Search results for: mobile game based learning

Authors: Matjaž Divjak, Simon Zelič, Aleš Holobar

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We present a dedicated video-based monitoring system for quantification of patient’s attention to visual feedback during robot assisted gait rehabilitation. Two different approaches for eye gaze and head pose tracking are tested and compared. Several metrics for assessment of patient’s attention are also presented. Experimental results with healthy volunteers demonstrate that unobtrusive video-based gaze tracking during the robot-assisted gait rehabilitation is possible and is sufficiently robust for quantification of patient’s attention and assessment of compliance with the rehabilitation therapy.

Keywords: video-based attention monitoring, gaze estimation, stroke rehabilitation, user compliance

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Authors: Tamar Bikashvili, Tamar Lordkipanidze, Ilia Lazrishvili

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Heavy metals remain one of serious environmental problems due to their toxic effects. The effect of arsenic and manganese compounds on rat behavior and neuromorphology was studied. Wistar rats were assigned to four groups: rats in control group were given regular water, while rats in other groups drank water with final manganese concentration of 10 mg/L (group A), 20 mg/L (group B) and final arsenic concentration 68 mg/L (group C), respectively, for a month. To study exploratory and anxiety behavior and also to evaluate aggressive performance in “home cage” rats were tested in “Open Field” and to estimate learning and memory status multi-branched maze was used. Statistically significant increase of motor and oriental-searching activity in experimental groups was revealed by an open field test, which was expressed in increase of number of lines crossed, rearing and hole reflexes. Obtained results indicated the suppression of fear in rats exposed to manganese. Specifically, this was estimated by the frequency of getting to the central part of the open field. Experiments revealed that 30-day exposure to 10 mg/ml manganese did not stimulate aggressive behavior in rats, while exposure to the higher dose (20 mg/ml), 37% of initially non-aggressive animals manifested aggressive behavior. Furthermore, 25% of rats were extremely aggressive. Obtained data support the hypothesis that excess manganese in the body is one of the immediate causes of enhancement of interspecific predatory aggressive and violent behavior in rats. It was also discovered that manganese intoxication produces non-reversible severe learning disability and insignificant, reversible memory disturbances. Studies of rodents exposed to arsenic also revealed changes in the learning process. As it is known, the distribution of metal ions differs in various brain regions. The principle manganese accumulation was observed in the hippocampus and in the neocortex, while arsenic was predominantly accumulated in nucleus accumbens, striatum, and cortex. These brain regions play an important role in the regulation of emotional state and motor activity. Histopathological analyzes of brain sections illustrated two morphologically distinct altered phenotypes of neurons: (1) shrunk cells with indications of apoptosis - nucleus and cytoplasm were very difficult to be distinguished, the integrity of neuronal cytoplasm was not disturbed; and (2) swollen cells - with indications of necrosis. Pyknotic nucleus, plasma membrane disruption and cytoplasmic vacuoles were observed in swollen neurons and they were surrounded by activated gliocytes. It’s worth to mention that in the cortex the majority of damaged neurons were apoptotic while in subcortical nuclei –neurons were mainly necrotic. Ultrastructural analyses demonstrated that all cell types in the cortex and the nucleus caudatus represent destructed mitochondria, widened neurons’ vacuolar system profiles, increased number of lysosomes and degeneration of axonal endings.

Keywords: arsenic, manganese, behavior, learning, neuron

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Authors: Ali Afaghi, Sehraneh Ghaemi

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The coordination of the multi-agent systems has been one of the interesting topic in recent years, because of its potential applications in many branches of science and engineering such as sensor networks, flocking, underwater vehicles and etc. In the most of the related studies, it is assumed that the dynamics of the multi-agent systems are integer-order and linear and the multi-agent systems with the fractional-order nonlinear dynamics are rarely considered. However many phenomena in nature cannot be described within integer-order and linear characteristics. This paper investigates the leader-following consensus problem for a class of nonlinear fractional-order multi-agent systems based on observer-based cooperative control. In the system, the dynamics of each follower and leader are nonlinear. For a multi-agent system with fixed directed topology firstly, an observer-based consensus protocol is proposed based on the relative observer states of neighboring agents. Secondly, based on the property of the stability theory of fractional-order system, some sufficient conditions are presented for the asymptotical stability of the observer-based fractional-order control systems. The proposed method is applied on a five-agent system with the fractional-order nonlinear dynamics and unavailable states. The simulation example shows that the proposed scenario results in the good performance and can be used in many practical applications.

Keywords: fractional-order multi-agent systems, leader-following consensus, nonlinear dynamics, directed graphs

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Authors: Reem El Chakik

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The levels of heavy metals in agricultural lands in Lebanon have been witnessing a noticeable increase in the past few years, due to increased anthropogenic pollution sources. Heavy metals pose a serious threat to the environment for being non-biodegradable and persistent, accumulating thus to dangerous levels in the soil. Besides the traditional laboratory and chemical analysis methods, Hyperspectral Imaging (HSI) has proven its efficiency in the rapid detection of HMs contamination. In Lebanon, a continuous environmental monitoring, including the monitoring of levels of HMs in agricultural soils, is lacking. This is due in part to the high cost of analysis. Hence, this proposed research aims at defining the current national status of HMs contamination in agricultural soil, and to evaluate the effectiveness of using HSI in the detection of HM in contaminated agricultural fields. To achieve the two main objectives of this study, soil samples were collected from different areas throughout the country and were analyzed for HMs using Atomic Absorption Spectrophotometry (AAS). The results were compared to those obtained from the HSI technique that was applied using Hyspex SWIR-384 camera. The results showed that the Lebanese agricultural soils contain high contamination levels of Zn, and that the more clayey the soil is, the lower reflectance it has.

