Miracle-dz/UniFAR-FTUs huggingface dataset:
Commentary: Teaching Games of Understanding (TGfU) coaching effects on Heart Rate among Malaysian and Indian Junior Hockey Players

Teaching Games for Understanding (TGfU) offers tactical-technical instruction is gaining international recognition for its ability to produce intelligent players via a problem-solving approach in game play such as hockey. However the effect of TGfU pedagogical approach through small side game play (SSG) towards physiology components of Heart Rate (HR) still takes a backseat compared to research on tactical decision making and skill execution that has been studied widely. SSG proposed in TGfU approach dwells around duration of game play (load), how fast the SSG game manouvers (intensity) and players cardiovascular fitness can be detected by HR tool and therefore HR crucial to be investigated. This quasi-experimental study investigated the effect of TGfU compared to skill mastery instruction, termed as Skill Drill Technical (SDT), among Malaysian and Indian elite junior hockey players in terms of SSG game play intensity via heart rate (HR) measurement at different points of game play. A total of n = 60 players with an average age of 15 ± 1.03 were selected via simple random technique from both countries involved in this study and assigned equally into groups, with 15 players per group for TGfU and for SDT across Malaysia and India. Gathered data were analysed using the ANOVA and ANCOVA techniques. There was significant higher warm-up HR bpm among players via TGfU compated to SDT across the two countries. Whereas HR bpm immediately after the 5 vs. 5 game play intervention and HR bpm after three minutes’ recovery, Indian players with TGfU recorded a higher and significant difference compared to SDT. However, in contrast, findings indicated no significant difference between these two instruction models among Malaysian player. Therefore, overall findings reiterated that TGfU is a useful approach for game play to enhance intensity and cardiac output through HR bpm measurement. In conclusion, future research can employ together HR and RPM (Borg Scale) or electronic device for more accurate reading coupled 6 sec and 15 sec HR readings. Future study, should too address the effect of TGfU on different variation of small sided game play intensity along skill execution and tactical decision making.
Compositional language processing for multilingual sentiment analysis

This dissertation presents new approaches in the field of sentiment analysis and polarity classification, oriented towards obtaining the sentiment of a phrase, sentence or document from a natural language processing point of view. It makes a special emphasis on methods to handle semantic composionality, i. e. the ability to compound the sentiment of multiword phrases, where the global sentiment might be different or even opposite to the one coming from each of their their individual components; and the application of these methods to multilingual scenarios. On the one hand, we introduce knowledge-based approaches to calculate the semantic orientation at the sentence level, that can handle different phenomena for the purpose at hand (e. g. negation, intensification or adversative subordinate clauses). On the other hand, we describe how to build machine learning models to perform polarity classification from a different perspective, combining linguistic (lexical, syntactic and semantic) knowledge, with an emphasis in noisy and micro-texts. Experiments on standard corpora and international evaluation campaigns show the competitiveness of the methods here proposed, in monolingual, multilingual and code-switching scenarios. The contributions presented in the thesis have potential applications in the era of the Web 2.0 and social media, such as being able to determine what is the view of society about products, celebrities or events, identify their strengths and weaknesses or monitor how these opinions evolve over time. We also show how some of the proposed models can be useful for other data analysis tasks.
Binocular rivalry : Central or peripheral selective processes?

The traditionally held notion that binocular rivalry reflects central selective processes that take effect subsequent to the analysis of both monocular stimuli contrasts with the currently popular view that the suppressed stimulus suffers inhibition, or blocking, at a relatively peripheral level. The available evidence supports the traditional approach. It is argued that although peripheral responses such as changes in pupil diameter or accommodation may be correlated with rivalry suppression, they may not be held responsible for the suppression itself. Similarly, processes of adaptation and contralateral inhibition are unable to explain binocular rivalry. There is evidence, however, that the suppressed stimulus in rivalry is being fully analyzed and evaluated. Perceptual experience is thereby shown to reflect processes over and above the analysis of sensory information, and binocular rivalry suggests itself as a useful context in which to isolate and investigate these processes.
Applying Unidimensional Models for Semiordered Data to Scale Data With Neutral Responses

The purpose of this study is to evaluate whether a recently developed semiordered model can be used to explore the functioning of neutral response options in rating scale data. Huggins-Manley, Algina, and Zhou developed a class of unidimensional models for semiordered data within scale items (i.e., items with both ordered response categories and an additional nominal response category) and found promising results when applying them to scale data with Not Applicable response categories. In this study, we extended the application of the semi–partial credit model (PCM) to evaluate whether the semi-PCM can be used to calibrate potentially unordered neutral responses in rating scale data, and if so, how the approach compares with alternate methods of dealing with the neutral response option. Findings indicate that the semi-PCM can (a) assist practitioners in evaluating the ordered or unordered nature of neutral responses and (b) provide a viable alternative for θ estimation in the presence of an unordered neutral category. The process used in this study also provides a methodological framework for researchers and practitioners to use when dealing with neutral responses in their own data.
Gender Inequality in Work Organizations

