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As the Museums and Interactivity-oriented Science Centres of the world are reinventing themselves more as creators of culture than just conservators of culture, they are getting keener to explore how various data retrieval and HCI technologies can symbiotically fit into the methods of museology. Museums, since their advent, have used spatial and temporal scanning to present stories that evolve either over time or through space. But these have always remained static timelines that are limited in content, lack interactive exploration, and miss any metaphorical interaction that allows one to have the experience of physically scanning a space or a timeline. In this work, we report how a new HCI technology was used to retrieve all-sky map data and present the multi-wavelength view of the universe to the uninitiated visitor having no skill to navigate through sophisticated astronomy instruments. We describe an intuitive interface that takes no training and learning for the visitors to operate. They can start analyzing multi-wavelength all-sky maps of our galaxy in no time -- exactly as professional astronomers do. Stressing upon the ease of usability, reliability of data, and fail-safe operation, visitors are given access to additional layers of information that can be presented in myriad options chosen by the visitor. They can compare thin slices of galactic images in various wavelengths and look for essential radiation sources that are otherwise not apparent in the naked eye or simple optical observations. The public exhibit was based on duplex data communication between a computer and a PIC microprocessor controller using IEEE 1284 parallel port in ECP mode thus making it a generic technology for interactive displays. [ABSTRACT FROM AUTHOR]

Copyright of Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji is the property of Gazi University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Gazi Üniversitesi Fen Bilimleri Dergisi Part C: Tasarım ve Teknoloji is the property of Gazi University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Highlights • Phishing email subject lines contain high and diverse persuasive power in just a few words. • The paper builds on the well-known and foundational work of Cialdini's (2007), Gragg's (2003) and Stajano and Wilson (2011) to derive a unique list of Principles of Persuasion in social engineering, resulting from the application of the relational method by two independent researchers. • The study of the relations between existing persuasion principles was applied to the content analysis, by two independent researchers, of a random sample of phishing emails subject lines (N = 194), dated from 2008 to 2017. A thematic content analysis and a sample characterization in terms of visual elements and targeted content, revealed that the most prominent persuasion principles were 'Authority', 'Strong Affect', 'Integrity' and 'Reciprocation'. The persuasion principle 'Strong Affect' was the one containing the larger percentage of references with the presence of visual elements. The use of the pronoun 'you' and 'your' was more evident for the categories 'Strong Affect' and 'Authority', while the employment of the pronouns 'we, us, our' was more expressive in the 'Reciprocation' principle. • This paper presents a method on the way to define a tool for automated identification of principles of human persuasion in social engineering, within phishing emails. Future solutions should focus on the use of socio-technical aspects related mainly to a small number of persuasion principles ('Authority' and 'Distraction – Strong Affect'), which seem to be the most commonly used in phishing emails. Abstract Phishing is a very dangerous form of social engineering with the aim to deceive people into disclosing private/confidential information. Despite widespread warnings and means to educate users to identify phishing messages, these are still a prevalent practice and a lucrative business. The authors believe that persuasion, as a style of human communication designed to influence others, has a central role in successful digital scams. Research on persuasion applied to phishing emails is scarce and tends to build on Cialdini's work alone. Only a single study has proposed a list of merged principles from three different perspectives but it has methodological limitations regarding the analysis' performance by a single researcher and the testing of principles in a small, not validated sample of phishing emails. This paper aims to fill those gaps by building on Cialdini's, Gragg's and Stajano & Wilson's works to derive a unique list of Principles of Persuasion in Social Engineering (PPSE), resulting from the application of the relational method by two independent researchers. The PPSE are identified, by two independent researchers (Kappa > 0.789) on a sample of phishing email subject lines (N = 194), dated from 2008 to 2017 and randomly selected from a reliable phishing archive (millersmiles.co.uk). A thematic content analysis, together with the sample characterization in terms of visual elements and targeted content, revealed that the most prominent principles of persuasion in phishing emails were 'Authority', 'Strong Affect', 'Integrity' and 'Reciprocation'. The larger percentage of references with the presence of visual elements was found for the 'Strong Affect' principle. The use of the pronouns 'you' and 'your' was more evident for the categories 'Strong Affect' and 'Authority', while the employment of the pronouns 'we, us, our' was more frequent in the 'Reciprocation' principle. This paper constitutes a step further in understanding the use of principles of persuasion in phishing emails with future applications on how their recognition can be automated. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the communicative potential of quick glances at objects in a very particular setting, namely when doctors turn their head briefly to look at their desk-top computer screen while they interact with patients during general practice consultations. The study proposes that these glances often are demonstrably produced to be more than means to acquire information; they are communicative actions that indexically enact a reference to (content on) the computer in support of something the doctor says or does - at the moment or subsequently. In particular, the paper identifies three different kinds of glances: silent glances, glances produced alongside talk, and glances produced in conjunction with pointing gestures and talk. Each type may be produced as a communicative action in its own way. The paper also illustrates how doctors' glances at their computer screens are produced as intrinsic parts of recurrent consultation activities such as test result deliveries, history-takings, and treatment recommendations etc. Overall, the study offers knowledge about the distribution, coordination and organization of glances, and about how doctors use their computers during consultations. Highlights • Doctors regularly glance at their computer screen to communicate and engage in a variety of goal-oriented activities. • Glances are produced to enact an embodied reference to (content on) the computer. • Glances may significantly be produced in silence; alongside talk; or in conjunction with pointing gestures and talk. [ABSTRACT FROM AUTHOR]

