Search results for: computer terms

Authors: Yogesh Kumar Tiwari

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Chhattisgarh has realized the fundamental role of information and communication technology in the globalized world where knowledge is at the top for the growth and intellectual development. They are spreading so widely that one feels lagging behind if not using them. The influence of these radiating and technological tools has encompassed all aspects of the educational, business, and economic sectors of our world. Undeniably the computer has not only established itself globally in all walks of life but has acquired a fundamental role of paramount importance in the educational process also. This role is getting all pervading and more powerful as computers are being manufactured to be cheaper, smaller in size, adaptable and easy to handle. Computers are becoming indispensable to teachers because of their enormous capabilities and extensive competence. This study aims at observing the effect of using computer based software program of English language on the achievement of undergraduate level students studying in tribal area like Sarguja Division, Chhattisgarh, India. To testify the effect of an innovative teaching in the graduate classroom in tribal area 50 students were randomly selected and separated into two groups. The first group of 25 students were taught English grammar i.e., passive voice/narration, through traditional method using chalk and blackboard asking some formal questions. The second group, the experimental one, was taught English grammar i.e., passive voice/narration, using computer, projector with power point presentation of grammatical items. The statistical analysis was done on the students’ learning capacities and achievement. The result was extremely mesmerizing not only for the teacher but for taught also. The process of the recapitulation demonstrated that the students of experimental group responded the answers of the questions enthusiastically with innovative sense of learning. In light of the findings of the study, it was recommended that teachers and professors of English ought to use self-made instructional program in their teaching process particularly in tribal areas.

Keywords: achievement computer assisted language learning, use of instructional program

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Authors: Donna H. Gabor

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This study aimed to develop and validate an electronic module in physics for first-year college students of Iloilo and find out if there would be a significant difference in the performance of students before and after using the electronic module. The e-module was composed of one topic with two sub-lessons in linear motion (kinematics). The participants of the study were classified into three groups: the subject matter experts who are physics instructors who suggested the content, physical appearance, and limitations of the e-module; the IT experts who are active both in teaching and developing computer programs; and 28 students divided into two groups, 15 in the pilot group and 13 in the final test group. A researcher created 30 items checklist form (difficulty of a sample problem, comprehension, application, and definition of terms) was prepared and validated by the experts in subject matter for gathering data. To test the difference in student performance in physics, the researcher prepared an achievement test containing 25 items, multiple choices. The findings revealed that there was an increase in the performance of students in the pretest and post-test. T-test results revealed that there was a significant difference in the test scores of the students before and after using the module which can be used as a future reference for linear motion as an additional teaching tool in physics.

Keywords: electronic module, kinematics, linear motion, physics

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Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

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Authors: Sarantos Psycharis

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Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM

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Authors: Wilailuk Meepracha

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The results of the study on the project evaluation to develop the competencies, capabilities, and skills in repairing computers of people in Jompluak Local Municipality, Bang Khonthi District, Samut Songkram Province showed that the overall result was good (4.33). When considering on each aspect, it was found that the highest one was on process evaluation (4.60) followed by product evaluation (4.50) and the least one was on feeding factor (3.97). When considering in details, it was found that: 1) the context aspect was high (4.23) with the highest item on the arrangement of the training situation (4.67) followed by the appropriateness of the target (4.30) and the least aspect was on the project cooperation (3.73). 2) The evaluation of average overall primary factor or feeding factor showed high value (4.23) while the highest aspect was on the capability of the trainers (4.47) followed by the suitable venue (4.33) while the least aspect was on the insufficient budget (3.47). 3) The average result of process evaluation was very high (4.60). The highest aspect was on the follow-op supervision (4.70) followed by responsibility of each project staffs (4.50) while the least aspect was on the present situation and the problems of the community (4.40). 4) The overall result of the product evaluation was very high (4.50). The highest aspect was on the diversity of the activities and the community integration (4.67) followed by project target achievement (4.63) while the least aspect was on continuation and regularity of the activities (4.33). The trainees reported high satisfaction on the project management at very high level (43.33%) while 40% reported high level and 16.67% reported moderate level. Suggestions for the project were on the additional number of the computer sets (37.78%) followed by longer training period especially on computer skills (43.48%).

