Search results for: video representation

Authors: Tatsuya Otoshi, Masayuki Murata

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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

Procedia PDF Downloads 80

Authors: Wala A. Bagunaid, Maram Meccawy, Arwa Allinjawi, Zilal Meccawy

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Continuous self-assessment becomes crucial in self-paced online learning environments. Students often depend on themselves to assess their progress; which is considered an essential requirement for any successful learning process. Today’s education institutions face major problems around student motivation and engagement. Thus, personalized e-learning systems aim to help and guide the students. Gamification provides an opportunity to help students for self-assessment and social comparison with other students through attempting to harness the motivational power of games and apply it to the learning environment. Furthermore, Open Social Student Modeling (OSSM) as considered as the latest user modeling technologies is believed to improve students’ self-assessment and to allow them to social comparison with other students. This research integrates OSSM approach and gamification concepts in order to provide self-assessment for English language learners at King Abdulaziz University (KAU). This is achieved through an interactive visual representation of their learning progress.

Keywords: e-learning system, gamification, motivation, social comparison, visualization

Procedia PDF Downloads 154

Authors: J. Urban, Á. S. Botella, L. E. Robaina, A. Bárta, P. Souček, P. Císař, Š. Papáček, L. M. Domínguez

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Skin coloration in fish is of great physiological, behavioral and ecological importance and can be considered as an index of animal welfare in aquaculture as well as an important quality factor in the retail value. Currently, in order to compare color in animals fed on different diets, biochemical analysis, and colorimetry of fished, mildly anesthetized or dead body, are very accurate and meaningful measurements. The noninvasive method using digital images of the fish body was developed as a standalone application. This application deals with the computation burden and memory consumption of large input files, optimizing piece wise processing and analysis with the memory/computation time ratio. For the comparison of color distributions of various experiments and different color spaces (RGB, CIE L*a*b*) the comparable semi-equidistant binning of multi channels representation is introduced. It is derived from the knowledge of quantization levels and Freedman-Diaconis rule. The color calibrations and camera responsivity function were necessary part of the measurement process.

Keywords: color distribution, fish skin color, piecewise transformation, object to background segmentation

Procedia PDF Downloads 263

Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

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Authors: Albert T. Akume, P. D. Dahida

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This paper examines the effect of various epochs of governments on policy making in Nigeria. The character of governance and public policy making of both epochs was exclusive, non-participatory and self-centric. As a consequence the interests of citizenry were not represented, neither protected nor sought to meet fairly the needs of all groups. The introduction of the post-1999 democratic government demand that the hitherto skewed pattern of policy making cease to be a character of governance. Hence, the need for citizen participation in the policy making process. The question then is what mode is most appropriate to engender public participation so as to make the policy making process functional? Given the prevailing social, economic and political dilemmas the utilization of the direct mode of citizen participation to affect policy outcome is doubtful if not unattainable. It is due to these predicament that this paper uses the documentary research design argues for the utilization of the indirect mode of citizen participation in the policy making process so as to affect public policy outcome appropriately and with less cost, acrimony and delays.

Keywords: governance, public policy, participation, representation, civil society

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Authors: Maria Joseph Israel, Ahmed Amer

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Our work aims to broaden the application of provenance technology beyond its traditional domains of scientific workflow management and database systems by offering a general provenance framework to capture richer and extensible metadata in unstructured textual data sources such as literary texts, commentaries, translations, and digital humanities. Specifically, we demonstrate the feasibility of capturing and representing expressive provenance metadata, including more of the context for citing scholarly works (e.g., the authors’ explicit or inferred intentions at the time of developing his/her research content for publication), while also supporting subsequent augmentation with similar additional metadata (by third parties, be they human or automated). To better capture the nature and types of possible citations, in our proposed provenance scheme metaScribe, we extend standard provenance conceptual models to form our proposed provCite ontology. This provides a conceptual framework which can accurately capture and describe more of the functional and rhetorical properties of a citation than can be achieved with any current models.