Keywords: agricultural soils in Lebanon, atomic absorption spectrophotometer, hyperspectral imaging., heavy metals contamination

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Authors: Ali Abdrhman M. Ukasha

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Data security needed in data transmission, storage, and communication to ensure the security. The color image is decomposed into red, green, and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using a key image that has same original size and is generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours of color image recovery can be obtained with accepted level of distortion using Canny edge detector. Experiments have demonstrated that proposed algorithm can fully encrypt 2D color image and completely reconstructed without any distortion. It has shown that the color image can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: color image, wavelet transform, edge detector, Arnold transform, lossy image encryption

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Authors: Nawras Kurzom, Avi Mendelsohn

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The effects of background music on learning and memory are inconsistent, partly due to the intrinsic complexity and variety of music and partly to individual differences in music perception and preference. A prominent musical feature that is known to elicit strong emotional responses is musical tension. Musical tension can be brought about by building anticipation of rhythm, harmony, melody, and dynamics. Delaying the resolution of dominant-to-tonic chord progressions, as well as using dissonant harmonics, can elicit feelings of tension, which can, in turn, affect memory formation of concomitant information. The aim of the presented studies was to explore how forming declarative memory is influenced by musical tension, brought about within continuous music as well as in the form of isolated chords with varying degrees of dissonance/consonance. The effects of musical tension on long-term memory of declarative information were studied in two ways: 1) by evoking tension within continuous music pieces by delaying the release of harmonic progressions from dominant to tonic chords, and 2) by using isolated single complex chords with various degrees of dissonance/roughness. Musical tension was validated through subjective reports of tension, as well as physiological measurements of skin conductance response (SCR) and pupil dilation responses to the chords. In addition, music information retrieval (MIR) was used to quantify musical properties associated with tension and its release. Each experiment included an encoding phase, wherein individuals studied stimuli (words or images) with different musical conditions. Memory for the studied stimuli was tested 24 hours later via recognition tasks. In three separate experiments, we found positive relationships between tension perception and physiological measurements of SCR and pupil dilation. As for memory performance, we found that background music, in general, led to superior memory performance as compared to silence. We detected a trade-off effect between tension perception and memory, such that individuals who perceived musical tension as such displayed reduced memory performance for images encoded during musical tension, whereas tense music benefited memory for those who were less sensitive to the perception of musical tension. Musical tension exerts complex interactions with perception, emotional responses, and cognitive performance on individuals with and without musical training. Delineating the conditions and mechanisms that underlie the interactions between musical tension and memory can benefit our understanding of musical perception at large and the diverse effects that music has on ongoing processing of declarative information.

Keywords: musical tension, declarative memory, learning and memory, musical perception

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

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Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

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An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

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Authors: Rui de Abrantes, André Luiz Silva Forcetto

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Air pollution is a big problem in many cities around the world. Brazilian big cities also have this problem, where millions of people are exposed daily to pollutants levels above the recommended by WHO. Brazil has taken several actions to reduce air pollution, among others, controlling the atmospheric emissions from vehicles, non-road mobile machinery, and motorcycles, but on the other side, there are no emissions controls for locomotives, which are exposing the population to tons of pollutants annually. The rail network is not homogeneously distributed in the national territory; it is denser near the big cities, and this way, the population is more exposed to pollutants; apart from that, the government intends to increase the rail network as one of the strategies for greenhouse gas mitigation, complying with the international agreements against the climate changes. This paper initially presents the estimated emissions from locomotive fleets with no emission control and with emission control equivalent to US Tier 3 from 2028 and for the next 20 years. However, we realized that a program equivalent to phase Tier 3 would not be effective, so we proposed a program in two steps that will avoid the release of more than 2.4 million tons of CO and 531,000 tons of hydrocarbons, 3.7 million tons of nitrogen oxides, and 102,000 tons of particulate matter in 20 years.

Keywords: locomotives, emission control, air pollution, pollutants emission

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Authors: Anant Sharma, Ashwin Rajan

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Customer experience is measured today based on defining a set of metrics and KPIs, setting up thresholds and defining triggers across those thresholds. While this is an effective way of measuring against a Key Performance Indicator ( referred to as KPI in the rest of the paper ), this approach cannot capture the various nuances that make up the overall customer experience. Customers consume a product or service at various levels, which is not reflected in metrics like Customer Satisfaction or Net Promoter Score, but also across other measurements like recurring revenue, frequency of service usage, e-learning and depth of usage. Here we explore an alternative method of measuring customer experience by flipping the traditional views. Rather than rolling customers up to a metric, we roll up metrics to hierarchies and then measure customer experience. This method allows any team to quantify customer experience across multiple touchpoints in a customer’s journey. We make use of various data sources which contain information for metrics like CXSAT, NPS, Renewals, and depths of service usage collected across a customer lifecycle. This data can be mined systematically to get linkages between different data points like geographies, business groups, products and time. Additional views can be generated by blending synthetic contexts into the data to show trends and top/bottom types of reports. We have created a framework that allows us to measure customer experience using the above logic.

