Search results for: secure online algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6728

Search results for: secure online algorithm

6338 Optimal Planning of Dispatchable Distributed Generators for Power Loss Reduction in Unbalanced Distribution Networks

Authors: Mahmoud M. Othman, Y. G. Hegazy, A. Y. Abdelaziz

Abstract:

This paper proposes a novel heuristic algorithm that aims to determine the best size and location of distributed generators in unbalanced distribution networks. The proposed heuristic algorithm can deal with the planning cases where power loss is to be optimized without violating the system practical constraints. The distributed generation units in the proposed algorithm is modeled as voltage controlled node with the flexibility to be converted to constant power factor node in case of reactive power limit violation. The proposed algorithm is implemented in MATLAB and tested on the IEEE 37 -node feeder. The results obtained show the effectiveness of the proposed algorithm.

Keywords: distributed generation, heuristic approach, optimization, planning

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6337 Towards Expanding the Use of the Online Judge UnitJudge for Java Programming Exercises and Web Development Practices in Computer Science Education

Authors: Iván García-Magariño, Javier Bravo-Agapito, Marta López-Fernández

Abstract:

Online judges have proven their utility in partial auto-evaluation of programming short exercises in the last decades. UnitJudge online judge has the advantage of facilitating the evaluation of separate units to provide more segregate and meaningful feedback to students in complex exercises and practices. This paper discusses the use of UnitUdge in advanced Java object-oriented programming exercises and web development practices. This later usage has been proposed by means of the Selenium Java library and classes to provide the web address. Consequently, UnitJudge is an online judge system that can be applied in several subjects, and therefore, many other students would take advantage of self-testing their exercises. This paper presents the experiments with a Java programming exercise for learning Java object-oriented classes with a generic type. Considering 10 students who voluntarily used UnitJudge, 80% successfully learned this concept, passing the judge exercise with correct results.

Keywords: online judges, programming skills, computer science education, auto-evaluation

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6336 Investigating the Potential of a Blended Format for the Academic Reading Module Course Redesign

Authors: Reham Niazi, Marwa Helmy, Susanne Rizzo

Abstract:

This classroom action research is designed to explore the possibility of adding effective online content to supplement and add learning value to the current reading module. The aim of this research was two-fold, first to investigate students’ acceptance of and interactivity with online components, chosen to orient students with the content, and to pave the way for more in-class activities and skill practice. Secondly, the instructor aimed to examine students’ willingness to have the course contact hours remain the same with some online components to be done at home (flipped approach) or if students were open to turn the class into a blended format with two scenarios; either to have the current contact hours and apply the blended and in this case the face to face component will be less or keep the number of face to face classes the same and add more online structured classes as part of the course hours.

Keywords: blended learning, flipped classroom, graduate students, education

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6335 Challenges Faced by the Teachers Regarding Student Assessment at Distant and Online Learning Mode

Authors: Ameema Mahroof, Muhammad Saeed

Abstract:

Purpose: The paper aimed to explore the problems faced by the faculty in a distant and online learning environment. It proposes the remedies of the problems faced by the teachers. In distant and online learning mode, the methods of student assessment are different than traditional learning mode. In this paper, the assessment strategies of these learning modes are identified, and the challenges faced by the teachers regarding these assessment methods are explored. Design/Methodology/Approach: The study is qualitative and opted for an exploratory study, including eight interviews with faculty of distant and online universities. The data for this small scale study was gathered using semi-structured interviews. Findings: Findings of the study revealed that assignment and tests are the most effective way of assessment in these modes. It further showed that less student-teacher interaction, plagiarized assignments, passive students, less time for marking are the main challenges faced by the teachers in these modes. Research Limitations: Because of the chosen research approach, the study might not be able to provide generalizable results. That’s why it is recommended to do further studies on this topic. Practical Implications: The paper includes implications for the better assessment system in online and distant learning mode. Originality/Value: This paper fulfills an identified need to study the challenges and problems faced by the teachers regarding student assessment.

