Search results for: learning motion patterns

Authors: Heesuk Seo, Yongtae Kim

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Online learning started in the 1990s, the spread of the Internet has been through the era of e-learning paradigm of online education in the era of smart learning change. Reflecting the different nature of the mobile to anywhere anytime, anywhere was also allows the form of learning, it was also available through the learning content and interaction. We are developing a cloud system, 'TLINKS CLOUD' that allows you to configure the environment of the smart learning without the need for additional infrastructure. Using the big-data analysis for e-learning contents, we provide an integrated solution for e-learning tailored to individual study.

Keywords: authority tool, big data analysis, e-learning, HTML5

Procedia PDF Downloads 369

Authors: Yudhajit Datta, Hamsi Iyer, Jonathan Bandi, Ankit Sethia

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Motion Tracking and Stereo Vision are complicated, albeit well-understood problems in computer vision. Existing softwares that combine the two approaches to perform stereo motion tracking typically employ complicated and computationally expensive procedures. The purpose of this study is to create a simple and effective solution capable of combining the two approaches. The study aims to explore a strategy to combine the two techniques of two-dimensional motion tracking using Kalman Filter; and depth detection of object using Stereo Vision. In conventional approaches objects in the scene of interest are observed using a single camera. However for Stereo Motion Tracking; the scene of interest is observed using video feeds from two calibrated cameras. Using two simultaneous measurements from the two cameras a calculation for the depth of the object from the plane containing the cameras is made. The approach attempts to capture the entire three-dimensional spatial information of each object at the scene and represent it through a software estimator object. In discrete intervals, the estimator tracks object motion in the plane parallel to plane containing cameras and updates the perpendicular distance value of the object from the plane containing the cameras as depth. The ability to efficiently track the motion of objects in three-dimensional space using a simplified approach could prove to be an indispensable tool in a variety of surveillance scenarios. The approach may find application from high security surveillance scenes such as premises of bank vaults, prisons or other detention facilities; to low cost applications in supermarkets and car parking lots.

Keywords: kalman filter, stereo vision, motion tracking, matlab, object tracking, camera calibration, computer vision system toolbox

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Authors: Rachel S. E. Lim, Winnie L. C. Tan

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Visual literacy is about making meaning through the interaction of images, words, and sounds. Graphic communication students typically develop visual literacy through critique and production of studio-based projects for their portfolios. However, the abrupt switch to online learning during the COVID-19 pandemic has made it necessary to consider new strategies of visualization and planning to scaffold teaching and learning. This study, therefore, investigated how MIRO, a cloud-based visual collaboration platform, could be used to develop the visual literacy confidence of 30 diploma in graphic communication students attending a graphic design course at a Singapore arts institution. Due to COVID-19, the course was taught fully online throughout a 16-week semester. Guided by Kolb’s Experiential Learning Cycle, the two lecturers developed students’ engagement with visual literacy concepts through different activities that facilitated concrete experiences, reflective observation, abstract conceptualization, and active experimentation. Throughout the semester, students create, collaborate, and centralize communication in MIRO with infinite canvas, smart frameworks, a robust set of widgets (i.e., sticky notes, freeform pen, shapes, arrows, smart drawing, emoticons, etc.), and powerful platform capabilities that enable asynchronous and synchronous feedback and interaction. Students then drew upon these multimodal experiences to brainstorm, research, and develop their motion design project. A survey was used to examine students’ perceptions of engagement (E), confidence (C), learning strategies (LS). Using multiple regression, it¬ was found that the use of MIRO helped students develop confidence (C) with visual literacy, which predicted performance score (PS) that was measured against their application of visual literacy to the creation of their motion design project. While students’ learning strategies (LS) with MIRO did not directly predict confidence (C) or performance score (PS), it fostered positive perceptions of engagement (E) which in turn predicted confidence (C). Content analysis of students’ open-ended survey responses about their learning strategies (LS) showed that MIRO provides organization and structure in documenting learning progress, in tandem with establishing standards and expectations as a preparatory ground for generating feedback. With the clarity and sequence of the mentioned conditions set in place, these prerequisites then lead to the next level of personal action for self-reflection, self-directed learning, and time management. The study results show that the affordances of MIRO can develop visual literacy and make up for the potential pitfalls of student isolation, communication, and engagement during online learning. The context of how MIRO could be used by lecturers to orientate students for learning in visual literacy and studio-based projects for future development are discussed.