Keywords: analytics, customers experience, BI, business operations, KPIs, metrics

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Authors: Panda Krouse

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This work is a marriage of the science of Applied Behavioral Analysis and an educator’s look at Neuroscience. The focus is integrating what we know about the anatomy of the brain in autism and evidence-based practices in education. It is a bold attempt to present links between neurological research and the application of evidence-based practices in education. In researching for this work, no discovery of articles making these connections was made. Consideration of the areas of structural differences in the brain are aligned with evidence-based strategies. A brief literary review identifies how identified areas affect overt behavior, which is what, as educators, is what we can see and measure. Giving further justification and validation of our practices in education from a second scientific field is significant for continued improvement in intervention for students on the autism spectrum.

Keywords: autism, evidence based practices, neurological differences, education intervention

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Authors: Mohamed Montassar Ben Slama, Mohamed Fadel Ladeb, Mohamed Ghanmi, Mohamed Ben Youssef, Fouad Zargouni

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The salt province Basin in Northern Tunisia is a complex of late Triassic to Early Cretaceous rift and sag basins which was inverted during the Tertiary folding. The deposition of evaporitic sediments during the Late Triassic times played a major role in the subsequent tectonic evolution of the basin. Within southern tethyan passive marge, the ductile salt mass shown early mobilization, vertical transport and withdrawal of the evaporites. These movements influenced the sedimentation during the late Jurassic and Early Cretaceous. The evaporites also influenced deformation during the inversion of the basin and the development of the Tertiary and Quaternary folding. In the studied area, the biostratigraphic and tectonic map analysis of the region of Jebel el Asoued / Ragoubet el Mahjbia can resolve between the hypotheses of the diapiric intrusion of the Triassic salt and the lateral spreading of the Triassic salt as salt ‘glacier’. Also the variation in thickness and facies of the Aptian sediments demonstrates the existence of continental rise architecture at the Aptian time. The observation in a mappable outcrop of the extension segment of the graben fault of Bou Arada on the one hand confirms the existence of a Cretaceous extensive architecture and the tectonic inversion during the Tertiary time has not filled the main game distension. The extent of our observations of Triassic/Aptian and Triassic/Early Campanian contacts, we propose a composite salt ‘glacier’ model as the structures recorded in the Gulf of Mexico in the subsurface and in the Ouenza east Algeria and in Tunisia within Fedj el Adoum, Touiref-Nebeur and Jebel Ech Cheid in the outcrops.

Keywords: Cretaceous rift, salt ‘glassier’, tertiary folding, Tunisia

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Authors: Ohud Adnan Saffar

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This study aims to know the effect of using universal design for learning (UDL) to improve the quality of vocational programme with intellectual disabilities (SID) and the challenges facing this method from the teachers' point of view. The significance of the study: There are comparatively few published studies on UDL in emerging nations. Therefore, this study will encourage the researchers to consider a new approaches teaching. Development of this study will contribute significant information on the cognitively disabled community on a universal scope. In order to collect and evaluate the data and for the verification of the results, this study has been used the mixed research method, by using two groups comparison method. To answer the study questions, we were used the questionnaire, lists of observations, open questions, and pre and post-test. Thus, the study explored the advantages and drawbacks, and know about the impact of using the UDL method on integrating SID with students non-special education needs in the same classroom. Those aims were realized by developing a workshop to explain the three principles of the UDL and train (16) teachers in how to apply this method to teach (12) students non-special education needs and the (12) SID in the same classroom, then take their opinion by using the questionnaire and questions. Finally, this research will explore the effects of the UDL on the teaching of professional photography skills for the SID in Saudi Arabia. To achieve this goal, the research method was a comparison of the performance of the SID using the UDL method with that of female students with the same challenges applying other strategies by teachers in control and experiment groups, we used the observation lists, pre and post-test. Initial results: It is clear from the previous response to the participants that most of the answers confirmed that the use of UDL achieves the principle of inclusion between the SID and students non-special education needs by 93.8%. In addition, the results show that the majority of the sampled people see that the most important advantages of using UDL in teaching are creating an interactive environment with using new and various teaching methods, with a percentage of 56.2%. Following this result, the UDL is useful for integrating students with general education, with a percentage of 31.2%. Moreover, the finding indicates to improve understanding through using the new technology and exchanging the primitive ways of teaching with the new ones, with a percentage of 25%. The result shows the percentages of the sampled people's opinions about the financial obstacles, and it concluded that the majority see that the cost is high and there is no computer maintenance available, with 50%. There are no smart devices in schools to help in implementing and applying for the program, with a percentage of 43.8%.