Abstract Internet mapping platforms are widely used in participatory planning. They carry the promise of accessibility, a wider audience, and more precise spatial data. However, they are critiqued for issues of trust, digital exclusion, and low usability. While the first two problems can be dependent on the local context, the last one is connected with the introduction of map editing tools. They change browser experience and require accessing spatial knowledge, which is a cognitively demanding task, especially for older people. This can negatively influence both quality and quantity of the data being produced. In this paper, we ask questions about the perception of online forms of participation, the accuracy and reliability of the data being collected in participatory mapping, differences between participants age groups, and design considerations for creating successful and inclusive participatory mapping tools? We conducted usability testing experiment with 30 participants. They were presented with various map editing tasks that were to be completed using a mock internet participatory mapping platform that was designed to mimic real-life applications. The sessions were recorded using eye-tracking equipment. We have observed a considerable enthusiasm for using and interacting with web mapping tools, but this was not reflected in the quality of the data which was very low overall. Known map features were added in wrong places even in simpler tasks. Although there were considerable differences between the oldest and youngest people in the map editing behavior, the quality and quantity of the data were similar. We conclude that mapping platforms can be useful for participatory planning and age of the participants is not a barrier for their inclusion when the interface is properly designed. But in the same time care is needed to provide robust quality control. We also propose a research agenda composed from three avenues of research: data quality, usability and user experience and utility of the map. Highlights • Using web map was a difficult task for experiment participants, regardless of age. • Accuracy of the data produced by participants was very low. • Participants had a positive attitude toward online participation in urban planning. • PPGIS research agenda is proposed: data quality, usability and utility of the map. [ABSTRACT FROM AUTHOR]

Highlights • The advanced calibrated camera and rotating head are utilized for image acquisition. • Each site of image data is processed using an independent adjustment method to obtain a three-dimensional point cloud data. • Each site constitutes a local area network and the bundle block adjustment method is used for each site point cloud data. Abstract At present, the three-dimensional (3D) reconstruction system is based on hand-held camera which causes certain problems, such as needing for a large number of human-computer interactions, demanding on high quality image data and insufficient accuracy of 3D reconstruction. Aiming at these problems, a fully automatic reconstruction of large scene based on multi-site point cloud stitching is presented in this paper. The proposed method uses the Kinect sensor for image acquisition. Since, there are multiple sites in the room, each site of image data is processed using a separate model in order to get good 3D point cloud data. Then, these sites are used to constitute a local area network, and the method of bundle block adjustment is employed to stitch each site point cloud data. The proposed method achieves a high-degree automation and provides a high-precision 3D reconstruction which has two main advantages: (i) the reconstruction process is fully automatic, without any human-computer interaction; (ii) the automatic reconstruction is robust. Experimental results show that proposed automatic reconstruction method is convenient and practical, and can provide better 3D reconstruction model than commonly used methods. Moreover, it can be applied to virtual reality shopping malls, Virtual Reality (VR) and other fields. [ABSTRACT FROM AUTHOR]

