Search results for: tracking task

Authors: Po-Fang Hsu, Chiching Wei

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In this paper, we present a novel neural graph matching approach applied to document comparison. Document comparison is a common task in the legal and financial industries. In some cases, the most important differences may be the addition or omission of words, sentences, clauses, or paragraphs. However, it is a challenging task without recording or tracing the whole edited process. Under many temporal uncertainties, we explore the potentiality of our approach to proximate the accurate comparison to make sure which element blocks have a relation of edition with others. In the beginning, we apply a document layout analysis that combines traditional and modern technics to segment layouts in blocks of various types appropriately. Then we transform this issue into a problem of layout graph matching with textual awareness. Regarding graph matching, it is a long-studied problem with a broad range of applications. However, different from previous works focusing on visual images or structural layout, we also bring textual features into our model for adapting this domain. Specifically, based on the electronic document, we introduce an encoder to deal with the visual presentation decoding from PDF. Additionally, because the modifications can cause the inconsistency of document layout analysis between modified documents and the blocks can be merged and split, Sinkhorn divergence is adopted in our neural graph approach, which tries to overcome both these issues with many-to-many block matching. We demonstrate this on two categories of layouts, as follows., legal agreement and scientific articles, collected from our real-case datasets.

Keywords: document comparison, graph matching, graph neural network, modification similarity, multi-modal

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Alexander Wachtel, Michael T. Franzen, Walter F. Tichy

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Programming requires years of training. With natural language and end user development methods, programming could become available to everyone. It enables end users to program their own devices and extend the functionality of the existing system without any knowledge of programming languages. In this paper, we describe an Interactive Spreadsheet Processing Module (ISPM), a natural language interface to spreadsheets that allows users to address ranges within the spreadsheet based on inferred table schema. Using the ISPM, end users are able to search for values in the schema of the table and to address the data in spreadsheets implicitly. Furthermore, it enables them to select and sort the spreadsheet data by using natural language. ISPM uses a machine learning technique to automatically infer areas within a spreadsheet, including different kinds of headers and data ranges. Since ranges can be identified from natural language queries, the end users can query the data using natural language. During the evaluation 12 undergraduate students were asked to perform operations (sum, sort, group and select) using the system and also Excel without ISPM interface, and the time taken for task completion was compared across the two systems. Only for the selection task did users take less time in Excel (since they directly selected the cells using the mouse) than in ISPM, by using natural language for end user software engineering, to overcome the present bottleneck of professional developers.

Keywords: natural language processing, natural language interfaces, human computer interaction, end user development, dialog systems, data recognition, spreadsheet

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: B. Vadiraj, S. N. Omkar, B. Kapil Bharadwaj, Yash Vardhan Gupta

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During manned exploration of space, missions will require astronaut crewmembers to perform Extra Vehicular Activities (EVAs) for a variety of tasks. These EVAs take place after long periods of operations in space, and in and around unique vehicles, space structures and systems. Considering the remoteness and time spans in which these vehicles will operate, EVA system operations should utilize common worksites, tools and procedures as much as possible to increase the efficiency of training and proficiency in operations. All of the preparations need to be carried out based on studies of astronaut motions. Until now, development and training activities associated with the planned EVAs in Russian and U.S. space programs have relied almost exclusively on physical simulators. These experimental tests are expensive and time consuming. During the past few years a strong increase has been observed in the use of computer simulations due to the fast developments in computer hardware and simulation software. Based on this idea, an effort to develop a computational simulation system to model human dynamic motion for EVA is initiated. This study focuses on the simulation of an astronaut moving the orbital replaceable units into the worksites or removing them from the worksites. Our physics-based methodology helps fill the gap in quantitative analysis of astronaut EVA by providing a multisegment human arm model. Simulation work described in the study improves on the realism of previous efforts, incorporating joint stops to account for the physiological limits of range of motion. To demonstrate the utility of this approach human arm model is simulated virtually using ADAMS/LifeMOD® software. Kinematic mechanism for the astronaut’s task is studied from joint angles and torques. Simulation results obtained is validated with numerical simulation based on the principles of Newton-Euler method. Torques determined using mathematical model are compared among the subjects to know the grace and consistency of the task performed. We conclude that due to uncertain nature of exploration-class EVA, a virtual model developed using multibody dynamics approach offers significant advantages over traditional human modeling approaches.