In this chapter, the author aims to present, through a review of literature, that the gender equality assumption of the human resource management (HRM) approach is not taken for granted. It seems there exist two sides of the same coin, one representing the HRM approach and the other representing the gendered approach to HRM practices. This chapter reviews HRM practices in work organizations as the potential facilitator of gender inequalities in organizations. In addition, the contentious function of HRM practices in maintaining gender inequalities within work organizations is reviewed. In spite of knowing the implication of HRM practices on being a gender-diverse organization, there remain few studies on the relationship between HRM practices and gender inequality in work organizations. Such research will add a different perspective to HRM practices and contribute to the awareness related to the gendered nature of organizations and their organizational practices.
Pose estimation of industrial objects towards robot operation

With the advantages of wide range, non-contact and high flexibility, the visual estimation technology of target pose has been widely applied in modern industry, robot guidance and other engineering practices. However, due to the influence of complicated industrial environment, outside interference factors, lack of object characteristics, restrictions of camera and other limitations, the visual estimation technology of target pose is still faced with many challenges. Focusing on the above problems, a pose estimation method of the industrial objects is developed based on 3D models of targets. By matching the extracted shape characteristics of objects with the priori 3D model database of targets, the method realizes the recognition of target. Thus a pose estimation of objects can be determined based on the monocular vision measuring model. The experimental results show that this method can be implemented to estimate the position of rigid objects based on poor images information, and provides guiding basis for the operation of the industrial robot.
Known Unknown: The Uncertainty and Inaccuracy of Consumer WearableDevices

The emergence of wearable technologies (e.g., smart watches, fitness trackers, smart clothing and jewelry) has enabled the widespread collection and tracking of data related to many aspects of health and human behavior. While self-tracking is most commonly used to support self-improvement and achievement of personal fitness goals, the process also can also enable better monitoring of physical activity, sleep, and other activities of interest among individuals with chronic medical conditions [1].
Ensuring Data Confidentiality and Authentication through Encryption at Application Layer

Cloud computing has emerged as a powerful and viable architecture to meet largescale and complex computational needs of the organizations. It extends the IT capability by providing on-demand access to computer resources for dedicated use. Data security and privacy are the major concerns over the cloud from user perspective. Consequently, the organizations which deal with cloud computing should amicably address the key data security risks. In this paper, a generic scheme of user authentication and data confidentiality has been introduced. We introduce a tool that encrypts/decrypts the user data at application layer using public key infrastructure. The information security experts of both the sides i.e. cloud users and service providers must comprehend and address the risk and security issues in detail before actually benefiting high-end computing power offered by the cloud computing paradigm.
Cultivating organizational compassion in healthcare

Abstract The compassion of healthcare workers towards patients is widely recognized, but research suggests a dearth of compassion among co-workers. Indeed, workplace bullying and negative employee outcomes are over-represented in the healthcare sector (including burnout and substantial staff turnover). In this paper, we discuss the cultivation of compassion for healthcare workers, using the lens of positive organizational scholarship. Our concern is not only with the individual level compassion (i.e. between employees), we also consider how compassion can be cultivated systemically across healthcare institutions at the organizational level. More specifically, we present a proposed Noticing, Empathising, Assessing and Responding Mechanisms Model of Organizational Compassion as a tool for consciously cultivating workplace compassion in healthcare organizations.
LINE-DRAWING ENHANCED INTERACTIVE MURAL RESTORATION FORDUNHUANG MOGAO GROTTOES

Abstract. Dunhuang Mogao Grottoes in western China is one of the most famous World Cultural Heritage Sites, known for its glorious Chinese Buddhist art spanning a period of 1,000 years. However, it has been suffering from damage and degradation caused by man-made and natural factors. In this article, we present a novel line-drawing enhanced interactive system for digital restoration of damaged murals in Mogao Grottoes. Our system consists of four components, namely data pre-processing, damaged area selection, line-drawing segmentation, and mural restoration. Each component is a hybrid of efficient algorithms and user interactions. We introduce the infrastructure and process of using our system, from data capture and collection, database establishment, to interactive restoration. We conduct a user study with 15 participants who have varied experiences with and skills on repairing murals and editing images. Results and feedback suggest that our system can achieve satisfactory restoration results without overburdening the users. It can benefit both experts trained in restoration and amateurs interested in cultural heritage conservation.
Evaluating emotion visualizations using AffectVis, an affect-aware dashboard for students

