Search results for: deep learning network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 12020

Search results for: deep learning network

10370 Teaching Physics: History, Models, and Transformation of Physics Education Research

Authors: N. Didiş Körhasan, D. Kaltakçı Gürel

Abstract:

Many students have difficulty in learning physics from elementary to university level. In addition, students' expectancy, attitude, and motivation may be influenced negatively with their experience (failure) and prejudice about physics learning. For this reason, physics educators, who are also physics teachers, search for the best ways to make students' learning of physics easier by considering cognitive, affective, and psychomotor issues in learning. This research critically discusses the history of physics education, fundamental pedagogical approaches, and models to teach physics, and transformation of physics education with recent research.

Keywords: pedagogy, physics, physics education, science education

Procedia PDF Downloads 259
10369 A Time Delay Neural Network for Prediction of Human Behavior

Authors: A. Hakimiyan, H. Namazi

Abstract:

Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

Procedia PDF Downloads 657
10368 Study on Network-Based Technology for Detecting Potentially Malicious Websites

Authors: Byung-Ik Kim, Hong-Koo Kang, Tae-Jin Lee, Hae-Ryong Park

Abstract:

Cyber terrors against specific enterprises or countries have been increasing recently. Such attacks against specific targets are called advanced persistent threat (APT), and they are giving rise to serious social problems. The malicious behaviors of APT attacks mostly affect websites and penetrate enterprise networks to perform malevolent acts. Although many enterprises invest heavily in security to defend against such APT threats, they recognize the APT attacks only after the latter are already in action. This paper discusses the characteristics of APT attacks at each step as well as the strengths and weaknesses of existing malicious code detection technologies to check their suitability for detecting APT attacks. It then proposes a network-based malicious behavior detection algorithm to protect the enterprise or national networks.

Keywords: Advanced Persistent Threat (APT), malware, network security, network packet, exploit kits

Procedia PDF Downloads 358
10367 Training Program for Kindergarden Teachers on Learning through Project Approach

Authors: Dian Hartiningsih, Miranda Diponegoro, Evita Eddie Singgih

Abstract:

In facing the 21st century, children need to be prepared in reaching their optimum development level which encompasses all aspect of growth and to achieve the learning goals which include not only knowledge and skill, but also disposition and feeling. Teachers as the forefront of education need to be equipped with the understanding and skill of a learning method which can prepare the children to face this 21st century challenge. Project approach is an approach which utilizes active learning which is beneficial for the children. Subject to this research are kindergarten teachers at Dwi Matra Kindergarten and Kirana Preschool. This research is a quantitative research using before and after study design. The result suggest that through preliminary training program on learning with project approach, the kindergarten teachers ability to explain project approach including understanding, benefit and stages of project approach have increased significantly, the teachers ability to design learning with project approach have also improved significantly. The result of learning design that the teachers had made shows a remarkable result for the first stage of the project approach; however the second and third design result was not as optimal. Challenges faced in the research will be elaborated further in the research discussion.

Keywords: project approach, teacher training, learning method, kindergarten

Procedia PDF Downloads 327
10366 Imparting Second Language Skill through M-Learning

Authors: Subramaniam Chandran, A. Geetha

Abstract:

This paper addresses three issues: how to prepare instructional design for imparting English language skill from inter-disciplinary self-learning material; how the disadvantaged students are benefited from such kind of language skill imparted through m-learning; and how do the m-learners perform better than the other learners. This paper examines these issues through an experimental study conducted among the distance learners enrolled in preparatory program for bachelor’s degree. This program is designed for the disadvantage learners especially for the school drop-outs to qualify to pursue graduate program through distant education. It also explains how mobile learning helps them to enhance their capacity in learning despite their rural background and other disadvantages. In India nearly half of the students enrolled in schools do not complete their study. The pursuance of higher education is very low when compared with developed countries. This study finds a significant increase in their learning capacity and mobile learning seems to be a viable alternative where conventional system could not reach the disadvantaged learners. Improving the English language skill is one of the reasons for such kind of performance. Exercises framed from the relevant self-learning material for enhancing English language skill not only improves language skill but also widens the subject-knowledge. This paper explains these issues out of the study conducted among the disadvantaged learners.

