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Realizing the building of urban resilience and improving urban resilience has become important contents of urban development. In view of this phenomenon, relying on the framework of trio spaces, which includes physical space, societal space, and cyberspace, the evaluation index system of urban resilience is established. The evaluation model of urban resilience is constructed by using CRITIC-entropy weight and the cloud evaluation method. Four sub-provincial cities in Northeast China, Harbin, Changchun, Shenyang, and Dalian, are selected as the analysis objects, and the resilience of each city is comprehensively evaluated and spatially evaluated. From the urban resilience comprehensive evaluation, this paper found the cities with the highest resilience levels in 2014, from 2015 to 2018, and from 2019 to 2020 are Dalian, Changchun, and Shenyang, respectively. The city with the lowest resilience level is Harbin. Although there are differences in resilience evaluation values of four cities, the resilience levels of these cities are all “qualified”. From the urban resilience sub-space evaluation, this paper explored the shortcomings of the resilience of physical space, societal space, and cyberspace of each city through the comparison. Then, some suggestions about highlighting the enhancement of cyberspace resilience, emphasizing resilience-building balance, conducting resilience evaluation, and monitoring regularly, and local government policy support are proposed to help to promote urban resilience from the concept of trio spaces.

This paper provides an overview of the current state of research on the evaluation methods of participatory processes in smart cities. Specifically, it aims to identify and analyze existing evaluation methods and frameworks for public participation (PP) in smart city development. The study focuses on the evaluation of participatory processes to find key indicators and enable an assessment of PP from multiple perspectives. A scoping literature review was conducted to analyze the past ten years of scientific literature on the topic. Relevant literature was retrieved from Scopus, Web of Science, and Google Scholar, and articles were selected based on a set of criteria to ensure quality and relevance. We found that digital participation, also known as “e-participation”, is the most used method either exclusively or mixed with in-person methods. The level of participation achieved was mostly limited to the first two degrees of PP (i.e., information and consultation), and only a few papers addressed the highest degrees (i.e., agenda-setting and co-management). The impact on participants was mostly related to knowledge and skills, awareness raising, and satisfaction with the process and method. This paper highlights the potential to upskill citizens and enhance their understanding of sustainable urban development, fostering their commitment to achieving the United Nations’ sustainability goals for climate change mitigation in the urban context.

Gesture recognition is a topic in computer science and language technology that aims to interpret human gestures with computer programs and many different algorithms. It can be seen as the way computers can understand human body language. Today, the main interaction tools between computers and humans are still the keyboard and mouse. Gesture recognition can be used as a tool for communication with the machine and interaction without any mechanical device such as a keyboard or mouse. In this paper, we present the results of a comparison of eight different machine learning (ML) classifiers in the task of human hand gesture recognition and classification to explore how to efficiently implement one or more tested ML algorithms on an 8-bit AVR microcontroller for on-line human gesture recognition with the intention to gesturally control the mobile robot. The 8-bit AVR microcontrollers are still widely used in the industry, but due to their lack of computational power and limited memory, it is a challenging task to efficiently implement ML algorithms on them for on-line classification. Gestures were recorded by using inertial sensors, gyroscopes, and accelerometers placed at the wrist and index finger. One thousand and eight hundred (1800) hand gestures were recorded and labelled. Six important features were defined for the identification of nine different hand gestures using eight different machine learning classifiers: Decision Tree (DT), Random Forests (RF), Logistic Regression (LR), Linear Discriminant Analysis (LDA), Support Vector Machine (SVM) with linear kernel, Naïve Bayes classifier (NB), K-Nearest Neighbours (KNN), and Stochastic Gradient Descent (SGD). All tested algorithms were ranged according to Precision, Recall, and F1-score (abb.: P-R-F1). The best algorithms were SVM (P-R-F1: 0.9865, 0.9861, and 0.0863), and RF (P-R-F1: 0.9863, 0.9861, and 0.0862), but their main disadvantage is their unusability for on-line implementations in 8-bit AVR microcontrollers, as proven in the paper. The next best algorithms have had only slightly poorer performance than SVM and RF: KNN (P-R-F1: 0.9835, 0.9833, and 0.9834) and LR (P-R-F1: 0.9810, 0.9810, and 0.9810). Regarding the implementation on 8-bit microcontrollers, KNN has proven to be inadequate, like SVM and RF. However, the analysis for LR has proved that this classifier could be efficiently implemented on targeted microcontrollers. Having in mind its high F1-score (comparable to SVM, RF, and KNN), this leads to the conclusion that the LR is the most suitable classifier among tested for on-line applications in resource-constrained environments, such as embedded devices based on 8-bit AVR microcontrollers, due to its lower computational complexity in comparison with other tested algorithms.

The paper presents a user-centric methodology in order to design successful mobile health (mHealth) applications. In addition to the theoretical background, such an example is presented with an application targeting chronic pain. The pain domain was decided due to its significance in many aspects: its complexity, dispersion in the population, the financial burden it causes, etc. The paper presents a step-by-step plan in order to build mobile health applications. Participatory design and interdisciplinarity are only some of the critical issues towards the desired result. In the given example (development of the PainApp), a participatory design was followed with a team of seventeen stakeholders that drove the design and development phases. Three physicians, one behavioral scientist, three IT and UX experts, and ten patients collaborated together to develop the final solution. The several features implemented in the PainApp solution are presented in details. The application is threefold: it supports the management, reporting, and treatment effectiveness monitoring. The paper is giving details on the methodological approach while presenting insights on the actual plan and the steps followed for having a patient-centric solution. Key success factors and barriers to mobile health applications that support the need for such an approach are also presented.

During the design stage of an HVAC (heating, ventilation, and air conditioning) system in a construction project, designers must decide on the most workable design scheme for the plant room in the building based on the evaluation of multiple aspects related to system performance that need to be considered, such as energy efficiency, economic effectiveness, etc. To solve this problem, this paper proposes a comprehensive evaluation method for the plant rooms of centralized air-conditioning systems in commercial buildings. This new method consists of two analyses used in tandem: Building Performance Simulation (BPS) models and a collection of real HVAC design cases (the carried-out design solutions). The BPS models and a knowledge of the reduction approach based on Rough Set (RS) theory are used to generate data and weight factors for the indices of energy efficiency, and the real design cases are employed with a heuristic algorithm to extract the compiled empirical information for other evaluation items of the centralized HVAC system. In addition, this paper also demonstrates an application in an actual case of a building construction project. By comparing the expert decision-making process and the evaluation results, it is found that they are basically consistent, which verifies the reasonability of the comprehensive evaluation method.

In order to ensure the safe and stable operation of a power system, the performance evaluation of transformer windings after a short-circuit test can predict whether the windings are deformed in order to provide a useful reference for the operation and maintenance of the power sector. This paper proposes a method for evaluating the performance of transformer windings in order to improve the overall effectiveness of a winding evaluation. The index data obtained based on a short-circuit impedance method, frequency response method, and oscillation wave method are used in the algorithm proposed in this paper. First, the transformer winding performance evaluation index system is constructed. Second, the weight of each index is determined by analytic hierarchy process, and then the fuzzy comprehensive assessment method is introduced, and the fuzzy evaluation matrix is established, the evaluation results are calculated using the evaluation formula. Finally, the maximum membership principle is used to determine the performance level of the transformer winding on the evaluation results, and the evaluation results of the transformer winding state are obtained. The example shows that the evaluation level of the measured transformer winding performance can be obtained by this method as “good”. Compared with the traditional method, this method can simplify the evaluation while maintaining higher accuracy.