Keywords: knowledge representation, provenance architecture, ontology, metadata, bibliographic citation, semantic web annotation

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Authors: Peter Sauer, Thomas Hinze, Petra Hofstedt

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To avoid obstacles in the surrounding environment and to navigate to a given target belong to the most important tasks for mobile robots. According to these tasks different data structures are suitable. To avoid near obstacles, occupancy grid maps are an ideal representation of the surroundings. For less fine grained tasks, such as navigating from one room to another in an apartment, pure grid maps are inappropriate. Grid maps are very detailed, calculating paths to navigate between rooms based on grid maps would take too long. Instead, graph-based data structures, so-called topologies, turn out to be a proper choice for such tasks. In this paper we present two methods to dynamically create topologies from grid maps. Both methods are based on non-uniform grid maps. The topologies are generated on-the-fly and can easily be modified to represent changes in the environment. This allows a hybrid approach to control mobile robots, where, depending on the situation and the current task, either the grid map or the generated topology may be used.

Keywords: robot navigation, occupancy grids, topological maps, dynamic map creation

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Authors: Ming-Jen Huang, Chun-Fang Huang, Chiching Wei

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With the recent advance of the deep neural network, we observe new applications of NLP (natural language processing) and CV (computer vision) powered by deep neural networks for processing business documents. However, creating a real-world document processing system needs to integrate several NLP and CV tasks, rather than treating them separately. There is a need to have a unified approach for processing documents containing textual and graphical elements with rich formats, diverse layout arrangement, and distinct semantics. In this paper, a framework that fulfills this unified approach is presented. The framework includes a representation model definition for holding the information generated by various tasks and specifications defining the coordination between these tasks. The framework is a blueprint for building a system that can process documents with rich formats, styles, and multiple types of elements. The flexible and lightweight design of the framework can help build a system for diverse business scenarios, such as contract monitoring and reviewing.

Keywords: document processing, framework, formal definition, machine learning

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Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

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Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

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Authors: Balraju Vadlakonda, Narasimha Mangadoddy

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The hydrodynamic behavior in a laboratory column flotation was analyzed using particle image velocimetry. For complete characterization of column flotation, it is necessary to determine the flow velocity induced by bubbles in the liquid phase, the bubble velocity and bubble characteristics:diameter,shape and bubble size distribution. An experimental procedure for analyzing simultaneous, phase-separated velocity measurements in two-phase flows was introduced. The non-invasive PIV technique has used to quantify the instantaneous flow field, as well as the time averaged flow patterns in selected planes of the column. Using the novel particle velocimetry (PIV) technique by the combination of fluorescent tracer particles, shadowgraphy and digital phase separation with masking technique measured the bubble velocity as well as the Reynolds stresses in the column. Axial and radial mean velocities as well as fluctuating components were determined for both phases by averaging the sufficient number of double images. Bubble size distribution was cross validated with high speed video camera. Average turbulent kinetic energy of bubble were analyzed. Different air flow rates were considered in the experiments.

Keywords: particle image velocimetry (PIV), bubble velocity, bubble diameter, turbulent kinetic energy

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Authors: Hyun-Woo Cho

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The real-time fault monitoring and diagnosis of large scale production processes is helpful and necessary in order to operate industrial process safely and efficiently producing good final product quality. Unusual and abnormal events of the process may have a serious impact on the process such as malfunctions or breakdowns. This work try to utilize process measurement data obtained in an on-line basis for the safe and some fault-free operation of industrial processes. To this end, this work evaluated the proposed intelligent process data monitoring framework based on a simulation process. The monitoring scheme extracts the fault pattern in the reduced space for the reliable data representation. Moreover, this work shows the results of using linear and nonlinear techniques for the monitoring purpose. It has shown that the nonlinear technique produced more reliable monitoring results and outperforms linear methods. The adoption of the qualitative monitoring model helps to reduce the sensitivity of the fault pattern to noise.