Keywords: project evaluation, competency development, the capability on computer repairing and computer skills

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Authors: S. Alotaibi, S. Omer, Y. Su

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The conventional Internal Combustion Engine (ICE) based vehicles are a threat to the environment as they account for a large proportion of the overall greenhouse gas (GHG) emissions in the world. Hence, it is required to replace these vehicles with more environment-friendly vehicles. Electric Vehicles (EVs) are promising technologies which offer both human comfort “noise, pollution” as well as reduced (or no) emissions of GHGs. In this paper, different types of EVs are reviewed and their advantages and disadvantages are identified. It is found that in terms of fuel economy, Plug-in Hybrid EVs (PHEVs) have the best fuel economy, followed by Hybrid EVs (HEVs) and ICE vehicles. Since Battery EVs (BEVs) do not use any fuel, their fuel economy is estimated as price per kilometer. Similarly, in terms of GHG emissions, BEVs are the most environmentally friendly since they do not result in any emissions while HEVs and PHEVs produce less emissions compared to the conventional ICE based vehicles. Fuel Cell EVs (FCEVs) are also zero-emission vehicles, but they have large costs associated with them. Finally, if the electricity is provided by using the renewable energy technologies through grid connection, then BEVs could be considered as zero emission vehicles.

Keywords: electric vehicles, zero emission car, fuel economy, CO₂ footprint

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Authors: Nebojša Janićijević

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The paper presents the results of a study on work-related values of Generation Z, comprised of young people born between the late 1990s and 2010. Following Millennials, Generation Z is the first generation of digital natives. This is the reason, along with some other circumstances that accompanied them during their growing up, why Generation Z has somewhat different work-related values than previous generations. Since they are just beginning to enter the labor market and will be the majority of the workforce in the next decade or two, it is very important and useful for their employers to understand what Generation Z values when it comes to work. The study was conducted by surveying the students of the Faculty of Economics, University of Belgrade, Serbia, during 2022 and 2023. The research results show that Generation Z values safety, achievement, and status the most in the workplace. From the individual perspective, future employees consider it most important that their job provides good working conditions, recognition for the work performed, and the possibility of achievement. It is noticeable that Generation Z students, to a significant extent, expect to be protected and safe at work in the future, both in terms of the job itself and in terms of social relations. According to the research findings, Generation Z is relatively homogeneous, and no significant differences in work-related values were found among them, except by gender.

Keywords: generation Z, work related values, students, Serbia

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Authors: M. A. Rahman, A. O. Enikuomehin

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Sharing commitment to reach a common goal in research by harnessing available resources from two or more parties can simply be referred to as collaborative research. Asides from avoiding duplication of research, the benefits often accrued from such research alliances include time economy as well as expenses reduction in completing such studies. Likewise, it provides an avenue to produce a wider horizon of scientific knowledge sequel to gathering of skills, knowledge and resources. In institutions of higher learning and research institutes, it often gives scholars an opportunity to strengthen the teaching and research capacity of their various institutions. Between industries and institutions, collaborative research breeds promising relationship that could be geared towards addressing different research problems such as producing and enhancing industrial-based products and services, including technological transfer. For Nigeria to take advantage of this collaboration, different issues like licensing of technology, intellectual property right, confidentiality, and funding among others, which could arise during this collaborative research programme, are identified in this paper. An important tool required to achieve this height in developing economy is the use of appropriate computer model. The paper highlights the costs of the collaborations and likewise stresses the need for evaluating the effectiveness and efficiency of such collaborative research activities and proposes an appropriate computer model to assist in this regard.

