present a theoretical social learning model to investigate how confirmation bias affects opinions when agents exchange information over a social network. Hence, besides exchanging opinions with friends, agents observe a public sequence of potentially ambiguous signals and interpret it according to a rule that includes confirmation bias. First, this study shows that regardless of level of ambiguity both for people or networked society, only two types of opinions can be formed, and both are biased. However, one opinion type is less biased than the other depending on the state of the world. The size of both biases depends on the ambiguity level and relative magnitude of the state and confirmation biases. Hence, long-run learning is not attained even when people impartially interpret ambiguity. Finally, analytically confirming the probability of emergence of the less-biased consensus when people are connected and have different priors is difficult. Hence, I used simulations to analyze its determinants and found three main results: i) some network topologies are more conducive to consensus efficiency, ii) some degree of partisanship enhances consensus efficiency even under confirmation bias and iii) open-mindedness (i.e. when partisans agree to exchange opinions with opposing partisans) might inhibit efficiency in some cases., Status: Accepted (Mathematical Social Sciences, Elsevier)
- Published
- 2023
15. Modeling rational decisions in ambiguous situations: a multi-valued logic approach
- Author
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Olga Metzger and Thomas Spengler
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Rationality ,Ambiguity ,Multi-valued logic ,Intuitionistic fuzzy values ,Business ,HF5001-6182 - Abstract
Abstract If a decision context is completely precise, making good decisions is relatively easy. In the presence of ambiguity, rational decision-making is incomparably more challenging. We understand ambiguous situations as cases, where the decision-maker has imprecise (uncertain or vague) knowledge that is acquired from incomplete information (without limiting it to probability judgements as in common terminology). From that, we assume that imprecisions in knowledge can affect all elements of the decision field as well as the objective function. For the modeling of such decision situations, classical logics are no longer considered as means of choice, so that we suggest using approaches from the field of multi-valued logic. In the present work, we take suitable calculi from the so-called intuitionistic fuzzy logic into account. On that basis, we propose a model for the formulation and solving of decision problems under ambiguity (in the general sense). Particularly, we address decision situations, in which a decision-maker has sufficient information to specify point probability values, but insufficient information to express point utility values. Our approach is also applicable for modeling cases in which the probability judgments or both, probability and utility judgements are imprecise. Our model is novel in that we combine core elements of established approaches for the formal handling of uncertainty (maxmin and $$ \alpha $$ α -maxmin expected utility models) with the mathematical foundation of intuitionistic fuzzy theory.
- Published
- 2019
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16. Self-Supervised Deep Monocular Depth Estimation With Ambiguity Boosting
- Author
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Munchurl Kim and Juan Luis Gonzalez Bello
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Estimation ,Boosting (machine learning) ,Monocular ,Computer science ,business.industry ,Applied Mathematics ,media_common.quotation_subject ,Stereoscopic view ,Pattern recognition ,Ambiguity ,Task (project management) ,Consistency (database systems) ,Computational Theory and Mathematics ,Single view ,Artificial Intelligence ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,Software ,media_common - Abstract
We propose a novel two-stage training strategy with ambiguity boosting for the self-supervised learning of single view depths from stereo images. Our proposed two-stage learning strategy firstly aims to obtain a coarse depth prior by training an auto-encoder network for a stereoscopic view synthesis task. This prior knowledge is then boosted and used to self-supervise the model in the second stage of training in our novel ambiguity boosting loss. Our ambiguity boosting loss is a confidence-guided type of data augmentation loss that improves the accuracy and consistency of generated depth maps under several transformations of the single-image input. To show the benefits of the proposed two-stage training strategy with boosting, our two previous depth estimation (DE) networks, one with t-shaped adaptive kernels and the other with exponential disparity volumes, are extended with our new learning strategy, referred to as DBoosterNet-t and DBoosterNet-e, respectively. Our self-supervised DBoosterNets are competitive, and in some cases even better, compared to the most recent supervised SOTA methods, and are remarkably superior to the previous self-supervised methods for monocular DE on the challenging KITTI dataset. We present intensive experimental results, showing the efficacy of our method for the self-supervised monocular DE task.
- Published
- 2022
17. A Systemic Approach for Natural Language Scenario Elicitation of Security Requirements
- Author
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Hanan Hibshi, Travis D. Breaux, and Stephanie Jones
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Statement (computer science) ,Structure (mathematical logic) ,business.industry ,Computer science ,Process (engineering) ,media_common.quotation_subject ,User story ,Security domain ,Ambiguity ,Action (philosophy) ,Electrical and Electronic Engineering ,Software engineering ,business ,Natural language ,media_common - Abstract
Security analysts rely on scenarios to assess vulnerabilities, project attacks, and decide on security requirements that mitigate the threat. However, eliciting natural language scenarios from stakeholders can be an ad-hoc process and subject to ambiguity and incompleteness. In this paper, we examine systematic scenario elicitation by introducing a method based on user stories that uses a simplified process model of iterative scenario refinement. The process consists of three steps: 1) eliciting an interaction statement that describes a critical action performed by a user or system process; 2) eliciting one or more descriptive statements about a technology that enables the interaction; and 3) refinement of the technology into technical variants that correspond to design alternatives. We empirically evaluated our method by implementing our prototype in a user study that collects 30 security scenarios from participants. Based on our analysis, our proposed method is shown effective. Participants had a 100% task completion rate with 57% of participants achieving complete task-success, and the remaining 43% of participants achieving partial task-success. We also show the effect of security domain knowledge, and the benefit of using structure when collecting security requirements in natural language text. Finally, we present lessons learned and future research directions.
- Published
- 2022
18. The interrelationships of work-related factors, person-environment fit, and employee turnover intention
- Author
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Chavis Ketkaew, Orasa Manglakakeeree, and Phaninee Naruetharadhol
- Subjects
work-related factors ,person-environment fit ,person-organization fit ,person supervisor fit ,person-job fit ,person group fit ,overload ,role ambiguity ,role conflict ,responsibility ,financial insecurity ,turnover intention ,Business ,HF5001-6182 ,Management. Industrial management ,HD28-70 - Abstract
Retaining human resources is essential for a company’s competitiveness. Losing a high-capacity employee can hurt a company’s performance. In this study, we investigate the inter-relationship among work-related factors, for instance, job stress, person-environment-fit, and quitting intention of employees in Thailand. Data were collected from 400 office workers in Bangkok, Thailand, utilizing structured questionnaires derived from the conceptual framework. The gathered data were analyzed using the structural equation modeling (SEM) approach. We found that work overload, role ambiguity, and role conflict, as mediated through job stress, would influence employee turnover intention. However, unlike the previous employee turnover intention model that factors were typically mediated through job stress, we found that higher responsibility and greater financial insecurity directly drive turnover intention (positively for financial insecurity but negatively for responsibility).