Keywords: process data, data mining, process operation, real-time monitoring

Procedia PDF Downloads 641

Authors: Dean Raiyasmi, Elvi Citraresmana, Sutiono Mahdi

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Language shapes the human mind and its concept toward things. Using image schemas, in nowadays technology, even AI (artificial intelligence) can concept things in response to their creator negativity or positivity. This is reflected inside one of the most selling game around the world in 2012 called Dragon Age Origins. The AI in form of NPC (Non-Playable Character) inside the game reflects on the creator of the game on negativity or positivity toward the lexical concept of mage. Through image schemas, shaping the lexical concept of mage deemed possible and proved the negativity or positivity creator of the game toward mage. This research analyses the cognitive-semantic process of image schema and shaping the concept of ‘mage’ by describing kinds of image schemas exist in the Dragon Age Origin Game. This research is also aimed to analyse kinds of image schemas and describing the image schemas which shaping the concept of ‘mage’ itself. The methodology used in this research is qualitative where participative observation is employed with five stages and documentation. The results shows that there are four image schemas exist in the game and those image schemas shaping the lexical concept of ‘mage’.

Keywords: cognitive semantic, image-schema, conceptual metaphor, video game

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Authors: Cheng Zeng, Xia Luo

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Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

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Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

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Authors: Margarita Grushanina

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After several prominent central banks including European Central Bank (ECB), Federal Reserve System (Fed), Bank of Japan and Bank of England employed unconventional monetary policies in the aftermath of the financial crisis of 2008-2009 the problem of identification of the effects from such policies became of great interest. One of the main difficulties in identification of shocks from unconventional monetary policy measures in structural VAR analysis is that they often are anticipated, which leads to a non-fundamental MA representation of the VAR model. Moreover, the unconventional monetary policy actions may indirectly transmit to markets information about the future stance of the interest rate, which raises a question of the plausibility of the assumption of orthogonality between shocks from unconventional and conventional policy measures. This paper offers a method of identification that takes into account the abovementioned issues. The author uses factor-augmented VARs to increase the information set and identification through heteroskedasticity of error terms and rank restrictions on the errors’ second moments’ matrix to deal with the cross-correlation of the structural shocks.

Keywords: factor-augmented VARs, identification through heteroskedasticity, monetary policy, structural VARs

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Authors: Edwin Cartledge, Jack Clark, Mazaher Molaei-Chalchooghi

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The mixing in the crystallization step of active pharmaceutical ingredient manufacturers was studied via advanced modeling tools to enable a successful scale-up. A virtual representation of the vessel was created, and computational fluid dynamics were used to simulate multiphase flow and, thus, the mixing environment within this vessel. The study identified a significant dead zone in the vessel underneath the impeller and found that increasing the impeller speed and power did not improve the mixing. A series of sensitivity analyses found that to improve mixing, the vessel had to be redesigned, and found that optimal mixing could be obtained by adding two extra cylindrical baffles. The same two baffles from the simulated environment were then constructed and added to the process vessel. By identifying these potential issues before starting the manufacture and modifying the vessel to ensure good mixing, this study mitigated a failed crystallization and potential batch disposal, which could have resulted in a significant loss of high-value material.

Keywords: active pharmaceutical ingredient, baffles, computational fluid dynamics, mixing, modelling

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Authors: R. C. Tyagi

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Quasi-periodicity of frequency intervals observed in Shruti based Absolute Scale of Music has been used to graphically identify the Anchor notes ‘Vadi’ and ‘Samvadi’ which are nodal points for expansion, elaboration and iteration of the emotional theme represented by the characteristic tonic arrangement in Raga compositions. This analysis leads to defining the Tonic parameters in the octave including the key-note frequency, tonic intervals’ anchor notes and the on-set and range of quasi-periodicities as exponents of 2. Such uniformity of representation of characteristic data would facilitate computational analysis and synthesis of music compositions and also help develop noise suppression techniques. Criteria for tuning of strings for compatibility with placement of frets on finger boards is discussed. Natural Rhythmic cycles in music compositions are analytically shown to lie between 3 and 126 beats.