Keywords: English language skill, disadvantaged learners, distance education, m-learning

Procedia PDF Downloads 660
10365 The Increasing Importance of the Role of AI in Higher Education

Authors: Joshefina Bengoechea Fernandez, Alex Bell

Abstract:

In its 2021 guidance for policy makers, the UNESCO has proposed 4 areas where AI can be applied in educational settings: These are: 1) Education management and delivery; 2) Learning and assessment; 3) Empowering teachers and facilitating teaching, and 4) Providing lifelong learning possibilities (UNESCO, 2021). Like with wblockchain technologies, AI will automate the management of educational institutions. These include, but are not limited to admissions, timetables, attendance, and homework monitoring. Furthermore, AI will be used to select relevant learning content across learning platforms for each student, based on his or her personalized needs. A problem educators face is the “one-size-fits-all” approach that does not work with a diverse student population. The purpose of this paper is to illustrate if the implementation of Technology is the solution to the Problems faced in Higher Education. The paper builds upon a constructivist approach, combining a literature review and research on key publications and academic reports.

Keywords: artificial intelligence, learning platforms, students personalised needs, life- long learning, privacy, ethics

Procedia PDF Downloads 98
10364 Applicability of Fuzzy Logic for Intrusion Detection in Mobile Adhoc Networks

Authors: Ruchi Makani, B. V. R. Reddy

Abstract:

Mobile Adhoc Networks (MANETs) are gaining popularity due to their potential of providing low-cost mobile connectivity solutions to real-world communication problems. Integrating Intrusion Detection Systems (IDS) in MANETs is a tedious task by reason of its distinctive features such as dynamic topology, de-centralized authority and highly controlled/limited resource environment. IDS primarily use automated soft-computing techniques to monitor the inflow/outflow of traffic packets in a given network to detect intrusion. Use of machine learning techniques in IDS enables system to make decisions on intrusion while continuous keep learning about their dynamic environment. An appropriate IDS model is essential to be selected to expedite this application challenges. Thus, this paper focused on fuzzy-logic based machine learning IDS technique for MANETs and presented their applicability for achieving effectiveness in identifying the intrusions. Further, the selection of appropriate protocol attributes and fuzzy rules generation plays significant role for accuracy of the fuzzy-logic based IDS, have been discussed. This paper also presents the critical attributes of MANET’s routing protocol and its applicability in fuzzy logic based IDS.

Keywords: AODV, mobile adhoc networks, intrusion detection, anomaly detection, fuzzy logic, fuzzy membership function, fuzzy inference system

Procedia PDF Downloads 173
10363 A Hybrid Feature Selection Algorithm with Neural Network for Software Fault Prediction

Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh

Abstract:

Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.

Keywords: feature selection, neural network, particle swarm optimization, software fault prediction

Procedia PDF Downloads 88
10362 Innovative Pictogram Chinese Characters Representation

Authors: J. H. Low, S. H. Hew, C. O. Wong

Abstract:

This paper proposes an innovative approach to represent the pictogram Chinese characters. The advantage of this representation is using an extraordinary to represent the pictogram Chinese character. This extraordinary representation is created accordingly to the original pictogram Chinese characters revolution. The purpose of this innovative creation is to assistant the learner learning Chinese as second language (SCL) in Chinese language learning specifically on memorize Chinese characters. Commonly, the SCL will give up and frustrate easily while memorize the Chinese characters by rote. So, our innovative representation is able to help on memorize the Chinese character by the help of visually storytelling. This innovative representation enhances the Chinese language learning experience of SCL.