Keywords: collaborative research, developing country, computerization, model

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Authors: Sevim Oztimurlenk

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This is an exploratory study on the information behavior of human resource managers. This study is conducted by using a questionnaire survey and an interview. The data is gathered from 140 HR managers who are members of the People Management Association of Turkey (PERYÖN), and the 15 interviewees were chosen among those 140 survey participants randomly. The goal of this exploratory study is to investigate the impact of some factors (i.e., gender, age, work experience, number of employee reporting, company size, industry type) on HR managers’ information behavior. More specifically, it examines if there is a relationship between those factors and HR managers’ information behavior in terms of what kind of information sources they consult and reviews and whom they prefer to communicate with for information sharing. It also aims to find out additional factors influencing the information behavior of HR managers. The results of the study show that age and industry type are the two factors affecting the information behavior of HR managers, among other factors investigated in terms of information source, use and share. Moreover, personality, technology, education, organizational culture, and culture are the top five factors among the 24 additional factors suggested by HR managers who participated in this study.

Keywords: information behavior, information use, information source, information share, human resource managers

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Authors: Md. Ehsan, Cyrus Ashok Arupratan Atis

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Significantly lower cost, bulk availability, absence of identification color additives and relative ease of mixing with fuels have made gas-field condensates a lucrative option as adulterant for gasoline in Bangladesh. Widespread adulteration of fuels with gas-field condensates being a problem existing mainly in developing countries like Bangladesh, Nigeria etc., research works regarding the effect of such fuel adulteration are very limited. Since the properties of the gas-field condensate vary widely depending on geographical location, studies need to be based on local condensate feeds. This study quantitatively evaluates the effects of blending of gas-field condensates with gasoline(octane) in terms of - fuel properties, engine performance and exhaust emission. Condensate samples collected from Kailashtila gas field were blended with octane, ranging from 30% to 75% by volume. However for blends with above 60% condensate, cold starting of engine became difficult. Investigation revealed that the condensate samples had significantly higher distillation temperatures compared to octane, but were not far different in terms of heating value and carbon residues. Engine tests showed Kailashtila blends performing quite similar to octane in terms of power and thermal efficiency. No noticeable knocking was observed from in-cylinder pressure traces. For all the gasoline-condensate blends the test engine ran with relatively leaner air-fuel mixture delivering slightly lower CO emissions but HC and NOx emissions were similar to octane. Road trials of a test vehicle in real traffic condition and on a standard gradient using 50%(v/v) gasoline-condensate blend were also carried out. The test vehicle did not exhibit any noticeable difference in drivability compared to octane.

Keywords: condensates, engine performance, fuel adulteration, gasoline-condensate blends

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Authors: Subhra Prosun Paul, Shruti Aggarwal

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Now a days Routing Protocol in Wireless Sensor Network has become a promising technique in the different fields of the latest computer technology. Routing in Wireless Sensor Network is a demanding task due to the different design issues of all sensor nodes. Network architecture, no of nodes, traffic of routing, the capacity of each sensor node, network consistency, service value are the important factor for the design and analysis of Routing Protocol in Wireless Sensor Network. Additionally, internal energy, the distance between nodes, the load of sensor nodes play a significant role in the efficient routing protocol. In this paper, our intention is to analyze the research trends in different routing protocols of Wireless Sensor Network in terms of different parameters. In order to explain the research trends on Routing Protocol in Wireless Sensor Network, different data related to this research topic are analyzed with the help of Web of Science and Scopus databases. The data analysis is performed from global perspective-taking different parameters like author, source, document, country, organization, keyword, year, and a number of the publication. Different types of experiments are also performed, which help us to evaluate the recent research tendency in the Routing Protocol of Wireless Sensor Network. In order to do this, we have used Web of Science and Scopus databases separately for data analysis. We have observed that there has been a tremendous development of research on this topic in the last few years as it has become a very popular topic day by day.

Keywords: analysis, routing protocol, research trends, wireless sensor network

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Authors: Asad Iqbal, Feixiang Zan, Xiaoming Liu, Guang-Hao Chen