Keywords: universal design for learning, intellectual disabilities, vocational programme, the challenges facing this method

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Authors: Wan You Ning

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Addressing the rising prevalence of mental health issues among youths, the Multi-dimensional Approach to Resilience and Support in Advanced School-based Mental Health Service Delivery (MARS-ASMHSD) framework proposes the implementation of advanced mental health services in low-resource areas to further instil mental health resilience among students in a school-based setting. Recognizing the unsustainability of direct service delivery due to rapidly growing demands and costs, the MARS-ASMHSD framework endorses the deinstitutionalization of mental healthcare and explores a tiered, multi-dimensional approach in mental healthcare provision, establishing advanced school-based mental health service delivery. The framework is developed based on sustainable and credible evidence-based practices and modifications of existing mental health service deliveries in Asia, including Singapore, Thailand, Malaysia, Japan, and Taiwan. Dissemination of the framework model for implementation will enable a more progressive and advanced school-based mental health service delivery in low-resource areas. Through the evaluation of the mental health landscape and the role of stakeholders in the respective countries, the paper concludes with a multi-dimensional framework model for implementation in low-resource areas. A mixed-method independent research study is conducted to facilitate the framework's development.

Keywords: mental health, youths, school-based services, framework development

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Authors: Xiong Xie, Yuhang Chen

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Vulnerability discovery technology is a significant field of the current. In this paper, a fuzzy framework based on concolic execution has been proposed. Fuzzy test and symbolic execution are widely used in the field of vulnerability discovery technology. But each of them has its own advantages and disadvantages. During the path generation stage, path traversal algorithm based on generation is used to get more accurate path. During the constraint solving stage, dynamic concolic execution is used to avoid the path explosion. If there is external call, the concolic based on function summary is used. Experiments show that the framework can effectively improve the ability of triggering vulnerabilities and code coverage.

Keywords: concolic execution, constraint solving, fuzzy test, vulnerability discovery

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Authors: M. Illias Kanchan

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The death of a woman during pregnancy and childbirth is not only a health issue, but also a matter of social injustice. This study makes an attempt to explore the association between maternal death and associated factors in West Bengal using the approaches of facility-based and community-based maternal death review. Bivariate and binary logistic regression analysis have been performed to understand the causes and circumstances of maternal deaths in West Bengal. Delay in seeking care was the major contributor in maternal deaths, near about one-third women died due to this factor. The most common cause of maternal death is found to be hypertensive disorders of pregnancy or eclampsia. We believe that these deaths can be averted by reducing hypertensive disorders of pregnancy or eclampsia.

Keywords: maternal death, facility-based, community-based, review, west Bengal, eclampsia

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Authors: Reyhan Tekin Sitrava

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Teachers should have robust and comprehensive content knowledge for effective mathematics teaching. It was explained that content knowledge includes knowing the facts, truths, and concepts; explaining the reasons behind these facts, truths and concepts, and making relationship between the concepts and other disciplines. By virtue of its importance, it will be significant to explore teachers and prospective teachers’ content knowledge related to variety of topics in mathematics. From this point of view, the purpose of this study was to investigate prospective mathematics teachers’ content knowledge. Particularly, it was aimed to reveal the prospective teachers’ knowledge regarding the definition of limit and derivate. To achieve the purpose and to get in-depth understanding, a qualitative case study method was used. The data was collected from 34 prospective mathematics teachers through a questionnaire containing 2 questions. The first question required the prospective teachers to define the limit and the second one required to define the derivative. The data was analyzed using content analysis method. Based on the analysis of the data, although half of the prospective teachers (50%) could write the definition of the limit, nine prospective teachers (26.5%) could not define limit. However, eight prospective teachers’ definition was regarded as partially correct. On the other hand, twenty-seven prospective teachers (79.5%) could define derivative, but seven of them (20.5%) defined it partially. According to the findings, most of the prospective teachers have robust content knowledge on limit and derivative. This result is important because definitions have a virtual role in learning and teaching of mathematics. More specifically, definition is starting point to understand the meaning of a concept. From this point of view, prospective teachers should know the definitions of the concepts to be able to teach them correctly to the students. In addition, they should have knowledge about the relationship between limit and derivative so that they can explain these concepts conceptually. Otherwise, students may memorize the rules of calculating the derivative and the limit. In conclusion, the present study showed that most of the prospective mathematics teachers had enough knowledge about the definition of derivative and limit. However, the rest of them should learn their definition conceptually. The examples of correct, partially correct, and incorrect definition of both concepts will be presented and discussed based on participants’ statements. This study has some implications for instructors. Instructors should be careful about whether students learn the definition of these concepts or not. In order to this, the instructors may give prospective teachers opportunities to discuss the definition of these concepts and the relationship between the concepts.