- Published
- 2020
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19. The Adoption of Marketing Decisions by Using Fuzzy Logic for Market Segmentation and Competitive Advantage Achieving A Hypothetical Application in Automotive Industry
- Author
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Sîrb Lucian, Molcuț Alin, and Nastor Flavius
- Subjects
marketing ,decisional process ,ambiguity ,fuzzy logic ,automotive ,Business ,HF5001-6182 ,Economics as a science ,HB71-74 - Abstract
In our contemporary period the businesses environment becomes more and more dynamicallyand surrounded by uncertainty, in the same time with the continuous increase of globalization andtechnology development. In this context, taking the most appropriate decisions, either strategical,tactical or operational ones, from different points of view within an organization, here makingreference to selecting the most suitable alternative in aspects like for example managerialdecisions, marketing decisions, human resources decisions and so on, represents for theorganization the vector for survival and development in an uncertain and ambiguous environment. The main purpose of this research is to find out which are the most preferred Dacia car brand in acertain region or country around the world in order to prioritize the production in a proactivelyand efficient way in accordance to the lean management and just in time production system.
- Published
- 2018
20. Text-Guided Human Image Manipulation via Image-Text Shared Space
- Author
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Xin Tao, Ying-Cong Chen, Xiaogang Xu, and Jiaya Jia
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Diagnostic Imaging ,Shared space ,Computer science ,business.industry ,Applied Mathematics ,media_common.quotation_subject ,Feature extraction ,Ambiguity ,Iterative reconstruction ,Space (commercial competition) ,Computational Theory and Mathematics ,Artificial Intelligence ,Task analysis ,Selection (linguistics) ,Humans ,Computer vision ,Neural Networks, Computer ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,Algorithms ,Software ,Natural language ,media_common - Abstract
Text is a new way to guide human image manipulation. Albeit natural and flexible, text usually suffers from inaccuracy in spatial description, ambiguity in the description of appearance, and incompleteness. We in this paper address these issues. To overcome inaccuracy, we use structured information (e.g., poses) to help identify correct location to manipulate, by disentangling the control of appearance and spatial structure. Moreover, we learn the image-text shared space with derived disentanglement to improve accuracy and quality of manipulation, by separating relevant and irrelevant editing directions for the textual instructions in this space. Our model generates a series of manipulation results by moving source images in this space with different degrees of editing strength. Thus, to reduce the ambiguity in text, our model generates sequential output for manual selection. In addition, we propose an efficient pseudo-label loss to enhance editing performance when the text is incomplete. We evaluate our method on various datasets and show its precision and interactiveness to manipulate human images.
- Published
- 2022
21. DeepIPR: Deep Neural Network Ownership Verification With Passports
- Author
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Lixin Fan, Qiang Yang, Chee Seng Chan, and Kam Woh Ng
- Subjects
Computer science ,media_common.quotation_subject ,Inference ,ComputingMilieux_LEGALASPECTSOFCOMPUTING ,Intellectual property ,Computer security ,computer.software_genre ,Data modeling ,Artificial Intelligence ,Code (cryptography) ,Humans ,Digital watermarking ,media_common ,business.industry ,Applied Mathematics ,Ownership ,Watermark ,Ambiguity ,Counterfeit ,Computational Theory and Mathematics ,Neural Networks, Computer ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,computer ,Algorithms ,Software - Abstract
With substantial amount of time, resources and human (team) efforts invested to explore and develop successful deep neural networks (DNN), there emerges an urgent need to protect these inventions from being illegally copied, redistributed, or abused without respecting the intellectual properties of legitimate owners. Following recent progresses along this line, we investigate a number of watermark-based DNN ownership verification methods in the face of ambiguity attacks, which aim to cast doubts on the ownership verification by forging counterfeit watermarks. It is shown that ambiguity attacks pose serious threats to existing DNN watermarking methods. As remedies to the above-mentioned loophole, this paper proposes novel passport-based DNN ownership verification schemes which are both robust to network modifications and resilient to ambiguity attacks. The gist of embedding digital passports is to design and train DNN models in a way such that, the DNN inference performance of an original task will be significantly deteriorated due to forged passports. In other words, genuine passports are not only verified by looking for the predefined signatures, but also reasserted by the unyielding DNN model inference performances. Extensive experimental results justify the effectiveness of the proposed passport-based DNN ownership verification schemes. Code is available at https://github.com/kamwoh/DeepIPR.
- Published
- 2022
22. PoCoS – Potsdam Coreference Scheme
- Author
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Olga Krasavina and Christian Chiarcos
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Scheme (programming language) ,Structure (mathematical logic) ,Coreference ,Information retrieval ,Computer science ,business.industry ,media_common.quotation_subject ,Comparability ,Ambiguity ,computer.software_genre ,Feature (linguistics) ,Identification (information) ,Annotation ,Artificial intelligence ,ddc:400 ,business ,computer ,Natural language processing ,media_common ,computer.programming_language - Abstract
This document outlines minimal design principles underlying annotation of coreference relations in PoCoS, a scheme for cross-linguistic anaphoric annotation. We identify language-independent principles for markable identification which are essential for comparability of annotations produced for different languages. We further suggest a clear and motivated structure of annotation stages, the separation of a coarse-grained core and a family of more elaborate extended schemes, and strategies for the systematic treatment of ambiguity. Explicit mark-up of ambiguities is a novel feature. We implemented three instantiations of PoCoS for German, English and Russian applied to corpora of newspaper texts.
- Published
- 2023
23. PEMODELAN STRES KERJA DALAM MENDORONG INTENSITAS KELUAR
- Author
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Muhdiyanto Muhdiyanto and Lukluk Atul Hidayati
- Subjects
role ambiguity ,stres kerja ,konflik peran ,intensitas keluar ,Business ,HF5001-6182 - Abstract
Tujuan penelitian ini adalah untuk menguji model stress kerja dalam mendorong intensitas keluar pada perusahaan asuransi di wilayah kedu. Survei dilakukan meggunakan kuesioner dari penelitian terdahulu. Kuesioner dikirim terhadap 14 perusahaan ansuransi diwilayah Kedu. Sampel terdiri dari 202 respoden. Uji validitas dan reliabilitas digunakan untuk menguji konten kuesioner. Penelitian menggunakan structural equation modeling (SEM) untuk menganalisa hipotesis. Hasil mendukung hipotesis.
- Published
- 2017
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24. Uncertain Waters: Participatory groundwater modelling in Chicago’s suburbs
- Author
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Daniel B. Abrams, Cecilia Cullen, Trevor Birkenholtz, and Devin H. Mannix
- Subjects
geography ,geography.geographical_feature_category ,Hydrogeology ,Sociology and Political Science ,business.industry ,media_common.quotation_subject ,Water supply ,Aquifer ,Ambiguity ,Focus group ,Urban planning ,Business ,Groundwater model ,Environmental planning ,Groundwater ,media_common - Abstract
Groundwater exists in underground aquifers and is largely hidden and intangible to water users. As such, groundwater models are one of the main vehicles through which groundwater is made legible. They are critical for water supply planning purposes. However, models are imperfect representations of limited data and contain much uncertainty, posing challenges for the water supply planning process. In this paper, we draw on a case from the Greater Chicago area to examine efforts by the authors and the Illinois State Water Survey to engage with local water managers to develop future water supply scenarios. Much of this area has been dependent upon the Cambrian-Ordovician Aquifer System for over 150 years. Over this period, water levels have declined by over 300 m and aquifers are expected to be unviable by 2030. Here we advance the growing field of participatory groundwater modelling (PGM) to identify forms of uncertainty and their influence on understandings of water supply and risk perceptions of depletion. Conceptually, we draw on the idea of models as world builders, where uncertainties are elucidated through knowledge production in the act of model building, while model development is simultaneously influenced by expectations, beliefs, and ambiguity surrounding those using the models. Through planning meetings and focus group discussions between groundwater modelers and water supply stakeholders, we identify four forms of interconnected uncertainty that hinder planning efforts: 1) hydrogeologic uncertainty, 2) modelling uncertainty; 3) water demand uncertainty; and 4) urban planning uncertainty. We describe our PGM efforts to reduce uncertainty and find stakeholder perceptions are as important as model uncertainties in water management decisions. Participatory modelling is effective in reducing and clarifying these four forms of uncertainty, particularly applied to short-term management decisions in a rapidly changing system. We conclude that future participatory modelling efforts need to focus on reducing communication barriers between scientists and local users.