Keywords: Chinese e-learning, innovative Chinese character representation, knowledge management, language learning

Procedia PDF Downloads 481
10361 Factors Affecting Happiness Learning of Students of Faculty of Management Science, Suan Sunandha Rajabhat University

Authors: Somtop Keawchuer

Abstract:

The objectives of this research are to compare the satisfaction of students, towards the happiness learning, sorted by their personal profiles, and to figure out the factors that affect the students’ happiness learning. This paper used survey method to collect data from 362 students. The survey was mainly conducted in the Faculty of Management Science, Suan Sunandha Rajabhat University, including 3,443 students. The statistics used for interpreting the results included the frequencies, percentages, standard deviations and One-way ANOVA. The findings revealed that the students are aware and satisfaction that all the factors in 3 categories (knowledge, skill and attitude) influence the happiness learning at the highest levels. The comparison of the satisfaction levels of the students toward their happiness learning leads to the results that the students with different genders, ages, years of study, and majors of the study have the similar satisfaction at the high level.

Keywords: happiness, learning satisfaction, students, Faculty of Management Science

Procedia PDF Downloads 307
10360 A Hybrid Genetic Algorithm and Neural Network for Wind Profile Estimation

Authors: M. Saiful Islam, M. Mohandes, S. Rehman, S. Badran

Abstract:

Increasing necessity of wind power is directing us to have precise knowledge on wind resources. Methodical investigation of potential locations is required for wind power deployment. High penetration of wind energy to the grid is leading multi megawatt installations with huge investment cost. This fact appeals to determine appropriate places for wind farm operation. For accurate assessment, detailed examination of wind speed profile, relative humidity, temperature and other geological or atmospheric parameters are required. Among all of these uncertainty factors influencing wind power estimation, vertical extrapolation of wind speed is perhaps the most difficult and critical one. Different approaches have been used for the extrapolation of wind speed to hub height which are mainly based on Log law, Power law and various modifications of the two. This paper proposes a Artificial Neural Network (ANN) and Genetic Algorithm (GA) based hybrid model, namely GA-NN for vertical extrapolation of wind speed. This model is very simple in a sense that it does not require any parametric estimations like wind shear coefficient, roughness length or atmospheric stability and also reliable compared to other methods. This model uses available measured wind speeds at 10m, 20m and 30m heights to estimate wind speeds up to 100m. A good comparison is found between measured and estimated wind speeds at 30m and 40m with approximately 3% mean absolute percentage error. Comparisons with ANN and power law, further prove the feasibility of the proposed method.

Keywords: wind profile, vertical extrapolation of wind, genetic algorithm, artificial neural network, hybrid machine learning

Procedia PDF Downloads 485
10359 Medical Image Augmentation Using Spatial Transformations for Convolutional Neural Network

Authors: Trupti Chavan, Ramachandra Guda, Kameshwar Rao

Abstract:

The lack of data is a pain problem in medical image analysis using a convolutional neural network (CNN). This work uses various spatial transformation techniques to address the medical image augmentation issue for knee detection and localization using an enhanced single shot detector (SSD) network. The spatial transforms like a negative, histogram equalization, power law, sharpening, averaging, gaussian blurring, etc. help to generate more samples, serve as pre-processing methods, and highlight the features of interest. The experimentation is done on the OpenKnee dataset which is a collection of knee images from the openly available online sources. The CNN called enhanced single shot detector (SSD) is utilized for the detection and localization of the knee joint from a given X-ray image. It is an enhanced version of the famous SSD network and is modified in such a way that it will reduce the number of prediction boxes at the output side. It consists of a classification network (VGGNET) and an auxiliary detection network. The performance is measured in mean average precision (mAP), and 99.96% mAP is achieved using the proposed enhanced SSD with spatial transformations. It is also seen that the localization boundary is comparatively more refined and closer to the ground truth in spatial augmentation and gives better detection and localization of knee joints.

Keywords: data augmentation, enhanced SSD, knee detection and localization, medical image analysis, openKnee, Spatial transformations

Procedia PDF Downloads 148
10358 Enhance Engineering Learning Using Cognitive Simulator

Authors: Lior Davidovitch

Abstract:

Traditional training based on static models and case studies is the backbone of most teaching and training programs of engineering education. However, project management learning is characterized by dynamics models that requires new and enhanced learning method. The results of empirical experiments evaluating the effectiveness and efficiency of using cognitive simulator as a new training technique are reported. The empirical findings are focused on the impact of keeping and reviewing learning history in a dynamic and interactive simulation environment of engineering education. The cognitive simulator for engineering project management learning had two learning history keeping modes: manual (student-controlled), automatic (simulator-controlled) and a version with no history keeping. A group of industrial engineering students performed four simulation-runs divided into three identical simple scenarios and one complicated scenario. The performances of participants running the simulation with the manual history mode were significantly better than users running the simulation with the automatic history mode. Moreover, the effects of using the undo enhanced further the learning process. The findings indicate an enhancement of engineering students’ learning and decision making when they use the record functionality of the history during their engineering training process. Furthermore, the cognitive simulator as educational innovation improves students learning and training. The practical implications of using simulators in the field of engineering education are discussed.

Keywords: cognitive simulator, decision making, engineering learning, project management

Procedia PDF Downloads 245
10357 Inferential Reasoning for Heterogeneous Multi-Agent Mission

Authors: Sagir M. Yusuf, Chris Baber

Abstract:

We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

Procedia PDF Downloads 142
10356 The Rigor and Relevance of the Mathematics Component of the Teacher Education Programmes in Jamaica: An Evaluative Approach

Authors: Avalloy McCarthy-Curvin

Abstract:

For over fifty years there has been widespread dissatisfaction with the teaching of Mathematics in Jamaica. Studies, done in the Jamaican context highlight that teachers at the end of training do not have a deep understanding of the mathematics content they teach. Little research has been done in the Jamaican context that targets the advancement of contextual knowledge on the problem to ultimately provide a solution. The aim of the study is to identify what influences this outcome of teacher education in Jamaica so as to remedy the problem. This study formatively evaluated the curriculum documents, assessments and the delivery of the curriculum that are being used in teacher training institutions in Jamaica to determine their rigor -the extent to which written document, instruction, and the assessments focused on enabling pre-service teachers to develop deep understanding of mathematics and relevance- the extent to which the curriculum document, instruction, and the assessments are focus on developing the requisite knowledge for teaching mathematics. The findings show that neither the curriculum document, instruction nor assessments ensure rigor and enable pre-service teachers to develop the knowledge and skills they need to teach mathematics effectively.

Keywords: relevance, rigor, deep understanding, formative evaluation

Procedia PDF Downloads 232
10355 Continuous Functions Modeling with Artificial Neural Network: An Improvement Technique to Feed the Input-Output Mapping

Authors: A. Belayadi, A. Mougari, L. Ait-Gougam, F. Mekideche-Chafa

Abstract:

The artificial neural network is one of the interesting techniques that have been advantageously used to deal with modeling problems. In this study, the computing with artificial neural network (CANN) is proposed. The model is applied to modulate the information processing of one-dimensional task. We aim to integrate a new method which is based on a new coding approach of generating the input-output mapping. The latter is based on increasing the neuron unit in the last layer. Accordingly, to show the efficiency of the approach under study, a comparison is made between the proposed method of generating the input-output set and the conventional method. The results illustrated that the increasing of the neuron units, in the last layer, allows to find the optimal network’s parameters that fit with the mapping data. Moreover, it permits to decrease the training time, during the computation process, which avoids the use of computers with high memory usage.

Keywords: neural network computing, continuous functions generating the input-output mapping, decreasing the training time, machines with big memories

Procedia PDF Downloads 276
10354 Awareness and Utilization of E-Learning Technologies in Teaching and Learning of Human Kinetics and Health Education Courses in Nigeria Universities

Authors: Ibrahim Laro ABUBAKAR

Abstract:

The study examined the Availability and Utilization of E-Learning Technologies in Teaching of Human Kinetics and Health Education courses in Nigerian Universities, specifically, Universities in Kwara State. Two purposes were formulated to guide the study from which two research questions and two hypotheses were raised. The descriptive research design was used in the research. Three Hundred respondents (100 Lecturers and 200 Students) made up the population for the study. There was no sampling, as the population of the study was not much. A structured questionnaire tagged ‘Availability and Utilization of E-Learning Technologies in Teaching and Learning Questionnaire’ (AUETTLQ) was used for data collection. The questionnaire was subjected to face and content validation, and it was equally pilot tested. The validation yielded a reliability coefficient of 0.78. The data collected from the study were statistically analyzed using frequencies and percentage count for personal data of the respondents, mean and standard deviation to answer the research questions. The null hypotheses were tested at 0.05 level of significance using the independent t-test. One among other findings of this study showed that lecturers and Student are aware of synchronous e-learning technologies in teaching and learning of Human Kinetics and Health Education but often utilize the synchronous e-learning technologies. It was recommended among others that lecturers and Students should be sensitized through seminars and workshops on the need to maximally utilize available e-learning technologies in teaching and learning of Human Kinetics and Health Education courses in Universities.

Keywords: awareness, utilization, E-Learning, technologies, human kinetics synchronous

Procedia PDF Downloads 113
10353 How to Modernise the ECN

Authors: Dorota Galeza

Abstract:

This paper argues that networks, such as the ECN and the American network, are affected by certain small events which are inherent to path dependence and preclude the full evolution towards efficiency. It is advocated that the American network is superior to the ECN in many respects due to its greater flexibility and longer history. This stems in particular from the creation of the American network, which was based on a small number of cases. Such structure encourages further changes and modifications which are not necessarily radical. The ECN, by contrast, was established by legislative action, which explains its rigid structure and resistance to change. It might be the case that the ECN is subject not so much to path dependence but to past dependence. It might have to be replaced, as happened to its predecessor. This paper is an attempt to transpose the superiority of the American network on to the ECN. It looks at concepts such as judicial cooperation, harmonization of procedure, peer review and regulatory impact assessments (RIAs), and dispute resolution procedures. The aim is to adopt these concepts into the EU setting without recourse to legal transplantation. The major difficulty is that many of these concepts have been tested only in the US and it is difficult to tell whether they could be modified to meet EU standards. Concepts such as judicial cooperation might be difficult due to different language traditions in EU member states. It is hoped that greater flexibility, as in the American network, would boost legitimacy and transparency.

Keywords: ECN, networks, regulation, competition

Procedia PDF Downloads 422
10352 Role of Feedbacks in Simulation-Based Learning

Authors: Usman Ghani

Abstract:

Feedback is a vital element for improving student learning in a simulation-based training as it guides and refines learning through scaffolding. A number of studies in literature have shown that students’ learning is enhanced when feedback is provided with personalized tutoring that offers specific guidance and adapts feedback to the learner in a one-to-one environment. Thus, emulating these adaptive aspects of human tutoring in simulation provides an effective methodology to train individuals. This paper presents the results of a study that investigated the effectiveness of automating different types of feedback techniques such as Knowledge-of-Correct-Response (KCR) and Answer-Until- Correct (AUC) in software simulation for learning basic information technology concepts. For the purpose of comparison, techniques like simulation with zero or no-feedback (NFB) and traditional hands-on (HON) learning environments are also examined. The paper presents the summary of findings based on quantitative analyses which reveal that the simulation based instructional strategies are at least as effective as hands-on teaching methodologies for the purpose of learning of IT concepts. The paper also compares the results of the study with the earlier studies and recommends strategies for using feedback mechanism to improve students’ learning in designing and simulation-based IT training.

Keywords: simulation, feedback, training, hands-on, labs

Procedia PDF Downloads 370
10351 [Keynote Talk]: Computer-Assisted Language Learning (CALL) for Teaching English to Speakers of Other Languages (TESOL/ESOL) as a Foreign Language (TEFL/EFL), Second Language (TESL/ESL), or Additional Language (TEAL/EAL)

Authors: Andrew Laghos

Abstract:

Computer-assisted language learning (CALL) is defined as the use of computers to help learn languages. In this study we look at several different types of CALL tools and applications and how they can assist Adults and Young Learners in learning the English language as a foreign, second or additional language. It is important to identify the roles of the teacher and the learners, and what the learners’ motivations are for learning the language. Audio, video, interactive multimedia games, online translation services, conferencing, chat rooms, discussion forums, social networks, social media, email communication, songs and music video clips are just some of the many ways computers are currently being used to enhance language learning. CALL may be used for classroom teaching as well as for online and mobile learning. Advantages and disadvantages of CALL are discussed and the study ends with future predictions of CALL.