Keywords: content knowledge, derivative, limit, prospective mathematics teachers

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Authors: Randall E. Osborne

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In a course on International Psychology, 8 theoretical perspectives (Critical Psychology, Liberation Psychology, Post-Modernism, Social Constructivism, Social Identity Theory, Social Reduction Theory, Symbolic Interactionism, and Vygotsky’s Sociocultural Theory) are used as a framework for getting students to understand the concept of and need for Globalization. One of critical psychology's main criticisms of conventional psychology is that it fails to consider or deliberately ignores the way power differences between social classes and groups can impact the mental and physical well-being of individuals or groups of people. Liberation psychology, also known as liberation social psychology or psicología social de la liberación, is an approach to psychological science that aims to understand the psychology of oppressed and impoverished communities by addressing the oppressive sociopolitical structure in which they exist. Postmodernism is largely a reaction to the assumed certainty of scientific, or objective, efforts to explain reality. It stems from a recognition that reality is not simply mirrored in human understanding of it, but rather, is constructed as the mind tries to understand its own particular and personal reality. Lev Vygotsky argued that all cognitive functions originate in, and must therefore be explained as products of social interactions and that learning was not simply the assimilation and accommodation of new knowledge by learners. Social Identity Theory discusses the implications of social identity for human interactions with and assumptions about other people. Social Identification Theory suggests people: (1) categorize—people find it helpful (humans might be perceived as having a need) to place people and objects into categories, (2) identify—people align themselves with groups and gain identity and self-esteem from it, and (3) compare—people compare self to others. Social reductionism argues that all behavior and experiences can be explained simply by the affect of groups on the individual. Symbolic interaction theory focuses attention on the way that people interact through symbols: words, gestures, rules, and roles. Meaning evolves from human their interactions in their environment and with people. Vygotsky’s sociocultural theory of human learning describes learning as a social process and the origination of human intelligence in society or culture. The major theme of Vygotsky’s theoretical framework is that social interaction plays a fundamental role in the development of cognition. This presentation will discuss how these theoretical perspectives are incorporated into a course on International Psychology, a course on the Politics of Hate, and a course on the Psychology of Prejudice, Discrimination and Hate to promote student thinking in a more ‘global’ manner.

Keywords: globalization, international psychology, society and culture, teaching interculturally

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Authors: Sourabh Jain, S. S. Jain

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Intelligent transportation system (ITS) is the application of technologies for developing a user–friendly transportation system to extend the safety and efficiency of urban transportation systems in developing countries. These systems involve vehicles, drivers, passengers, road operators, managers of transport services; all interacting with each other and the surroundings to boost the security and capacity of road systems. The goal of urban corridor management using ITS in road transport is to achieve improvements in mobility, safety, and the productivity of the transportation system within the available facilities through the integrated application of advanced monitoring, communications, computer, display, and control process technologies, both in the vehicle and on the road. Intelligent transportation system is a product of the revolution in information and communications technologies that is the hallmark of the digital age. The basic ITS technology is oriented on three main directions: communications, information, integration. Information acquisition (collection), processing, integration, and sorting are the basic activities of ITS. In the paper, attempts have been made to present the endeavor that was made to interpret and evaluate the performance of the 27.4 Km long study corridor having eight intersections and four flyovers. The corridor consisting of six lanes as well as eight lanes divided road network. Two categories of data have been collected such as traffic data (traffic volume, spot speed, delay) and road characteristics data (no. of lanes, lane width, bus stops, mid-block sections, intersections, flyovers). The instruments used for collecting the data were video camera, stop watch, radar gun, and mobile GPS (GPS tracker lite). From the analysis, the performance interpretations incorporated were the identification of peak and off-peak hours, congestion and level of service (LOS) at midblock sections and delay followed by plotting the speed contours. The paper proposed the urban corridor management strategies based on sensors integrated into both vehicles and on the roads that those have to be efficiently executable, cost-effective, and familiar to road users. It will be useful to reduce congestion, fuel consumption, and pollution so as to provide comfort, safety, and efficiency to the users.

Keywords: ITS strategies, congestion, planning, mobility, safety

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Authors: Wen Zhen

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Compared to content words, function words have been relatively overlooked by English learners especially articles. The article system, to a certain extent, becomes a resistance to know English better, driven by different elements. Three principal factors can be summarized in term of the nature of the articles when referring to the difficulty of the English article system. However, making the article system more complex are difficulties in the second acquisition process, for [-ART] learners have to create another category, causing even most non-native speakers at proficiency level to make errors. According to the sequences of acquisition of the English article, it is showed that the zero article is first acquired and in high inaccuracy. The zero article is often overused in the early stages of L2 acquisition. Although learners at the intermediate level move to underuse the zero article for they realize that the zero article does not cover any case, overproduction of the zero article even occurs among advanced L2 learners. The aim of the study is to investigate noun-phrase factors which give rise to incorrect usage or overuse of the zero article, thus providing suggestions for L2 English acquisition. Moreover, it enables teachers to carry out effective instruction that activate conscious learning of students. The research question will be answered through a corpus-based, data- driven approach to analyze the noun-phrase elements from the semantic context and countability of noun-phrases. Based on the analysis of the International Thurber Thesis corpus, the results show that: (1) Although context of [-definite,-specific] favored the zero article, both[-definite,+specific] and [+definite,-specific] showed less influence. When we reflect on the frequency order of the zero article , prototypicality plays a vital role in it .(2)EFL learners in this study have trouble classifying abstract nouns as countable. We can find that it will bring about overuse of the zero article when learners can not make clear judgements on countability altered from (+definite ) to (-definite).Once a noun is perceived as uncountable by learners, the choice would fall back on the zero article. These findings suggest that learners should be engaged in recognition of the countability of new vocabulary by explaining nouns in lexical phrases and explore more complex aspects such as analysis dependent on discourse.