- Published
- 2022
25. Deep Learning-Embedded Social Internet of Things for Ambiguity-Aware Social Recommendations
- Author
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Jerry Chun-Wei Lin, Zhiwei Guo, Keping Yu, Gautam Srivastava, and Yu Li
- Subjects
Computer Networks and Communications ,Computer science ,Data management ,media_common.quotation_subject ,02 engineering and technology ,Machine learning ,computer.software_genre ,01 natural sciences ,Bridge (interpersonal) ,Data modeling ,Robustness (computer science) ,0202 electrical engineering, electronic engineering, information engineering ,media_common ,Social computing ,business.industry ,Deep learning ,010401 analytical chemistry ,020206 networking & telecommunications ,Ambiguity ,0104 chemical sciences ,Computer Science Applications ,Control and Systems Engineering ,Benchmark (computing) ,Artificial intelligence ,business ,computer - Abstract
With the increasing demand of users for personalized social services, social recommendation (SR) has been an important concern in academia. However, current research on SR universally faces two main challenges. On the one hand, SR lacks the considerable ability of robust online data management. On the other hand, SR fails to take the ambiguity of preference feedback into consideration. To bridge these gaps, a deep learning-embedded social Internet of Things (IoT) is proposed for ambiguity-aware SR (SIoT-SR). Specifically, a social IoT architecture is developed for social computing scenarios to guarantee reliable data management. A deep learning-based graph neural network model that can be embedded into the model is proposed as the core algorithm to perform ambiguity-aware SR. This design not only provides proper online data sensing and management but also overcomes the preference ambiguity problem in SR. To evaluate the performance of the proposed SIoT-SR, two real-world datasets are selected to establish experimental scenarios. The method is assessed using three different metrics, selecting five typical methods as benchmarks. The experimental results show that the proposed SIoT-SR performs better than the benchmark methods by at least 10% and has good robustness.
- Published
- 2022
26. Characteristics of Malay translated hadith corpus
- Author
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Siti Syakirah Sazali, Nurazzah Abd Rahman, and Zainab Binti Abu Bakar
- Subjects
General Computer Science ,Zipf's law ,business.industry ,Computer science ,media_common.quotation_subject ,Search engine indexing ,020206 networking & telecommunications ,Context (language use) ,02 engineering and technology ,Ambiguity ,computer.software_genre ,language.human_language ,Field (computer science) ,0202 electrical engineering, electronic engineering, information engineering ,Benchmark (computing) ,language ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,Cluster analysis ,computer ,Natural language processing ,media_common ,Malay - Abstract
Annotated corpus can greatly assist in the natural language processing field. For example, computers can understand more of the document context, and indexing and clustering in information retrieval can be done precisely with less or no ambiguity of words. However, there are only a few annotated corpora in Malay language, which are not publicly shared. In this paper, we delve into analysing and annotating Malay translated hadith documents in terms of tagging and entities. There are three phases, which are manual filtering and cleaning, analysing the corpus and creating the benchmark. As the result, an analysis and benchmark of Malay translated hadith corpus were produced in term of part-of-speech and named entities tags that follows the Zipf’s law distribution.
- Published
- 2022
27. ROLE AMBIGUITY AND PSYCHOLOGICAL EMPOWERMENT MEDIATE PERFORMANCE MEASUREMENT SYSTEMS TO MANAGERIAL PERFORMANCE
- Author
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Rosinta Ery Prastuti and Yuswanto Yuswanto
- Subjects
Performance Measurement System ,Managerial Performance ,Role Ambiguity ,Psychological Empowerment ,Management. Industrial management ,HD28-70 ,Business ,HF5001-6182 - Abstract
The purpose of this study is to analyze the effect of Performance Measurement System to Managerial Performance with mediation variables Role Ambiguity and Psychological Empowerment. This type of research is causality. This research was conducted on non-profit organization that is 7 Private University in Malang. The sample in this study the educational staffequivalent to the manager, the number of samples in this study was 79. The data analysis method used in this study is SEM PLS using WarpPLS 5.0 software. The results of this study indicate that the Performance Measurement System has a positive effect on Managerial Performance through mediation variables Role Ambiguity and Psychological Empowerment. Performance Measurement System has a positive and significant effect on managerial performance. The Performance Measurement System has an indirect relationship with Managerial Performance through Psychological Empowerment. The conclusion is that this study supports the hypothesis developed by Marginson, et al. (2015), but there are some unsupported hypotheses because of the different research objects that each type of organization has different characteristics.
- Published
- 2018
- Full Text
- View/download PDF
28. A Psychologically Inspired Fuzzy Cognitive Deep Learning Framework to Predict Crowd Behavior
- Author
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Stefano Berretti, Sabu M. Thampi, and Elizabeth B. Varghese
- Subjects
Exploit ,business.industry ,Computer science ,Deep learning ,media_common.quotation_subject ,Cognition ,02 engineering and technology ,Ambiguity ,Machine learning ,computer.software_genre ,Fuzzy logic ,Visualization ,Human-Computer Interaction ,Data_GENERAL ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Personality ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,Crowd psychology ,computer ,Software ,media_common - Abstract
In an intelligent surveillance system, detecting and predicting diverse collective crowd behaviors has emerged as a challenging problem for efficient crowd management. In real-world scenarios, potential disasters and hazards can be averted by considering crowd psychology for predicting crowd behaviors. This paper proposes an approach that exploits the psychological and cognitive aspects of human behavior in determining nine diverse crowd behaviors. The proposed approach is a combination of two cognitive deep learning frameworks and a psychological fuzzy computational model that utilizes OCC theory of emotions, OCEAN five-factor model of personality and visual attention for detecting crowd behaviors. Experiments are performed on different datasets and the results prove that our approach is successful in detecting and predicting crowd behavior in confronting situations and also outperforms the state-of-the-art methods. In particular, considering psychological aspects and cognition in determining crowd behavior is beneficial for rectifying the semantic ambiguity in identifying crowd behaviors.