Keywords: extra vehicular activity, biomechanics, inverse kinematics, human body modeling

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Authors: Mariya V. Yanyukina, Michael A. Bolotov

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Assembling accuracy is the degree of accordance between the actual values of the parameters obtained during assembly, and the values specified in the assembly drawings and technical specifications. However, the assembling accuracy depends not only on the quality of the production process but also on the correctness of the assembly process. Therefore, preliminary calculations of assembly stages are carried out to verify the correspondence of real geometric parameters to their acceptable values. In the aviation industry, most calculations involve interacting dimensional chains. This greatly complicates the task. Solving such problems requires a special approach. The purpose of this article is to carry out the problem of improving the technology of assembly of aviation units by use of computer calculations. One of the actual examples of the assembly unit, in which there is an interacting dimensional chain, is the turbine wheel of gas turbine engine. Dimensional chain of turbine wheel is formed by geometric parameters of disk and set of blades. The interaction of the dimensional chain consists in the formation of two chains. The first chain is formed by the dimensions that determine the location of the grooves for the installation of the blades, and the dimensions of the blade roots. The second dimensional chain is formed by the dimensions of the airfoil shroud platform. The interaction of the dimensional chain of the turbine wheel is the interdependence of the first and second chains by means of power circuits formed by a plurality of middle parts of the turbine blades. The timeliness of the calculation of the dimensional chain of the turbine wheel is the need to improve the technology of assembly of this unit. The task at hand contains geometric and mathematical components; therefore, its solution can be implemented following the algorithm: 1) research and analysis of production errors by geometric parameters; 2) development of a parametric model in the CAD system; 3) creation of set of CAD-models of details taking into account actual or generalized distributions of errors of geometrical parameters; 4) calculation model in the CAE-system, loading of various combinations of models of parts; 5) the accumulation of statistics and analysis. The main task is to pre-simulate the assembly process by calculating the interacting dimensional chains. The article describes the approach to the solution from the point of view of mathematical statistics, implemented in the software package Matlab. Within the framework of the study, there are data on the measurement of the components of the turbine wheel-blades and disks, as a result of which it is expected that the assembly process of the unit will be optimized by solving dimensional chains.

Keywords: accuracy, assembly, interacting dimension chains, turbine

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Authors: Ktiri Fouad

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Objectives: The present study examined how the polyvalent nursing students of the Higher Institute of Nursing Professions and Health Techniques (ISPITS-Rabat-Morocco) conceived the term "feeling stressed.” We checked whether they were referring to a specific type of sensation (emotional, mental, physical) or both or all of them when they said they were stressed at the time they felt it. Materials and methods: A quantitative cross-sectional study was conducted among students of the three years of polyvalent nursing courses. Using a 7-Likert scale, the students were asked to assess their states of stress and the emotional, mental and physical sensations they were experiencing before and after carrying out a mental arithmetic task. An ordinal logistic regression method was used to investigate the association between the states of stress and the 3 types of sensations. Results: 222 polyvalent nursing students out of 307 were included in the experience. Their increased perceived states of stress after carrying out the mental task were found to be significantly associated with emotional distress and mental fatigue and not with physical tiredness. The mental sensation (mental fatigue) was found to have more effects in predicting the likelihood of feeling stressed. In addition, the lower the intensity of emotional or mental sensation, the more likely the students were to experience stress, given that one of both sensations is held constant, whatever the intensity of the physical sensation. We conclude that the polyvalent nursing students refer to mental fatigue and emotional distress and not to physical tiredness when they say they felt stressed, the mental fatigue having more effects. The implications of the study are discussed.

Keywords: feeling stressed”, emotional sensation, mental sensation, physical sensation

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Authors: Marwa Ahmed Abd El Hamied

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In this paper In this paper, a new technique based on Artificial Immunity System (AIS) technique has been developed to track Maximum Power Point (MPP). AIS system is implemented in a photovoltaic system that is subjected to variable temperature and insulation condition. The proposed novel is simulated using Mat Lab program. The results of simulation have been compared to those who are generated from Observation Controller. The proposed model shows promising results as it provide better accuracy comparing to classical model.