Keywords: absolute scale, anchor notes, computational analysis, frets, innovation, noise suppression, Quasi-periodicity, rhythmic cycle, tonic interval, Shruti

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Authors: C. G. Jinimole, A. Harsha

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One of the key problems facing in the analysis of Computed Tomography (CT) images is the poor contrast of the images. Image enhancement can be used to improve the visual clarity and quality of the images or to provide a better transformation representation for further processing. Contrast enhancement of images is one of the acceptable methods used for image enhancement in various applications in the medical field. This will be helpful to visualize and extract details of brain infarctions, tumors, and cancers from the CT image. This paper presents a comparison study of five contrast enhancement techniques suitable for the contrast enhancement of CT images. The types of techniques include Power Law Transformation, Logarithmic Transformation, Histogram Equalization, Contrast Stretching, and Laplacian Transformation. All these techniques are compared with each other to find out which enhancement provides better contrast of CT image. For the comparison of the techniques, the parameters Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE) are used. Logarithmic Transformation provided the clearer and best quality image compared to all other techniques studied and has got the highest value of PSNR. Comparison concludes with better approach for its future research especially for mapping abnormalities from CT images resulting from Brain Injuries.

Keywords: computed tomography, enhancement techniques, increasing contrast, PSNR and MSE

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Authors: Chingwen Yeh, Yu Ru Chen

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This paper aims to explore the growth and development of children in the creative dance class of Cloud Gate Dance School in Taichung Taiwan. Professor Chingwen Yeh’s qualitative research method was applied in this study. First of all, application of Dalcroze Eurhythmic teaching materials such as music, teaching aids, speaking language through classroom situation was collected and exam. Second, the in-class observation on the participation of the young children's learning situation was recorded both by words and on video screen as the research data. Finally, data analysis was categorized into the following aspects: children's body movement coordination, children’s mind concentration and imagination and children’s verbal expression. Through the in-depth interviews with the in-class teachers, parents of participating children and other in class observers were conducted from time to time; this research found the children's body rhythm, language skills, and social learning growth were improved in certain degree through the creative dance training. These authors hope the study can contribute as the further research reference on the related topic.

Keywords: Cloud Gate Dance School, creative dance, Dalcroze, Eurhythmic

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Authors: Doo W. Lee, Soo J. Lee, Bye R. Yoon, Jae Y. Jho, Kyehan Rhee

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Hand exoskeletons have been developed in order to assist daily activities for disabled and elder people. A figure exoskeleton was developed using ionic polymer metal composite (IPMC) actuators, and the performance of it was evaluated in this study. In order to study dynamic performance of a finger dummy performing pinching motion, force generating characteristics of an IPMC actuator and pinching motion of a thumb and index finger dummy actuated by IMPC actuators were analyzed. The blocking force of 1.54 N was achieved under 4 V of DC. A thumb and index finger dummy, which has one degree of freedom at the proximal joint of each figure, was manufactured by a three dimensional rapid prototyping. Each figure was actuated by an IPMC actuator, and the maximum fingertip force was 1.18 N. Pinching motion of a dummy was analyzed by two video cameras in vertical top and horizontal left end view planes. A figure dummy powered by IPMC actuators could perform flexion and extension motion of an index figure and a thumb.