Keywords: design education, graphic communication, online learning, visual literacy

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: wavelet transform, computational error, computational duration, strong ground motion data

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Authors: Ching-Ting Hsu, Wei-Hua Ho, Yi-Chun Chang

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Video object tracking is one of the popular research topics in computer graphics area. The trajectory can be applied in security, traffic control, even the sports training. The trajectory for sports training can be utilized to analyze the athlete’s performance without traditional sensors. There are many relevant works which utilize mean shift algorithm with background subtraction. This kind of the schemes should select a kernel function which may affect the accuracy and performance. In this paper, we consider the motion information in the pre-coded bitstream. The proposed algorithm extracts the trajectory by composing the motion vectors from the pre-coded bitstream. We gather the motion vectors from the overlap area of the object and calculate mean of the overlapped motion vectors. We implement and simulate our proposed algorithm in H.264 video codec. The performance is better than relevant works and keeps the accuracy of the object trajectory. The experimental results show that the proposed trajectory extraction can extract trajectory form the pre-coded bitstream in high accuracy and achieve higher performance other relevant works.

Keywords: H.264, video bitstream, video object tracking, sports training

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Authors: Alfonsina Buoniconto

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The aim of this study is to investigate the degree of cross-linguistic and intra-linguistic variation in the encoding of motion events (MEs) in English and Italian, these being typologically different languages both showing signs of disobedience to their respective types. As a matter of fact, the traditional typological classification of MEs encoding distributes languages into two macro-types, based on the preferred locus for the expression of Path, the main ME component (other components being Figure, Ground and Manner) characterized by conceptual and structural prominence. According to this model, Satellite-framed (SF) languages typically express Path information in verb-dependent items called satellites (e.g. preverbs and verb particles) with main verbs encoding Manner of motion; whereas Verb-framed languages (VF) tend to include Path information within the verbal locus, leaving Manner to adjuncts. Although this dichotomy is valid altogether, languages do not always behave according to their typical classification patterns. English, for example, is usually ascribed to the SF type due to the rich inventory of postverbal particles and phrasal verbs used to express spatial relations (i.e. the cat climbed down the tree); nevertheless, it is not uncommon to find constructions such as the fog descended slowly, which is typical of the VF type. Conversely, Italian is usually described as being VF (cf. Paolo uscì di corsa ‘Paolo went out running’), yet SF constructions like corse via in lacrime ‘She ran away in tears’ are also frequent. This paper will try to demonstrate that such a typological overlapping is due to the fact that the semantic units making up MEs are distributed within several loci of the sentence –not only verbs and satellites– thus determining a number of different constructions stemming from convergent factors. Indeed, the linguistic expression of motion events depends not only on the typological nature of languages in a traditional sense, but also on a series morphological, lexical, and syntactic resources, as well as on inferential, discursive, usage-related, and cultural factors that make semantic information more or less accessible, frequent, and easy to process. Hence, rather than describe English and Italian in dichotomic terms, this study focuses on the investigation of cross-linguistic and intra-linguistic variation in the use of all the strategies made available by each linguistic system to express motion. Evidence for these assumptions is provided by parallel corpora analysis. The sample texts are taken from two contemporary Italian novels and their respective English translations. The 400 motion occurrences selected (200 in English and 200 in Italian) were scanned according to the MODEG (an acronym for Motion Decoding Grid) methodology, which grants data comparability through the indexation and retrieval of combined morphosyntactic and semantic information at different levels of detail.

Keywords: construction typology, motion event encoding, parallel corpora, satellite-framed vs. verb-framed type

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Authors: Hussein Altartouri

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In this paper the kinematic and kinetic models of an omnidirectional holonomic mobile robot is presented. The kinematic and kinetic models form the OmniDrive model. Therefore, a mathematical model for the robot equipped with three- omnidirectional wheels is derived. This model which takes into consideration the kinematics and kinetics of the robot, is developed to state space representation. Relative analysis of the velocities and displacements is used for the kinematics of the robot. Lagrange’s approach is considered in this study for deriving the equation of motion. The drive train and the mechanical assembly only of the Festo Robotino® is considered in this model. Mainly the model is developed for motion control. Furthermore, the model can be used for simulation purposes in different virtual environments not only Robotino® View. Further use of the model is in the mechatronics research fields with the aim of teaching and learning the advanced control theories.