Keywords: noun phrase, zero article, corpus, second language acquisition

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Authors: Manish Kumar Pillai, Madhavi Pathak Pillai, Rajender Lal, Dinesh P. Sharma

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India has not yet been able to produce many weightlifters in the past years. Karnam Malleshwari is the only woman to win a medal for India in Olympics. When we try to introspect, there seem to be different reasons. One of the probable cause could be the lack of biomechanical analysis for technique improvements. The analysis of motion in sports has gained prime importance for technical improvement. It helps an athlete to develop a better understanding of his own skills and increasing the rate of technical learning process. Kinematics is concerned with describing and quantifying both the linear and angular position of bodies and their time derivatives. The techniques analysis of barbell movement is very important in weightlifting. But women weightlifting has a shorter history than men’s. Research on women weightlifting based on video analysis is less; there is a lack of scientific evidence based on kinematic analysis of especially on Indian weightlifters at national level are limited. Hence, the present investigation was aimed to analyze the barbell kinematics of women weightlifters in India. The study was delimited to the medal winners of 69-kilogram weight category in the All India Inter-University Competition, age ranging between 18 and 28 years. The variables selected for the mechanical analysis of Barbell kinematics included barbell trajectory, velocity, acceleration, potential energy, kinetic energy, mechanical energy, and average power output. The performance was captured during the competition by two DV PC-60 Digital cameras (Panasonic Company, Ltd). Two cameras were placed 6-meters perpendicular to the plane of the motion, 130 cm. above the ground to record/capture the frontal and lateral view of the lifters simultaneously. Video recordings were analyzed by using Dartfish software, and barbell kinematics were analyzed with the information derived with the help of software. The result documented on the basis of the finding of the study clearly states that there are differences in the selected kinematic variables in all three lifters in respect to their technique in five phases during snatch technique using by them.

Keywords: dartfish, digital camera, kinematic, snatch, weightlifting

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Authors: Todd Enslen

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In order to attract more international students to study for undergraduate degrees in Japan, many universities have been developing English-Medium Instruction degree programs. This means that many faculty members must now teach their courses in English, which raises a number of concerns. A common misconception of English-Medium Instruction (EMI) is that teaching in English is simply a matter of translating materials. Since much of the teaching in Japan still relies on a more traditional, teachercentered, approach, continuing with this style in an EMI environment that targets international students can cause a clash between what is happening and what students expect in the classroom, not to mention what the Scholarship of Teaching and Learning (SoTL) has shown is effective teaching. A variety of considerations need to be taken into account in EMI classrooms such as varying English abilities of the students, modifying input material, and assuring comprehension through interactional checks. This paper analyzes the effectiveness of the English-Medium Instruction (EMI) undergraduate degree programs in engineering, agriculture, and science at a large research university in Japan by presenting the results from student surveys regarding the areas where perceived improvements need to be made. The students were the most dissatisfied with communication with their teachers in English, communication with Japanese students in English, adherence to only English being used in the classes, and the quality of the education they received. In addition, the results of a needs analysis survey of Japanese teachers having to teach in English showed that they believed they were most in need of English vocabulary and expressions to use in the classroom and teaching methods for teaching in English. The result from the student survey and the faculty survey show similar concerns between the two groups. By helping the teachers to understand student-centered teaching and the benefits for learning that it provides, teachers may begin to incorporate more student-centered approaches that in turn help to alleviate the dissatisfaction students are currently experiencing. Through analyzing the current environment in Japanese higher education against established best practices in teaching and EMI, three areas that need to be addressed in professional development workshops were identified. These were “culture” as it relates to the English language, “classroom management techniques” and ways to incorporate them into classes, and “language” issues. Materials used to help faculty better understand best practices as they relate to these specific areas will be provided to help practitioners begin the process of helping EMI faculty build awareness of better teaching practices. Finally, the results from faculty development workshops participants’ surveys will show the impact that these workshops can have. Almost all of the participants indicated that they learned something new and would like to incorporate the ideas from the workshop into their teaching. In addition, the vast majority of the participants felt the workshop provided them with new information, and they would like more workshops like these.

Keywords: English-medium instruction, materials development, professional development, teaching effectiveness

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Authors: Stefano Scippo, Damiana Luzzi, Stefano Cuomo, Maria Ranieri