Keywords: finger exoskeleton, ionic polymer metal composite, flexion and extension, motion analysis

Procedia PDF Downloads 238

Authors: Sonia Gonzalez Cruz

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Subtitling activities allow for acquiring and developing certain translation skills, and they also have a great impact on the students' motivation. Active subtitling is a relatively recent activity that has generated a lot of interest particularly in the field of second-language acquisition, but it is also present within both the didactics of general translation and language teaching for translators. It is interesting to analyze the level of inclusion of these new resources into the existent curricula and observe to what extent these different teaching methods are being used in the translation classroom. Although subtitling has already become an independent discipline of study and it is considered to be a type of translation on its own, it is necessary to do further research on the different didactic varieties that this type of audiovisual translation offers. Therefore, this project is framed within the field of the didactics of translation, and it focuses on the relationship between the didactics of general translation and active subtitling as a didactic tool. Its main objective is to analyze the inclusion of interlinguistic active subtitling in general translation curricula at different universities. As it has been observed so far, the analyzed curricula do not make any type of reference to the use of this didactic tool in general translation classrooms. However, they do register the inclusion of other audiovisual activities such as dubbing, script translation or video watching, among others. By means of online questionnaires and interviews, the main goal is to confirm the results obtained after the observation of the curricula and find out to what extent subtitling has actually been included into general translation classrooms.

Keywords: subtitling, general translation, didactics, translation competence

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Authors: Harold Jideofor Nnachetam

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Maintenance management in Nigeria Polytechnic faced many issues due to poor service delivery, inadequate finance, and poor maintenance plan and maintenance backlogs. The purpose of this study is to improve the conventional method practices which tend to be ineffective in Nigeria Polytechnic. The case study was conducted with eight Polytechnics in Nigeria. The selected Polytechnic is based on conventional method practices and its major problems, attempt to implement computerized technology and the willingness of staff to share their experiences. All feedbacks from respondents through semi-structured interview were recorded using video camera and transcribed verbatim. The overall findings of this research indicated; poor service delivery, inadequate financial, poor maintenance planning and maintenance backlogs. There is also need to overcome less man power competencies of maintenance management practices which existed with all eight Polytechnics. In addition, the study also found that the Polytechnics still use conventional maintenance management processes in managing building facility condition. As a result, the maintenance management staff was not able to improve the maintenance management performance at the Polytechnics. The findings are intended to be used for maintenance management practices at Nigeria Polytechnics in order to provide high-quality of building facility with safe and healthy environments.

Keywords: maintenance management, conventional method, maintenance management system, Nigeria polytechnic

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Authors: Edwin Hidayat, Redi Yulianto, Disi Hanafiah

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On the one hand, parameters which are used for determining the number of lane on the new road construction are average annual average daily traffic (AADT) and peak hour factor (K-factor). On the other hand, the value of K-factor listed in the guidelines and manual for road planning in Indonesia is a value of adoption or adaptation from foreign guidelines or manuals. Thus, the value is less suitable for Indonesian condition due to differences in road conditions, vehicle type, and driving behavior. The purpose of this study is to provide an example on how to determine k-factor values at a road segment with particular conditions in north coast road, West Java. The methodology is started with collecting traffic volume data for 24 hours over 365 days using PLATO (Automated Traffic Counter) with the approach of video image processing. Then, the traffic volume data is divided into per hour and analyzed by comparing the peak traffic volume in the 30th hour (or other) with the AADT in the same year. The analysis has resulted that for the 30th peak hour the K-factor is 0.97. This value can be used for planning road geometry or evaluating the road capacity performance for the 4/2D interurban road.

Keywords: road geometry, K-factor, annual average daily traffic, north coast road

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Authors: Ayesha Selwyn, Annapoorni Chandrashekar, Kumar Ashwarya, Nishant Baghel