Keywords: mobile robot, omni-direction wheel, mathematical model, holonomic mobile robot

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Authors: Tracy Ho, Huann-Shyang Lin, Mina Lin

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This study investigated the different learning path of students with different learning attitude and learning styles in Arts Creation. Based on direct instruction, guided-discovery learning, and discovery learning theories, a tablet app including the following three learning areas were developed for students: (1) replication and remix practice area, (2) guided creation area, and (3) free creation area. Thirty. students with different learning attitude and learning styles were invited to use this app. Students’ learning behaviors were categorized and defined. The results will provide both educators and researchers with insights that can form a useful foundation for designing different content and strategy with the application of new technologies in school teaching. It also sheds light on how an educational App can be designed to enhance Arts Creation.

Keywords: App, arts creation, learning attitude, learning style, tablet

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Authors: Sung-Pill Kim, Dae-Gyu Sung, Hee-Sung Shin, Jong-Chun Park

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When a sloshing tank filled partially with liquid is excited with the motion of platform, it can be observed that the center of mass inside the tank is changed and impact loads is instantaneously applied to the wall, which causes dynamic loads additionally to the supporting links of platform. In this case, therefore, the dynamic behavior of platform associated with fluid motion should be considered in the early stage of design for safety and economics of the system. In this paper, the dynamic loads due to liquid sloshing motion in a rectangular tank which is loaded up on the upper deck of a Stewart platform are simulated using a coupled analysis of Moving Particle Simulation (MPS) and Flexible Multi-Body Dynamics (FMBD). The co-simulation is performed using two commercial softwares, Recurdyn for solving FMBD and Particleworks for analyzing fluid motion based on MPS method. For validating the present coupled system, a rectangular sloshing tank being enforced with inline sway motion by 1-DOF motion platform is assumed, and time-varied free-surface elevation and reaction force at a fixed joint are compared with experiments.

Keywords: dynamic loads, liquid sloshing tank, Stewart platform, moving particle semi-implicit (MPS) method, flexible multi-body dynamics (FMBD)

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Authors: Esra Alhamal

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Islamic architecture is known for the ornamental patterns that cover the architectural surfaces: floors, walls, and ceilings. This quality in Islamic buildings has long impressed other civilisation, and it is a visual language that exists across the Islamic lands. Ornamentation is divided into three types: geometry, biomorphs, and Arabic calligraphy. The focus of this study is the biomorphic ornaments. This paper will aim to define and characterise biomorphic patterns and trace their development from the 7th to the 18th centuries. Although the time period is seemingly long, the biomorphic patterns and their motifs have been consistent and supported by a geometric system underlying the free flowing, symmetrical motifs. The methodology of this paper consists of analysing and comparing biomorphic patterns from each Islamic period using rules of geometry and symmetry. The study is concluded with a table showcasing the main motifs and how they developed under each Islamic dynasty. This research is a documentation of the biomorphic language and having this record will help contemporary designers employ biomorphic ornaments thoughtfully.

Keywords: architectural surface, biomorphic patterns, Islamic patterns, Islamic ornamentation

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Authors: N. Ipiña, R. Basagoiti, O. Jimenez, I. Arriaran

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Higher education students are increasingly enrolling in online courses, they are, at the same time, generating data about their learning process in the courses. Data collected in those technology enhanced learning spaces can be used to identify patterns and therefore, offer recommendations/personalized courses to future online students. Moreover, recommendations are considered key aspects for personalization in online learning. Taking into account the above mentioned context, the aim of this paper is to explore the perception of higher education students and teachers towards receiving recommendations in online courses. The study was carried out with 322 students and 10 teachers from two different faculties (Engineering and Education) from Mondragon University. Online questionnaires and face to face interviews were used to gather data from the participants. Results from the questionnaires show that most of the students would like to receive recommendations in their online courses as a guide in their learning process. Findings from the interviews also show that teachers see recommendations useful for their students’ learning process. However, teachers believe that specific pedagogical training is required. Conclusions can also be drawn as regards the importance of personalization in technology enhanced learning. These findings have significant implications for those who train online teachers due to the fact that pedagogy should be the driven force and further training on the topic could be required. Therefore, further research is needed to better understand the impact of recommendations on online students’ learning process and draw some conclusion on pedagogical concerns.