Recent civilizational transformations have led us to search for and introduce new didactic solutions. One of these is e-learning, which is a response to the needs of the education system and its individual stakeholders. The e-learning systems currently available offer similar solutions. Only during direct interaction with a given tool can one notice significant differences in their functionality. By carrying out evaluation studies the indicators that determine this functionality can be identified. The paper presents e-learning in the context of the academic training of the future generations of teachers. The reflections revolve around digital literacy and experience in using modern information and communication technologies in education. The goal of the research was to evaluate three areas: the functionality of the SELI platform, individual experiences with e-learning, and digital literacy. The technique used was an e-learning survey appended to the end of two e-learning courses offered on the platform. The survey was addressed to teachers and students of the biggest pedagogical university in Poland. The general impression of the content presented on the platform was, in most cases, rated as being very good or good. The platform itself was also evaluated positively. Based on the analyses conducted, two groups of platform users were identified. One third of the users have diverse experiences with e-learning, which corresponds with their digital literacy. The remaining two thirds of the respondents need more training in the areas evaluated. The authors of the paper believe that this type of study should accompany all activities that introduce e-learning at every stage of education. Only then will it be possible to discover where the digital divide lies among the teaching staff and learners.

The COST CARES project aims to support healthcare cost containment and improve healthcare quality across Europe by developing the research and development necessary for person-centred care (PCC) and health promotion. This paper presents an overview evaluation strategy for testing &lsquo, Exploratory Health Laboratories&rsquo, to deliver these aims. Our strategy is theory driven and evidence based, and developed through a multi-disciplinary and European-wide team. Specifically, we define the key approach and essential criteria necessary to evaluate initial testing, and on-going large-scale implementation with a core set of accompanying methods (metrics, models, and measurements). This paper also outlines the enabling mechanisms that support the development of the &ldquo, Health Labs&rdquo, towards innovative models of ethically grounded and evidenced-based PCC.

Ecological space in a densely urbanized region plays a very important role in its development. Therefore, a scientific evaluation of ecological spaces in a densely urbanized region is the main prerequisite for corresponding ecological space planning. Taking the Wu-E-Huang-Huang Metropolitan Interlocking Region as the study area, the paper selects six types of ecological factors, including the location index, land status, terrain conditions (elevation, slope), hydrological conditions (rivers, lakes), landscape value, and road traffic. By using a single factor evaluation and a multi-factor comprehensive evaluation method involving GIS, the paper presents an evaluation of the ecological space conditions of the Wu-E-Huang-Huang Metropolitan Interlocking Region. In line with the result, the ecological environment of the region is divided into four levels: highly sensitive areas, sensitive areas, weakly sensitive areas and insensitive areas. On this basis, the underlying problems and mechanisms are explored further.

We evaluated the One Health-ness (OH-ness) of the surveillance system for antimicrobial resistance (AMR) in Norway by using the recently developed “Evaluation tool for One Health epidemiological surveillance capacities and capabilities” (OH–EpiCap tool). First, we defined the Norwegian AMR surveillance system that we would evaluate. The tool was applied by a group of stakeholders (key persons in the Norwegian AMR surveillance programmes and authors of this paper). The evaluation was performed using a consensus approach. The evaluation resulted in an overall OH-ness score of 68% across all three dimensions included in the tool: Organisation, Operation, and Impact. Suggestions for improvement were only indicated within the areas of internal evaluation and operational costs, whereas most of the indicators included in the tool showed good adherence to the One Health principles. By performing this internal evaluation, we recognized that AMR surveillance in the environment needs to be included in a more systematic and standardized way to improve the OH-ness as defined by the quadripartite organisations. Last but not least, it was beneficial to bring key stakeholders together to conduct the evaluation. It increased a joint perception of the OH-ness of AMR surveillance in Norway and encouraged further collaboration in the future.

The ideology behind process modelling is to visualise lengthy event logs into simple representations interpretable to the end user. Classifying process models as simple or complex is based on criteria that evaluate attributes of models and quantify them on a scale. These metrics measure various characteristics of process models and describe their qualities. Over the years, vast amounts of metrics have been proposed in the community, making it difficult to find and select the appropriate ones for implementation. This paper presents a state-of-the-art meta-review that lists and summarises all the evaluation metrics proposed to date. We have studied the behaviour of the four most widely used metrics in process mining with an experiment. Further, we have used seven healthcare domain datasets of varying natures to analyse the behaviour of these metrics under different threshold conditions. Our work aims to propose and demonstrate the capabilities to use our selected metrics as a standard of measurement for the process mining domain.

According to recent estimates (Reuters), the cost of implementing the sustainable development goals of Agenda 2030 will be USD 176 trillion. This amount seems unattainable, even when considering the public resources currently available to governments that are part of the United Nations. It is undoubtedly necessary to involve the private financial sector, within the so-called finance for sustainable development. To achieve the SDGs, it may be also necessary to schedule local-level initiatives and actions that consider the environmental, social, and governance (ESG) criteria, which can be used to source forms of private finance for sustainable development and contribute to the implementation of the SDGs. Based on these observations, this article deals with the study of clearly defined parameters: (1) the factors that should be considered when assessing the sustainability of a (local) real-estate project and, in particular, of a housing project, in order for the project to be considered sustainable and participate, albeit pro rata, in achieving one (or more) of the eleven SDG sub-goals; and (2) funding opportunities in the world of sustainable-development finance. The specific goal of the research contribution presented in this paper was to use the Delphi method to define a set of local-level evaluation criteria and indicators for real-estate projects, specifically housing projects, with an ESG matrix and in line with some of the SDG 11 targets, considering the Florence Metropolitan Area as a case study. The application of the Delphi method to the case study made it possible to test the usability of this method for the definition of the criteria and indicators, at the local level, for assessing the level of implementation of the SDGs. Specifically, a set of 48 criteria and 74 indicators were defined for assessing the consistency of housing projects with SDG 11 and ESG criteria.

There is a big wave in China of retrofitting single-purpose coal-fired systems for district heating into heat-oriented combined heat and power (CHP) systems to save energy. Back-pressure steam turbines (BPSTs) and extraction steam turbines (ESTs) are both common in retrofitted systems, but contrastive analyses of their effects on the systems’ operation performance are lacking. Moreover, comprehensive evaluation methods of the retrofitted systems remain unknown. In this paper, exergy, exergoeconomic, and exergoenvironmental analyses were conducted to evaluate the thermodynamic, economic, and environmental performances of two real CHP systems: system A using a BPST and system B using an EST. Additionally, a new multi-criteria evaluation method based on rank correlation analysis was proposed for the retrofitted system. The results show that system A is better than system B in thermodynamic and environmental aspects but poorer in the economic aspect. Overall, the multi-criteria evaluation result indicates that system A has a better comprehensive performance than system B. Therefore, the BPST has a better effect than the EST on the retrofitted CHP system for district heating in this study. The findings could provide a reference point for retrofitting work in the future.