- Published
- 2022
29. Clinical Ambiguity and Conflicts of Interest in Interventional Cardiology Decision Making
- Author
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Xiaofang Wang, Tinglong Dai, and Chao-Wei Hwang
- Subjects
medicine.medical_specialty ,050208 finance ,Interventional cardiology ,business.industry ,Strategy and Management ,medicine.medical_treatment ,media_common.quotation_subject ,05 social sciences ,Percutaneous coronary intervention ,Ambiguity ,030204 cardiovascular system & hematology ,Management Science and Operations Research ,medicine.disease ,03 medical and health sciences ,0302 clinical medicine ,0502 economics and business ,Health care ,Conventional PCI ,Key (cryptography) ,medicine ,Healthcare operations management ,Medical emergency ,business ,Health policy ,media_common - Abstract
Problem definition: Among the most vexing issues in the U.S. healthcare ecosystem is inappropriate use of percutaneous coronary intervention (PCI) procedures, also known as overstenting. A key driver of overstenting is physician subjectivity in eyeballing a coronary angiogram. Advanced tests such as fractional flow reserve (FFR) provide more precise and objective measures of PCI appropriateness, yet the decision to perform these tests is endogenous and not immune to clinical ambiguity associated with eyeballing. Additionally, conflicts of interest, arising from revenue-generating incentives, play a role in overstenting. Academic/practical relevance: Conventional wisdom suggests more precise diagnostic testing will help reduce overtreatment. However, the literature rarely recognizes that the testing decision is itself endogenous. Our research highlights the role of endogeneity surrounding interventional cardiology decision making. Methodology: This study uses stochastic modeling and simulation. Results: Under a low conflict-of-interest level, the physician performs the advanced test for intermediate lesions. Under a high conflict-of-interest level, however, the physician would perform the advanced test only for high-grade lesions, because of a financial disincentive: Performing the advanced test may lower PCI revenue if the test results argue against the procedure. Surprisingly, despite this disincentive, a more revenue-driven physician can be more inclined to perform the advanced test. Managerial implications: Our model leads to implications for various efforts aimed at tackling overstenting: (1) Attention should be paid not only to the sheer quantity of FFR procedures but to which patients receive FFR procedures; (2) reducing the risk of the advanced test has a behavior-inducing effect, yet a modest risk reduction may lower patient welfare; and (3) offering a bonus to the physician for performing FFR procedures equal to a third of its reimbursement rate will cause only a 5% increase in average physician payment while inducing a 26% decline in overstenting. In addition, we show implementing a bundled payment scheme may discourage the use of FFR procedures and lead to more salient overstenting.
- Published
- 2022
30. Correlation ambiguity, listing choice, and market microstructure
- Author
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Helen Hui Huang, Junyong He, and Shunming Zhang
- Subjects
Strategy and Management ,media_common.quotation_subject ,General Decision Sciences ,Ambiguity aversion ,Ambiguity ,Market microstructure ,Management Information Systems ,Market liquidity ,Microeconomics ,Control and Systems Engineering ,Cost of capital ,Management of Technology and Innovation ,Capital asset pricing model ,Asset (economics) ,Business ,Business and International Management ,Listing (finance) ,Engineering (miscellaneous) ,media_common - Abstract
This paper investigates the implication of correlation ambiguity to investor behavior, asset pricing and issuers' listing choices from a market microstructure perspective. We introduce two markets to a multi-asset model: Market A is transparent and Market B is opaque, or Market A with low and Market B with high ambiguity perceived by investors. Each firm can choose only a unique market to list its stock. Due to ambiguity aversion, a naive investor's demand function demonstrates piecewise linear. Such trading behavior may lead to different equilibria and hence different market-clearing prices for each listing outcome. Rational entrepreneurs make their optimal listing decisions depending on asset prices on alternative markets. We further demonstrate that a crafted design of specific features of the microstructure, such as listing standards and disclosure requirements, can effectively reduce the perceived ambiguity and induce more naive investors' participation to improve market liquidity, maintain greater volume, and lower the cost of capital, so as to attract more new listings.
- Published
- 2022
31. The Use of Fuzzy Logic as Augmentation to Quantitative Analysis to Unleash Knowledge of Participants’ Uncertainty When Filling a Survey: Case of Cloud Computing
- Author
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Issam Kouatli
- Subjects
Measure (data warehouse) ,Variables ,Computer science ,business.industry ,Process (engineering) ,media_common.quotation_subject ,Ambiguity ,Machine learning ,computer.software_genre ,Fuzzy logic ,Field (computer science) ,Computer Science Applications ,Computational Theory and Mathematics ,Quantitative analysis (finance) ,Respondent ,Artificial intelligence ,business ,computer ,Information Systems ,media_common - Abstract
Quantitative analysis is a solid, well established mathematical technique that can be used to analyze the result of survey(s) in a specific field. Survey analysis is usually based on the study of the effect of independent variables on a dependent variable. Although quantitative analysis can use an R-Squared value as a method to measure the strength of the relationship between the independent and dependent variables, it does not capture the effect of participants' ambiguity when answering questionnaires. The source of such ambiguity stems from the process of completing the survey, whereby the respondent may have answered most of the independent questions with ease, but has difficulty in responding to the overall dependent question (or vice versa). The objective of this paper is to demonstrate the use of fuzzy logic as a mechanism to measure the uncertainty faced by participants when filling a questionnaire. Based on the participants' responses to the independent variables, the proposed technique uses fuzzy logic inference to measure the subjectivity (qualitative aspect) of the participants' response to the dependent variable. Beyond quantitative analysis, augmentation with such a fuzzy module can provide clearer picture to analysts when analyzing the survey results.
- Published
- 2022
32. Cyber-Resilient Multi-Energy Management for Complex Systems
- Author
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Meysam Qadrdan, Pengfei Zhao, Zhaoyu Wang, Zhidong Cao, Xinlei Chen, Shuangqi Li, Yue Xiang, Xiaohe Yan, Chenghong Gu, and Dajun Zeng
- Subjects
Flexibility (engineering) ,Mathematical optimization ,Computer science ,Energy management ,business.industry ,media_common.quotation_subject ,Complex system ,Robust optimization ,Ambiguity ,Computer Science Applications ,Renewable energy ,Moment (mathematics) ,Control and Systems Engineering ,Electrical and Electronic Engineering ,Resilience (network) ,business ,Information Systems ,media_common - Abstract
This paper addresses the cyber resilience issues of multi-vector energy distribution systems (MEDS) caused by false data injection FDI, considering the uncertainty from renewable resources. A novel two-stage distributionally robust optimization (DRO) is proposed to realize the day-ahead and real-time resilience improvement. The first stage determines an initial plan for day-ahead reserve preparation and the second stage makes adjustment and takes resilience-based actions after potential load redistribution (LR) attacks and renewable output deviation. The ambiguity set is based on both the Wasserstein distance and moment information. Compared to robust optimization which considers the worst case, DRO yields less-conservative solutions and thus provides more economic operation schemes. The Wasserstein-metric based ambiguity set enables to provide additional flexibility hedging against renewable uncertainty. Case studies are demonstrated on two representative MEDS networked with energy hubs, i.e., a 33-bus-20-node MEDS and a 69-bus-20-node-MEDS, illustrating the effectiveness of the proposed cyber-secured model.