Keywords: component, artificial immunity technique, solar energy, perturbation and observation, power based methods

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Authors: Jean Ware, Susan W. Jones

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Background: The benefits of grammar instruction in the teaching of writing is contested in most English speaking countries. A majority of Anglophone countries abandoned the teaching of grammar in the 1950s based on the conclusions that it had no positive impact on learners’ development of reading, writing, and language. Although the decontextualised teaching of grammar is not helpful in improving writing, a curriculum with a focus on grammar in an embedded and meaningful way can help learners develop their understanding of the mechanisms of language. Although British learners are generally not taught grammar rules explicitly, learners in schools in France, the Netherlands, and Germany are taught explicitly about the structure of their own language. Exposing learners to grammatical analysis can help them develop their understanding of language. Indeed, if learners are taught that each part of speech has an identified role in the sentence. This means that rather than have to memorise lists of words or spelling patterns, they can focus on determining each word or phrase’s task in the sentence. These processes of categorisation and deduction are higher order thinking skills. When considering definitions of dyslexia available in Great Britain, the explicit teaching of grammar in context could help learners with persistent literacy difficulties. Indeed, learners with dyslexia often develop strengths in problem solving; the teaching of grammar could, therefore, help them develop their understanding of language by using analytical and logical thinking. Aims: This study aims at gaining a further understanding of how the explicit teaching of grammar in context can benefit learners with persistent literacy difficulties. The project is designed to identify ways of adapting existing grammar focussed teaching materials so that learners with specific learning difficulties such as dyslexia can use them to further develop their writing skills. It intends to improve educational practice through action, analysis and reflection. Research Design/Methods: The project, therefore, uses an action research design and multiple sources of evidence. The data collection tools used were standardised test data, teacher assessment data, semi-structured interviews, learners’ before and after attempts at a writing task at the beginning and end of the cycle, documentary data and lesson observation carried out by a specialist teacher. Existing teaching materials were adapted for use with five Year 9 learners who had experienced persistent literacy difficulties from primary school onwards. The initial adaptations included reducing the amount of content to be taught in each lesson, and pre teaching some of the metalanguage needed. Findings: Learners’ before and after attempts at the writing task were scored by a colleague who did not know the order of the attempts. All five learners’ scores were higher on the second writing task. Learners reported that they had enjoyed the teaching approach. They also made suggestions to be included in the second cycle, as did the colleague who carried out observations. Conclusions: Although this is a very small exploratory study, these results suggest that adapting grammar focused teaching materials shows promise for helping learners with persistent literacy difficulties develop their writing skills.

Keywords: explicit teaching of grammar in context, literacy acquisition, persistent literacy difficulties, writing skills

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Authors: Sara Corvino

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The aim of this study is to explore the potential of inclusive learning and assessment strategies to foster students' engagement with historical debates surrounding the field of graphic design. The goal is to respond to the diversity of L4 Graphic Design students, at Nottingham Trent University, in a way that instead of 'lowering standards' can benefit everyone. This research tests, measures, and evaluates the impact of a specific intervention, an assessment task, to develop students' critical visual analysis skills and stimulate a deeper engagement with the subject matter. Within the action research approach, this work has followed a case study research method to understand students' views and perceptions of a specific project. The primary methods of data collection have been: anonymous electronic questionnaire and a paper-based anonymous critical incident questionnaire. NTU College of Business Law and Social Sciences Research Ethics Committee granted the Ethical approval for this research in November 2019. Other methods used to evaluate the impact of this assessment task have been Evasys's report and students' performance. In line with the constructivist paradigm, this study embraces an interpretative and contextualized analysis of the collected data within the triangulation analytical framework. The evaluation of both qualitative and quantitative data demonstrates that active learning strategies and the disruption of thinking patterns can foster greater students' engagement and can lead to meaningful learning.