Keywords: higher education, perceptions, recommendations, online courses

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Authors: Haq Nawaz, Muhammad Amjad Iqbal, Kamran Malik

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"Altasreef" is an automated system available for Web and Android users which provide facility to the users to learn the Quran verbs. It provides the facility to the users to practice the learned material and also provide facility of exams of Arabic verbs variation focusing on Quran text. Arabic is a highly inflectional language. Almost all of its words connect to roots of three, four or five letters which approach the meaning of all their inflectional forms. In Arabic, a verb is formed by inserting the consonants into one of a set of verb patterns. Suffixes and prefixes are then added to generate the meaning of number, person, and gender. The active/passive voice and perfective aspect and other patterns are than generated. This application is designed for learners of Quranic Arabic who already have learn basics of Arabic conjugation. Application also provides the facility of translation of generated patterns. These translations are generated with the help of rule-based approach to give 100% results to the learners.

Keywords: NLP, Quran, Computational Linguistics, E Learning

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Authors: S. Jagadeesh Kumar

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This expose presents a luculent of recent machine learning practices as employed in the modern and as pertinent to prospective automatic speech recognition schemes. The aspiration is to promote additional traverse ablution among the machine learning and automatic speech recognition factions that have transpired in the precedent. The manuscript is structured according to the chief machine learning archetypes that are furthermore trendy by now or have latency for building momentous hand-outs to automatic speech recognition expertise. The standards offered and convoluted in this article embraces adaptive and multi-task learning, active learning, Bayesian learning, discriminative learning, generative learning, supervised and unsupervised learning. These learning archetypes are aggravated and conferred in the perspective of automatic speech recognition tools and functions. This manuscript bequeaths and surveys topical advances of deep learning and learning with sparse depictions; further limelight is on their incessant significance in the evolution of automatic speech recognition.

Keywords: automatic speech recognition, deep learning methods, machine learning archetypes, Bayesian learning, supervised and unsupervised learning

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Authors: Adelia Desi Agnesita

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The advent of a new disease called covid-19 made many major changes in the world, one of which is the process of learning and teaching. Learning formerly offline but now is done online, which makes students need adaptation to the learning process. The covid-19 pandemic that occurs almost worldwide causes activities that involve many people to be avoided, one of which is learning to teach. In Indonesia, since March 2020, the process of college learning is turning into online/ long-distance learning. It's to prevent the spread of the covid-19. Student online learning presents some of the obstacles to poor signals, many of the tasks, lack of focus, difficulty sleeping, and resulting stress.

Keywords: learning, online, covid-19, pandemic

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Authors: Sandeep, A. Joshi, Kamal, Piu Dhibar, Parveen Kumar

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In the present work strong ground motion has been simulated using a modified semi-empirical technique (MSET), with frequency dependent radiation pattern model. Joshi et al. (2014) have modified the semi-empirical technique to incorporate the modeling of strong motion generation areas (SMGAs). A frequency dependent radiation pattern model is applied to simulate high frequency ground motion more precisely. Identified SMGAs (Kurahashi and Irikura 2012) of the 2011 Tohoku earthquake (Mw 9.0) were modeled using this modified technique. Records are simulated for both frequency dependent and constant radiation pattern function. Simulated records for both cases are compared with observed records in terms of peak ground acceleration and pseudo acceleration response spectra at different stations. Comparison of simulated and observed records in terms of root mean square error suggests that the method is capable of simulating record which matches in a wide frequency range for this earthquake and bears realistic appearance in terms of shape and strong motion parameters. The results confirm the efficacy and suitability of rupture model defined by five SMGAs for the developed modified technique.

Keywords: strong ground motion, semi-empirical, strong motion generation area, frequency dependent radiation pattern, 2011 Tohoku Earthquake

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Authors: Jonathan J. Foo, Keng Hao Chew