Purpose The purpose of this paper is to evaluate four visualizations that represent affective states of students. Design/methodology/approach An empirical-experimental study approach was used to assess the usability of affective state visualizations in a learning context. The first study was conducted with students who had knowledge of visualization techniques (n=10). The insights from this pilot study were used to improve the interpretability and ease of use of the visualizations. The second study was conducted with the improved visualizations with students who had no or limited knowledge of visualization techniques (n=105). Findings The results indicate that usability, measured by perceived usefulness and insight, is overall acceptable. However, the findings also suggest that interpretability of some visualizations, in terms of the capability to support emotional awareness, still needs to be improved. The level of students’ awareness of their emotions during learning activities based on the visualization interpretation varied depending on previous knowledge of information visualization techniques. Awareness was found to be high for the most frequently experienced emotions and activities that were the most frustrating, but lower for more complex insights such as interpreting differences with peers. Furthermore, simpler visualizations resulted in better outcomes than more complex techniques. Originality/value Detection of affective states of students and visualizations of these states in computer-based learning environments have been proposed to support student awareness and improve learning. However, the evaluation of visualizations of these affective states with students to support awareness in real life settings is an open issue.
A comparative study of sociality and prosociality in geladas, Theropithecus gelada, and mandrills, Mandrillus Sphinx

Sociality or group living has evolved independently in many animal taxa, but only in some of them it is based on social bonds between group members that are serviced through the exchange of a variety of social behaviours with multiple partners. This bonded sociality of nonhuman (and human) primates and of a few other taxa stands out for its reliance on prosociality or cooperation between individuals who typically know well one another and who engage in long-term, highly individualized partnerships. The patterns of sociality and prosociality observed in primates reflect trade-offs between several antagonistic but equally welfare- and fitness-enhancing activities and, ultimately, are the outcome of the way the individuals skilfully manage their inevitable conflicts of interest through strategies of aggressive competition, cooperation and post-conflict reconciliation. Contemporary theory on primate sociality and prosociality emphasizes the need for integrating socioecology (i.e., ecological, demographic and social factors), phylogeny (i.e., evolutionary history) and life history (i.e., life history traits) in any account of the proximate and ultimate causes of variation in primate social systems. The present research was aimed to study sociality and prosociality in two groups of African papionins, the gelada (Theropithecus gelada) or montane baboon and the mandrill (Mandrillus sphinx) or forest baboon, housed in rather similarly naturalized, sized and vegetated enclosures in captivity.
Procesos innovadores en las prácticas investigativas de los docentes

La investigación tuvo como propósito general conocer los procesos innovadores dentro de las practicas investigativas de los docentes; sustentada teóricamente en la opinión de autores como Hogg (2010), Castañeda (2005), Cámara de Comercio de Cali, (2014), así como los aportes de los informantes y del investigador. Desde el análisis de una investigación cualitativa, el desarrollo del estudio está en línea con el método hermenéutico interpretativo como camino para crear una teoría sustantiva, fundamentada en los procesos de enseñanza y aprendizaje de las prácticas investigativas de docentes; así como responder las incógnitas planteadas. La información se obtuvo mediante observaciones directas y entrevistas semiestructuradas a cuatro (4) sujetos, conformados por docentes, los cuales fueron escogidos por su antigüedad dentro de las instituciones. La fiabilidad de dicha población es relativa, al igual fue aplicada la técnica del análisis cualitativo de la triangulación. Entre las reflexiones finales se tuvo que los procesos innovadores dentro de las prácticas educativas docentes, tienen una íntima relación con el sector tecnológico, aun cuando los objetivos suelen ser difusos y estar en mutuo conflicto; los objetivos de corto plazo no están necesariamente de acuerdo con los de largo plazo, aunque es difícil descubrir los efectos no deseados de las innovaciones educativas. Es la inducción hacia cambios funcionales novedosos, es el volver a trabajar sobre campos de acción conocidos para aplicarlos a nuevas circunstancias, y la creación de nuevas formas de percibir y acercarse a los problemas.
The Subjective Experience of Children with Disruptive Behavior Problems as Reflected in “Person Picking an Apple from a Tree” Drawings