Keywords: active learning, assessment for learning, graphic design, higher education, student engagement

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Authors: Asowata Osamede

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Optimized gain in respect to output power of stand-alone photovoltaic (PV) systems is one of the major focus of PV in recent times. This is evident to its low carbon emission and efficiency. Power failure or outage from commercial providers in general does not promote development to the public and private sector, these basically limit the development of industries. The need for a well-structured PV system is of importance for an efficient and cost-effective monitoring system. The purpose of this paper is to validate the maximum power point of an off-grid PV system taking into consideration the most effective tilt and orientation angles for PV's in the southern hemisphere. This paper is based on analyzing the system using a solar charger with MPPT from a pulse width modulation (PWM) perspective. The power conditioning device chosen is a solar charger with MPPT. The practical setup consists of a PV panel that is set to an orientation angle of 0o north, with a corresponding tilt angle of 36 o, 26o and 16o. The load employed in this set-up are three Lead Acid Batteries (LAB). The percentage fully charged, charging and not charging conditions are observed for all three batteries. The results obtained in this research is used to draw the conclusion that would provide a benchmark for researchers and scientist worldwide. This is done so as to have an idea of the best tilt and orientation angles for maximum power point in a basic off-grid PV system. A quantitative analysis would be employed in this research. Quantitative research tends to focus on measurement and proof. Inferential statistics are frequently used to generalize what is found about the study sample to the population as a whole. This would involve: selecting and defining the research question, deciding on a study type, deciding on the data collection tools, selecting the sample and its size, analyzing, interpreting and validating findings Preliminary results which include regression analysis (normal probability plot and residual plot using polynomial 6) showed the maximum power point in the system. The best tilt angle for maximum power point tracking proves that the 36o tilt angle provided the best average on time which in turns put the system into a pulse width modulation stage.

Keywords: power-conversion, meteonorm, PV panels, DC-DC converters

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Authors: Adam Jenkins

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The Maritime RobotX Challenge provides a platform for postgraduate students conducting research in autonomous robotic systems to participate in an international competition. Although targeted to postgraduate students, the problem domain lends itself to a wide range of different levels of student expertise. In 2022, undergraduate Information Technology students from the University of South Australia undertook the challenge, utilizing a System of the Systems approach to the project's architecture. Each student group produced an independent solution to an identified task, which was then implemented on a Single Board Computer (SBC). A Central Control System then engaged each solution when appropriate, allowing the encapsulated SBC systems to manage each task as it was encountered. This approach facilitated collaboration among the multiple independent student teams over an 18-month period, and the fundamental system-agnostic architecture allowed for both the variance in student solutions and the limitations caused by the global electronics shortage. By adopting this approach, Information Technology teams were able to work independently yet produce an effective solution, leveraging their expertise to develop and construct an autonomous catamaran capable of meeting the competition's demanding requirements while producing a high level of engagement. The System of Systems approach is recommended to other universities interested in competing at this level and engaging students in a real-world problem.

Keywords: case study, robotics, education, programming, system of systems, multi-disciplinary collaboration

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Paul E. Olsen

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Researchers, businesses, and governments study the glass ceiling faced by women and members of minority groups at work, but the experiences of gay men, lesbians, and bisexual men and women with the lavender ceiling have not received similar attention. This qualitative research traces similarities between the lavender ceiling and the glass ceiling. More specifically, it presents a study designed to elucidate the experiences of gay men at work and compare them with those of women and minority group members, as reported in research literature on the glass ceiling. This research asked: 1) What have gay men experienced in the workplace? 2) What experiences have they had with recruitment, mentors, corporate climate, advancement opportunities, performance evaluation, social activities, harassment, and task force and committee assignments? 3) How do these experiences compare with those of women and minorities who have described their experiences with the glass ceiling? Purposeful and convenience sampling were used as participant selection strategies. Participants were diverse in terms of age, education, and industry. Data for this study were collected through semi-structured individual interviews with eight self-identified gay men working in human services, manufacturing, marketing, finance, government, the nonprofit sector, and retail. The gay men in the study described workplace experiences similar to descriptions of the glass ceiling faced by women and minorities. The lavender ceiling parallels the glass ceiling in corporate climates, harassment, mentors, social activities, promotions and performance appraisal, and task force and committee assignments at work. Women and most minorities do not, however, face the disclosure dilemma: Should one reveal his sexual orientation at work?