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Water, food, and energy nexus is a vital subject to achieve sustainable development goals worldwide. Wastewater (WW) and food waste (FW) from municipal sources are primary contributors to their respective wastage sum from a country. Along with the loss of these invaluable natural resources, their treatment systems also consume a lot of abiotic energy and resources input with a perceptible contribution to global warming. Hence, the global paradigm has evolved from simple pollution mitigation to a resource recovery system (RRS). In this study, the prospects of six alternative FW treatment scenarios are quantitatively evaluated for Hong Kong in terms of energy use and greenhouse emissions (GHEs) potential, using life cycle assessment (LCA). Considered scenarios included: aerobic composting, anaerobic digestion (AD), combine AD and composting (ADC), co-disposal, and treatment with wastewater (CoD-WW), incineration, and conventional landfilling as base-case. Results revealed that in terms of GHEs saving, all-new scenarios performed significantly better than conventional landfilling, with ADC scenario as best-case and incineration, AD alone, CoD-WW ranked as second, third, and fourth best respectively. Whereas, composting was the worst-case scenario in terms of energy balance, while incineration ranked best and AD alone, ADC, and CoD-WW ranked as second, third, and fourth best, respectively. However, these results are highly sensitive to boundary settings, e.g., the inclusion of the impact of biogenic carbon emissions and waste collection and transportation, and several other influential parameters. The study provides valuable insights and policy guidelines for the decision-makers locally and a generic modelling template for environmental impact assessment.

Keywords: food waste, resource recovery, greenhouse emissions, energy balance

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Authors: Jenney Perez Bacalla

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The study was conducted to assess the five (5) identified school administrators of the identified secondary schools in terms of professional characteristics, management skills and values patterns in the Division of Leyte Area IV for a proposed enhancement model for school administrators. The study utilized the qualitative method. There were two (2) groups of respondents: the teachers and the school administrators. The teachers perceived the management skills of the school administrators in their technical and conceptual skills and values in planning and organizing work, allocating and using of funds, submitting reports, decision-making, leading people, public relations and community involvement and other value development. It was found out in the study that most of the school administrators’ management skills were very well manifested. Their value patterns were also very well manifested. Most of them had earned master’s degree and with a unit in doctoral and five (5) years and above in service as a school administrator. Most administrators were performing and successfully execute the planning, organizing and utilizing funds and they were able to lead their subordinates. In planning, it shows that administrators studied the future and arrange the plan. Administrators also were able to manage, maintained the good environment wherein individual work together. School administrators were creating an environment conducive to learning. The school administrator is manifesting the desirable practices in school management. In terms of their educational qualifications, they were all qualified. Academic preparation, trainings and maturation were their attributes to the development of managerial skills of the school administrators. They showed competence in the areas of management skills that they were able to carry their functions with utmost responsibility and capability. School administrators in terms of seminars and trainings on administration and supervision were already equipped. It is concluded that the school administrators possessed the necessary skills and work values in administering the school.

Keywords: management skills and values, public secondary schools, qualitative, school administrators

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Authors: Q. Raza

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Getting old is inevitable, tasks which were once simple are now a daily struggle. This paper is a study of how older users interact with web application based upon a series of experiments. The experiments conducted involved 12 participants and the experiments were split into two parts. The first set gives the users a feel of current social networks and the second set take into considerations from the participants and the results of the two are compared. This paper goes in detail on the psychological aspects such as social exclusion, Metacognition memory and Therapeutic memories and how this relates to users becoming isolated from society, social networking can be the roof on a foundation of successful computer interaction. The purpose of this paper is to carry out a study and to propose new ideas to help users to be able to use social networking sites easily and efficiently.

Keywords: cognitive psychology, special memory, social networking and human computer interaction

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Authors: Vaibhav Dalmia, Manoj Phirke, Renith G

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With the wide adoption of UAVs (unmanned aerial vehicles) in various industries by the government as well as private corporations for solving computer vision tasks it’s necessary that their potential is analyzed completely. Recent advances in Deep Learning have also left us with a plethora of algorithms to solve different computer vision tasks. This study provides a comprehensive survey on solving the Visual Object Tracking problem and explains the tradeoffs involved in building a real-time yet reasonably accurate object tracking system for UAVs by looking at existing methods and evaluating them on the aerial datasets. Finally, the best trackers suitable for UAV-based applications are provided.

Keywords: deep learning, drones, single object tracking, visual object tracking, UAVs

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Authors: Rafael Iliasov, Alessandro Golkar

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Object detection based on event vision has been a dynamically growing field in computer vision for the last 16 years. In this work, we create multiple channels from a single event camera and propose an event fusion method (EFM) to enhance object detection in event-based vision systems. Each channel uses a different accumulation buffer to collect events from the event camera. We implement YOLOv7 for object detection, followed by a fusion algorithm. Our multichannel approach outperforms single-channel-based object detection by 0.7% in mean Average Precision (mAP) for detection overlapping ground truth with IOU = 0.5.