The rapid development of automated vehicle technology requires reasonable test scenarios and comprehensive evaluation methods. This paper proposes an evaluation method for automated vehicles combining subjective and objective factors. First, we propose a method for automatically generating test scenarios and for batch testing autonomous vehicles. Then, the use of the target layer, total index layer, and index layer of automated vehicles is proposed to establish a more comprehensive evaluation system for automated vehicles. Specifically, the analytic hierarchy process (AHP, subjective) and improved criteria importance though intercriteria correlation (CRITIC, objective) methods are used to determine the weight of the indicators, and a two-level fuzzy comprehensive (subjective and objective) evaluation method is adopted to comprehensively evaluate the performance of the automated vehicles. Finally, the effectiveness of the proposed evaluation method combining subjective and objective factors is verified through virtual simulations and real-world experiments. Through a combination of subjective and objective methods, improved results can be obtained for safety, efficiency, economy, intelligence, and comfort tests.

Page stream segmentation (PSS) is the task of retrieving the boundaries that separate source documents given a consecutive stream of documents (for example, sequentially scanned PDF files). The task has recently gained more interest as a result of the digitization efforts of various companies and organizations, as they move towards having all their documents available online for improved searchability and accessibility for users. The current state-of-the-art approach is neural start of document page classification on representations of the text and/or images of pages using models such as Visual Geometry Group-16 (VGG-16) and BERT to classify individual pages. We view the task of PSS as a clustering task instead, hypothesizing that pages from one document are similar to each other and different to pages in other documents, something that is difficult to incorporate in the current approaches. We compare the segmentation performance of an agglomerative clustering method with a binary classification model based on images on a new publicly available dataset and experiment with using either pretrained or finetuned image vectors as inputs to the model. To adapt the clustering method to PSS, we propose the switch method to alleviate the effects of pages of the same class having a high similarity, and report an improvement in the scores using this method. Unfortunately, neither clustering with pretrained embeddings nor clustering with finetuned embeddings outperformed start of document page classification for PSS. However, clustering with either pretrained or finetuned representations is substantially more effective than the baseline, with finetuned embeddings outperforming pretrained embeddings. Finally, having the number of documents K as part of the input, in our use case a realistic assumption, has a surprisingly significant positive effect. In contrast to earlier papers, we evaluate PSS with the overlap weighted partial match F1 score, developed as a Panoptic Quality in the computer vision domain, a metric that is particularly well-suited to PSS as it can be used to measure document segmentation.

This paper presents the opinions of primary education teachers in relation to school trips (outdoor learning environment). The following questions are answered: What importance do educational trips have in the context of the curriculum? Does the teacher take advantage of the resources that the environment offers? Are the contents of the curriculum taught during field trips? Are outings planned with the aim of showing students the heritage of the surrounding area? What do students’ families think? In order to answer these questions, a structured questionnaire (CUELX-M ©) was designed, which was then completed by 124 primary school teachers who work in the Region of Murcia (Spain). Through the analysis of the responses to this questionnaire, a detailed study of teachers’ perceptions according to age, gender and teaching experience has been carried out. The reliability of the questionnaire was subjected to expert validation by judges (content, technical and methodological aspects). The reliability of each of the dimensions was also studied, and finally, the construct validity of the scales was studied. The results of Cronbach’s alpha test (=0.867) show that the questionnaire is internally consistent. 98% of the teachers participating in the study agree that school field trips should not be merely recreational and that heritage resources located in the surroundings of schools and cities should be used. However, they also point out that parents of students are sometimes reluctant for their children to participate in such activities due to their economic cost.

The exit-lanes for a left-turn (EFL) is an unconventional method of organizing traffic for left-turns at signalized intersections. In this paper, we propose a nonlinear optimization model to minimize delay by establishing a delay-time diagram for the left-turn traffic when the left-turn traffic is non-oversaturated, considering the relationship between the pre-signal start node of the exit-lanes for a left-turn and the queuing dissipation time of left-turn vehicles. Model validation is performed with example calculations to compare and analyze each operating index and fleet type after signal timing optimization of intersection lane borrowing left-turn lanes. The results show that compared with the conventional left-turn lane, the average delay of vehicles operating with the model decreased by 15.7%, exhaust emission decreased by 11.4%, and capacity increased by 65.7%. The model can support EFL pre-signal design, where signal control is related to queue dissipation time. In practice, a well-designed pre-signal control scheme based on traffic volume can improve capacity and reduce emissions while minimizing average vehicle delays.

Food insecurity amongst households with children is a growing concern globally. The impacts in children include poor mental health and reduced educational attainment. Providing universal free school meals is one potential way of addressing these impacts. This paper reports findings on the impact of a universal free school meals pilot in two English secondary schools. We adopted a mixed-methods, quasi-experimental design. The intervention schools were one mainstream school (n = 414) and one school for students with special educational needs (n = 105). Two other schools were used as comparators (n = 619; n = 117). The data collection comprised a cross sectional student survey during the pilot (n = 404); qualitative interviews with students (n = 28), parents (n = 20) and school staff (n = 12); and student observations of lunchtimes (n = 57). Qualitative data were analysed using thematic analysis, and descriptive analyses and logistic regressions were conducted on the quantitative data. Self-reports of food insecurity were high at both intervention (26.6%) and comparator schools (25.8%). No effects of the intervention were seen in the quantitative findings on either hunger or food insecurity. Qualitative findings indicated that students, families and staff perceived positive impact on a range of outcomes including food insecurity, hunger, school performance, family stress and a reduction in stigma associated with means-tested free school meals. Our research provides promising evidence in support of universal free school meals in secondary schools as a strategy for addressing growing food insecurity. Future research should robustly test the impact of universal free school meals in a larger sample of secondary schools, using before and after measures as well as a comparator group.

The three dimensions of ecological, economic, and social vulnerability in the mountainous countryside are caused by the fragility of the natural ecosystems of the mountains, which overlap with the geographical location of the countryside and are associated with farm production and low productivity. This study conducts a vulnerability evaluation of mountainous rural areas based on the fundamentals of ecological vulnerability in mountainous regions by combining “RS and GIS + multistage land use/land cover change (LUCC) + rural vulnerability evaluation theory and quantitative and practical techniques”. The goal of this project is to establish a comprehensive evaluation system that takes into account the various vulnerability levels in rural areas. It is based on the results of the three phases (2000, 2010, and 2020) of land use/land cover remote sensing images of Yunnan Province. The Delphi approach was used to determine the indicator weights. In order to quantitatively assess the rural vulnerability of 129 counties in Yunnan Province in 2000, 2010, and 2020, as well as to reveal the spatiotemporal characteristics of the rural vulnerability of the entire province in each county from 2000 to 2020, the qualitative comprehensive analysis method and the quantitative multi-index comprehensive evaluation method were organically combined. This paper’s objective is to offer a basis for the strategic planning and management of sustainable rural development and revitalization in mountainous provinces. The findings demonstrate that the ecological, economic, and social vulnerability levels all dramatically decreased over the previous two decades in rural Yunnan Province and its counties. The overall vulnerability of rural areas has been somewhat diminished, with an average annual decline of 1.17% over the past 20 years in the whole province. This demonstrates how the construction and development of rural areas over the past two decades have significantly decreased the overall vulnerability of rural areas. There are, nevertheless, substantial geographical variations. At present, the levels of ecological, economic, social, and overall vulnerability in rural areas of Yunnan Province are high.