- Published
- 2022
33. Risk-Based Contingency-Constrained Optimal Power Flow With Adjustable Uncertainty Set of Wind Power
- Author
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Tapan Kumar Saha, Hui Ma, Gang Liu, and Lei You
- Subjects
Mathematical optimization ,Wind power ,Computer science ,business.industry ,media_common.quotation_subject ,Probabilistic logic ,Robust optimization ,Ambiguity ,Computer Science Applications ,Set (abstract data type) ,Control and Systems Engineering ,Decomposition (computer science) ,Probability distribution ,Electrical and Electronic Engineering ,Contingency ,business ,Information Systems ,media_common - Abstract
This article proposes a risk-based contingency-constrained optimal power flow model by leveraging the methods of both adjustable uncertainty set and distributionally robust optimization. In the proposed model, an adjustable uncertainty set of wind power is developed with network contingencies explicitly incorporated. Based on this uncertainty set, the proposed model is capable of securing the network against both wind power fluctuations and contingencies in a probabilistic manner with the optimal balance between operation cost and risk. Meanwhile, a data-driven L 1-norm-based ambiguity set is employed so that the proposed model is distributionally robust to the ambiguous probability distribution of wind power and the size of the model remains unchanged as the available wind power data increases. A decomposition-based algorithm is also derived so that the proposed model is solvable by off-the-shelf solvers. Numerical studies on IEEE 14- and 118-bus systems are conducted to verify the effectiveness of the proposed model.
- Published
- 2022
34. AMBIGUITY IN THE IDENTITY TRANSFORMATION OF PUBLIC HEALTH ORGANIZATIONS
- Author
-
Eduardo Acuña and Matias Sanfuentes
- Subjects
Ambiguity ,identity ,change ,history ,organizations ,Business ,HF5001-6182 - Abstract
This study explores the transformations implemented by health authorities in a hospital over the last forty years with the purpose of institutionalizing geriatrics in the Chilean public health system. The transformations have been implemented through a process of identity conversion that had implied high levels of ambiguity due to the contradictory coexistence of the old hospital’s identity with the new geriatric practices. These ambiguities are associated with the erratic, precarious support provided by state authorities to the development of the public geriatric framework. Through the handling of images, authorities have paradoxically amplified the achievements of these transformations, thus promoting apparent complacency in internal and external audiences.
- Published
- 2016
35. Role Stressors and Job Performance: An Empirical Investigation in Malaysia
- Author
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Aizzat Mohd. Nasurdin and Soon Lay Khuan
- Subjects
role conflict ,role ambiguity ,task performance ,contextual performance ,customer contact employees ,Malaysia ,Business ,HF5001-6182 - Published
- 2016
- Full Text
- View/download PDF
36. A study on impact of Job role stressors on Frontline employee role performance towards the customers
- Author
-
Kasturi Naik and Srini R. Srinivasan
- Subjects
Role conflict ,role ambiguity ,frontline employee ,departmental stores ,customers ,Business ,HF5001-6182 ,Business communication. Including business report writing, business correspondence ,HF5717-5734.7 - Abstract
Rapid developments in the Indian Economy post-liberalization in 1991 have prompted institutions like the World Bank to forecast that India would be the fourth largest economy in the world by 2020 (Budhwar and Bhatnagar, 2009). Following globalization this has attracted a large numbers of foreign investors and companies to India. HRM in India has evolved as a specialised function (Budhwar and Bhatnagar, 2009). According to Budhwar and Bhatnagar, 2009 India had a long history of labour legislation and industrial relations and there are many challenges to the HRM systems in India, due to the diverse nature of India’s society which is marked by regional, sectoral, socio-cultural and political variation. In such a climate it is extremely difficult to have a uniform HR system. According to Wheatherly and Tansik (1993) employees have to deal with the demands from superiors as well as the needs and wishes of customers. Because of such a boundary spanning role, the retail frontline employees are in dilemma whether to customize the retail services as per customers needs or to obey the organizational guidelines and procedures (Bitner, 1990). This dilemma often leads to job role stress. There are different types of job role stress (Pareek, 1993) of these the research under study deals with the two job role stressors prominent in retail industry job role conflict and job role ambiguity ( Kahn et.al, 1964). According to Heskett et al. (2003) front line employee’s behavior and perception affects the customer satisfaction and intent of buying behavior which in turn have impact on service productivity. There have been many studies conducted on job role stress and its impact on employee job performance but hardly any with respect to organized Indian retail sector.In the prior research studies it can be noted that employee point of view is hardly taken into consideration. Hence as an attempt to fill in this gap the research focuses on understanding how job role stressors (role conflict & role ambiguity) have significant impact on frontline employee role performance towards the customers with special reference to departmental stores located in central, western and harbor suburbs of Mumbai. The study starts with investigating whether frontline employee role performance towards the customers is dependent on job role stressors i.e. role conflict and role ambiguity by means of non-parametric chi-square test. Then it is investigated whether there is negative or positive relationship between job role stress i.e. role conflict and role ambiguity and frontline employee role performance by using Spearman correlation coefficient. The research is explanatory in nature. The sampling design used is stratified random sampling. The research focuses on the dynamics of human element, especially employee engagement, which is key contributor of success with respect to service sector, especially in retail in India.
- Published
- 2016
37. ROLE CONFLICT AND ROLE AMBIGUITY ON LOCAL GOVERNMENT INTERNAL AUDITORS: THE DETERMINANT AND IMPACTS
- Author
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Agil Novriansa and Bambang Riyanto LS.
- Subjects
role conflict ,role ambiguity ,local government ,internal auditors ,Business ,HF5001-6182 - Abstract
The bureaucratic reform at the local government level in Indonesia that was instituted in 2012 has turned local government internal auditors into an important part of government governance systems. The role of local government internal auditors has been expanded to include not only the area of audit oversight, but also the areas of anti-corruption-related and consulting activities. These fundamental changes may potentially induce role conflict and role ambiguity among internal auditors. The objective of this study is to examine empirically the determinants and consequences of role conflict and role ambiguity among local government internal auditors. More specifically, this study attempts to examine the extent to which formalization determines role conflict and role ambiguity; it further tests the impact of role conflict and role ambiguity on commitment to independence and job performance. Questionnaires were distributed to 248 local government internal auditors from 12 Regional Inspectorates in the provinces of Yogyakarta, South Sumatra, and East Java. A total of 176 responses were received, and 124 useable responses from the 176 responses were analysed to test the hypotheses. Using Structural Equation Modelling-Partial Least Square the results show that: formalization is negatively related to role conflict and role ambiguity; role ambiguity has a negative impact on commitment to independence; role conflict has a positive impact on job performance; and role ambiguity has a negative impact on job performance. These findings serve as important external validity evidence on the phenomena associated with role conflict and role ambiguity that occur in the public sector, especially among internal auditors at local government institutions.
- Published
- 2016
- Full Text
- View/download PDF
38. ‘Taking the Bull by the Horns’ with English Business Idioms
- Author
-
Alina Leonte and Alexandra-Lavinia Istratie-Macarov
- Subjects
idiom ,business ,ESL ,ambiguity ,literal interpretation ,Business ,HF5001-6182 ,Economics as a science ,HB71-74 - Abstract
This study looks at the recognition of written idioms by Romanian business students learningEnglish as a second language. An experiment has been conducted, in which 114 students ofeconomic sciences were given definitions of idioms, with the task of finding the idiom that best fitsthe definition. They were also asked to rate the degree of familiarity with the idiom (1 – Familiar, 2– Less familiar, 3 – Unfamiliar). The analysis of the students’ matches reveals that less than half of the students involved in thestudy were able to make a clear connection between the idiom and the proposed definition. Uponfurther evaluation, we are confident in our assessment that students in the field of business are inneed of a more detailed course presentation on idioms and colloquial language commonly found ina corporate office building.