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Project-based learning (PBL) activities are typically implemented in technology-enabled schools by highly trained teachers. In rural India, students have limited access to technology and quality education. Implementing typical PBL activities is challenging. This study details how Pratham Education Foundation’s Hybrid Learning model was used to implement two PBL activities related to music in 900 remote Indian villages with 46,000 students aged 10-14. The activities were completed by 69% of groups that submitted a total of 15,000 videos (completed projects). Pratham’s H-Learning model reaches 100,000 students aged 3-14 in 900 Indian villages. The community-driven model engages students in 20,000 self-organized groups outside of school. The students are guided by 6,000 youth volunteers and 100 facilitators. The students partake in learning activities across subjects with the support of community stakeholders and offline digital content on shared Android tablets. A training and implementation toolkit for PBL activities is designed by subject experts. This toolkit is essential in ensuring efficient implementation of activities as facilitators aren’t highly skilled and have limited access to training resources. The toolkit details the activity at three levels of student engagement - enrollment, participation, and completion. The subject experts train project leaders and facilitators who train youth volunteers. Volunteers need to be trained on how to execute the activity and guide students. The training is focused on building the volunteers’ capacity to enable students to solve problems, rather than developing the volunteers’ subject-related knowledge. This structure ensures that continuous intervention of subject matter experts isn’t required, and the onus of judging creativity skills is put on community members. 46,000 students in the H-Learning program were engaged in two PBL activities related to Music from April-June 2019. For one activity, students had to conduct a “musical survey” in their village by designing a survey and shooting and editing a video. This activity aimed to develop students’ information retrieval, data gathering, teamwork, communication, project management, and creativity skills. It also aimed to identify talent and document local folk music. The second activity, “Pratham Idol”, was a singing competition. Students participated in performing, producing, and editing videos. This activity aimed to develop students’ teamwork and creative skills and give students a creative outlet. Students showcased their completed projects at village fairs wherein a panel of community members evaluated the videos. The shortlisted videos from all villages were further evaluated by experts who identified students and adults to participate in advanced music workshops. The H-Learning framework enables students in low resource settings to engage in PBL and develop relevant skills by leveraging community support and using video creation as a tool. In rural India, students do not have access to high-quality education or infrastructure. Therefore designing activities that can be implemented by community members after limited training is essential. The subject experts have minimal intervention once the activity is initiated, which significantly reduces the cost of implementation and allows the activity to be implemented at a massive scale.

Keywords: community supported learning, project-based learning, self-organized learning, education technology

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Authors: Alexander Hudson, Shaogang Gong

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Structure determination is key to understanding protein function at a molecular level. Whilst significant advances have been made in predicting structure and function from amino acid sequence, researchers must still rely on expensive, time-consuming analytical methods to visualise detailed protein conformation. In this study, we demonstrate that it is possible to make accurate (≥80%) predictions of protein class and architecture from structures determined at low (>3A) resolution, using a deep convolutional neural network trained on high-resolution (≤3A) structures represented as 2D matrices. Thus, we provide proof of concept for high-speed, low-cost protein structure classification at low resolution, and a basis for extension to prediction of function. We investigate the impact of the input representation on classification performance, showing that side-chain information may not be necessary for fine-grained structure predictions. Finally, we confirm that high resolution, low-resolution and NMR-determined structures inhabit a common feature space, and thus provide a theoretical foundation for boosting with single-image super-resolution.

Keywords: transfer learning, protein distance maps, protein structure classification, neural networks

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Authors: Dalila Souilem, Salma Boumiza, Abdelkarim Abdelkader

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The Clarifier Dialogue Interface (CDI) is a part of an online teaching system based on human-machine communication in learning situation. This interface used in the system during the learning action specifically in the evaluation step, to clarify ambiguities in the learner's response. The CDI can generate patterns allowing access to an information system, using the selectors associated with lexical units. To instantiate these patterns, the user request (especially learner’s response), must be analyzed and interpreted to deduce the canonical form, the semantic form and the subject of the sentence. For the efficiency of this interface at the interpretation level, a set of substitution operators is carried out in order to extend the possibilities of manipulation with a natural language. A second approach that will be presented in this paper focuses on the object languages with new prospects such as combination of natural language with techniques of handling information system in the area of online education. So all operators, the CDI and other interfaces associated to the domain expertise and teaching strategies will be unified using FRAME representation form.