In the five years between 2017 and 2022, IP video traffic tripled, according to Cisco. User-Generated Content (UGC) is mainly responsible for user-generated IP video traffic. The development of widely accessible knowledge and affordable equipment makes it possible to produce UGCs of quality that is practically indistinguishable from professional content, although at the beginning of UGC creation, this content was frequently characterized by amateur acquisition conditions and unprofessional processing. In this research, we focus only on UGC content, whose quality is obviously different from that of professional content. For the purpose of this paper, we refer to “in the wild” as a closely related idea to the general idea of UGC, which is its particular case. Studies on UGC recognition are scarce. According to research in the literature, there are currently no real operational algorithms that distinguish UGC content from other content. In this study, we demonstrate that the XGBoost machine learning algorithm (Extreme Gradient Boosting) can be used to develop a novel objective “in the wild” video content recognition model. The final model is trained and tested using video sequence databases with professional content and “in the wild” content. We have achieved a 0.916 accuracy value for our model. Due to the comparatively high accuracy of the model operation, a free version of its implementation is made accessible to the research community. It is provided via an easy-to-use Python package installable with Pip Installs Packages (pip).

It is widely acknowledged that climate change has caused serious environmental issues, including drought, bushfires, floods, and heatwaves, and urban sustainability is currently seriously threatened as a result. Arden is one of the key urban regeneration areas set to experience dramatic residential changes under Melbourne’s development blueprint within the next 20 years. The Arden Structure Plan (2022) outlines specific implementation steps but does not go into detail about the strategies and tactics used to address climate change and urban sustainability. Therefore, there are still problems with the plan, including a lack of information and time-bound development targets, ambiguous public engagement, little focus on urban crime, and insufficient climate change adaptation measures. The plan also considers affordable housing, a mixed-use development pattern that will significantly decrease environmental harm, and active transportation options, primarily walking and bicycling. Considering climate change, this plan will make Arden a suitable location for population growth. This paper aims to evaluate the Arden Structure Plan and make recommendations on how to improve the plan’s urban sustainability and climate change considerations. Furthermore, it provides guidance on whether Arden is a suitable location for Melbourne’s population growth in light of the climate change impacts anticipated to occur by 2100.

In this paper, a fuzzy-based evaluation method is presented for the impact of e-learning on several aspects of the learning lives of academic students of Information and Communication Technologies (ICT) during the COVID-19 pandemic. Specifically, the academic year 2020–2021 was considered when a general lockdown was imposed in Greece and all courses were delivered exclusively through the web. The evaluation criteria are (i) e-learning acceptance, (ii) learning effectiveness, (iii) students’ engagement and (iv) socializing and interpersonal relationships in the educational community. The evaluation was conducted through questionnaires. Ninety two (92) undergraduate and postgraduate students and Ten (10) computer science in-structors of the department of Informatics of the University of Piraeus, Greece, participated in this survey. The questionnaire answers were analyzed using a fuzzy-based mechanism. Particularly, five fuzzy sets were used to describe the 5-point Likert scale answers to the questionnaires with linguistic values, and four other fuzzy sets were used for the description of the evaluation results concerning the four defined evaluation criteria. Moreover, 209 fuzzy rules were created to analyze and calculate the evaluation results per criterion, considering both the students’ answers (119 fuzzy rules) and the instructors’ answers (90 fuzzy rules) to the questionnaires. The gain of this approach is that the analysis of evaluation data with fuzzy rules imitates the human way of thinking and, thus, makes the process more explainable. The evaluation results showed a positive impact of e-learning on student confidence, self-discipline and active participation and a negative impact on student interpersonal relationships. The impact of e-learning on other learning issues was neutral.

The virtual setting is an important setting for health promotion as individuals increasingly go online for health information and support. Yet, users can have difficulty finding valid, trustworthy, and user-friendly health information online. In 2022, we launched an interactive Fact or Fiction Tobacco virtual health tool. The virtual health tool uses evidence-informed tailored content to engage users and refer them to local tobacco cessation resources. The present paper describes the development, user testing, and evaluation of this tool. The Fact or Fiction virtual health tool was designed by tobacco cessation and health marketing experts and informed by health behaviour theories of change. The tool captures data on who is seeking health information, the user’s stage of readiness to quit tobacco products, and whether they act by accessing referred resources. In 2021, we conducted two phases of user testing prior to marketing the tool publicly. After 7 weeks of marketing, we collected data on user interactions with the tool and evaluated the reach of the tool. Results from user testing found the tool to be engaging, easy to use, and quick to complete. Adaptations were made to simplify and condense text and include additional animations. During the first seven weeks of the tool being live, it reached 2306 users, and 38.7% of those users were current or occasional tobacco users. Users were classified based on their intention to quit. Bivariate analysis found that the tool was successful in driving tobacco users towards action as 21.2% tobacco users who were looking to quit and 8.8% of tobacco users who were not looking to quit clicked on local tobacco cessation resources. This virtual health tool is reaching the targeted population and providing tailored information needed at each stage of the continuum of health behaviour change. Among tobacco users looking to quit, this virtual health tool acts as a quick referral to local tobacco cessation resources.

To have a more comprehensive understanding of the water ecological services of Xiangxi, the index system of water ecological service is constructed and the intensity of its influencing factors founded on the geographic detector model (GDM) is obtained in this paper. Then, the water ecological service index of eight cities in Xiangxi to evaluate the function level is determined. It is proved that: (a) The overall service value of water cultural function as a key factor in the construction of water ecological services, soil conservation value, and water supply value are relatively poor. (b) The value of the water ecological culture function type is the largest, with an overall value of 353.32 billion yuan. The value of water resources supply is the smallest, with a value of only 4.37 billion yuan, which indicates that human activities have a strong interference with the service function of the water ecosystem. (c) Based on GDM, four factors, including precipitation, resident population, sewage discharge, and water quality compliance rate, have a significant impact on water ecological services. Among them, per capita GDP(X7) > vegetation coverage (X6) > precipitation (X2) > resident population (X4), which further clearly explains the impact intensity of mountain climate basic conditions and human socio-economic activities on water ecological services. The results can offer a practical basis for the spatial development and protection of the water ecosystem to coordinate humans and the environment.