The purpose of the study is to model the micro-scale process patterns which can be identified during team conceptual design activities. A state-transition model has been developed and used to empirically investigate the patterns of design operations during two types of team conceptual design activities: ideation and concept review. The presented work builds on the perception of design problems as ill-defined and implies that conceptual design activities involve the simultaneous development of problems and solutions using three distinctive design operations—analysis, synthesis, and evaluation. The three design operations have been defined as fine-grain design steps performed by design teams when exploring the content of both the problem and the solution dimensions of the design space. Moreover, design operations have been conceptualised as transitions between states of the explored design space, thus providing a basis for the state-transition model. The model's ability to map and visualise proportions of design operation sequences emerging during ideation and concept review has facilitated the identification of both the activity-specific patterns and patterns that were likely to appear during both types of empirically investigated activities. The two activities exhibited similar patterns, such as alternation of solution synthesis and analysis, sequences of synthesis, analysis and evaluation within solution space, and the potential co-evolution episodes. Nevertheless, divergent traits have been identified for ideation, and convergent traits for concept review, based on the significant differences in proportions of design operations and their sequences. [ABSTRACT FROM AUTHOR]

The article presents the author's views on the role of women in computing and technology since 1969. Topics discussed include their role in moon landing on July 20, 1969, their growth in the field of software engineering, computer pioneers of 19th century, their works in scientific laboratories and development of human computers.

How the human user trusts and interacts with an automation system is influenced by how well the system capabilities are conveyed to the user. When interacting with the automation system, the user can obtain the system reliability information through an explicit description of the reliability or through experiencing the system over time. The term description-experience gap illustrates the difference between description-based and experience-based human decisions. In the current study, we investigated how this description-experience gap applies to human-automation interaction with a phishing-detection task in the cyber domain. In two experiments, participants’ performance in detecting phishing emails and their trust in the phishing detection system were measured when system reliability, description, and experience (i.e., feedback) were varied systematically in easy and difficult phishing detection tasks. The results suggested that system reliability had a profound influence on human performance in the system, but the benefits of having a more reliable system may depend on task difficulty. Also, providing feedback increased trust calibration in terms of both objective and subjective trust measures, yet providing description of system reliability increased only subjective trust. This result pattern not only shows the gap in the effects of feedback and description, but it also extends the description-experience gap concept from rare events to common events. [ABSTRACT FROM AUTHOR]

As there is an excellent advancement in the technology in recent years, there has been much improvement in various fields of computing such as Human Computer Interface (HCI), Computer Vision and Perceptual User Interface (PUI). The input to the computers has sensed information about the physical properties of the user, places, or things. For example, a computer mouse operates by motion imparted by the user's hand. Many active researchers have been working on finding an alternative solution to control computer mouse like by using a finger, eye, hand/palm, marked gloves, etc. These all techniques may not be suitable to physically disabled people. The system of control the mouse cursor by the movement of the head of a person who is positioned in front of the monitor of a microcomputer is presented in this paper. At the top of a monitor is a color video camera with the tem Committee (NTSC) output that captures user images. These images are processed using digital image processing techniques, and the final objective is to proportionally relate the user's head movements (identified by a blue circle painted on a tassel) with the mouse cursor. The captured of the colored images are 320 pixels by 240 wide by high. Preliminary results have shown efficiency in controlling the position of the cursor on the computer screen. [ABSTRACT FROM AUTHOR]

Visual tracking is a challenging research topic in the field of computer vision with many potential applications. A large number of tracking methods have been proposed and achieved designed tracking performance. However, the current state-of-the-art tracking methods still can not meet the requirements of real-world applications. One of the main challenges is to design a good appearance model to describe the target’s appearance. In this paper, we propose a novel visual tracking method, which uses compressed features to model target’s appearances and then uses SVM to distinguish the target from its background. The compressed features were obtained by the zero-tree coding on multiscale wavelet coefficients extracted from an image, which have both the low dimensionality and discriminate ability and therefore ensure to achieve better tracking results. The experimental comparisons with several state-of-the-art methods demonstrate the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