Keywords: online learning, distant learning, student assessment, assignments

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6334 Research Repository System (RRS) for Academics

Authors: Ajayi Olusola Olajide, O. Ojeyinka Taiwo, Adeolara Oluwawemimo Janet, Isheyemi Olufemi Gabriel, Lawal Muideen Adekunle

Abstract:

In an academic world where research work is the tool for promotion and elevation to higher cadres, the quest for a system that secure researchers’ work, monitor as well as alert researchers of pending academic research work, cannot be over-emphasized. This study describes how a research repository system for academics is designed. The invention further relates to a system for archiving any paperwork and journal that comprises of a database for storing all researches. It relates to a method for users to communicate through messages which will also allow reviewing all the messages. To create this research repository system, PHP and MySQL were married together for the system implementation.

Keywords: research, repository, academic, archiving, secure, system, implementation

Procedia PDF Downloads 581
6333 Educational Equity in Online Art Education: The Reggio Emilia Approach in White Ant Atelier for Persian-Speaking Children

Authors: Mahsa Mohammadhosseini

Abstract:

This study investigates the effectiveness of adapting the Reggio Emilia approach to online art education, specifically through White Ant Atelier (W.A.A), a virtual art initiative for Persian-speaking children. Employing an action research framework, the study examines the implementation of Reggio Emilia principles via the "Home" art project, which spanned four months and included 16 sessions. The analysis covers 50 artworks produced by participants, including 17 pieces created collaboratively by mothers and their children. The results demonstrate that integrating the Reggio Emilia approach into online platforms significantly improves children's creative expression and engagement. This finding illustrates that virtual education when integrated with child-centered methodologies like Reggio Emilia, can effectively address and reduce educational inequities among Persian-speaking children.

Keywords: Reggio Emilia, online education, art education, educational equity

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6332 Effective Teaching of Thermofluid Pratical Courses during COVID-19

Authors: Opeyemi Fadipe, Masud Salimian

Abstract:

The COVID-19 pandemic has introduced a new normal into the world; online teaching is now the most used method of teaching over the face to face meeting. With the emergency of these teaching, online-teaching has been improved over time and with more technological advancement tools introduced. Practical courses are more demanding to teach because it requires the physical presence of the student as well as a demonstration of the equipment. In this study, a case of Lagos State University thermofluid practical was the understudy. A survey was done and give to a sample of students to fill. The result showed that the blend-approach is better for practical course teaching. Software simulation of the equipment used to conduct practical should be encouraged in the future.

Keywords: COVID-19, online teaching, t-distribution, thermofluid

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6331 The Idea of Reputation in a Post-Truth Era

Authors: Karen Armstrong

Abstract:

This paper considers the importance of acquiring, cultivating, and protecting one’s personal online reputation in a post-truth era. Although the idea of the individual is essential psychological construct, the concept necessarily now includes our online reputation. The idea of this online reputation has expanded to become almost more important than any other factor in terms of our professional, social and psychological development. The discussion will first consider philosophical ideas of the self, followed by an examination of underlying concepts of perception and interpretation in a post-truth world. Then, the idea of the recent shift to a consideration of posted images, through words and photos, in the construction of self, will be discussed. Next, the relation between private personal life and exterior social life, including our reputation in a variety of realms will be addressed. This will include the adoption of specific strategies and behaviors, which facilitate accuracy, currency and necessary modifications with regard to our online reputation. Finally, specific ways in which we can negotiate the fluid dynamic between reputation, and inner and outer selves to optimum effect will conclude the discussion.

Keywords: image, post-truth, privacy, reputation, surveillance

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6330 Lessons Learned from Covid19 - Related ERT in Universities

Authors: Sean Gay, Cristina Tat

Abstract:

This presentation will detail how a university in Western Japan has implemented its English for Academic Purposes (EAP) program during the onset of CoViD-19 in the spring semester of 2020. In the spring semester of 2020, after a 2 week delay, all courses within the School of Policy Studies EAP Program at Kwansei Gakuin University were offered in an online asynchronous format. The rationale for this decision was not to disadvantage students who might not have access to devices necessary for taking part in synchronous online lessons. The course coordinators were tasked with consolidating the materials originally designed for face-to-face14 week courses for a 12 week asynchronous online semester and with uploading the modified course materials to Luna, the university’s network, which is a modified version of Blackboard. Based on research to determine the social and academic impacts of this CoViD-19 ERT approach on the students who took part in this EAP program, this presentation explains how future curriculum design and implementation can be managed in a post-CoViD world. There are a wide variety of lessons that were salient. The role of the classroom as a social institution was very prominent; however, awareness of cognitive burdens and strategies to mitigate that burden may be more valuable for teachers. The lessons learned during this period of ERT can help teachers moving forward.