Keywords: event camera, object detection with multimodal inputs, multichannel fusion, computer vision

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Authors: Min Chen, Hui Lin

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VGEs are a kind of typical web- and computer-based geographic environment, with aims of merging geographic knowledge, computer technology, virtual reality technology, network technology, and geographic information technology, to provide a digital mirror of physical geographic environments to allow users to ‘feel it in person’ by a means for augmenting the senses and to ‘know it beyond reality’ through geographic phenomena simulation and collaborative geographic experiments. Many achievements have appeared in this field, but further evolution should be explored. With the exploration of the conception of VGEs, and some examples, this article illustrated the role of VGEs and their contribution to currently GIScience. Based on the above analysis, questions are proposed for discussing about the future way of VGEs.

Keywords: virtual geographic environments (VGEs), GIScience, virtual reality, geographic information systems

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Authors: Hyun-Woo Cho

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Continuous monitoring of industrial plants is one of necessary tasks when it comes to ensuring high-quality final products. In terms of monitoring and diagnosis, it is quite critical and important to detect some incipient abnormal events of manufacturing processes in order to improve safety and reliability of operations involved and to reduce related losses. In this work a new multivariate statistical online diagnostic method is presented using a case study. For building some reference models an empirical discriminant model is constructed based on various past operation runs. When a fault is detected on-line, an on-line diagnostic module is initiated. Finally, the status of the current operating conditions is compared with the reference model to make a diagnostic decision. The performance of the presented framework is evaluated using a dataset from complex industrial processes. It has been shown that the proposed diagnostic method outperforms other techniques especially in terms of incipient detection of any faults occurred.

Keywords: data mining, empirical model, on-line diagnostics, process fault, process monitoring

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: artificial neural networks (ANNs), classifier algorithms, credit risk assessment, logistic regression, machine Learning, support vector machines

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Authors: Tapas Karmaker

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Centuries ago, we came to know about ‘Golden Ratio’ also known as Golden Angle. The idea of this research is based on this theme. Researcher perceives ‘The Golden Ratio’ in terms of harmony, meaning that every single item in the universe follows a harmonic behavior. In case of human being, brain responses easily and quickly to this harmony to help memorization. In this theory, harmony means a link. This study has been carried out on a segment of school students and a segment of common people for a period of three years from 2003 to 2006. The research in this respect intended to determine the impact of harmony in the brain of these people. It has been found that students and common people can increase their memorization capacity as much as 70 times more by applying this method. This method works faster and better between age of 8 and 30 years. This result was achieved through tests to assess memorizing capacity by using tools like words, rhymes, texts, math and drawings. The research concludes that this harmonic method can be applied for improving the capacity of learning languages, for the better quality of lifestyle, or any other terms of life as well as in professional activity.

Keywords: language, education, golden brain, learning, teaching

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Authors: Ezgi Cetinkaya

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In the psychological literature, there are a few studies that focus on actors' self-perceptions and their social adjustment skills. Therefore the aim of the study was to shed light on the self-concept clarity, sociotrophy, and self-monitoring levels of professional actors. For this purpose, actors and non-actors are compared to their peers. The study was conducted with the participation of 106 actors and 131 non-actors. A descriptive method of research was employed and data was collected through the concept Clarity scale by Campbell et al. (1996), the Pleasing Others and Concern For Disapproval subscales of Sociotrophy and Autonomy scale by Beck et al. (1983), and the Self-Monitoring Scale by Snyder ( 1983). ANOVA and correlation analysis was done by using SPSS. Results showed that there is no significant difference between actors and non-actors at any age in terms of Self Concept Clarity. 25-25 years non-actors were found to have the highest self-concept clarity while the young actors had the lowest. The study didn’t reveal significant differences between the groups in terms of Sociotropy scores. The actor’s sociothropic tendencies weren’t enhanced by the experience. The study demonstrated that 25-35-year-old actors are higher self-monitors than 25-35-year-old non-actors.