Keywords: computer-assisted language learning (CALL), teaching English as a foreign language (TEFL/EFL), adult learners, young learners

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10350 Japanese Language Learning Strategies : Case study student in Japanese subject part, Faculty of Humanities and Social Sciences, Suan Sunandha Rajabhat University

Authors: Pailin Klinkesorn

Abstract:

The research aimed to study the use of learning strategies for Japanese language among college students with different learning achievements who study Japanese as a foreign language in the Higher Education’s level. The survey was conducted by using a questionnaire adapted from Strategy Inventory for language Learning or SILL (Oxford, 1990), consisting of two parts: questions about personal data and questions about the use of learning strategies for Japanese language. The samples of college students in the Japanese language program were purposively selected from Suansunandha Rajabhat University. The data from the questionnaire was statistically analyzed by using mean scores and one-way ANOVA. The results showed that Social Strategies was used by the greatest number of college students, whereas Memory Strategies was used by the least number of students. The students in different levels used various strategies, including Memory Strategies, Cognitive Strategies, Metacognitive Strategies and Social Strategies, at the significance level of 0.05. In addition, the students with different learning achievements also used different strategies at the significance level of 0.05. Further studies can explore learning strategies of other groups of Japanese learners, such as university students or company employees. Moreover, learning strategies for language skills, including listening, speaking, reading and writing, can be analyzed for better understanding of learners’ characteristics and for teaching applications.

Keywords: language learning strategies, achievement, Japanese, college students

Procedia PDF Downloads 389
10349 Functional Instruction Set Simulator of a Neural Network IP with Native Brain Float-16 Generator

Authors: Debajyoti Mukherjee, Arathy B. S., Arpita Sahu, Saranga P. Pogula

Abstract:

A functional model to mimic the functional correctness of a neural network compute accelerator IP is very crucial for design validation. Neural network workloads are based on a Brain Floating Point (BF-16) data type. The major challenge we were facing was the incompatibility of GCC compilers to the BF-16 datatype, which we addressed with a native BF-16 generator integrated into our functional model. Moreover, working with big GEMM (General Matrix Multiplication) or SpMM (Sparse Matrix Multiplication) Work Loads (Dense or Sparse) and debugging the failures related to data integrity is highly painstaking. In this paper, we are addressing the quality challenge of such a complex neural network accelerator design by proposing a functional model-based scoreboard or software model using SystemC. The proposed functional model executes the assembly code based on the ISA of the processor IP, decodes all instructions, and executes as expected to be done by the DUT. The said model would give a lot of visibility and debug capability in the DUT, bringing up micro-steps of execution.

Keywords: ISA, neural network, Brain Float-16, DUT

Procedia PDF Downloads 87
10348 A Study on Pakistani Students’ Attitude towards Learning Mathematics and Science at Secondary Level

Authors: Aroona Hashmi

Abstract:

Student’s success in Mathematics and Science depends upon their learning attitude towards both subjects. It also influences the participation rate of the learner. The present study was based on a survey of high school students about their attitude towards Mathematics and Science at Secondary level. Students of the both gender constitute the population of this study. Sample of the study was 276 students and 20 teachers from 10 Government schools from Lahore District. Questionnaire and interview were selected as tool for data collection. The results showed that Pakistani students’ positive attitude towards learning Mathematics and Science. There was a significance difference between the students’ attitude towards learning Mathematics and no significance difference was found in the students’ attitude towards learning Science at Secondary level.

Keywords: attitude, mathematics, science, secondary level

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10347 Case Study: Throughput Analysis over PLC Infrastructure as Last Mile Residential Solution in Colombia

Authors: Edward P. Guillen, A. Karina Martinez Barliza

Abstract:

Powerline Communications (PLC) as last mile solution to provide communication services, has the advantage of transmitting over channels already used for electrical distribution. However these channels have been not designed with this purpose, for that reason telecommunication companies in Colombia want to know how good would be using PLC in costs and network performance in comparison to cable modem or DSL. This paper analyzes PLC throughput for residential complex scenarios using a PLC network scenarios and some statistical results are shown.