Keywords: discrimination, diversity, gay and lesbian, human resource

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Authors: Eric Granholm, Christophe Delay, Jason Holden, Peter Link

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Negative symptoms are an important unmet treatment needed for schizophrenia. We conducted an open trial of a novel blended intervention called mobile-assisted cognitive behavior therapy for negative symptoms (mCBTn). mCBTn is a weekly group therapy intervention combining in-person and smartphone-based CBT (CBT2go app) to improve experiential negative symptoms in people with schizophrenia. Both the therapy group and CBT2go app included recovery goal setting, thought challenging, scheduling of pleasurable activities and social interactions, and pleasure savoring interventions to modify defeatist attitudes, a target mechanism associated with negative symptoms, and improve experiential negative symptoms. We tested whether participants with schizophrenia or schizoaffective disorder (N=31) who met prospective criteria for persistent negative symptoms showed improvement in experiential negative symptoms. Retention was excellent (87% at 18 weeks) and severity of defeatist attitudes and motivation and pleasure negative symptoms declined significantly in mCBTn with large effect sizes. We also tested whether pupillary responses, a measure of cognitive effort, predicted improvement in negative symptoms mCBTn. Pupillary responses were recorded at baseline using a Tobii pupillometer during the digit span task with 3-, 6- and 9-digit spans. Mixed models showed that greater dilation during the task at baseline significantly predicted a greater reduction in experiential negative symptoms. Pupillary responses may provide a much-needed prognostic biomarker of which patients are most likely to benefit from CBT. Greater pupil dilation during a cognitive task predicted greater improvement in experiential negative symptoms. Pupil dilation has been linked to motivation and engagement of executive control, so these factors may contribute to benefits in interventions that train cognitive skills to manage negative thoughts and emotions. The findings suggest mCBTn is a feasible and effective treatment for experiential negative symptoms and justify a larger randomized controlled clinical trial. The findings also provide support for the defeatist attitude model of experiential negative symptoms and suggest that mobile-assisted interventions like mCBTn can strengthen and shorten intensive psychosocial interventions for schizophrenia.

Keywords: cognitive-behavioral therapy, mobile interventions, negative symptoms, pupillometry schizophrenia

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Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

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Authors: Erin Curtis, Avraham Schwiger

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Neuropsychological testing and evaluation is a crucial step in providing patients with effective diagnoses and treatment while in clinical care. The variety of batteries used in these evaluations can help clinicians better understand the nuanced declivities in a patient’s cognitive, behavioral, or emotional functioning, consequently equipping clinicians with the insights to make intentional choices about a patient’s care. Despite the knowledge these batteries can yield, some aspects of neuropsychological testing remain largely inaccessible to certain patient groups as a result of fundamental cultural, educational, or social differences. One such battery includes the Dot Counting Test (DCT), during which patients are required to count a series of dots on a page as rapidly and accurately as possible. As the battery progresses, the dots appear in clusters that are designed to be easily multiplied. This task evaluates a patient’s cognitive functioning, attention, and level of effort exerted on the evaluation as a whole. However, there is evidence to suggest that certain social groups, particularly Latinx groups, may perform worse on this task as a result of cultural or educational differences, not reduced cognitive functioning or effort. As such, this battery fails to account for baseline differences among patient groups, thus creating questions surrounding the accuracy, generalizability, and value of its results. Accessibility and cultural sensitivity are critical considerations in the testing and treatment of marginalized groups, yet have been largely ignored in the literature and in clinical settings to date. Implications and improvements to applications are discussed.

Keywords: culture, latino, neuropsychological assessment, neuropsychology, accessibility

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Authors: Chih-Chiang Hua, Yi-Hsiung Fang, Cyuan-Jyun Wong

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An improved PV balancer for photovoltaic applications is proposed in this paper. The proposed PV balancer senses the voltage and current of PV module and adjusts the output voltage of converter. Thus, the PV system can implement maximum power point tracking (MPPT) independently for each module whether it is under shading, different irradiation or degradation of PV cell. In addition, the cost of PV balancer can be reduced due to the low power rating of converter. To assess the effectiveness of the proposed system, two PV balancers are designed and verified through simulation under different shading conditions. The proposed PV balancers can provide more energy than the traditional PV balancer.