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Interest in virtual reality (VR) technologies as virtual learning environments have been on the rise in recent years. With thanks to the aggressively competitive consumer electronics environment, VR technology has been made affordable and accessible to the average person with developments like Google Cardboard and Oculus Go. While the promise of virtual access to unique virtual learning environments with the benefits of experiential learning sounds extremely attractive, there are still concerns over user comfort in the psychomotor, cognitive, and affective domains. Reports of motion sickness and short durations create doubt and have stunted its growth. In this paper, a multidimensional framework is proposed for the evaluation of VR learning environments within the three dimensions: tactual quality, didactic quality, and autodidactic quality. This paper further proposes a mixed-methods experimental research plan that sets out to evaluate a virtual reality training simulator in the context of amateur sports fencing. The study will investigate if an immersive VR learning environment can effectively simulate an authentic learning environment suitable for instruction, practice, and assessment while providing the user comfort in the tactual, didactic, and autodidactic dimensions. The models and recommendations developed for this study are designed in the context of fencing, but the potential impact is a guide for the future design and evaluation of all VR developments across sports and technical classroom education.

Keywords: autodidactic quality, didactic quality, tactual quality, virtual reality

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Authors: Tomas Trainys, Algimantas Venckauskas

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Application of biometric features to the cryptography for human identification and authentication is widely studied and promising area of the development of high-reliability cryptosystems. Biometric cryptosystems typically are designed for patterns recognition, which allows biometric data acquisition from an individual, extracts feature sets, compares the feature set against the set stored in the vault and gives a result of the comparison. Preprocessing and fusion of biometric data are the most important phases in generating a feature vector for key generation or authentication. Fusion of biometric features is critical for achieving a higher level of security and prevents from possible spoofing attacks. The paper focuses on the tasks of initial processing and fusion of multiple representations of finger vein modality patterns. These tasks are solved by applying conventional image preprocessing methods and machine learning techniques, Convolutional Neural Network (SVM) method for image segmentation and feature extraction. An article presents a method for generating sets of biometric features from a finger vein network using several instances of the same modality. Extracted features sets were fused at the feature level. The proposed method was tested and compared with the performance and accuracy results of other authors.

Keywords: bio-cryptography, biometrics, cryptographic key generation, data fusion, information security, SVM, pattern recognition, finger vein method.

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Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Ajeevan Gautam, Gulam Anwer Khan, Pratibha Pokhrel

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Introduction: Dermatoglyphics is the science which deals with the study of dermal ridge configuration on the digits, palms and soles. It is grooved by ridges and forms variety of configurations. The aim of the study was to identify dermal ridge patterns on fingertip of hypertensive patients and in normal population and to compare patterns among them. Methods: The subjects of the study were 130 hypertensives and 130 non-hypertensives cases of Kathmandu Valley aged between 40 to 80 years. Case history was recorded after consent finger prints were taken. Different parameters as whorl, loop, arch and composite patterns were studied and analysed. Result: It revealed, increased whorl pattern in hypertensive. It showed 65.69% whorl, 29.23% loop and 5.07% arch patterns in right hand of hypertensive people. In control, it was found to be 34.46% whorl, 58.15% loop and 5.38% arch patterns respectively. Similarly in left hand 63.69% whorl, 32% loop and 4.30% arch in hypertensive group. In control group it was 60.15% as loop, 35.69% as whorl and 15% as arch. Discussion: Based on findings of the result, it was concluded that the whorl, loop and arch patterns observed as 65.69%, 29.23% and 5.07% respectively in hypertensive cases in right hand. Similarly in left hand, it was found to be 4.30% as arch, 32% as loop and 63.69% as whorl patterns, but in normotensive subjects these patterns were recorded as 36.43%, 58.15%, 5.38% in right hand and 35.69%, 60.15%, 4.15% in left hand as whorl, loop and arch respectively.

Keywords: arch, dermatoglyphics, hypertension, loop, whorl

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Authors: Mohammed Alaa Alwafaie, Bela Kovacs

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With the rapid emergence and evolution of renewable energy sources like wind and solar power, there is an increasing demand for effective energy harvester architectures. This paper focuses on investigating the concept of energy harvesting using a wheel-motion energy source. The proposed method involves the placement of magnets and copper coils inside the hubcap rod of a wheel. When the wheel is set in motion, following Faraday's Law, the movement of the magnet within the coil induces an electric current. The paper includes an experiment to measure the output voltage of electromagnetics, as well as a numerical simulation to further explore the potential of this energy harvesting approach. By harnessing the rotational motion of wheels, this research aims to contribute to the development of innovative techniques for generating electrical power in a sustainable and efficient manner.