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Background: In response to the rise in natural disasters linked to climate change, numerous studies on Disaster Risk Reduction Education (DRRE) have emerged since the '90s, mainly using a didactic transmission-based approach. Effective DRRE should align with an interactive, experiential, and participatory educational model, which can be costly and risky. A potential solution is using simulations facilitated by eXtended Reality (XR). Research Question: This study aims to conduct a scoping review to explore educational methodologies that use XR to enhance knowledge among teachers, students, and citizens about environmental risks, natural disasters (including climate-related ones), and their management. Method: A search string of 66 keywords was formulated, spanning three domains: 1) education and target audience, 2) environment and natural hazards, and 3) technologies. On June 21st, 2023, the search string was used across five databases: EBSCOhost, IEEE Xplore, PubMed, Scopus, and Web of Science. After deduplication and removing papers without abstracts, 2,152 abstracts (published between 2013 and 2023) were analyzed and 2,062 papers were excluded, followed by the exclusion of 56 papers after full-text scrutiny. Excluded studies focused on unrelated technologies, non-environmental risks, and lacked educational outcomes or accessible texts. Main Results: The 34 reviewed papers were analyzed for context, risk type, research methodology, learning objectives, XR technology use, outcomes, and educational affordances of XR. Notably, since 2016, there has been a rise in scientific publications, focusing mainly on seismic events (12 studies) and floods (9), with a significant contribution from Asia (18 publications), particularly Japan (7 studies). Methodologically, the studies were categorized into empirical (26) and non-empirical (8). Empirical studies involved user or expert validation of XR tools, while non-empirical studies included systematic reviews and theoretical proposals without experimental validation. Empirical studies were further classified into quantitative, qualitative, or mixed-method approaches. Six qualitative studies involved small groups of users or experts, while 20 quantitative or mixed-method studies used seven different research designs, with most (17) employing a quasi-experimental, one-group post-test design, focusing on XR technology usability over educational effectiveness. Non-experimental studies had methodological limitations, making their results hypothetical and in need of further empirical validation. Educationally, the learning objectives centered on knowledge and skills for surviving natural disaster emergencies. All studies recommended XR technologies for simulations or serious games but did not develop comprehensive educational frameworks around these tools. XR-based tools showed potential superiority over traditional methods in teaching risk and emergency management skills. However, conclusions were more valid in studies with experimental designs; otherwise, they remained hypothetical without empirical evidence. The educational affordances of XR, mainly user engagement, were confirmed by the studies. Authors’ Conclusions: The analyzed literature lacks specific educational frameworks for XR in DRRE, focusing mainly on survival knowledge and skills. There is a need to expand educational approaches to include uncertainty education, developing competencies that encompass knowledge, skills, and attitudes like risk perception.

Keywords: disaster risk reduction education, educational technologies, scoping review, XR technologies

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Authors: Rita Chattopadhyay, Vivek Anand Thoutam

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Speech is the most acceptable means of communication where we can quickly exchange our feelings and thoughts. Quite often, people can communicate orally but cannot interact or work with computers or devices. It’s easy and quick to give speech commands than typing commands to computers. In the same way, it’s easy listening to audio played from a device than extract output from computers or devices. Especially with Robotics being an emerging market with applications in warehouses, the hospitality industry, consumer electronics, assistive technology, etc., speech-based human-machine interaction is emerging as a lucrative feature for robot manufacturers. Considering this factor, the objective of this paper is to design the “Audio-Visual Co-Data Processing Pipeline.” This pipeline is an integrated version of Automatic speech recognition, a Natural language model for text understanding, object detection, and text-to-speech modules. There are many Deep Learning models for each type of the modules mentioned above, but OpenVINO Model Zoo models are used because the OpenVINO toolkit covers both computer vision and non-computer vision workloads across Intel hardware and maximizes performance, and accelerates application development. A speech command is given as input that has information about target objects to be detected and start and end times to extract the required interval from the video. Speech is converted to text using the Automatic speech recognition QuartzNet model. The summary is extracted from text using a natural language model Generative Pre-Trained Transformer-3 (GPT-3). Based on the summary, essential frames from the video are extracted, and the You Only Look Once (YOLO) object detection model detects You Only Look Once (YOLO) objects on these extracted frames. Frame numbers that have target objects (specified objects in the speech command) are saved as text. Finally, this text (frame numbers) is converted to speech using text to speech model and will be played from the device. This project is developed for 80 You Only Look Once (YOLO) labels, and the user can extract frames based on only one or two target labels. This pipeline can be extended for more than two target labels easily by making appropriate changes in the object detection module. This project is developed for four different speech command formats by including sample examples in the prompt used by Generative Pre-Trained Transformer-3 (GPT-3) model. Based on user preference, one can come up with a new speech command format by including some examples of the respective format in the prompt used by the Generative Pre-Trained Transformer-3 (GPT-3) model. This pipeline can be used in many projects like human-machine interface, human-robot interaction, and surveillance through speech commands. All object detection projects can be upgraded using this pipeline so that one can give speech commands and output is played from the device.

Keywords: OpenVINO, automatic speech recognition, natural language processing, object detection, text to speech

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Authors: Hichem Sassi

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Pneumonia, being a respiratory infection, has garnered global attention due to its rapid transmission and relatively high mortality rates. Timely detection and treatment play a crucial role in significantly reducing mortality associated with pneumonia. Presently, X-ray diagnosis stands out as a reasonably effective method. However, the manual scrutiny of a patient's X-ray chest radiograph by a proficient practitioner usually requires 5 to 15 minutes. In situations where cases are concentrated, this places immense pressure on clinicians for timely diagnosis. Relying solely on the visual acumen of imaging doctors proves to be inefficient, particularly given the low speed of manual analysis. Therefore, the integration of artificial intelligence into the clinical image diagnosis of pneumonia becomes imperative. Additionally, AI recognition is notably rapid, with convolutional neural networks (CNNs) demonstrating superior performance compared to human counterparts in image identification tasks. To conduct our study, we utilized a dataset comprising chest X-ray images obtained from Kaggle, encompassing a total of 5216 training images and 624 test images, categorized into two classes: normal and pneumonia. Employing five mainstream network algorithms, we undertook a comprehensive analysis to classify these diseases within the dataset, subsequently comparing the results. The integration of artificial intelligence, particularly through improved network architectures, stands as a transformative step towards more efficient and accurate clinical diagnoses across various medical domains.