Keywords: MPPT, partial shading, PV System, converter

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Authors: Arwa Alzughaibi

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Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Khelifa Benahmed, Tarek Benahmed

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There are diverse applications of wireless sensor networks (WSNs) in the real world, typically invoking some kind of monitoring, tracking, or controlling activities. In an application, a WSN is deployed over the area of interest to sense and detect the events and collect data through their sensors in a geographical area and transmit the collected data to a Base Station (BS). This paper presents an overview of the research solutions available in the field of environmental monitoring applications, more precisely the problems of critical area monitoring using wireless sensor networks.

Keywords: critical infrastructure monitoring, environment monitoring, event region detection, wireless sensor networks

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Authors: S. Jonsson, D. Millard, C. Bokhove

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Smartphones are ubiquitous and frequently used as learning tools, which makes the design of educational apps an important area of research. A key issue is designing apps to encourage engagement while maintaining a focus on the educational aspects of the app. Flow experience is a promising method for addressing this issue, which refers to a mental state of cognitive absorption and positive emotion. Flow experience has been shown to be associated with positive emotion and increased learning performance. Studies have shown that immediate feedback is an antecedent to Flow. This experiment investigates the effect of immediate feedback on Flow experience. An app teaching Spanish phrases was developed, and 30 participants completed both a 10min session with immediate feedback and a 10min session with delayed feedback. The app contained a task where the user assembles Spanish phrases by pressing bricks with Spanish words. Immediate feedback was implemented by incorrect bricks recoiling, while correct brick moved to form part of the finished phrase. In the delayed feedback condition, the user did not know if the bricks they pressed were correct until the phrase was complete. The level of Flow experienced by the participants was measured after each session using the Flow Short Scale. The results showed that higher levels of Flow were experienced in the immediate feedback session. It was also found that 14 of the participants indicated that the demands of the task were ‘just right’ in the immediate feedback session, while only one did in the delayed feedback session. These results have implications for how to design educational technology and opens up questions for how Flow experience can be used to increase performance and engagement.

Keywords: feedback timing, flow experience, L2 language learning, mobile learning

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Authors: Seyed Roozbeh Pishva, Alireza Aboudi Asl

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In this investigation a hydrocyclone by using for separation particles from fluid in oil and gas, mining and other industries is simulated. Case study is cone – cylindrical and solid - liquid hydrocyclone. The fluid is water and the solid is a type of silis having diameters of 53, 75, 106, 150, 212, 250, and 300 micron. In this investigation CFD method used for analysis flow and movement of particles in hydrocyclone. In this modeling flow is three-dimention, turbulence and RSM model have been used for solving. Particles are three dimensional, spherical and non rotating and for tracking them Lagrangian model is used. The results of this study in addition to analyzing flowfield, obtaining efficiency of hydrocyclone in 5, 7, 12, and 15 percent concentrations and compare them with experimental result that both of them had suitable agreement with each other.

Keywords: hydrocyclone, RSM Model, CFD, copper industry

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Authors: Rebecca Hafner, David Elmes, Daniel Read

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The current research applies decision-making theory to the problem of increasing uptake of energy efficient technologies in the market place, where uptake is currently slower than one might predict following rational choice models. We apply the alignable/non-alignable features effect and explore the impact of varying information structure on the consumers’ preference for standard versus energy efficient technologies. In two studies we present participants with a choice between similar (boiler vs. boiler) vs. dissimilar (boiler vs. heat pump) technologies, described by a list of alignable and non-alignable attributes. In study One there is a preference for alignability when options are similar; an effect mediated by an increased tendency to infer missing information is the same. No effects of alignability on preference are found when options differ. One explanation for this split-shift in attentional focus is a change in construal levels potentially induced by the added consideration of environmental concern. Study two was designed to explore the interplay between alignability and construal level in greater detail. We manipulated construal level via a thought prime task prior to taking part in the same heating systems choice task, and find that there is a general preference for non-alignability, regardless of option type. We draw theoretical and applied implications for the type of information structure best suited for the promotion of energy efficient technologies.