- Published
- 2016
39. Variational Abnormal Behavior Detection With Motion Consistency
- Author
-
Qingwang Huang, Shengyong Chen, Yingjun Du, Xiantong Zhen, Jing Li, Ling Shao, and Video & Image Sense Lab (IvI, FNWI)
- Subjects
Backbone network ,Computer science ,business.industry ,media_common.quotation_subject ,Optical flow ,Probabilistic logic ,Pattern recognition ,Ambiguity ,Computer Graphics and Computer-Aided Design ,Consistency (database systems) ,Artificial intelligence ,Abnormality ,Crowd psychology ,business ,Latent variable model ,Software ,media_common - Abstract
Abnormal crowd behavior detection has recently attracted increasing attention due to its wide applications in computer vision research areas. However, it is still an extremely challenging task due to the great variability of abnormal behavior coupled with huge ambiguity and uncertainty of video contents. To tackle these challenges, we propose a new probabilistic framework named variational abnormal behavior detection (VABD), which can detect abnormal crowd behavior in video sequences. We make three major contributions: (1) We develop a new probabilistic latent variable model that combines the strengths of the U-Net and conditional variational auto-encoder, which also are the backbone of our model; (2) We propose a motion loss based on an optical flow network to impose the motion consistency of generated video frames and input video frames; (3) We embed a Wasserstein generative adversarial network at the end of the backbone network to enhance the framework performance. VABD can accurately discriminate abnormal video frames from video sequences. Experimental results on UCSD, CUHK Avenue, IITB-Corridor, and ShanghaiTech datasets show that VABD outperforms the state-of-the-art algorithms on abnormal crowd behavior detection. Without data augmentation, our VABD achieves 72.24% in terms of AUC on IITB-Corridor, which surpasses the state-of-the-art methods by nearly 5%.
- Published
- 2022
40. At Your Own Risk: A Model of Delegation with Ambiguous Guidelines
- Author
-
Jieun Kim
- Subjects
Hierarchy ,Delegation ,Argument ,Restructuring ,media_common.quotation_subject ,Flexibility (personality) ,Bureaucracy ,Business ,Ambiguity ,Discretion ,media_common ,Law and economics - Abstract
Counter-intuitive to the lessons of principal-agent models, Chinese leaders have often provided local officials with ambiguous policy guidelines that do not clarify the boundaries of discretion. While ambiguity can give local officials flexibility in policy implementation, it can also instill fear of punishment among possible transgressors and encourage preemptive self-censoring. Incorporating both perspectives, I develop a formal model that analyzes a situation in which ambiguity allows flexibility for certain types of local officials while intimidating others. I argue that central leaders use ambiguity as a screening tool to encourage only the competent type of local officials—or those who have policy expertise for producing good outcomes—to choose a gray-area policy at their own risk, while deterring the incompetent type from doing so. I illustrate the model with the case of state-owned enterprise restructuring in China. The argument is broadly applicable to interactions between any upper- and lower-level actors in bureaucratic hierarchy.
- Published
- 2022
41. Graph-Based Visual-Semantic Entanglement Network for Zero-Shot Image Recognition
- Author
-
Wendy Hall, Yang Hu, Dan Dai, Pei Yang, Mingnan Luo, Yingxue Xu, Adriane Chapman, and Guihua Wen
- Subjects
FOS: Computer and information sciences ,Computer Science - Machine Learning ,Computer science ,Computer Vision and Pattern Recognition (cs.CV) ,media_common.quotation_subject ,Computer Science - Computer Vision and Pattern Recognition ,Space (commercial competition) ,Convolutional neural network ,Machine Learning (cs.LG) ,FOS: Electrical engineering, electronic engineering, information engineering ,Media Technology ,Electrical and Electronic Engineering ,Representation (mathematics) ,media_common ,business.industry ,Image and Video Processing (eess.IV) ,Pattern recognition ,Ambiguity ,Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science Applications ,Signal Processing ,Graph (abstract data type) ,Embedding ,Visual modeling ,Artificial intelligence ,business ,Word (computer architecture) - Abstract
Zero-shot learning uses semantic attributes to connect the search space of unseen objects. In recent years, although the deep convolutional network brings powerful visual modeling capabilities to the ZSL task, its visual features have severe pattern inertia and lack of representation of semantic relationships, which leads to severe bias and ambiguity. In response to this, we propose the Graph-based Visual-Semantic Entanglement Network to conduct graph modeling of visual features, which is mapped to semantic attributes by using a knowledge graph, it contains several novel designs: 1. it establishes a multi-path entangled network with the convolutional neural network (CNN) and the graph convolutional network (GCN), which input the visual features from CNN to GCN to model the implicit semantic relations, then GCN feedback the graph modeled information to CNN features; 2. it uses attribute word vectors as the target for the graph semantic modeling of GCN, which forms a self-consistent regression for graph modeling and supervise GCN to learn more personalized attribute relations; 3. it fuses and supplements the hierarchical visual-semantic features refined by graph modeling into visual embedding. Our method outperforms state-of-the-art approaches on multiple representative ZSL datasets: AwA2, CUB, and SUN by promoting the semantic linkage modelling of visual features., 15 pages, 11 figures, on IEEE Transactions on Multimedia
- Published
- 2022
42. Multiple Instance Learning for Emotion Recognition Using Physiological Signals
- Author
-
Andrea Cavallo, Nadia Berthouze, Lucia Pepa, Luca Romeo, and Massimiliano Pontil
- Subjects
Support Vector Machine ,Diverse Density ,Computer science ,media_common.quotation_subject ,Reliability (computer networking) ,Multiple Instance Learning ,02 engineering and technology ,Physiological signals ,Machine learning ,computer.software_genre ,050105 experimental psychology ,0202 electrical engineering, electronic engineering, information engineering ,Natural (music) ,0501 psychology and cognitive sciences ,Affective computing ,media_common ,business.industry ,05 social sciences ,Ambiguity ,Emotion Recognition ,Time Ambiguity ,Human-Computer Interaction ,Support vector machine ,Task analysis ,020201 artificial intelligence & image processing ,State (computer science) ,Artificial intelligence ,Sequence learning ,business ,computer ,Software - Abstract
The problem of continuous emotion recognition has been the subject of several studies. The proposed affective computing approaches employ sequential machine learning algorithms for improving the classification stage, accounting for the time ambiguity of emotional responses. Modeling and predicting the affective state over time is not a trivial problem because continuous data labeling is costly and not always feasible. This is a crucial issue in real-life applications, where data labeling is sparse and possibly captures only the most important events rather than the typical continuous subtle affective changes that occur. In this work, we introduce a framework from the machine learning literature called Multiple Instance Learning, which is able to model time intervals by capturing the presence or absence of relevant states, without the need to label the affective responses continuously (as required by standard sequential learning approaches). This choice offers a viable and natural solution for learning in a weakly supervised setting, taking into account the ambiguity of affective responses. We demonstrate the reliability of the proposed approach in a gold-standard scenario and towards real-world usage by employing an existing dataset (DEAP) and a purposely built one (Consumer). We also outline the advantages of this method with respect to standard supervised machine learning algorithms.