Keywords: deep learning, computer vision, pneumonia, models, comparative study

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Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

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Authors: Tesfaye Alamirew, Delele Worku, Solomon W. Fanta, Nigus Gabbiye

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Recently graphen based nanocomposites are become an emerging research areas for fabrication of enzymatic biosensors due to their property of large surface area, conductivity and biocompatibility. This review summarizes recent research reports of graphen based nanocomposites for the fabrication of glucose and ethanol enzymatic biosensors. The newly fabricated enzyme free microwave treated nitrogen doped graphen (MN-d-GR) had provided highest sensitivity towards glucose and GCE/rGO/AuNPs/ADH composite had provided far highest sensitivity towards ethanol compared to other reported graphen based nanocomposites. The MWCNT/GO/GOx and GCE/ErGO/PTH/ADH nanocomposites had also enhanced wide linear range for glucose and ethanol detection respectively. Generally, graphen based nanocomposite enzymatic biosensors had fast direct electron transfer rate, highest sensitivity and wide linear detection ranges during glucose and ethanol sensing.

Keywords: glucose, ethanol, enzymatic biosensor, graphen, nanocomposite

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Authors: Musbah Abdussayed

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The washback effect refers to the influence of assessment on teaching and learning, and this washback effect can either be positive or negative. This study implemented, sequentially, self-assessment (SA) and peer assessment (PA) and examined the washback effect of self and peer assessment (SPA) activities on the writing growth during the revision phase in the writing process. Twenty advanced Arabic as a second language learners from a private school in the USA participated in the study. The participants composed and then revised a short Arabic story as a part of a midterm grade. Qualitative data was collected, analyzed, and synthesized from ten interviews with the learners and from the twenty learners’ post-reflective journals. The findings indicate positive washback effects on the learners’ writing growth. The PA activity enhanced descriptions and meaning, promoted creativity, and improved textual coherence, whereas the SA activity led to detecting editing issues. Furthermore, both SPA activities had washback effects in common, including helping the learners meet the writing genre conventions and developing metacognitive awareness. However, the findings also demonstrate negative washback effects on the learners’ attitudes during the revision phase in the writing process, including bias toward self-evaluation during the SA activity and reluctance to rate peers’ writing performance during the PA activity. The findings suggest that self-and peer assessment activities are essential teaching and learning tools that can be utilized sequentially to help learners tackle multiple writing areas during the revision phase in the writing process.

Keywords: self assessment, peer assessment, washback effect, second language writing, writing process

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Authors: Eteri Kharaishvili, Marina Chavleishvili, Manana Lobzhanidze, Nino Grigolia

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The article analyzes Georgia's involvement in global migration processes, assessing migration research and policy regulatory documents. The socio-economic situation of young people has been studied in the paper, their employment and unemployment levels are analyzed, reasons for migration of youth are revealed, the impact of migration on the socio-economic development of the country is substantiated. Youth demand on education is also assessed, problems in the education sector are identified, educational migration indicators are analyzed according to the internationalization process of this sector. Based on the analysis of the motivations of young people in Georgia, orientation of values and the aspects conditioning life strategies the factors affecting educational migration are determined and the results of the positive and negative impact of educational migration on the socio-economic development of the country are substantiated. The importance of efficient management of educational migration for Georgia in getting closer to the EU and achieving inclusive economic grow this substantiated. Recommendations for efficient management of the process of Georgian citizens’ learning and acquiring experience, as well as the internationalization of education sector and educational migration, are drawn.

Keywords: educational migration, migration management, migration of youth, socio-economic results of educational migration, youth employment

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Authors: B. Padmaja, V. V. Rama Prasad, K. V. N. Sunitha, E. Krishna Rao Patro

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Stress is a psychological condition that reduces the quality of sleep and affects every facet of life. Constant exposure to stress is detrimental not only for mind but also body. Nevertheless, to cope with stress, one should first identify it. This paper provides an effective method for the cognitive stress level detection by using data provided from a physical activity tracker device Fitbit. This device gathers people’s daily activities of food, weight, sleep, heart rate, and physical activities. In this paper, four major stressors like physical activities, sleep patterns, working hours and change in heart rate are used to assess the stress levels of individuals. The main motive of this system is to use machine learning approach in stress detection with the help of Smartphone sensor technology. Individually, the effect of each stressor is evaluated using logistic regression and then combined model is built and assessed using variants of ordinal logistic regression models like logit, probit and complementary log-log. Then the quality of each model is evaluated using Akaike Information Criterion (AIC) and probit is assessed as the more suitable model for our dataset. This system is experimented and evaluated in a real time environment by taking data from adults working in IT and other sectors in India. The novelty of this work lies in the fact that stress detection system should be less invasive as possible for the users.

Keywords: physical activity tracker, sleep pattern, working hours, heart rate, smartphone sensor

Procedia PDF Downloads 243