Keywords: alignability effects, decision making, energy-efficient technologies, sustainable behaviour change

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Authors: Hsing Yuan Liu

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Background: Considerable theoretical and empirical work has identified a relationship between collaboration interactions and creativity in an organizational context. The mechanisms underlying this link, however, are not well understood in healthcare education. Objectives: The aims of this study were to explore the impact of collaboration interactions on team creativity and its underlying mechanism and to verify a moderated mediation model. Design, setting, and participants: This study utilized a cross-sectional, quantitative, descriptive design. The survey data were collected from 177 nursing students who enrolled in 18-week capstone courses of small interdisciplinary groups collaborating to design healthcare products in Taiwan during 2018 and 2019. Methods: Questionnaires assessed the nursing students' perceptions about their teams' swift trust (of cognition- and affect-based), conflicts (of task, process, and relationship), interaction behaviors (constructive controversy, helping behaviors, and spontaneous communication), and creativity. This study used descriptive statistics to compare demographics, swift trust scores, conflict scores, interaction behavior scores, and creativity scores for interdisciplinary teams. Data were analyzed using Pearson’s correlation coefficient and simple and hierarchical multiple regression models. Results: Pearson’s correlation analysis showed the cognition-based team swift trust was positively correlated with team creativity. The mediation model indicated constructive controversy fully mediated the effect of cognition-based team swift trust on student teams’ creativity. The moderated mediation model indicated that task conflict negatively moderates the mediating effect of the constructive controversy on the link between cognition-based team swift trust and team creativity. Conclusion: Our findings suggest nursing student teams’ interaction behaviors and task conflict are crucial mediating and moderated mediation variables on the relationship between collaboration interactions and team creativity, respectively. The empirical data confirms the validity of our proposed moderated mediation models of team creativity. Therefore, this study's validated moderated mediation model could provide guidance for nursing educators to improve collaboration interaction outcomes and creativity on nursing student teams.

Keywords: team swift trust, team conflict, team interaction behavior, moderated mediating effects, interdisciplinary education, nursing students

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Authors: Hajara Abdulkarim Aliyu, Abdulbasid Ismail Isa

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This research paper studies electrohydraulic system for its role in position and motion control system and develops as mathematical model describing the behaviour of the system. The research further proposes Fuzzy logic and conventional PID controllers in order to achieve both accurate positioning of the payload and overall improvement of the system performance. The simulation result shows Fuzzy logic controller has a superior tracking performance and high disturbance rejection efficiency for its shorter settling time, less overshoot, smaller values of integral of absolute and deviation errors over the conventional PID controller at all the testing conditions.

Keywords: electrohydraulic, fuzzy logic, modelling, NZ-PID

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Authors: Eko Liao, Cheryl Zhang

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Employee job crafting refers to employee’s proactive behaviors of making customized changes to their jobs on cognitive, relationship, and task levels. Previous studies have investigated different situations triggering employee’s job crafting. However, much less is known about what would be the consequences for both employee themselves and their work groups. Guided by conservation of resources theory (COR), this study investigates how employees job crafting increases their objective task performance and promotive voice behaviors at work. It is argued that employee would gain more resources when they actively craft their job tasks, which in turn increase their job performance and encourage them to have more constructive speak-up behaviors. Specifically, employee’s psychological resources (i.e., job engagement) and relational resources (i.e., leader-member relationships) would be enhanced from effective crafting behaviors, because employees are more likely to regard their job tasks as meaningful, and their leaders would be more likely to notice and recognize their dedication at work when employees craft their job frequently. To test this research model, around 400 employees from various Chinese organizations from mainland China joins the two-wave data collection stage. Employee’s job crafting behaviors in three aspects are measured at time 1. Perception of resource gain (job engagement and leader-member exchange), voice, and job performance are measured at time 2. The research model is generally supported. This study contributes to the job crafting literature by broadening the theoretical lens to a resource-based perspective. It also has practical implications that organizations should pay more attention to employee crafting behaviors because they are closely related to employees in-role performance and constructive voice behaviors.