Keywords: home network, power line communication, throughput analysis, power factor, cost, last mile solution

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10346 Mobile Network Users Amidst Ultra-Dense Networks in 5G Using an Improved Coordinated Multipoint (CoMP) Technology

Authors: Johnson O. Adeogo, Ayodele S. Oluwole, O. Akinsanmi, Olawale J. Olaluyi

Abstract:

In this 5G network, very high traffic density in densely populated areas, most especially in densely populated areas, is one of the key requirements. Radiation reduction becomes one of the major concerns to secure the future life of mobile network users in ultra-dense network areas using an improved coordinated multipoint technology. Coordinated Multi-Point (CoMP) is based on transmission and/or reception at multiple separated points with improved coordination among them to actively manage the interference for the users. Small cells have two major objectives: one, they provide good coverage and/or performance. Network users can maintain a good quality signal network by directly connecting to the cell. Two is using CoMP, which involves the use of multiple base stations (MBS) to cooperate by transmitting and/or receiving at the same time in order to reduce the possibility of electromagnetic radiation increase. Therefore, the influence of the screen guard with rubber condom on the mobile transceivers as one major piece of equipment radiating electromagnetic radiation was investigated by mobile network users amidst ultra-dense networks in 5g. The results were compared with the same mobile transceivers without screen guards and rubber condoms under the same network conditions. The 5 cm distance from the mobile transceivers was measured with the help of a ruler, and the intensity of Radio Frequency (RF) radiation was measured using an RF meter. The results show that the intensity of radiation from various mobile transceivers without screen guides and condoms was higher than the mobile transceivers with screen guides and condoms when call conversation was on at both ends.

Keywords: ultra-dense networks, mobile network users, 5g, coordinated multi-point.

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10345 Assessing Students’ Readiness for an Open and Distance Learning Higher Education Environment

Authors: Upasana G. Singh, Meera Gungea

Abstract:

Learning is no more confined to the traditional classroom, teacher, and student interaction. Many universities offer courses through the Open and Distance Learning (ODL) mode, attracting a diversity of learners in terms of age, gender, and profession to name a few. The ODL mode has surfaced as one of the famous sought-after modes of learning, allowing learners to invest in their educational growth without hampering their personal and professional commitments. This mode of learning, however, requires that those who ultimately choose to adopt it must be prepared to undertake studies through such medium. The purpose of this research is to assess whether students who join universities offering courses through the ODL mode are ready to embark and study within such a framework. This study will be helpful to unveil the challenges students face in such an environment and thus contribute to developing a framework to ease adoption and integration into the ODL environment. Prior to the implementation of e-learning, a readiness assessment is essential for any institution that wants to adopt any form of e-learning. Various e-learning readiness assessment models have been developed over the years. However, this study is based on a conceptual model for e-Learning Readiness Assessment which is a ‘hybrid model’. This hybrid model consists of 4 main parameters: 1) Technological readiness, 2) Culture readiness, 3) Content readiness, and 4) Demographics factors, with 4 sub-areas, namely, technology, innovation, people and self-development. The model also includes the attitudes of users towards the adoption of e-learning as an important aspect of assessing e-learning readiness. For this study, some factors and sub-factors of the hybrid model have been considered and adapted, together with the ‘Attitude’ component. A questionnaire was designed based on the models and students where the target population were students enrolled at the Open University of Mauritius, in undergraduate and postgraduate courses. Preliminary findings indicate that most (68%) learners have an average knowledge about ODL form of learning, despite not many (72%) having previous experience with ODL. Despite learning through ODL 74% of learners preferred hard copy learning material and 48% found difficulty in reading learning material on electronic devices.