Keywords: asynchronous online learning, emergency remote teaching (ERT), online curriculum design, synchronous online learning

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6329 An Aspiring Solution to the Man in the Middle Bootstrap Vulnerability

Authors: Mouad Zouina, Benaceur Outtaj

Abstract:

The proposed work falls within the context of improving data security for m-commerce systems. In this context we have placed under the light some flaws encountered in HTTPS the most used m-commerce protocol, particularly the man in the middle attack, shortly MITM. The man in the middle attack is an active listening attack. The idea of this attack is to target the handshake phase of the HTTPS protocol which is the transition from a non-secure connection to a secure connection in our case HTTP to HTTPS. This paper proposes a solution to fix those flaws based on the upgrade of HSTS standard handshake sequence using the DNSSEC standard.

Keywords: m-commerce, HTTPS, HSTS, DNSSEC, MITM bootstrap vulnerability

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6328 Developing a Secure Iris Recognition System by Using Advance Convolutional Neural Network

Authors: Kamyar Fakhr, Roozbeh Salmani

Abstract:

Alphonse Bertillon developed the first biometric security system in the 1800s. Today, many governments and giant companies are considering or have procured biometrically enabled security schemes. Iris is a kaleidoscope of patterns and colors. Each individual holds a set of irises more unique than their thumbprint. Every single day, giant companies like Google and Apple are experimenting with reliable biometric systems. Now, after almost 200 years of improvements, face ID does not work with masks, it gives access to fake 3D images, and there is no global usage of biometric recognition systems as national identity (ID) card. The goal of this paper is to demonstrate the advantages of iris recognition overall biometric recognition systems. It make two extensions: first, we illustrate how a very large amount of internet fraud and cyber abuse is happening due to bugs in face recognition systems and in a very large dataset of 3.4M people; second, we discuss how establishing a secure global network of iris recognition devices connected to authoritative convolutional neural networks could be the safest solution to this dilemma. Another aim of this study is to provide a system that will prevent system infiltration caused by cyber-attacks and will block all wireframes to the data until the main user ceases the procedure.

Keywords: biometric system, convolutional neural network, cyber-attack, secure

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6327 Applying Polyphonic Dialogue as an Approach to Thematically Analyse the Development of Online Identities in Social Media

Authors: Maryam Khosronejad

Abstract:

In social media, differences between individuals become salient as they become a member of different groups with particular social and cultural practices and get engaged in various conversations. The influence of the presence of social media on the promotion of self-expression and polyphonic dialogue is an understudied area and is, therefore, the focus of this paper. This exploration aims to understand the formation of online identities as an ongoing process of orchestrating polyphonic dialogue and responding to available positions. In addition, applying the thematic analysis, it gives examples of how discursive transactions facilitate this process. The implications for the use of social media in education will be discussed based on the findings.

Keywords: online identity, polyphonic dialogue, self expression, social media

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6326 Block Based Imperial Competitive Algorithm with Greedy Search for Traveling Salesman Problem

Authors: Meng-Hui Chen, Chiao-Wei Yu, Pei-Chann Chang

Abstract:

Imperial competitive algorithm (ICA) simulates a multi-agent algorithm. Each agent is like a kingdom has its country, and the strongest country in each agent is called imperialist, others are colony. Countries are competitive with imperialist which in the same kingdom by evolving. So this country will move in the search space to find better solutions with higher fitness to be a new imperialist. The main idea in this paper is using the peculiarity of ICA to explore the search space to solve the kinds of combinational problems. Otherwise, we also study to use the greed search to increase the local search ability. To verify the proposed algorithm in this paper, the experimental results of traveling salesman problem (TSP) is according to the traveling salesman problem library (TSPLIB). The results show that the proposed algorithm has higher performance than the other known methods.

Keywords: traveling salesman problem, artificial chromosomes, greedy search, imperial competitive algorithm

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6325 Alternative Futures for the Middle East

Authors: Dorsa Bakhshandehgeyazdi

Abstract:

This paper examines elective future of security in the Middle East trying to find a way that could take the district from a shaky past to a more secure future. Taking a gander at five situations about the eventual future of world legislative issues, in particular, globalization, fragmentation, conflict of civilizations, majority rule peace and the development of a security group, the paper contends that albeit every situation has its qualities (and in addition shortcomings), it is the situation that predicts the foundation of a security group that joins a more express thought for forming a more secure future for the Middle East.