The Computer Science department at Tecnológico Nacional de México-CENIDET, Mexico, with the collaboration of the Psychological department of the University of Castilla-La Mancha (UCLM), Spain, is on a developing process for the creation of an immersive virtual environment through virtual reality (VR) for the e-learning educational area. Such environment, works through electroencephalographic lectures (EEG) from the students, acquired by a Brain-Computer Interface (BCI), to adapt the virtual content to the profile and needs of the student on real-time basis. This system can detect the accuracy of attention and concentration levels on mental states, for the optimum development of the activities requested on an e-learning platform; if the student is not on a suitable concentration level, the system is able to induce the student to the requested mental state. The present document shows the proposal of different recommended activities that induce the mentioned mental states and the EEG response of each one. As well, the definition of the ideal learning emotional state that will be included as a part of the future works. It is important to mention that such activities are based on psychological researches that are dedicated to measure the levels of attention, concentration and other executive functions. [ABSTRACT FROM AUTHOR]

Al GRANO: Framing Worlds is a composite gallery installation with individually installable artifacts that can be shown in various combinations. Three cognitive "chunks" explore different electronic technologies to address historical, cultural, scientific and geopolitical positions related to maize, a contested grain considered both food and cultural symbol in Mexico and a source of macro profits for multinational agribusiness. [ABSTRACT FROM AUTHOR]

It is common to use counting strategies to produce time intervals accurately. Does counting improve the accuracy (deviation of produced duration from veridical duration) and precision (variability of produced duration) of time productions in the range of seconds to minutes? In a series of experiments, we compared chronometric counting to intuitive timing (no counting) and to attentional control (simultaneously performing mental arithmetic). In a field experiment, participants had to produce time intervals of 60-s duration in a classroom setting. Relative to intuitive timing, counting did not improve the accuracy (absolute error) of time productions but led to overproduction of duration (larger constant error). In four laboratory experiments, we tested the effects of counting on time production of 10-, 30-, 45-, 60-, and 90-s intervals. Consistently, counting did not improve the accuracy of time production. The relative overproduction due to counting was replicated for long intervals (60 and 90 s) but disappeared at shorter intervals. However, across all intervals tested, counting had positive effects on the precision of time production. As expected, mental arithmetic impaired accuracy and precision and led to overproduction of duration, indicating that participants followed instructions. Based on the experimental data, the overproduction of longer intervals due to counting can neither be explained in terms of attentional processes nor by means of a word-length effect when counting multisyllabic numbers or when participants switch their pace of counting from mono- to multisyllables. [ABSTRACT FROM AUTHOR]

SUMMARY Input systems using eye blinks have been proposed. A main purpose of these systems is communication aid for the severely disabled. For employing eye blinks as a command input, these input systems need to detect voluntary (conscious) blinks. We developed a measurement method for variation in pixels of open-eye area from an image sequence. This measurement method enables us to extract blinking waver patterns. We previously proposed an automatic classification method between one type of voluntary blinks and involuntary (unconscious) blinks. If the type of classifiable voluntary blinks increase, we can assign an individual command to each type. Applying this blink type classification to a human-computer interface will improve the efficiency when inputting commands. In this paper, we introduce a new type of voluntary blinks to increase classifiable blink type. In addition, our classification method is extended for automatic classification between two types of voluntary blinks and involuntary blinks. This new classification method is realized by two blink type determinations based on wave pattern parameters that we employ. We clarify proper parameter combinations for the new classification method. Using these proper parameter combinations, we achieved approximately 95% classification rates for 10 subjects. [ABSTRACT FROM AUTHOR]