PurpleAir particulate matter (PM) sensors are increasingly used in the United States and other countries for real-time air quality information, particularly during wildfire smoke episodes. Uncorrected PurpleAir data can be biased and may exhibit a nonlinear response at extreme smoke concentrations (>300 µg/m3). This bias and nonlinearity result in a disagreement with the traditional ambient monitoring network, leading to the public’s confusion during smoke episodes. These sensors must be evaluated during smoke-impacted times and then corrected for bias, to ensure that accurate data are reported. The nearby public PurpleAir sensor and monitor pairs were identified during the summer of 2020 and were used to supplement the data from collocated pairs to develop an extended U.S.-wide correction for high concentrations. We evaluated several correction schemes to identify an optimal correction, using the previously developed U.S.-wide correction, up to 300 µg/m3, transitioning to a quadradic fit above 400 µg/m3. The correction reduces the bias at each air quality index (AQI) breakpoint; most ambient collocations that were studied met the Environmental Protection Agency’s (EPA) performance targets (twelve of the thirteen ambient sensors met the EPA’s targets) and some smoke-impacted sites (5 out of 15 met the EPA’s performance targets in terms of the 1-h averages). This correction can also be used to improve the comparability of PurpleAir sensor data with regulatory-grade monitors when they are collectively analyzed or shown together on public information websites; the methods developed in this paper can also be used to correct future air-sensor types. The PurpleAir network is already filling in spatial and temporal gaps in the regulatory monitoring network and providing valuable air-quality information during smoke episodes.

Multi-path transmission can well solve the data transmission reliability problems and life cycle problems caused by single-path transmission. However, the accuracy of the routing scheme generated by the existing multi-path routing algorithms is difficult to guarantee. In order to improve the accuracy of the multi-path routing scheme, this paper innovatively proposes a multi-path routing algorithm for a wireless sensor network (WSN) based on the evaluation. First, we design and implement the real-time evaluation algorithm based on semi-supervised learning (RESL). We prove that RESL is better in evaluation time and evaluation accuracy through comparative experiments. Then, we combine RESL to design and implement the multi-path routing algorithm for wireless sensor networks based on semi-supervised learning (MRSSL). Then, we prove that MRSSL has advantages in improving the accuracy of the multi-path routing scheme through comparative experiments.

The Taihu Lake drainage basin is the birthplace of the Mulberry-dyke and Fish-pond System (MFS), a traditional eco-agricultural system. In 2017, the largest and best-preserved “Zhejiang Huzhou Mulberry-dyke and Fish-pond System” located by the South Bank of Taihu Lake, China was recognized as Globally Important Agricultural Heritage Systems (GIAHS) by the Food and Agriculture Organization of the United Nations (FAO), and its value has been appreciated. As a dynamic heritage, the sustainable development of MFS is a fundamental requirement of the conservation of GIAHS. In this regard, it is necessary to figure out an approach to evaluating the status of its sustainable development. This paper analyzes and contrasts the emergy embodied in the three patterns of MFS over different periods, then constructs an index system of sustainability evaluation involving the production and consumption processes based on that. Finally, it provides the evaluation and analysis. The three patterns of MFS differ in the system structure. In the Ming and Qing Dynasties (abbreviated as Ming-Qing pattern), MFS was an integrated system compromised of mulberry cultivation, silkworm breeding, fish breeding, and sheep breeding, while other patterns exclude sheep breeding, but increase the input of fertilizer, and add the production of mulberry-leaf tea and other local specialties. The results show that the MFS in the Ming-Qing pattern has the highest integrated evaluation index of sustainable development, followed by the traditional MFS pattern and the new MFS pattern employed nowadays. This indicates that the current capability of sustainable development has decreased compared to that in the Ming and Qing Dynasties. The integrated evaluation index regarding the consumption process of the new MFS pattern is higher than the traditional one, suggesting that it needs to promote sustainability in the production process, especially via the utilization rates of renewable resources and wastes.

Precipitation, as an important component of the Earth’s water cycle, plays a determinant role in various socio-economic practices. Consequently, having access to high-quality and reliable precipitation datasets is highly demanded. Although Gridded Precipitation Products (GPPs) have been widely employed in different applications, the lack of quantitative assessment of GPPs is a critical concern that should be addressed. This is because the inherent errors in GPPs would propagate into any models in which precipitation values are incorporated, introducing uncertainties into the final results. This paper aims to quantify the capability of six well-known GPPs (TMPA, CHIRPS, PERSIANN, GSMaP, IMERG, and ERA5) at multiple time scales (daily, monthly, and yearly) using in situ observations (over 1.7 million) throughout Iran over the past two decades (2000–2020). Both continuous and categorical metrics were implemented for precipitation intensity and occurrence assessment based on the point-to-pixel comparison approach. Although all metrics did not support the superior performance of any specific GPP, taking all investigations into account, the findings suggested the better performance of the Global Satellite Mapping of Precipitation (GSMaP) in estimating daily precipitation (CC = 0.599, RMSE = 3.48 mm/day, and CSI = 0.454). Based on the obtained continuous metrics, all the GPPs had better performances in dry months, while this did not hold for the categorical metrics. The validation at the station level was also carried out to present the spatial characteristics of errors throughout Iran, indicating higher overestimation/underestimation in regions with higher precipitation rates. The validation analysis over the last two decades illustrated that the GPPs had stable performances, and no improvement was seen, except for the GSMaP, in which its bias error was significantly reduced. The comparisons on monthly and yearly time scales suggested the higher accuracy of monthly and yearly averaged precipitation values than accumulated values. Our study provides valuable guidance to the selection and application of GPPs in Iran and also offers beneficial feedback for further improving these products.

Satellite-based precipitation products (SPPs) provide valuable precipitation information for various applications. Their performance, however, varies significantly from region to region due to various data sources and production processes. This paper aims to evaluate four selected SPPs (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Gauge-adjusted Global Satellite Mapping of Precipitation (GSMAP-gauge), and Global Precipitation Measurement (GPM)) over mainland China from 2016 to 2019. Both conventional statistical indicators (e.g., correlation coefficients (CC), root mean square error (RMSE), mean absolute error (MAE), relative bias (RB), and Nash–Sutcliffe efficiency (NSE)) and categorical indicators (probability of detection (POD), probability of true detection (POTD), false-alarm rate (FAR), and critical success index (CSI)) are used for quantitative analysis. The results show that: (1) GSMAP-gauge and GPM perform best in reproducing the spatial distribution pattern of precipitation over mainland China, whereas SPPs generally underestimate summer precipitation with a high frequency of no-rain cases. (2) MSWEP has the best capability for recording precipitation events, although some parts of northern China exhibit abnormal overestimations for winter precipitation. (3) All SPPs, especially the PERSIANN-CDR, significantly underestimate the precipitation in the mountainous areas of southwestern China. (4) The GSMAP-gauge and GPM outperformed the other two of the four SPPs, in terms of the probability density function of daily precipitation for cases (PDFc) and the probability density function of daily precipitation for volume (PDFv). Generally, PERSIANN-CDR shows the poorest performance when compared to the other three products. The product’s algorithm for estimating heavy precipitation and mountainous precipitation needs further improvement.