Keywords: dialogue, e-learning, FRAME, information system, natural language

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Authors: M. Rashid Hussain, Shady S. Refaat

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The high voltage power transformer is the most essential part of the electrical power utilities. Reliability on the transformers is the utmost concern, and any failure of the transformers can lead to catastrophic losses in electric power utility. The causes of transformer failure include insulation failure by partial discharge, core and tank failure, cooling unit failure, current transformer failure, etc. For the study of power transformer defects, finite element analysis (FEA) can provide valuable information on the severity of defects. FEA provides a more accurate representation of complex geometries because they consider thermal, electrical, and environmental influences on the insulation models to obtain basic characteristics of the insulation system during normal and partial discharge conditions. The purpose of this paper is the time domain analysis of defects 3D model of high voltage power transformer using FEA to study the electric field distribution at different points on the defects.

Keywords: power transformer, finite element analysis, dielectric response, partial discharge, insulation

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Authors: Nadjat Zerf Boudjettou, Fahima Nader, Rachid Chalal

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Knowledge management is to acquire and represent knowledge relevant to a domain, a task or a specific organization in order to facilitate access, reuse and evolution. This usually means building, maintaining and evolving an explicit representation of knowledge. The next step is to provide access to that knowledge, that is to say, the spread in order to enable effective use. Knowledge management in the medical field aims to improve the performance of the medical organization by allowing individuals in the care facility (doctors, nurses, paramedics, etc.) to capture, share and apply collective knowledge in order to make optimal decisions in real time. In this paper, we propose a knowledge management approach based on integration technique of heterogeneous data in the medical field by creating a data warehouse, a technique of extracting knowledge from medical data by choosing a technique of data mining, and finally an exploitation technique of that knowledge in a case-based reasoning system.

Keywords: data warehouse, data mining, knowledge discovery in database, KDD, medical knowledge management, Bayesian networks

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Authors: Tai-Young Park, Yangjin Park

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Introduction: This study analyzed a family therapy case involving a female client in her thirties with panic disorder (PD) in South Korea. We identified five stages of the psychological process in the development of PD and examined external situations, family dynamics, and psychological experiences at each stage. Method: The client, mother, sister, and husband participated in therapy. Researchers analyzed the transcripts, notes, and video recordings of the therapy sessions. A thematic analysis was used to examine the data and display our findings using a network. Results: The developmental process of PD was as follows: (1) formation of anxiety, (2) sheltered life, (3) crisis, (4) loss of safe haven, and (5) inner breakdown. Conclusion: The family dynamics that developed as a result of coping with external situations in each stage contributed to clients’ psychological experiences. These psychological experiences triggered anxiety, which led to the development of PD. Moreover, this study empirically suggests that family dynamics can be associated with a person’s internal experiences that could lead to PD. Our findings highlight the significance of functional family dynamics and coping patterns when facing difficult external situations or crises.

Keywords: developmental process, family therapy, panic disorder, psychological dynamics

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Authors: Sandhya Rao Mehta

Abstract:

As ChatGpt and other Artificial Intelligence (AI) forms are becoming part of our regular academic world, the consequences are being gradually discussed. The extent to which an essay written by a student is itself of any value if it has been downloaded by some form of AI is perhaps central to this discourse. A larger question is whether writing should be taught as an academic skill at all. In literature classrooms, this has major consequences as writing a traditional paper is still the single most preferred form of assessment. This study suggests that it is imperative to investigate alternative forms of assessment in literature, not only because the existing forms can be written by AI, but in a larger sense, students are increasingly skeptical of the purpose of such work. The extent to which an essay actually helps the students professionally is a question that academia has not yet answered. This paper suggests that using real-world tasks like creating podcasts, video tutorials, and websites is a far better way to evaluate students' critical thinking and application of ideas, as well as to develop digital skills which are important to their future careers. Using the example of a course in literature, this study will examine the possibilities and challenges of creating digital projects as a way of confronting the complexities of student evaluation in the future. The study is based on a specific university English as a Foreign Language (EFL) context.

Keywords: assessment, literature, digital humanities, chatgpt

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