The framework of plateaus, dips, and leaps shines light on periods when individuals may be inventing new methods of skilled performance. We begin with a review of the role performance plateaus have played in (a) experimental psychology, (b) human-computer interaction, and (c) cognitive science. We then reanalyze two classic studies of individual performance to show plateaus and dips which resulted in performance leaps. For a third study, we show how the statistical methods of Changepoint Analysis plus a few simple heuristics may direct our focus to periods of performance change for individuals. For the researcher, dips become the marker of exploration where performance suffers as new methods are invented and tested. Leaps mark the implementation of a successful new method and an incremental jump above the path plotted by smooth and steady log-log performance increments. The methods developed during these dips and leaps are the key to surpassing one's teachers and acquiring extreme expertise. [ABSTRACT FROM AUTHOR]

In contrast to the first and second wave of Human Computer Interaction, the third wave grapples with wicked problems. However, re-solutions to wicked problems embodied in artifacts frame and change the understanding of the problem itself. Research through Design (RtD) is a constructive methodology to understand this interplay of problem framing through designing artifacts. RtD is also suited to resurface the theory within those artifacts through annotation. These annotations expose and emphasize qualities, values and assumptions held within artifacts by its creators. In addition to those modes for annotation, we will suggest two additional abstract frames through which RtD artifacts can be further annotated: Open Research Agenda and Interdisciplinarity. We will apply both frames to one research artifact, Loaded Dice to distill qualities from this artifact's framing. Through this we will show how creating and deploying an artifact can change its environment which also includes its creators. [ABSTRACT FROM AUTHOR]

In the area of human-computer interaction, over the last decade, there has been a growing interest on emotional factors, valuing above all the user experience. Emotions play a crucial role-in terms of both performance and influence-in areas such as attention, motivation, memory, decisionmaking and behavior. Therefore, not only emotion influences the interaction with websites but they also trigger emotional responses and these responses can determine which website users choose. Therefore, were analyzed the emotional responses triggered in the interaction with Duolingo's interface (a learning languages website) taking into account the different components of emotional design, using data gathering instruments such as eye tracking and self-reporting methods. In this way, the present work intended to contribute to the design of interfaces that appeal in a greater extent to the user's emotions, in order to improve their user experience while increasing their level of engagement. [ABSTRACT FROM AUTHOR]

Interruptions of ongoing activities have spread since the development of and global increase in technology use and the general speeding in pace we all experience every day. Their negative effects are well known: decline in performance and emotional distress. However, the literature still needs to shed light on the exact cognitive mechanisms involved in the way users decide to reply to an interruption, on the effects of interruptions of different durations, and on factors influencing reactivation of task schemata and goals at resumption. Therefore, the aim of this article is to review the existing literature and models, uncover unresolved challenges, and propose new ways to confront them. We first review the substantive findings of recent decades from different domains (human-computer interaction, cognitive and experimental psychology, ergonomics), and their respective methodological and theoretical contributions. Then we propose a general and operationalized definition of an interruption; review the different cognitive models of attention, executive control, and working memory that best explain the impact of interruptions; describe current challenges and questions that remain open for future studies; and finally propose an integrative research framework, the DETOUR , which clarifies the cognitive processes at play during interruptions. We believe this work can directly affect the current state of the art, leading to new fundamental studies and applied solutions for the management of interruptions. [ABSTRACT FROM AUTHOR]

This paper reviews recent progress of portable short-range noncontact microwave radar systems for motion detection, positioning, and imaging applications. With the continuous advancements of modern semiconductor technologies and embedded computing, many functionalities that could only be achieved by bulky radar systems in the past are now integrated into portable devices with integrated circuit chips and printed circuits boards. These portable solutions are able to provide high motion detection sensitivity, excellent signal-to-noise ratio, and satisfactory range detection capability. Assisted by on-board signal processing algorithms, they can play important roles in various areas, such as health and elderly care, veterinary monitoring, human-computer interaction, structural monitoring, indoor tracking, and wind engineering. This paper reviews some system architectures and practical implementations for typical wireless sensing applications. It also discusses potential future developments for the next-generation portable smart radar systems. [ABSTRACT FROM AUTHOR]

Spatial information acquisition happens in large part through the visual sense. Studying visual attention and its connection to cognitive processes has been the interest of many research efforts in spatial cognition over the years. Recent technological developments have led to an increasing popularity of eye-tracking methodology for investigating research questions related to spatial cognition, geographic information science (GIScience) and cartography. At the same time, eye trackers can nowadays be used as an input device for (cognitively engineered) user interfaces to geographic information. We provide an overview of the most recent literature advancing and utilizing eye-tracking methodology in these fields, introduce the research articles in this Special Issue, and discuss challenges and opportunities for future research. [ABSTRACT FROM AUTHOR]