Keywords: job crafting, resource-based perspective, voice, job performance

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

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Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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Authors: Anxuan Xie, Chun-Chan Yu

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Survey evidence provides support that auditors can gain professional knowledge not only from client firms but also from teammates they work with. Furthermore, given that knowledge is accumulated in nature, along with the reality that auditors today must work in an environment of increased diversity, whether the attributes of teammates will influence the effects of knowledge sharing and accumulation and ultimately influence an audit partner’s audit quality should be interesting research issues. We test whether the gender of co-signers will moderate the effect of a lead partner’s cooperative experiences on financial restatements. Furthermore, if the answer is “yes”, we further investigate the underlying reasons. We use data from Taiwan because, according to Taiwan’s law, engagement partners, who are basically two certificate public accountants from the same audit firm, are required to disclose (i.e., sign) their names in the audit report of public companies since 1983. Therefore, we can trace each engagement partner’s historic direct cooperative (co-signing) records and get large-sample data. We find that the benefits of knowledge sharing manifest primarily via co-signing audit reports with audit partners of different gender from the lead engagement partners, supporting the argument that in an audit setting, accumulated gender-diverse working relationship is positively associated with knowledge sharing, and therefore improve lead engagements’ audit quality. This study contributes to the extant literature in the following ways. First, we provide evidence that in the auditing setting, the experiences accumulated from cooperating with teammates of a different gender from the lead partner can improve audit quality. Given that most studies find evidence of negative effects of surface-level diversity on team performance, the results of this study support the prior literature that the association between diversity and knowledge sharing actually hinges on the context (e.g., organizational culture, task complexity) and “bridge” (a pre-existing commonality among team members that can smooth the process of diversity toward favorable results) among diversity team members. Second, this study also provides practical insights with respect to the audit firms’ policy of knowledge sharing and deployment of engagement partners. For example, for audit firms that appreciate the merits of knowledge sharing, the deployment of auditors of different gender within an audit team can help auditors accumulate audit-related knowledge, which will further benefit the future performance of those audit firms. Moreover, nowadays, client firms also attach importance to the diversity of their engagement partners. As their policy goals, lawmakers and regulators also continue to promote a gender-diverse working environment. The findings of this study indicate that for audit firms, gender diversity will not be just a means to cater to those groups. Third, for audit committees or other stakeholders, they can evaluate the quality of existing (or potential) lead partners by tracking their co-signing experiences, especially whether they have gender-diverse co-signing experiences.

Keywords: co-signing experiences, audit quality, knowledge sharing, gender diversity

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Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

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Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

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Authors: Yonit Nissim, Eyal Weissblueth

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This research is the continuation of a process that began in 2010 with the goal of redesigning the training program for future early childhood teachers at the Ohalo College, to integrate technology and provide 21st-century skills. The article focuses on a study of the processes involved in developing a special educational unit which challenged students with the task of designing, planning and building an internet site for kindergartens. This project was part of their second-year studies in the early childhood track of an interdisciplinary course entitled 'Educating for the Future.' The goal: enabling students to gain experience in developing an internet site specifically for kindergartens, and gain familiarity with Google platforms, the acquisition and use of innovative skills and the integration of technology in pedagogy. Research questions examined how students handled the task of building an internet site. The study explored whether the guided process of building a site helped them develop proficiency in creativity, teamwork, evaluation and learning appropriate to the 21st century. The research tool was a questionnaire constructed by the researchers and distributed online to the students. Answers were collected from 50-course participants. Analysis of the participants’ responses showed that, along with the significant experience and benefits that students gained from building a website for kindergarten, ambivalence was shown toward the use of new, unfamiliar and complex technology. This attitude was characterized by unease and initial emotional distress triggered by the departure from routine training to an island of uncertainty. A gradual change took place toward the adoption of innovation with the help of empathy, training, and guidance from the instructors, leading to the students’ success in carrying out the task. Initial success led to further successes, resulting in a quality product and a feeling of personal competency among the students. A clear and extreme emotional shift was observed on the spectrum from a sense of difficulty and dissatisfaction to feelings of satisfaction, joy, competency and cognitive understanding of the importance of facing a challenge and succeeding. The findings of this study can contribute to increased understanding of the complex training process of future kindergarten teachers, coping with a changing world, and pedagogy that is supported by technology.

Keywords: early childhood teachers, educating for the future, emotions, kindergarten website

Procedia PDF Downloads 136