Keywords: self-concept, self-monitoring, autonomy, sociotropy, theatre, acting, creativity, identity

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Authors: Harshit Mittal, Neeraj Garg

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Hand symbol recognition is a pivotal component in the domain of computer vision, with far-reaching applications spanning sign language interpretation, human-computer interaction, and accessibility. This research paper discusses the approach with the integration of the Canny Edge algorithm and convolutional neural network. The significance of this study lies in its potential to enhance communication and accessibility for individuals with hearing impairments or those engaged in gesture-based interactions with technology. In the experiment mentioned, the data is manually collected by the authors from the webcam using Python codes, to increase the dataset augmentation, is applied to original images, which makes the model more compatible and advanced. Further, the dataset of about 6000 coloured images distributed equally in 5 classes (i.e., 1, 2, 3, 4, 5) are pre-processed first to gray images and then by the Canny Edge algorithm with threshold 1 and 2 as 150 each. After successful data building, this data is trained on the Convolutional Neural Network model, giving accuracy: 0.97834, precision: 0.97841, recall: 0.9783, and F1 score: 0.97832. For user purposes, a block of codes is built in Python to enable a window for hand symbol recognition. This research, at its core, seeks to advance the field of computer vision by providing an advanced perspective on hand sign recognition. By leveraging the capabilities of the Canny Edge algorithm and convolutional neural network, this study contributes to the ongoing efforts to create more accurate, efficient, and accessible solutions for individuals with diverse communication needs.

Keywords: hand symbol recognition, computer vision, Canny edge algorithm, convolutional neural network

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Authors: A. Ozkose

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This study was conducted to determination of yield and yield components of some fodder beet types (Amarilla Barres, Feldherr, Kyros, Magnum, and Rota) under the Konya region conditions. Fodder beet was obtained from the Selcuk University, Faculty of Agriculture, at 2006-2007 season and the experiment was established in a randomized complete block design with three replicates. Differences among the averages of the fodder beet cultivars are statistically important in terms of all the characteristics investigated. Leaf attitude value was 1.2–2.2 (1=erect; 5= prostrate), root shape scale value was (1=spheroidal – 9=cylindrical), root diameter 11.0–12.2 cm, remaining part of root on the ground was 6.3–13.7 cm, root length was 21.4 – 29.6 cm, leaf yield 1592 – 1917 kg/da, root yield was 10083–12258 kg/da, root dry matter content was %8.2– 18.6 and root dry matter yield was 889–1887 kg/da. As a result of the study, it was determined that fodder beet cultivars are different conditions in terms of yield and yield components. Therefore, determination of appropriate cultivars for each region affect crop yield importantly.

Keywords: fedder beet, root yield, yield components, Konya, agriculture

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Authors: Nelson K. Lujara

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The performance characteristics of a photovoltaic induction motor drive water pumping system with and without maximum power tracker is analyzed and presented. The analysis is done through determination and assessment of critical loss components in the system using computer aided design (CAD) tools for optimal operation of the system. The results can be used to formulate a well-calibrated computer aided design package of photovoltaic water pumping systems based on the induction motor drive. The results allow the design engineer to pre-determine the flow rate and efficiency of the system to suit particular application.

Keywords: photovoltaic, water pumping, losses, induction motor

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Authors: Benjamin Bobbia, Matthias Picard

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In recent years active learning methodologies based on the representativity of the data seems more promising to limit overfitting. The presented query methodology for regression using the Wasserstein distance measuring the representativity of our labelled dataset compared to the global distribution. In this work a crucial use of GroupSort Neural Networks is made therewith to draw a double advantage. The Wasserstein distance can be exactly expressed in terms of such neural networks. Moreover, one can provide explicit bounds for their size and depth together with rates of convergence. However, heterogeneity of the dataset is also considered by weighting the Wasserstein distance with the error of approximation at the previous step of active learning. Such an approach leads to a reduction of overfitting and high prediction performance after few steps of query. After having detailed the methodology and algorithm, an empirical study is presented in order to investigate the range of our hyperparameters. The performances of this method are compared, in terms of numbers of query needed, with other classical and recent query methods on several UCI datasets.