- Published
- 2022
43. Rapid Labels: Point-Feature Labeling on GPU
- Author
-
Vaclav Pavlovec and Ladislav Cmolik
- Subjects
Point (typography) ,business.industry ,Computer science ,media_common.quotation_subject ,Pattern recognition ,Ambiguity ,Computer Graphics and Computer-Aided Design ,Image (mathematics) ,ComputingMethodologies_PATTERNRECOGNITION ,Data visualization ,Constant (computer programming) ,Position (vector) ,Feature (computer vision) ,Component (UML) ,Signal Processing ,Computer Vision and Pattern Recognition ,Artificial intelligence ,business ,Software ,media_common - Abstract
Labels, short textual annotations are an important component of data visualizations, illustrations, infographics, and geographical maps. In interactive applications, the labeling method responsible for positioning the labels should not take the resources from the application itself. In other words, the labeling method should provide the result as fast as possible. In this work, we propose a greedy point-feature labeling method running on GPU. In contrast to existing methods that position the labels sequentially, the proposed method positions several labels in parallel. Yet, we guarantee that the positioned labels will not overlap, nor will they overlap important visual features. When the proposed method is searching for the label position of a point-feature, the available label candidates are evaluated with respect to overlaps with important visual features, conflicts with label candidates of other point-features, and their ambiguity. The evaluation of each label candidate is done in constant time independently from the number of point-features, the number of important visual features, and the resolution of the created image. Our measurements indicate that the proposed method is able to position more labels than existing greedy methods that do not evaluate conflicts between the label candidates. At the same time, the proposed method achieves a significant increase in performance. The increase in performance is mainly due to the parallelization and the efficient evaluation of label candidates.
- Published
- 2022
44. Improving Semantic Segmentation in Aerial Imagery via Graph Reasoning and Disentangled Learning
- Author
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Kun Fu, Yu Tian, Xian Sun, Yingchao Feng, Ruigang Niu, and Wenhui Diao
- Subjects
Relation (database) ,Computer science ,business.industry ,media_common.quotation_subject ,Ambiguity ,Machine learning ,computer.software_genre ,Discriminative model ,Feature (computer vision) ,General Earth and Planetary Sciences ,Graph (abstract data type) ,Segmentation ,Pyramid (image processing) ,Artificial intelligence ,Electrical and Electronic Engineering ,business ,Feature learning ,computer ,media_common - Abstract
Semantic segmentation in aerial imagery is still an important yet challenging task due to the complex characteristics of remote sensing data. The critical issues consist of 1) extreme foreground-background imbalance, 2) large intra-class variance and 3) arbitrary-oriented, dense and small objects. The above challenges make it unlikely to model the effective global interdependencies of semantic heterogeneous regions. Besides, general semantic segmentation methods suffer from feature ambiguity due to the joint feature learning paradigm, leading to inferior detail information. In this paper, we propose an improved semantic segmentation framework to tackle these problems via graph reasoning and disentangled learning. On the one hand, a simple yet effective graph reasoning (GR) unit is introduced to implement coordinate-interaction space mapping and perform relation reasoning over the graph. It can be deployed on the feature pyramid network (FPN) to exploit cross-stage multi-scale information. On the other hand, we propose a so-called disentangled learning paradigm to explicitly model the foreground and boundary objects, instantiated as foreground prior estimation and boundary alignment. The indication of the intermediate feature can be effectively emphasized to enhance the discriminative abilities of the network. Extensive experiments over iSAID, ISPRS Vaihingen and the general Cityscapes data sets demonstrate the effectiveness and efficiency of the proposed framework over other state-of-the-art semantic segmentation methods.
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- 2022
45. Advancing the science of health professions education through a shared understanding of terminology: a content analysis of terms for 'faculty'
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Lambert Schuwirth, Anique Atherley, Steven J. Durning, Dujeepa D. Samarasekera, Pim W. Teunissen, Wendy Hu, Jennifer J. Cleland, Hiroshi Nishigori, Eric S. Holmboe, Lauren A. Maggio, Susan van Schalkwyk, RS: SHE - R1 - Research (OvO), Onderwijsontw & Onderwijsresearch, and Amsterdam Reproduction & Development (AR&D)
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media_common.quotation_subject ,Literature study ,Education ,Terminology ,law.invention ,Social group ,law ,Health care ,Humans ,media_common ,Faculty terminology ,Medical education ,business.industry ,Mentors ,Subject (documents) ,Ambiguity ,Variety (linguistics) ,Faculty ,Research Personnel ,Content analysis ,Health Occupations ,CLARITY ,Original Article ,Psychology ,business - Abstract
Introduction Health professions educators risk misunderstandings where terms and concepts are not clearly defined, hampering the field’s progress. This risk is especially pronounced with ambiguity in describing roles. This study explores the variety of terms used by researchers and educators to describe “faculty”, with the aim to facilitate definitional clarity, and create a shared terminology and approach to describing this term. Methods The authors analyzed journal article abstracts to identify the specific words and phrases used to describe individuals or groups of people referred to as faculty. To identify abstracts, PubMed articles indexed with the Medical Subject Heading “faculty” published between 2007 and 2017 were retrieved. Authors iteratively extracted data and used content analysis to identify patterns and themes. Results A total of 5,436 citations were retrieved, of which 3,354 were deemed eligible. Based on a sample of 594 abstracts (17.7%), we found 279 unique terms. The most commonly used terms accounted for approximately one-third of the sample and included faculty or faculty member/s (n = 252; 26.4%); teacher/s (n = 59; 6.2%) and medical educator/s (n = 26; 2.7%) were also well represented. Content analysis highlighted that the different descriptors authors used referred to four role types: healthcare (e.g., doctor, physician), education (e.g., educator, teacher), academia (e.g., professor), and/or relationship to the learner (e.g., mentor). Discussion Faculty are described using a wide variety of terms, which can be linked to four role descriptions. The authors propose a template for researchers and educators who want to refer to faculty in their papers. This is important to advance the field and increase readers’ assessment of transferability. Supplementary Information The online version of this article (10.1007/s40037-021-00683-8) contains supplementary material, which is available to authorized users.
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- 2022
46. Multiview Feature Aggregation for Facade Parsing
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Shibiao Xu, Hongbin Zha, Wenguang Ma, and Wei Ma
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Parsing ,Feature aggregation ,business.industry ,Computer science ,media_common.quotation_subject ,ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION ,Ambiguity ,Geotechnical Engineering and Engineering Geology ,computer.software_genre ,Convolutional neural network ,Fuse (electrical) ,Computer vision ,Facade ,Artificial intelligence ,Electrical and Electronic Engineering ,Architecture ,business ,Representation (mathematics) ,computer ,media_common - Abstract
Facade image parsing is essential to the semantic understanding and 3-D reconstruction of urban scenes. Considering the occlusion and appearance ambiguity in single-view images and the easy acquisition of multiple views, in this letter, we propose a multiview enhanced deep architecture for facade parsing. The highlight of this architecture is a cross-view feature aggregation module that can learn to choose and fuse useful convolutional neural network (CNN) features from nearby views to enhance the representation of a target view. Benefitting from the multiview enhanced representation, the proposed architecture can better deal with the ambiguity and occlusion issues. Moreover, our cross-view feature aggregation module can be straightforwardly integrated into existing single-image parsing frameworks. Extensive comparison experiments and ablation studies are conducted to demonstrate the good performance of the proposed method and the validity and transportability of the cross-view feature aggregation module.