Cache attacks exploit the hardware vulnerabilities inherent to modern processors and pose a new threat to Internet of Things (IoT) devices. Intuitively, different cache parameter configurations directly impact the attack effectiveness, but the current research on this issue is not systematic or comprehensive enough. This paper’s primary focus is to evaluate how different cache parameter configurations affect access-driven attacks. We build a flexible and configurable simulation verification environment based on the Chipyard framework. To reduce the interference of other factors, we established a baseline for each category of parameter evaluation. We propose a novel evaluation model, called Key Score Scissors Differential (KSSD), for evaluating common private and shared cache parameters under the local and cross-core attack models, respectively; among these are private cache replacement policy, private cache capacity, cache line size, private cache associativity, shared cache capacity, and shared cache associativity. Ours is the first evaluation of the shared cache under a cross-core attack model. As a result of the evaluation, the quantitative metrics can provide a reliable indication of information leakage level under the current cache configuration, which is helpful for attackers, defenders, and evaluators. Furthermore, we provide detailed explanations and discussions of inconsistent findings by comparing our results with the existing literature.

A complex command and control task was selected as the test task, which included observing the overall and local situation, the interactive operation and situation display of detection equipment, the erection and launch of air defense equipment, and the check and display status. The disadvantages of the traditional two-dimensional display interactive system include poor intuitiveness, insufficient information display dimension and complicated interactive operation. The mixed reality display interaction system can avoid these problems well and has the advantages of good portability and high efficiency, but this display interaction system has the problem of high cognitive load. Therefore, based on the premise of completing the same complex task, how to select and improve the display interaction system has become a problem worthy of urgent research. Based on the same complex command and control task, this paper compared the traditional two-dimensional display interaction system and the mixed reality display interaction system and analyzed the performance and cognitive load of the two systems. It is concluded that when completing the same task, the performance of the mixed reality display interaction system is significantly higher than that of the traditional two-dimensional display interaction system, but the cognitive load is slightly higher than that of the traditional two-dimensional display. Cognitive load was reduced while task performance was improved through multi-channel improvements to the mixed reality display interaction system. Considering the effects of performance and cognitive load, the improved multi-channel mixed reality display interaction system is superior to the unimproved mixed reality display interaction system and the two-dimensional display interaction system. This research provides an improvement strategy for the existing display interaction system and provides a new display interaction mode for future aerospace equipment and multi-target, multi-dimensional command and control tasks in war.

The Health in All Policies (HiAP) approach has emerged as a central strategy for promoting health at local, regional, and state levels in different countries. Representing a complex and complicated strategy, evaluations of HIAP at the local level are scarce, and scholars call for more knowledge and critical discussions regarding how to evaluate at this level. In this conceptual paper, I discuss how summative and formative evaluation approaches might supplement each other when evaluating HiAP at the local level. First, I discuss the possibilities of using summative and formative evaluation of HiAP. Further, I discuss how formative-dialogue research might represent possibilities for evaluation by combining the two approaches. Finally, I ask if there has been a shift in the Norwegian evaluation discourse, from the promotion of summative evaluation alone to a combination of both summative and formative methods.

Assessing the social cost of fisheries is generally seen as a matter of how to monetize the components of fisheries. This paper presents an assessment of the societal cost of fishing activities, seen as a social process that is expected to contribute to the better management of aquatic resources, affecting sustainable development in coastal areas around the world. The originality of this article lies in considering the sustainability assessment from a deliberative perspective. It aims at defining the types of guiding concepts, frameworks, and information sets that might be appropriate for decision support, as we enlarge our scope of concern from fisheries to the ecosystems of eco-regions in the long term. In defining the societal cost of fisheries, through interviews, the objective is, first of all, to identify the social effects (positive and negative) of fishing métiers. By comparing fishing activities in a multi-criteria and multi-actor analysis, this evaluation is intended as a means for the actors to express in different ways (scientific indicators, institutional objectives, etc.) their judgment regarding the sustainability of the fishing profession. This analysis is the basis for defining the methods of monetizing these effects in different eco-regions (West African coastal upwelling and the deltas of Southeast Asia).

FY-4A GIIRS temperature profile products have provided unprecedented information for studying the atmospheric characteristics of thermal structures since 2020. The main objective of this paper is to evaluate GIIRS temperature profile products by using radiosonde observations and then apply them to the diagnosis of winter precipitation types in southern China. GIIRS temperature profile products for four types (clear sky perfect quality, cloudy sky perfect quality, cloudy sky good quality and cloudy sky bad quality) show different performances. Relatively, the cloud can affect the quality and quantity of GIIRS products. At different pressure levels, the perfect flagged data under the clear or cloudy sky show the best agreement with radiosonde observations, yielding the highest Pearson correlation coefficient and lowest mean bias as well as root mean square error. The good flagged data have a slight deviation from the perfect data. The impact on the quantity of the GIIRS temperature data is greater than that on the quality with an increase in cloud top height. A case investigation was carried out to analyze the performance of GIIRS temperature profiles for the diagnosis of precipitation types in a winter storm of 2022. The GIIRS temperature profiles represent the reasonable atmospheric thermal structures in the rain and snow in Hubei and Hunan provinces. The GIIRS temperature below 700 hPa is an important indictor to precipitation type diagnosis. Furthermore, two critical thresholds for GIIRS temperatures, which are below −2 °C at 850 hPa and below 0 °C at 925 hPa, respectively, are proposed for the occurrence of snowfall in this winter storm. In addition, the distribution of GIIRS temperature at different pressure levels is consistent with radiosonde observations in a freezing rain event in Guiyang, all of which show the warm rain mechanism by combining the cloud top information.

The design of location-based games (LBGs) for cultural heritage should ensure the active participation and contribution of local communities and heritage professionals to achieve contextual relevance, importance, and content validity. This paper presents an approach and methods of the participatory and co-design of LBGs that promote awareness and learning about the intangible cultural heritage of craftsmanship and artisanal technology throughout a long-term project from sensitization to implementation. Following the design thinking process, we outline the participatory methods (and reflect on results and lessons learnt) of involving cultural heritage professionals, local communities, and visitors (users) of museums and cultural settlements, mainly: field visits, design workshops, field playtesting, and field studies. We discuss issues of participatory design that we experienced throughout the project such as participant centrality and representativeness, producing tangible output from meetings, co-creation of content via playtesting, and implications from the pandemic. This work contributes a case of participatory and co-design of LBGs for cultural heritage that is characterized by longevity and engagement throughout the design process for three LBGs of a museum network in different cultural sites.

Evaluating AI is a challenging task, as it requires an operative definition of intelligence and the metrics to quantify it, including amongst other factors economic drivers, depending on specific domains. From the viewpoint of AI basic research, the ability to play a game against a human has historically been adopted as a criterion of evaluation, as competition can be characterized by an algorithmic approach. Starting from the end of the 1990s, the deployment of sophisticated hardware identified a significant improvement in the ability of a machine to play and win popular games. In spite of the spectacular victory of IBM’s Deep Blue over Garry Kasparov, many objections still remain. This is due to the fact that it is not clear how this result can be applied to solve real-world problems or simulate human abilities, e.g., common sense, and also exhibit a form of generalized AI. An evaluation based uniquely on the capacity of playing games, even when enriched by the capability of learning complex rules without any human supervision, is bound to be unsatisfactory. As the internet has dramatically changed the cultural habits and social interaction of users, who continuously exchange information with intelligent agents, it is quite natural to consider cooperation as the next step in AI software evaluation. Although this concept has already been explored in the scientific literature in the fields of economics and mathematics, its consideration in AI is relatively recent and generally covers the study of cooperation between agents. This paper focuses on more complex problems involving heterogeneity (specifically, the cooperation between humans and software agents, or even robots), which are investigated by taking into account ethical issues occurring during attempts to achieve a common goal shared by both parties, with a possible result of either conflict or stalemate. The contribution of this research consists in identifying those factors (trust, autonomy, and cooperative learning) on which to base ethical guidelines in agent software programming, making cooperation a more suitable benchmark for AI applications.