Keywords: harvesting energy, electromagnetic, hubcap rod wheel, magnet movement inside coil, faraday law

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Authors: Jun Wang, Ge Zhang

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Machine learning has been used in many areas today. It thrives at reviewing large volumes of data and identifying patterns and trends that might not be apparent to a human. Given the huge potential benefit and the amount of data available in the financial market, it is not surprising to see machine learning applied to various financial products. While future prices of financial securities are extremely difficult to forecast, we study them from a different angle. Instead of trying to forecast future prices, we apply machine learning algorithms to predict the direction of future price movement, in particular, whether a sector Exchange Traded Fund (ETF) would outperform or underperform the market in the next week or in the next month. We apply several machine learning algorithms for this prediction. The algorithms are Linear Discriminant Analysis (LDA), k-Nearest Neighbors (KNN), Decision Tree (DT), Gaussian Naive Bayes (GNB), and Neural Networks (NN). We show that these machine learning algorithms, most notably GNB and NN, have some predictive power in forecasting out-performance and under-performance out of sample. We also try to explore whether it is possible to utilize the predictions from these algorithms to outperform the buy-and-hold strategy of the S&P 500 index. The trading strategy to explore out-performance predictions does not perform very well, but the trading strategy to explore under-performance predictions can earn higher returns than simply holding the S&P 500 index out of sample.

Keywords: machine learning, ETF prediction, dynamic trading, asset allocation

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Authors: Meng-Yu Lin, Wan-Ju Lee

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Pore-water pressure, which mediates effective stress and shear strength at grain contacts, has a great influence on the motion of debris flow. The factors that control the diffusion of excess pore-water pressure play very important roles in the debris-flow motion. This research investigates these effects by solving the distribution of pore-water pressure numerically in an unsteady, surging motion of debris flow. The governing equations are the depth-averaged equations for the motion of debris-flow surges coupled with the one-dimensional diffusion equation for excess pore-water pressures. The pore-pressure diffusion equation is solved using a Fourier series, which may improve the accuracy of the solution. The motion of debris-flow surge is modelled using a Lagrangian particle method. From the computational results, the effects of pore-pressure diffusivities and the initial excess pore pressure on the formations of debris-flow surges are investigated. Computational results show that the presence of pore water can increase surge velocities and then changes the profiles of depth distribution. Due to the linear distribution of the vertical component of pore-water velocity, pore pressure dissipates rapidly near the bottom and forms a parabolic distribution in the vertical direction. Increases in the diffusivity of pore-water pressure cause the pore pressures decay more rapidly and then decrease the mobility of the surge.

Keywords: debris flow, diffusion, Lagrangian particle method, pore-pressure diffusivity, pore-water pressure

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Authors: Nur Azlina Mohamed Mokmin, Mona Masood

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Guided by the theory of learning style, this study is based on the development of a multimedia learning application for students with mastery learning style. The learning material was developed by applying a graduated difficulty learning strategy. Algebraic fraction was chosen as the learning topic for this application. The effectiveness of this application in helping students learn is measured by giving a pre- and post-test. The result shows that students who learn using the learning material that matches their preferred learning style performs better than the students with a non-personalized learning material.

Keywords: algebraic fractions, graduated difficulty, mastery learning style, multimedia

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Authors: Kamel Taıbı, Abdelmadjid Rais

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Nickel–Aluminium ferrites with the general formula Ni Alx Fe2-x O4 (0 ≤ x ≤ 1) were studied using X-ray diffraction, Infra Red and Raman spectroscopy. XRD diffraction patterns and their Reitveld refinements show that all samples have a pure single-phase cubic spinel structure. From these patterns, the lattice parameters of these samples have been calculated and compared with those predicted theoretically. Most of the values were found to decrease with increasing Al content. Infra Red spectra showed two significant absorption bands. The high band corresponds to tetrahedral (A) sites and the lower band to octahedral [B] sites, thus confirming the single phase spinel structure. For all compositions, Raman spectra show the five active modes A1g + E1g + 3 T2g of the motion of O2- ions and both the A-site and B-site ions. The Raman frequencies trend with aluminium concentration show a blue shift for all modes consistent with the replacement of Fe3+ by lower mass Al3+. Composition dependence of the Raman frequency modes is discussed in relationship with the cations distribution among the A-sites and B-sites.