Keywords: active learning, Lipschitz regularization, neural networks, optimal transport, regression

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Authors: Ali Berkan Ural

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This paper presents the analysis, evaluation, and pre-diagnosis of early stage breast based diagnostic problems (breast cancer, nodulesorlumps) by Computer Aided Diagnosing (CAD) system from mammogram radiological images. According to the statistics, the time factor is crucial to discover the disease in the patient (especially in women) as possible as early and fast. In the study, a new algorithm is developed using advanced image processing and deep learning method to detect and classify the problem at earlystagewithmoreaccuracy. This system first works with image processing methods (Image acquisition, Noiseremoval, Region Growing Segmentation, Morphological Operations, Breast BorderExtraction, Advanced Segmentation, ObtainingRegion Of Interests (ROIs), etc.) and segments the area of interest of the breast and then analyzes these partly obtained area for cancer detection/lumps in order to diagnosis the disease. After segmentation, with using the Spectrogramimages, 5 different deep learning based methods (specified Convolutional Neural Network (CNN) basedAlexNet, ResNet50, VGG16, DenseNet, Xception) are applied to classify the breast based problems.

Keywords: computer aided diagnosis, breast cancer, region growing, segmentation, deep learning

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Authors: Amir Ikram, Qin Su, Muhammad Fiaz, Muhammad Waqas Shabbir

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Women entrepreneurship witnessed a healthy rise in the last decade or so, and the scenario in Pakistan is not different. However female leaders are facing various, cultural, career oriented, and professional challenges. The study investigates the impact of social and industry-specific challenges on female entrepreneurship; social challenges was evaluated in terms of culture, and industry-specific challenges was measured in terms of team management and career growth. Purposive sampling was employed to collect data from 75 multicultural organizations operating in the culturally diverse and historic city of Lahore, Pakistan. Cronbach’s alpha was conducted to endorse the reliability of survey questionnaire, while correlation and regression analysis were used to test hypotheses. Industry-specific challenges were found to be more significant as compared to cultural factors. The paper also highlights the importance of female entrepreneurship for emerging economies, and suggests that bringing women to mainstream professions can lead to economic success.

Keywords: cultural challenges, emerging economy, female entrepreneurship, leadership

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Authors: Essang Anwana Onuntuei, Chinyere Blessing Azunwoke

Abstract:

The study centred on investigating the influence of multimedia systems and computer graphic design on global and local scale economies. Firstly, the study pinpointed the significant participants and top five global digital media distribution in the digital media market. Then, the study investigated whether a tie or variance existed between the digital media vendor and market shares. Also, the paper probed whether the global and local desktop, mobile, and tablet markets differ while assessing the association between the top five digital media and global market shares. Finally, the study explored the extent of growth, economic gains, major setbacks, and opportunities within the industry amidst global and local scale economic flux. A multiple regression analysis method was employed to analyse the significant influence of the top five global digital media on the total market share, and the Analysis of Variance (ANOVA) was used to analyse the global digital media vendor market share data. The findings were intriguing and significant.

Keywords: computer graphics, digital media market, global market share, market size, media vendor, multimedia, social media, systems design

Procedia PDF Downloads 31

Authors: Mohammad Hashemi, John Herbert

Abstract:

Quantifying and measuring Quality of Experience (QoE) are important and difficult concerns in Human Computer Interaction (HCI). Quality of Service (QoS) and the actual User Interface (UI) of the application are both important contributors to the QoE of a user. This paper describes a framework that measures accurately the way a user uses the UI in order to model users' behaviours and profiles. It monitors the use of the mouse and use of UI elements with accurate time measurement. It does this in real-time and does so unobtrusively and efficiently allowing the user to work as normal with the application. This real-time accurate measurement of the user's interaction provides valuable data and insight into the use of the UI, and is also the basis for analysis of the user's QoE.

Keywords: user modelling, user interface experience, quality of experience, user experience, human and computer interaction

Procedia PDF Downloads 503

Authors: Mohammadamin Abbasnejad

Abstract:

The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

Procedia PDF Downloads 356