Nowadays, there are many metrics for overall Quality of Experience (QoE), both those with Full Reference (FR), such as Peak Signal-to-Noise Ratio (PSNR) or Structural Similarity (SSIM), and those with No Reference (NR), such as Video Quality Indicators (VQI), which are successfully used in video processing systems to evaluate videos whose quality is degraded by different processing scenarios. However, they are not suitable for video sequences used for recognition tasks (Target Recognition Videos, TRV). Therefore, correctly estimating the performance of the video processing pipeline in both manual and Computer Vision (CV) recognition tasks is still a major research challenge. There is a need for objective methods to evaluate video quality for recognition tasks. In response to this need, we show in this paper that it is possible to develop the new concept of an objective model for evaluating video quality for face recognition tasks. The model is trained, tested and validated on a representative set of image sequences. The set of degradation scenarios is based on the model of a digital camera and how the luminous flux reflected from the scene eventually becomes a digital image. The resulting degraded images are evaluated using a CV library for face recognition as well as VQI. The measured accuracy of a model, expressed as the value of the F-measure parameter, is 0.87.

Over the last decade, e-learning and the use of digital tools have received a great boost in higher education. This paper presents a content curation methodology to assess the acquisition of specific content and soft skills during the attainment of a Degree in Industrial Electronic Engineering at the University of Jaén. In this teaching–learning experience, 101 engineering students were involved in activities with digital tools related to content curation, and four steps were proposed: search, select, sense making, and share. As evaluation tools, a rubric and a questionnaire of the digital tools were proposed. Moreover, a curation index was defined in order to assess the degree of achievement of the content curation. The academic results after using the rubric were better than previous years. The average content curation index obtained was 53.53. Of the four evaluated steps, search and sense making had the lowest scores and, therefore, these steps should be further developed in the future. In addition, the Kaiser–Meyer–Olkin test and Pearson’s correlation were used for analyzing the results of the questionnaires. It was concluded that the experience had a great impact on the skills related to collaborative work, digital information management, and lifelong learning, which are transversal skills at the university level. Thus, the results highlight the great educational potential of content curation.

The digitalization of industrial processes is being driven forward worldwide. In parallel, the education system must also be transformed. Currently, education does not follow the opportunities and development of technologies. We can ask ourselves how we can integrate technologies into a traditional learning process or how we can adapt the learning process to these technologies. We focused on robotics education in secondary vocational education. The paper contains research results from a modern learning model that addresses student problem-solving using cyber–physical systems. We proposed a reference model for industrial robotics education in the 21st century based on an innovative cyber-physical didactic model (CPLM). We conducted procedure time measurements, questionnaire evaluations, and EEG evaluations. We could use VR to influence the improvement of spatial and visual memory. The more intense representation of the given information influences multiple centers in the brain and, thus, the formation of multiple neural connections. We can influence knowledge, learning more effectively with short-term training in the virtual world than with classical learning methods. From the studied resources, we can conclude that the newer approach to teaching robotics is not yet available in this form. The emerging modern technologies and the possibility of developing training in this area should be investigated further.

The aim of this paper, in line with the 2030 European Agenda and 2021 Italian “Recovery and Resilience Plan” objectives, is to define an evaluation methodology and tool to support public administrations to detect buildings, currently unused or underused, that might be apt for transformation interventions. The focus is on historical Italian healthcare buildings since these show widespread decay and neglect. A five-step methodology has been developed: screening of public assets; classification, evaluation, and identification of buildings, based on the “potential index”; GIS mapping and inventory; selection of buildings for in-depth analysis; BIM digitization and definition of the “transformability index”. In the fifth phase, an evaluation tool is integrated into the BIM software to automatically calculate the transformability index of each building using six indicators: usability, fragmentation, modifiability, roof implementation, external envelope, and window-to-wall ratio. The “transformability index” helps define the most appropriate buildings to intervene with for reuse. Building transformation is connected to construction features and layout organization and it is limited by architectural, structural, and artistic constraints.

State of the art diarization systems now achieve decent performance but those performances are often not good enough to deploy them without any human supervision. Additionally, most approaches focus on single audio files while many use cases involving multiple recordings with recurrent speakers require the incremental processing of a collection. In this paper, we propose a framework that solicits a human in the loop to correct the clustering by answering simple questions. After defining the nature of the questions for both single file and collection of files, we propose two algorithms to list those questions and associated stopping criteria that are necessary to limit the work load on the human in the loop. Experiments performed on the ALLIES dataset show that a limited interaction with a human expert can lead to considerable improvement of up to 36.5% relative diarization error rate (DER) for single files and 33.29% for a collection.

The COVID-19 pandemic has significantly affected the energy sector. The new behavior of industrial and non-commercial consumers changes the energy consumption model. In addition, the constraints associated with the coronavirus crisis have led to environmental effects from declining economic activity. The research is based on evidence from around the world showing significant reductions in emissions and improved air quality. This situation requires rethinking the energy development strategy, particularly the construction of smart grids as a leading direction of energy development. Evaluating the efficiency of smart grids is a vital tool for disseminating successful experience in improving their management. This paper proposes an approach to a comprehensive assessment of smart grids based on a comparative analysis of existing methods, taking into account the changes that need to be considered after the experience gained from the COVID-19 pandemic. The approach provides an accurate set of efficiency indicators for assessing smart grids to account for the direct and indirect effects of smart grids’ implementation. This evaluation approach can be helpful to policymakers in developing energy efficiency programs and implementing energy policy.

In this paper, we propose a method to evaluate Highway Driving Assist (HDA) systems using the theoretical formula and dual cameras, which eliminates the need of experts or expensive equipment and reduces the time, effort, and cost required in such tests. A theoretical evaluation formula that can be calculated was proposed and used. The optimal position of the dual cameras, image and focal length correction, and lane detection methods proposed in previous studies were used, and a theoretical equation for calculating the distance from the front wheel of the vehicle to the driving lane was proposed. For the actual vehicle testing, HDA safety evaluation scenarios proposed in previous studies were used. According to the test results, the maximum errors were within 10%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. Problems such as road surface vibration, shaking due to air resistance, changes in ambient brightness, and the process of focusing the video occurred during driving. In the future, it is judged that it will be necessary to verify the complex transportation environment during morning and evening rush hour, and it is believed that tests will be needed in bad weather such as snow and rain.