In this paper, a novel analysis method for iterative learning control (ILC) algorithms is presented. Even though expressed in the lifted system representation and hence in the time-domain, the convergence rate as a function of the frequency content of the error signal can be determined. Subsequently, based on the analysis method, a novel ILC algorithm (F-ILC) is proposed. The convergence rate at specific frequencies can be set directly in the design process, which allows simple tuning and a priori known convergence rates. Using the F-ILC design, it is shown how to predict the required number of iterations until convergence is achieved, depending on the reference trajectory and information on the system repeatability. Numerical examples are given and experimental results obtained on an internal combustion engine test bench are shown for validation. [ABSTRACT FROM AUTHOR]

With deep learning becoming the dominant approach in computer vision, the use of representations extracted from Convolutional Neural Nets (CNNs) is quickly gaining ground on Fisher Vectors (FVs) as favoured state-of-the-art global image descriptors for image instance retrieval. While the good performance of CNNs for image classification are unambiguously recognised, which of the two has the upper hand in the image retrieval context is not entirely clear yet. We propose a comprehensive study that systematically evaluates FVs and CNNs for image instance retrieval. The first part compares the performances of FVs and CNNs on multiple publicly available data sets and for multiple criteria. We show that no descriptor is systematically better than the other and that performance gains can usually be obtained by using both types together. The second part of the study focuses on the impact of geometrical transformations. We show that performance of CNNs can quickly degrade in the presence of certain transformations and propose a number of ways to incorporate the required invariances in the CNN pipeline. Our findings are organised as a reference guide offering practically useful and simply implementable guidelines to anyone looking for state-of-the-art global descriptors best suited to their specific image instance retrieval problem. [ABSTRACT FROM AUTHOR]

Both individual learning (IL) and collaborative learning (CL) provide students with different benefits. However, previous research indicates that cognitive styles affect students’ learning preferences. Thus, it is necessary to examine how cognitive styles influence students’ reactions to IL and CL. Among various cognitive styles, Pask’s Holist/Serialist biases have recently received considerable attention. Accordingly, the current study aims to illuminate how Holists and Seriailsts react to IL and CL. Subsequent results indicate heterogeneous groups with both Holists and Serialists obtain the best learning performance when undertaking CL. Furthermore, the findings suggest that there is a need to provide Serialists with additional support, regardless of either IL or CL. [ABSTRACT FROM AUTHOR]

In image classification, can sparse representation (SR) associate one test image with all training ones from the correct class, but not associate with any training ones from the incorrect classes? The backward sparse representation (bSR) which contains complementary information in an opposite direction can remedy the imperfect associations discovered by the general forward sparse representation (fSR). Unfortunately, this complementarity between the fSR and the bSR has not been studied in face recognition. There are two key problems to be solved. One is how to produce additional bases for the bSR. In face recognition, there is no other bases than the single test face image itself for the bSR, which results in large reconstruction residual and weak classification capability of the bSR. The other problem is how to deal with the robustness of the bSR to image corruption. In this paper, we introduce a CoSR model, which combines the fSR and the bSR together, into robust face recognition, by proposing two alternative methods to these two key problems: learning bases and unknown faces help to enrich the bases set of the bSR. Thereby, we also propose two improved algorithms of the CoSR for robust face recognition. Our study shows that our CoSR algorithms obtain inspiring and competitive recognition rates, compared with other state-of-the-art algorithms. The bSR with the proposed methods enriching the bases set contributes the most to the robustness of our CoSR algorithm, and unknown faces works better than learned bases . Moreover, since our CoSR model is performed in a subspace with a very low dimensionality, it gains an overwhelming advantage on time consumption over the traditional RSR algorithm in image pixel space. In addition, our study also reveals that the sparsity plays an important role in our CoSR algorithm for face recognition. [ABSTRACT FROM AUTHOR]