Keywords: Ni-Al ferrites, spinel structure, XRD, Raman spectroscopy

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Authors: Amany Mohamed, Alaa Balbaa, Magdoline Mishel

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Background: Pain in the neck or scapular region is one of the most frequent symptoms in cervical radiculopathy, which is commonly caused by degenerative process in the spine. Purpose: To determine the effect of scapular stabilization exercises in the treatment of chronic neck pain regarding pain and disability and limitation in the range of motion. Patients and Methods: Thirty male and female patients with chronic neck pain were involved. Aged between 30-50 years old. They were randomly assigned into two groups. In group (A), patients received physical therapy program in the form of infrared, transcutaneous electrical nerve stimulation (TENS), Stretching and cervical stabilization exercises. In group (B), patients received scapular stabilization exercises in addition to the same physical therapy program. Treatment was given 3 times a week for 4 weeks. Range of motion of the cervical spine, range of motion of the scapula, neck pain and disability were assessed before and after treatment. Results: There was significant improvement in both groups (A and B) in cervical range of motion, pain and disability. Group (B) showed more significant improvement than group (A) in cervical range of motion and pain and disability. There was no significant improvement in both groups in scapular range of motion. Conclusion: Scapular stabilization exercises should be used as an integral part in the rehabilitation program

Keywords: Neck pain, neck stabilization exercise, scapular stabilization exercise, chronic neck pain

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Authors: Ashwini Mahesh Jagatap

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This paper presents the language learning strategy with respect to speaking skill with collaborative learning approach. Collaborative learning has been proven to be efficient learning methodology for all kinds of students. Students are working in groups of two or more, reciprocally searching for understanding, Solutions, or meanings, or creating a product. The presentation highlights the different stages which can be implemented during actual implementation of the methodology in the class room teaching learning process.

Keywords: collaborative classroom, collaborative learning approach, language skills, traditional teaching

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Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

Abstract:

we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

Procedia PDF Downloads 108

Authors: Amir Taghizadeh Vahed, Adithya Thaduri

Abstract:

Shovels are the main components in the mining transportation system. The productivity of the mines depends on the availability of shovels due to its high capital and operating costs. The unplanned failure/shutdowns of a shovel results in higher repair costs, increase in downtime, as well as increasing indirect cost (i.e. loss of production and company’s reputation). In order to mitigate these failures, predictive maintenance can be useful approach using failure prediction. The modern mining machinery or shovels collect huge datasets automatically; it consists of reliability and maintenance data. However, the gathered datasets are useless until the information and knowledge of data are extracted. Machine learning as well as data mining, which has a major role in recent studies, has been used for the knowledge discovery process. In this study, data mining and machine learning approaches are implemented to detect not only anomalies but also patterns from a dataset and further detection of failures.

Keywords: maintenance, machine learning, shovel, conditional based monitoring

Procedia PDF Downloads 170

Authors: Ting-Ting Wen, H. C. Lin

Abstract:

This paper reports a study for the light outcoupling efficiency of the PLED device. In use of a designed substrate combined with nano-line patterns in PLED device, the light outcoupling efficiency can be significantly enhanced. The designed substrate was made by UV imprinting technology, such as triangular microlens arrays on the front and periodic corrugated patterns on the back surface. The nano-line patterns in PLED device was fabricated by advanced microstamping and ink-jet printing techniques. For high angles of observation with respect to the substrate surface normal, the light out intensity of the developed PLED device is increased from 0.05 (a.u.) up to 0.69 (a.u.) at the view angle 85 degree. The designed integration leads to 64% increase of the light out intensity compared with the conventional PLED device.

Keywords: triangular microlens, corrugation patterns, nano-line patterns, PLED device, UV imprinting technology, microstamping

Procedia PDF Downloads 441

Authors: Darshana Lal, Sonu Rana

Abstract:

Learning Resource Centers (LRC) are acquiring different kinds of documents like books, journals, thesis, dissertations, standard, databases etc. in print and e-form. This article deals with the different types of sources available in LRC. It also discusses the concept of the web, as a tool, as a multimedia system and the different interfaces available on the web. The reasons for establishing LRC are highlighted along with the assignments of LRC. Different features of LRC‘S like self-learning and group learning are described. It also implements a group of activities like reading, learning, educational etc. The use of LRC by students and faculties are given and concluded with the benefits.

Keywords: internet, search engine, resource centre, opac, self-learning, group learning

Procedia PDF Downloads 344