ABSTRACT This study administered the “Person Picking an Apple from a Tree” drawing task to inquire into the subjective experience of children with Disruptive Behavior Problems. A total of 40 4th-6th grade students from an elementary school in Crete participated: 20 children showed signs of Disruptive Behavior Problems according to their teacher’s reports, and the other 20 did not. The drawings and verbal narratives were analyzed using a qualitative method. Findings present differences in two central themes: the environment as a context was duller, and self-agency representations showed less agency and subjectivity in the first group. The discussion deals with the findings in terms of object relations and agency theories. Therapeutic implications, study limitations, and future research are also discussed.
Scan Context 3D Lidar Inertial Odometry via Iterated ESKF and Incremental K-Dimensional Tree

This paper focused on a 3D lidar inertial odometry algorithm framework that improves the LeGO-LOAM by constructing a new back-end optimization algorithm. In comparison with the LeGO-LOAM, the feature extraction and image projection processes are still the same. Two-step Levenberg Marquardt was replaced with an iterated ESKF method in the lidar odometry to produce a better initial pose for the robots, and the k-d tree method in the lidar mapping is replaced with the ikd-Tree method to ensure high performance mapping process in real time. In the loop closure, a scan context search method is added to better correct the algorithm’s final trajectory. We compare the improved algorithm with LeGO-LOAM and the two other methods, LIO-SAM and A-LOAM, using three datasets gathered from the Mulran dataset with different large-scale outdoor scenes. We show that the improved algorithm achieves similar or better accuracy in real-time than the other three algorithms.
(De)Mystifying the information and communication technology business model concept

Modern enterprises are currently experiencing volatile and rapid information and communication technology (ICT) change. A key challenge for business leaders is to ensure their organisations are ready for that change. This is particularly challenging when it comes to emerging ICT that may disrupt the management of existing enterprise information systems or business processes. The business model has been cited as an effective tool which organisations can use to prepare for ICT related change. However, there is evidence to suggest that the business model remains largely a nebulous concept to most organisations. This is compounded by the siloed nature of existing business model research. Using a content analysis research approach, this paper provides a holistic review of contemporary academic literature to ascertain and classify the various approaches to the study of ICT enabled business models. The literature examined is classified into nine specific thematic descriptors which underpin these specific business models. A comprehensive definition is also developed for ICT business models. This paper therefore extends our understanding of the business model concept and can be used to guide and coalesce future research on illuminating how organisations can operationalise effective business models in order to leverage new digital ICT.
The gender gap in work–life balance satisfaction across occupations

PurposeThe purpose of this study is to compare the gender gaps in work–life balance satisfaction across occupations. Due to data limitations, the studies of work–life balance satisfaction have generally relied on researcher collected data. As a result, large-scale studies encompassing all occupations in the same social and policy context are rare. In several cycles of the Canadian General Social Survey, the respondents are directly asked about their work–life balance (WLB) satisfaction. The present paper takes advantage of this unique opportunity to compare the gender gap in WLB satisfaction across occupations in Canada.Design/methodology/approachThis paper pools four cross-sectional datasets (N = 37,335). Multivariate regression analysis is used.FindingsWomen in management and education are found to have a lower WLB satisfaction than their male counterparts. Conversely, and rather surprisingly, a WLB satisfaction advantage is found for women in transport over males in this occupation. Further investigation shows that the female WLB advantage in transport is driven by the relatively low WLB satisfaction of males in this occupation, while the opposite is true for education.Social implicationsThe findings are discussed in light of the WLB policies and their increasing gender-blindness.Originality/valueThis paper is the first large-scale study which compares the gender gap in WLB satisfaction across occupations, in a given policy context.
Voice Liveness Detection using Constant-Q Transform-Based Features

In this work, we propose to use the Constant-Q transform (CQT)-based feature set for voice liveness detection (VLD), which can enhance the confidence in authenticity of the speaker in Automatic Speaker Verification (ASV) system. The live speaker can be characterized via his/her voice using the presence of the pop noise in the speech signal. Pop noise comes out as a burst and possesses the low frequency characteristics. In this paper, we present the modified CQT-based approach over the traditional Short-Time Fourier Transform (STFT)-based algorithm (baseline) for VLD. The experiments are performed on recently released POp noise COrpus (POCO) dataset with various statistical, discriminative, and deep learning-based classifiers, namely, Gaussian Mixture Models (GMMs), Support Vector Machine (SVM), Convolutional Neural Networks (CNN), and Light-CNN (LCNN), respectively. The significant improvement in performance is observed for the proposed CQT-based features over STFT-based features. Relatively best performance is obtained for CQT-LCNN architecture, which shows 81.93% accuracy on evaluation set. Furthermore, we analyzed the performance of the CNN and LCNN-based VLD systems for each word using proposed CQT-based vs. STFT-based baseline features.