China's rise is increasingly impacting on the global financial and monetary order. To manage its growing centrality in global financial flows and its new relevance for patterns of currency usage, Beijing has been creating a set of new institutional arrangements in three crucial fields: the provision of crisis liquidity, development financing, and a global infrastructure to internationalize its currency. In contrast to the dominant power political interpretation of such developments, this article highlights the strong linkages of Beijing's new initiatives with the changes in China's capitalist development path and stresses their experimental character that serves to manage the economic and political risks of China's accelerating financial internationalization. With a distinct learning attitude regarding its rising geoeconomic prominence and engagement, Beijing's risk-averse strategy involves a very careful linking, layering, and nesting of new arrangements. [ABSTRACT FROM AUTHOR]

Although human-computer interaction (HCI) has been developing for thirty years, the field has advanced slowly due to a lack of knowledge about HCI structure. This research thus seeks to explore and clarify HCI intellectual structure. Data collected from the ISI Web of Knowledge totaled 1,168 HCI related articles, and 33,724 references were identified. There were 75 highly cited research articles identified using a citation analysis and then implementing co-citation analyses, including factor analysis, multidimensional scaling and cluster analysis. According to cluster analysis, twelve core knowledge domains of HCI were identified: System capability. User interface design, Task of the HCI system, Evaluation of interaction, User acceptance of technology, Personalized system design, Interface analysis, Performance measurement and improvement, Development of interaction. Human reaction to technology, Facial expression, and Effective interaction. Among these topics, two of them, "Personalized system design" and "Facial expression", are new intellectual cores which did not appear in previous related researches. The findings of this study provide an intellectual structure and research directions for researchers and practitioners interested in the HCI field. [ABSTRACT FROM AUTHOR]

This paper present the use of hand gestures for human-computer interaction, this paper presents an approach to identify hand gestures using muscle activity separated from electromyogram (EMG) using ANN. To retain a constraint-free user's environment, EMG sensing is limited to three arm muscles. EMG signals are processed to attain parameters that are related to the muscles temporal activities. The attainment of these parameters through time constructs a unique signature for each particular gesture. Experimental investigation was carried out to examine the system's reliability in recognizing 6 arm gestures. The results show that the system can recognize the 6 gestures with a success rate of 97.5%. The advantage of such a system is that it is easy to train by a layer, and can easily be implemented in real time after the initial training. [ABSTRACT FROM AUTHOR]

The purpose of this article is to identify how principals shape the adoption and implementation of professional learning communities. The study employed a sequential mixed-methods approach in which interviews, observations, and document analysis informed survey design. Teachers were surveyed in four elementary schools about the practices and supports they received in grade-level professional learning communities. Qualitative and survey data reveal that principals influence both what teachers undertake in professional learning communities and how well they carry out these activities. The study was limited to a small sample of only four schools in two districts and relied primarily on principal and teacher self-reports. More work is needed to explore the role of principals in a broader sample as well as the relationship between district and building leadership. Findings are discussed in terms of what actions principals can undertake to sustain meaningful professional communities. This article provides guidance on how principals can influence and support teacher collaboration. [ABSTRACT FROM AUTHOR]

This exploration of principal learning mechanisms (PLM) to support a learning-centered school aimed to develop, field-test, and validate a PLM-measuring instrument. Following exploratory and confirmatory factor analyses of items to examine factorial validity, the developed scale was correlated with other work-related established constructs (e.g., principal’s instructional leadership, teacher’s organizational commitment). Findings revealed that the four-factor model (Storing and retrieving, Receiving, Disseminating, and Analyzing) was the best fit between the empirical results and the conceptual formulation. The PLM may prove an efficient tool for principals to assess how to promote learning in and by the organization. [ABSTRACT FROM AUTHOR]

The successful adoption of e-learning systems is mainly dependent on the learners' attitude and willingness to use them. This survey was conducted to investigate agricultural extension workers' attitudes toward using e-learning for on-the-job training in Iran and factors which affect it. Using the stratified sampling technique a sample of 379 extension workers were selected from six provinces. A structured questionnaire was used to collect data through an interview method. Findings show that extension workers' attitude toward e-learning is generally positive. Extension workers' knowledge of elearning, access to technical support, and their motivation influence their attitude toward the use of e-learning for on-the job training. Therefore, recommendations are provided to promote the experts' motivation, knowledge and to improve infrastructures. [ABSTRACT FROM AUTHOR]