Keywords: Middle East, Globalization, Fragmentation, Conflict of civilizations, Majority rule peace, Development of a security group

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6324 Communities of Practice as a Training Model for Professional Development of In-Service Teachers: Analyzing the Sharing of Knowledge by Teachers

Authors: Panagiotis Kosmas

Abstract:

The advent of new technologies in education inspires practitioners to approach teaching from a different angle with the aim to professionally develop and improve teaching practices. Online communities of practice among teachers seem to be a trend associated with the integration efforts for a modern and pioneering educational system and training program. This study attempted to explore the participation in online communities of practice and the sharing of knowledge between teachers with aims to explore teachers' incentives to participate in such a community of practice. The study aims to contribute to international research, bringing in global debate new concerns and issues related to the professional learning of current educators. One official online community was used as a case study for the purposes of research. The data collection was conducted from the content analysis of online portal, by questionnaire in 184 community members and interviews with ten active users of the portal. The findings revealed that sharing of knowledge is a key motivation of members of a community. Also, the active learning and community participation seem to be essential factors for the success of an online community of practice.

Keywords: communities of practice, teachers, sharing knowledge, professional development

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6323 Genetic Algorithm for Bi-Objective Hub Covering Problem

Authors: Abbas Mirakhorli

Abstract:

A hub covering problem is a type of hub location problem that tries to maximize the coverage area with the least amount of installed hubs. There have not been many studies in the literature about multi-objective hubs covering location problems. Thus, in this paper, a bi-objective model for the hub covering problem is presented. The two objectives that are considered in this paper are the minimization of total transportation costs and the maximization of coverage of origin-destination nodes. A genetic algorithm is presented to solve the model when the number of nodes is increased. The genetic algorithm is capable of solving the model when the number of nodes increases by more than 20. Moreover, the genetic algorithm solves the model in less amount of time.

Keywords: facility location, hub covering, multi-objective optimization, genetic algorithm

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6322 Scheduling in Cloud Networks Using Chakoos Algorithm

Authors: Masoumeh Ali Pouri, Hamid Haj Seyyed Javadi

Abstract:

Nowadays, cloud processing is one of the important issues in information technology. Since scheduling of tasks graph is an NP-hard problem, considering approaches based on undeterminisitic methods such as evolutionary processing, mostly genetic and cuckoo algorithms, will be effective. Therefore, an efficient algorithm has been proposed for scheduling of tasks graph to obtain an appropriate scheduling with minimum time. In this algorithm, the new approach is based on making the length of the critical path shorter and reducing the cost of communication. Finally, the results obtained from the implementation of the presented method show that this algorithm acts the same as other algorithms when it faces graphs without communication cost. It performs quicker and better than some algorithms like DSC and MCP algorithms when it faces the graphs involving communication cost.

Keywords: cloud computing, scheduling, tasks graph, chakoos algorithm

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6321 Examining the Relationship Between Traditional Property Rights and Online Intellectual Property Rights in the Digital Age

Authors: Luljeta Plakolli-Kasumi

Abstract:

In the digital age, the relationship between traditional property rights and online intellectual property rights is becoming increasingly complex. On the one hand, the internet and advancements in technology have allowed for the widespread distribution and use of digital content, making it easier for individuals and businesses to access and share information. On the other hand, the rise of digital piracy and illegal file-sharing has led to increased concerns about the protection of intellectual property rights. This paper aims to examine the relationship between traditional property rights and online intellectual property rights in the digital age by analyzing the current legal frameworks, key challenges and controversies that arise, and potential solutions for addressing these issues. The paper will look at how traditional property rights concepts such as ownership and possession are being applied in the online context and how they intersect with new and evolving forms of intellectual property such as digital downloads, streaming services, and online content creation. It will also discuss the tension between the need for strong intellectual property protection to encourage creativity and innovation and the public interest in promoting access to information and knowledge. Ultimately, the paper will explore how the legal system can adapt to better balance the interests of property owners, creators, and users in the digital age.