The paper is based on a review of the established principles for evaluating the natural qualities of landscapes and developing procedures that can contribute to current methods, upgraded with indicators derived from the perception and attitudes of the public. They were implemented into an integrated model of natural landscape qualities. The method included modeling of the natural landscape qualities for the southern part of the Krka National Park in Croatia. The first evaluation model was based on a survey whose responses were processed and classified using the AHP method and GIS. The results showed that the respondents recognize the diversity of land cover and relief forms and the degree of their fragmentation as the highest natural landscape quality. The second step included overlapping the vulnerability model of natural landscape qualities and the model of perception of natural qualities. It was found that the implementation of perceived natural qualities in the evaluation process affects the model of vulnerability of landscape quality. It also indicates the possibility of implementing the perceived natural qualities of certain landscape types into the complete landscape evaluation process, which encompasses all values in the space, including human perception. Therefore, the whole procedure pointed out the importance of the implementation of perceived values into landscape evaluation, something which is also emphasized by the European Landscape Convention (ELC).

Scientific instrument platforms (SIPs) suffer from a lack of opinion and suggestions on sustainable operation management, leading to widely poor operation status nowadays. It is possible to guarantee the quality and efficiency of scientific and technological innovation activities and to improve the economic and social benefits of scientific and technological resources by constructing a framework system to promote the sustainability of the operation and management for SIPs. To meet the examination and evaluation requirements of the current operation and management of SIPs in China, this paper aims to establish an evaluation framework composed of indicators and attributes running through the construction and development of the SIPs from four aspects of learning and growth, process management, customers, and finance. Based on the existing research and operation practice, and according to the knowledge and preference of 627 SIP stakeholders, factor analysis has been adopted to extract and validate the hierarchical structure containing key sustainability indicators. The results show that the attribute characteristics of sustainable operating management for SIPs involve four significant dimensions of target positioning, team building, internal process control, and external service, among which the first and third ones have relatively higher priority. An effective and reliable evaluation tool is identified to be designed and provided for SIP operating management, which can also be used for self-evaluation and unified management of the sustainable operation of SIPs.

In recent years, the trend for implementing exoskeletons in industrial workplaces has significantly increased. A variety of systems have been developed to support different tasks, body parts, and movements. As no standardized procedure for evaluating industrial exoskeletons is currently available, conducted laboratory and field tests with different setups and methodologies aim to provide evidence of, e.g., the support for selected isolated activities. Accordingly, a comparison between exoskeletons and their workplace applicability proves to be challenging. In order to address this issue, this paper presents a generic method and modular test course for evaluating industrial exoskeletons: First, the seven-phase model proposes steps for the comprehensive evaluation of exoskeletons. Second, the test course comprises a quick check of the system’s operational requirements as well as workstations for an application-related evaluation of exoskeletons’ (short-term) effects. Due to the vastness and heterogeneity of possible application scenarios, the test course offers a pool of modular configurable stations or tasks, and thus enables a guided self-evaluation for different protagonists. Finally, several exemplary exoskeletons supporting varying body regions passed the test course to evaluate and reflect its representativity and suitability as well as to derive discernible trends regarding the applicability and effectiveness of exoskeleton types.

With the variability of the business environment, the various tools that have emerged during the formation of management to support its functionality have been flexibly changed, used, or interchanged. With emphasis on the level of strategic management, it is not only the right choice of strategy and its implementation, but also the use of adequate theory or method of strategy implementation. There is a whole range of such methods, including management by objectives (MBO) by P. Drucker, a pioneer in modern management. The paper focuses on the implementation and use of a management system according to objectives in Slovak companies. Based on the content analysis of available professional resources, it defines the theoretical basis of the researched issues and the basic principles that relate to the MBO method. The analytical part is a case study of a selected Slovak company, in which we analyze the current state of management using qualitative and quantitative methods. Subsequently, based on the main findings, we propose possible recommendations for more effective management according to the objectives of the surveyed company.

Virtualization is a core technology for cloud computing, server consolidation and multi-platform support. However, there is a concern regarding performance degradation due to the duplicated I/O stacks virtualization environments. In this paper, we propose a new I/O framework, we refer to it as Direct-Virtio, that manipulates storage directly, which makes it feasible to avoid the duplicated overhead. In addition, we devise two novel mechanisms, called vectored I/O and adaptive polling, to process multiple I/O requests collectively and to check I/O completion efficiently. Real implementation-based evaluation shows that our proposal can enhance performance for both micro and macro benchmarks.

The article summarizes the arguments within the scientific discussion about performance management in mining companies and their significance for obtaining competitiveness in the market of mining companies in the direction of sustainable development and economic growth. The main goal of the paper is to evaluate the performance indicators of mining processes after the implementation of strategic innovation—a new layout of the mining area focused on a combination of stationary and mobile mining equipment and their influence on the environment in a selected mining company in Slovakia in area of mining of limestone. Methods of research were focused on using economic indicators for the valuation of the efficiency and functionality of the mining processes. We used Pareto analysis for evaluation that points to critical mining processes and their significance in the financial area with orientation to costs, revenues. This research was used economic analysis with direction to efficiency, an indicator of cost and profit. Those indicators create a base for effective business in the mining area. The research empirically confirms that the new innovation of layout of mining place brings improvement of mining processes and indicators point to effective (over limit 0.70) and functional (over limit 0.90) mining processes in the year 2020. Pareto analysis showed the best processes (mining, expedition, transport, sorting) for financial benefits, the volume of production, demand, the satisfaction of customers, the cover needs of industries but at the same they are processes with high costs. Strategic innovation brought improvement too in the area of the environment. The results of the research can be useful for other mining companies in performance management and achievement mining market position.

The COVID-19 pandemic has boosted the growth of the online food delivery (OFD) market in every corner of the world. In Vietnam, the food delivery service is rising rapidly and opening a large gateway of opportunities for numerous OFD platforms, also making it a competing business market in this country. Thus, to keep up with the ever-changing market dynamics, there are numerous measures and dimensions for the OFD entrepreneurs to take into consideration towards sustainable development. This paper’s objective is to evaluate major OFD companies in Vietnam based on a comprehensive set of criteria, which are social and environmental criteria (healthy and safety, information security, and environmental impact), economic criteria (delivery cost, operational capability, and risk management), service quality (order fulfillment, delivery speed, convenience of payment, online/offline service level, and customer feedback), and technology (web design, real-time tracking systems, and marketing techniques). To achieve this objective, this work proposes a multi-criteria decision-making (MCDM)-based framework combining the fuzzy analytic hierarchy process (FAHP) and the weighted aggregated sum product assessment (WASPAS). The FAHP is used to generate criteria weights in which fuzzy set theory is applied to translate the linguistic evaluation statements of experts. Then, WASPAS is used to rank the OFD companies against the selected criteria. The evaluation criteria that have obtained maximum weight priority in the FAHP analysis are “convenience of payment”, “delivery speed”, “online service level”, “order fulfillment”, and “delivery cost”. From the final ranking of WASPAS, Foody is today the best performing OFD player in Vietnam regarding the selected criteria, followed by GrabFood and Now. The proposed methodology can be an accurate and robust evaluation model for the industry, while the managerial implications of this study provide significant materials for decision-makers in the OFD market in improving their businesses towards sustainable development.