A vision-based 3D tracking of articulated human hand is one of the major issues in the applications of human computer interactions and understanding the control of robot hand. This paper presents an improved approach for tracking and recovering the 3D position and orientation of a human hand using the Kinect sensor. The basic idea of the proposed method is to solve an optimization problem that minimizes the discrepancy in 3D shape between an actual hand observed by Kinect and a hypothesized 3D hand model. Since each of the 3D hand pose has 23 degrees of freedom, the hand articulation tracking needs computational excessive burden in minimizing the 3D shape discrepancy between an observed hand and a 3D hand model. For this, we first created a 3D hand model which represents the hand with 17 different parts. Secondly, Random Forest classifier was trained on the synthetic depth images generated by animating the developed 3D hand model, which was then used for Haar-like feature-based classification rather than performing per-pixel classification. Classification results were used for estimating the joint positions for the hand skeleton. Through the experiment, we were able to prove that the proposed method showed improvement rates in hand part recognition and a performance of 20-30 fps. The results confirmed its practical use in classifying hand area and successfully tracked and recovered the 3D hand pose in a real time fashion. [ABSTRACT FROM AUTHOR]

Rare event learning has not been actively researched since lately due to the unavailability of algorithms which deal with big samples. The research addresses spatio-temporal streams from multi-resolution sensors to find actionable items from a perspective of real-time algorithms. This computing framework is independent of the number of input samples, application domain, labelled or label-less streams. A sampling overlap algorithm such as Brooks-Iyengar is used for dealing with noisy sensor streams. We extend the existing noise pre-processing algorithms using Data-Cleaning trees. Pre-processing using ensemble of trees using bagging and multi-target regression showed robustness to random noise and missing data. As spatio-temporal streams are highly statistically correlated, we prove that a temporal window based sampling from sensor data streams converges after n samples using Hoeffding bounds. Which can be used for fast prediction of new samples in real-time. The Data-cleaning tree model uses a nonparametric node splitting technique, which can be learned in an iterative way which scales linearly in memory consumption for any size input stream. The improved task based ensemble extraction is compared with non-linear computation models using various SVM kernels for speed and accuracy. We show using empirical datasets the explicit rule learning computation is linear in time and is only dependent on the number of leafs present in the tree ensemble. The use of unpruned trees (t) in our proposed ensemble always yields minimum number (m) of leafs keeping pre-processing computation to n x t logm compared to N² for Gram Matrix. We also show that the task based feature induction yields higher Qualify of Data (QoD) in the feature space compared to kernel methods using Gram Matrix. [ABSTRACT FROM AUTHOR]

Traditionally, affective computing usually focuses on individual's affective dynamics instead of buildups of those of groups from a holistic perspective. Practically, the forms of group decision makers' preferences associated with multi-attribute decision-making problems are too complex to calculate programs' orders by judgment matrix, suffering difficulties in achieving the weights of sub-attributes based on the group judgment preferences. Currently, few researches are concerned with the definitions and generating methods of group affective preferences from the perspective of affective dynamics. In response to these challenges, this paper explicitly presents a stimulated and transferring affective computing model, along with the definition of group affective preferences and the interactive generating methods, which can gradually grasp group's experience in group decision making and help reduce group's subjective fatigue and make decisions more quickly. To exemplify applications of the proposed methods for a kind of multi-attribute decision-making problems, a test function and a chemical process control issue are investigated, giving rise to satisfied results and showing validity of the contribution. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a hand gesture recognition method using concentric with the coordinate information. Hand, the image of the area who entered through the camera through the binarization task and the change in the color space to extract the skin area was to determine forming a circle with the center of the center of the hand region to obtain the change of the input data. The circle and measure the similarity of the two concentric circles of different sizes. Concentric with coordinate information through image processing than the existing recognizer and the recognition through learning process is possible using a hand gesture recognition gesture. [ABSTRACT FROM AUTHOR]