Keywords: intellectual property, traditional property, digital age, digital content

Procedia PDF Downloads 88
6320 Gene Prediction in DNA Sequences Using an Ensemble Algorithm Based on Goertzel Algorithm and Anti-Notch Filter

Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

Abstract:

In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

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6319 Online Impulse Buying: A Study Based on Hedonic Shopping Value and Website Quality

Authors: Chechen Liao, Hung Wen Shaw

Abstract:

Recently, online impulse buying has been growing rapidly. It has become a major issue of concern and provided a lot of opportunities for online businesses. This study examines the effect of hedonic shopping values on hedonic motivations, and in turn affecting the urge of impulse buying. The study also explores the effects of website quality and the individual characteristics of impulsiveness on the urge of impulse buying. A total of 459 valid questionnaires were collected. Structural equation modelling was used to test the research hypothesis. This study found that adventure shopping, value shopping, and social shopping have a positive effect on hedonic motivations, which in turn positively affect the urge of impulse buying. Website quality and the individual characteristics of impulsiveness have a positive effect on the urge of impulse buying. The result of this study validates the phenomenon of online impulse buying behavior. This study also suggests that having a good website quality is the most important factor for increasing the likelihood of consumer impulse purchase. The study could serve as a basis for future research regarding online impulse buying behavior.

Keywords: hedonic motivation, hedonic shopping value, impulse buying, impulsiveness, website quality

Procedia PDF Downloads 203
6318 Secure Image Encryption via Enhanced Fractional Order Chaotic Map

Authors: Ismail Haddad, Djamel Herbadji, Aissa Belmeguenai, Selma Boumerdassi

Abstract:

in this paper, we provide a novel approach for image encryption that employs the Fibonacci matrix and an enhanced fractional order chaotic map. The enhanced map overcomes the drawbacks of the classical map, especially the limited chaotic range and non-uniform distribution of chaotic sequences, resulting in a larger encryption key space. As a result, this strategy improves the encryption system's security. Our experimental results demonstrate that our proposed algorithm effectively encrypts grayscale images with exceptional efficiency. Furthermore, our technique is resistant to a wide range of potential attacks, including statistical and entropy attacks.

Keywords: image encryption, logistic map, fibonacci matrix, grayscale images

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6317 An Exploration of First Year Bachelor of Education Degree Students’ Learning Preferences in Academic Literacy in a Private Higher Education Institution: A Case for the Blended Learning Approach

Authors: K. Kannapathi-Naidoo

Abstract:

The higher education landscape has undergone changes in the past decade, with concepts such as blended learning, online learning, and hybrid models appearing more frequently in research and practice. The year 2020 marked a mass migration from face-to-face learning and more traditional forms of education to online learning in higher education institutions across the globe due to the Covid-19 pandemic. As a result, contact learning students and lecturing staff alike were thrust into the world of online learning at an unprecedented pace. Traditional modes of learning had to be amended, and pedagogical strategies required adjustments. This study was located within a compulsory first-year academic literacy module in a higher education institution. The study aimed to explore students’ learning preferences between online, face-face, and blended learning within the context of academic literacy. Data was collected through online qualitative questionnaires administered to 150 first-year students, which were then analysed thematically. The findings of the study revealed that 48.5% of the participants preferred a blended learning approach to academic literacy. The main themes that emerged in support of their preference were best of both worlds, flexibility, productivity, and lecturer accessibility. As a result, this paper advocates for the blended learning approach for academic literacy skills-based modules.

Keywords: academic literacy, blended learning, online learning, student learning preferences

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6316 ICanny: CNN Modulation Recognition Algorithm

Authors: Jingpeng Gao, Xinrui Mao, Zhibin Deng

Abstract:

Aiming at the low recognition rate on the composite signal modulation in low signal to noise ratio (SNR), this paper proposes a modulation recognition algorithm based on ICanny-CNN. Firstly, the radar signal is transformed into the time-frequency image by Choi-Williams Distribution (CWD). Secondly, we propose an image processing algorithm using the Guided Filter and the threshold selection method, which is combined with the hole filling and the mask operation. Finally, the shallow convolutional neural network (CNN) is combined with the idea of the depth-wise convolution (Dw Conv) and the point-wise convolution (Pw Conv). The proposed CNN is designed to complete image classification and realize modulation recognition of radar signal. The simulation results show that the proposed algorithm can reach 90.83% at 0dB and 71.52% at -8dB. Therefore, the proposed algorithm has a good classification and anti-noise performance in radar signal modulation recognition and other fields.