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- 2022
47. Place recognition and heading retrieval are mediated by dissociable cognitive systems in mice
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Russell A. Epstein, Isabel A. Muzzio, Alexander T. Keinath, and Joshua B. Julian
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Male ,Heading (navigation) ,media_common.quotation_subject ,Place identity ,Geometric shape ,Models, Psychological ,Spatial memory ,050105 experimental psychology ,Mice ,03 medical and health sciences ,Cognition ,0302 clinical medicine ,Orientation (mental) ,Orientation ,Animals ,0501 psychology and cognitive sciences ,media_common ,Uncategorized ,Analysis of Variance ,Communication ,Multidisciplinary ,business.industry ,05 social sciences ,Recognition, Psychology ,Ambiguity ,Cognitive architecture ,Biological Sciences ,Mice, Inbred C57BL ,Geography ,Cues ,business ,030217 neurology & neurosurgery ,Spatial Navigation ,Cognitive psychology - Abstract
A lost navigator must identify its current location and recover its facing direction to restore its bearings. We tested the idea that these two tasks--place recognition and heading retrieval--might be mediated by distinct cognitive systems in mice. Previous work has shown that numerous species, including young children and rodents, use the geometric shape of local space to regain their sense of direction after disorientation, often ignoring nongeometric cues even when they are informative. Notably, these experiments have almost always been performed in single-chamber environments in which there is no ambiguity about place identity. We examined the navigational behavior of mice in a two-chamber paradigm in which animals had to both recognize the chamber in which they were located (place recognition) and recover their facing direction within that chamber (heading retrieval). In two experiments, we found that mice used nongeometric features for place recognition, but simultaneously failed to use these same features for heading retrieval, instead relying exclusively on spatial geometry. These results suggest the existence of separate systems for place recognition and heading retrieval in mice that are differentially sensitive to geometric and nongeometric cues. We speculate that a similar cognitive architecture may underlie human navigational behavior.
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- 2023
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48. Antecedents and Effectiveness of Human Resource Business Partner Performance: Evidence from Banking Sector of Pakistan
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Sobia Shahid and Danish Ahmed Siddiqui
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History ,Knowledge management ,Polymers and Plastics ,business.industry ,media_common.quotation_subject ,Ambiguity ,Affect (psychology) ,Organizational performance ,Industrial and Manufacturing Engineering ,Structural equation modeling ,Banking sector ,Confirmatory factor analysis ,Business and International Management ,business ,Human resources ,Line management ,media_common - Abstract
The lack of synergy between the HRM functions and the ambiguity of human resources business partnering (HRBP) role are significantly blocking the way of HR professionals to become business partners. The paper proposed a theoretical framework, based on Ibrahim (2015) model focusing on the antecedents of HRBP performance, and further link HRBP performance to Organizational Performance and effectiveness. We proposed that factors such as having HR Business Knowledge by Management, Top Management & Line Manager support to HRBP, Management understanding of HRBP’s Role, and Synergy between HRM practices, positively affect the performance of HRBP, and better performance would lead to increased Organizational Performance and effectiveness. To establish the empirical validity, we conducted a self-administered study, from 250 employees belongs to HR top management, line managers, and professionals working in the banking sector. Data were analyzed using confirmatory factor analysis and structured equation modeling. The results showed that among other factors, Synergy between HRM practices has a positive and significant influence on HRBP performance. However, HRBP performance positively and significantly affects both Organizational Performance and effectiveness. The findings revealed that HRBP would play an important and positive role to achieve goals, implement HR strategy, and also increased Synergy between HRM functions makes HRBP performance more effective.
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- 2023
49. PENGARUH PENGARUH JOB INSECURITY DAN INTENTION TO LEAVE TERHADAP KINERJA KARYAWAN KONTRAK DI DINAS TENAGA KERJA KOTA SURABAYA
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Pinky Pininta Dewi and Dina Novita
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Service (business) ,Employee performance ,Job insecurity ,media_common.quotation_subject ,Organizational change ,Business administration ,Sample (statistics) ,Ambiguity ,Business ,Role conflict ,media_common - Abstract
This study aims to determine the effect of Job Insecurity and Intention to Leave on the Performance of Contract Employees at the Surabaya City Manpower Office. The approach used is quantitative with the type of inferential research. The sample in this study was 30 employees in the Surabaya City Manpower Office. The analysis technique used is Partial Least Square (PLS). This study proves that Job Insecurity has a positive effect on employee performance at the Surabaya City Manpower Office. In this study, job insecurity is influenced by factors such as role conflict, role ambiguity, and organizational change. Intention To Leave has a positive effect on employee performance at the Surabaya City Manpower Service
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- 2021
50. Human-Computer Interaction in Translation Activity: Fluency of Machine Translation
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Roman Králik, Barbara Jakubickova, and Katarina Welnitzova
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Machine translation ,Computer science ,media_common.quotation_subject ,slovak ,computer.software_genre ,machine translation ,Education ,Synthetic language ,Fluency ,human-computer interaction ,Psychology ,Slovak ,Dimension (data warehouse) ,fluency ,media_common ,business.industry ,General Medicine ,Ambiguity ,language.human_language ,BF1-990 ,Analytic language ,language ,translation quality ,Source text ,Artificial intelligence ,business ,english ,computer ,Natural language processing - Abstract
Digitalization is one of the key distinctive features of modern environment and social life. Nowadays more and more functions are transferred to the artificial mind. How effective is the replacement of human activity with computer activity? In the given article, this problem is solved by an example of integration of digital technologies into translation activities. It this paper, emphasis is placed on the quality of machine translation (MT) output of legal texts in the language pair English - Slovak. It studies a Criminal Code formulated in the Slovak language which was translated by a human translator into English and consequently via machine translation system Google Translate (GT) back into Slovak. The back-translation - translation of a translated text back into its original language - as a quality assessment tool to detect discrepancies, mistranslations and inevitable differences between the source text and the target text was used. The quality of MT output was evaluated according to Multidimensional Quality Metrics (MQM) standards with the focus on the dimension of Fluency. The multiple comparisons were applied to determine which issues (errors) in Fluency dimension differ from the others. A statistically significant difference is noticed between Agreement and other issues, as well as between Ambiguity and other issues. The errors in Agreement are related to the differences between the languages: English is considered mostly an analytic language, Slovak represents a synthetic language. The issues in the Ambiguity dimension correlate with the type of the text being examined, since legal texts are characterized by relatively complicated wording and numerous terms; moreover, accuracy and unambiguity need to be preserved. Generally, the MT output is able to provide users with basic information about the text. On the other hand, most of the segments need revision and/or correction; in such cases, human intervention and post-editing is necessary.
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- 2021
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