Keywords: open learning, distance learning, student readiness, a hybrid model

Procedia PDF Downloads 105
10344 Computational Neurosciences: An Inspiration from Biological Neurosciences

Authors: Harsh Sadawarti, Kamal Malik

Abstract:

Humans are the unique and the most powerful creature on this planet just because of the high level of intelligence gifted by nature. Computational Intelligence is highly influenced by the term natural intelligence, neurosciences and mathematics. To deal with the in-depth study of computational intelligence and to utilize it in real-life applications, it is quite important to understand its simulation with the human brain. In this paper, the three important parts, Frontal Lobe, Occipital Lobe and Parietal Lobe of the human brain, are compared with the ANN(Artificial Neural Network), CNN(Convolutional Neural network), and RNN(Recurrent Neural Network), respectively. Intelligent computational systems are created by combining deductive reasoning, logical concepts and high-level algorithms with the simulation and study of the human brain. Human brain is a combination of Physiology, Psychology, emotions, calculations and many other parameters which are of utmost importance that determines the overall intelligence. To create intelligent algorithms, smart machines and to simulate the human brain in an effective manner, it is quite important to have an insight into the human brain and the basic concepts of biological neurosciences.

Keywords: computational intelligence, neurosciences, convolutional neural network, recurrent neural network, artificial neural network, frontal lobe, occipital lobe, parietal lobe

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10343 Exploring Twitter Data on Human Rights Activism on Olympics Stage through Social Network Analysis and Mining

Authors: Teklu Urgessa, Joong Seek Lee

Abstract:

Social media is becoming the primary choice of activists to make their voices heard. This fact is coupled by two main reasons. The first reason is the emergence web 2.0, which gave the users opportunity to become content creators than passive recipients. Secondly the control of the mainstream mass media outlets by the governments and individuals with their political and economic interests. This paper aimed at exploring twitter data of network actors talking about the marathon silver medalists on Rio2016, who showed solidarity with the Oromo protesters in Ethiopia on the marathon race finish line when he won silver. The aim is to discover important insight using social network analysis and mining. The hashtag #FeyisaLelisa was used for Twitter network search. The actors’ network was visualized and analyzed. It showed the central influencers during first 10 days in August, were international media outlets while it was changed to individual activist in September. The degree distribution of the network is scale free where the frequency of degrees decay by power low. Text mining was also used to arrive at meaningful themes from tweet corpus about the event selected for analysis. The semantic network indicated important clusters of concepts (15) that provided different insight regarding the why, who, where, how of the situation related to the event. The sentiments of the words in the tweets were also analyzed and indicated that 95% of the opinions in the tweets were either positive or neutral. Overall, the finding showed that Olympic stage protest of the marathoner brought the issue of Oromo protest to the global stage. The new research framework is proposed based for event-based social network analysis and mining based on the practical procedures followed in this research for event-based social media sense making.

Keywords: human rights, Olympics, social media, network analysis, social network ming

Procedia PDF Downloads 254
10342 Integrating Service Learning into a Business Analytics Course: A Comparative Investigation

Authors: Gokhan Egilmez, Erika Hatfield, Julie Turner

Abstract:

In this study, we investigated the impacts of service-learning integration on an undergraduate level business analytics course from multiple perspectives, including academic proficiency, community awareness, engagement, social responsibility, and reflection. We assessed the impact of the service-learning experience by using a survey developed primarily based on the literature review and secondarily on an ad hoc group of researchers. Then, we implemented the survey in two sections, where one of the sections was a control group. We compared the results of the empirical survey visually and statistically.

Keywords: business analytics, service learning, experiential education, statistical analysis, survey research

Procedia PDF Downloads 101
10341 Augmented Reality and Its Impact on Education

Authors: Aliakbar Alijarahi, Ali Khaleghi, Azadehe Afrasiyabi

Abstract:

One of the emerging technologies in the field of education that can be effectively profitable, called augmented reality, where the combination of real world and virtual images in real time produces new concepts that can facilitate learning. The paper, providing an introduction to the general concept of augmented reality, aims at surveying its capabitities in different areas, with an emphasis on Education, It seems quite necessary to have comparative study on virtual/e-learning and augmented reality and conclude their differences in education methods. As an review article, the paper is composed, instead of producing new concepts, to sum-up and analayze accomplished works related to the subject.

Keywords: augmented reality, education, virtual learning, e-learning

Procedia PDF Downloads 335