Keywords: modulation recognition, image processing, composite signal, improved Canny algorithm

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6315 Student Perceptions of Defense Acquisition University Courses: An Explanatory Data Collection Approach

Authors: Melissa C. LaDuke

Abstract:

The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and spoke to either teacher-centered or student-centered educational practices within Defense Acquisitions University. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses, including the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality

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6314 Web Data Scraping Technology Using Term Frequency Inverse Document Frequency to Enhance the Big Data Quality on Sentiment Analysis

Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

Abstract:

Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

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6313 Secure Content Centric Network

Authors: Syed Umair Aziz, Muhammad Faheem, Sameer Hussain, Faraz Idris

Abstract:

Content centric network is the network based on the mechanism of sending and receiving the data based on the interest and data request to the specified node (which has cached data). In this network, the security is bind with the content not with the host hence making it host independent and secure. In this network security is applied by taking content’s MAC (message authentication code) and encrypting it with the public key of the receiver. On the receiver end, the message is first verified and after verification message is saved and decrypted using the receiver's private key.

Keywords: content centric network, client-server, host security threats, message authentication code, named data network, network caching, peer-to-peer

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6312 Robotic Arm Control with Neural Networks Using Genetic Algorithm Optimization Approach

Authors: Arbnor Pajaziti, Hasan Cana

Abstract:

In this paper, the structural genetic algorithm is used to optimize the neural network to control the joint movements of robotic arm. The robotic arm has also been modeled in 3D and simulated in real-time in MATLAB. It is found that Neural Networks provide a simple and effective way to control the robot tasks. Computer simulation examples are given to illustrate the significance of this method. By combining Genetic Algorithm optimization method and Neural Networks for the given robotic arm with 5 D.O.F. the obtained the results shown that the base joint movements overshooting time without controller was about 0.5 seconds, while with Neural Network controller (optimized with Genetic Algorithm) was about 0.2 seconds, and the population size of 150 gave best results.

Keywords: robotic arm, neural network, genetic algorithm, optimization

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6311 A Hybrid Method for Determination of Effective Poles Using Clustering Dominant Pole Algorithm

Authors: Anuj Abraham, N. Pappa, Daniel Honc, Rahul Sharma

Abstract:

In this paper, an analysis of some model order reduction techniques is presented. A new hybrid algorithm for model order reduction of linear time invariant systems is compared with the conventional techniques namely Balanced Truncation, Hankel Norm reduction and Dominant Pole Algorithm (DPA). The proposed hybrid algorithm is known as Clustering Dominant Pole Algorithm (CDPA) is able to compute the full set of dominant poles and its cluster center efficiently. The dominant poles of a transfer function are specific eigenvalues of the state space matrix of the corresponding dynamical system. The effectiveness of this novel technique is shown through the simulation results.

Keywords: balanced truncation, clustering, dominant pole, Hankel norm, model reduction

Procedia PDF Downloads 596
6310 Influence Maximization in Dynamic Social Networks and Graphs

Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

Abstract:

Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

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6309 Automatic Facial Skin Segmentation Using Possibilistic C-Means Algorithm for Evaluation of Facial Surgeries

Authors: Elham Alaee, Mousa Shamsi, Hossein Ahmadi, Soroosh Nazem, Mohammad Hossein Sedaaghi

Abstract:

Human face has a fundamental role in the appearance of individuals. So the importance of facial surgeries is undeniable. Thus, there is a need for the appropriate and accurate facial skin segmentation in order to extract different features. Since Fuzzy C-Means (FCM) clustering algorithm doesn’t work appropriately for noisy images and outliers, in this paper we exploit Possibilistic C-Means (PCM) algorithm in order to segment the facial skin. For this purpose, first, we convert facial images from RGB to YCbCr color space. To evaluate performance of the proposed algorithm, the database of Sahand University of Technology, Tabriz, Iran was used. In order to have a better understanding from the proposed algorithm; FCM and Expectation-Maximization (EM) algorithms are also used for facial skin segmentation. The proposed method shows better results than the other segmentation methods. Results include misclassification error (0.032) and the region’s area error (0.045) for the proposed algorithm.

Keywords: facial image, segmentation, PCM, FCM, skin error, facial surgery

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