Search results for: digital prehabilitation

Authors: Ricardo Merlo

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The use of simulation as a digital didactic tool allowed students to reproduce the laws of Physics in order to improve their academic performance. The didactic resource of simulation also favored the motivation of most of the young people, depending on the subject of Physics to be developed in the classroom and in that sense, it was significant to know the favorable or unfavorable attitude that the students presented about the use of simulation resources to maximize the anchorage of the contents planned for the different classes developed in the classroom. The different real-time simulation applications that were offered free of charge through the Internet were not presented as a specific resource that could be used in a didactic model, and in that framework, the teachers of Physics at the university level did not apply these resources in a systematic way with the knowledge of the favorable or unfavorable attitude of the students towards these didactic resources. For this reason, this work proposed the design and application of attitude questionnaires to enhance the use of those simulation resources that allowed for improving the quality of the class and the academic performance of the students.

Keywords: physics teaching, attitude, motivation, didactic resources

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Authors: Mohammad A. Alia

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With the rapid evolution of the internet applications, cloud computing becomes one of today’s hottest research areas due to its ability to reduce costs associated with computing. Cloud is, therefore, increasing flexibility and scalability for computing services in the internet. Cloud computing is Internet based computing due to shared resources and information which are dynamically delivered to consumers. As cloud computing share resources via the open network, hence cloud outsourcing is vulnerable to attack. Therefore, this paper will explore data security of cloud computing by implementing chaotic cryptography. The proposal scenario develops a problem transformation technique that enables customers to secretly transform their information. This work proposes the chaotic cryptographic algorithms have been applied to enhance the security of the cloud computing accessibility. However, the proposed scenario is secure, easy and straightforward process. The chaotic encryption and digital signature systems ensure the security of the proposed scenario. Though, the choice of the key size becomes crucial to prevent a brute force attack.

Keywords: chaos, cloud computing, security, cryptography

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Authors: Razak Rahmat, Azizah Ahmad, Rafidah Razak, Roshidi Din, Azizi Abas

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Telecenter is a place where communities can access computers, the Internet, and other digital technologies to enable them to gather information, create, learn, and communicate with others. However, previous studies found that sustainability issues related to economic, political and institutional, social and technology is one of the major problem faced by the telecenter. Based on that problem, this research is planning to design a possible solution on rural telecenters sustainability with the support of business intelligence (BI). The empirical study will be conducted through the qualitative and quantitative method including interviews and observations with a range of stakeholders including ministry officers, telecenters managers and operators. Result from the data collection will be analyze using the causal modeling approach of SEM SmartPLS for the validity. The expected finding from this research is the Business Intelligent Requirement Model as a guild for sustainability of the rural telecenters.

Keywords: Rural ICT Telecenter(RICTT), business intelligence, sustainability, requirement analysis modal

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Authors: R. R. Govind

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In the digital age, artificial intelligence (AI) is having a significant impact on the rapid changes that cities are experiencing. This study explores the profound impact of AI on urban morphology, especially with regard to promoting friendly design choices. It addresses a significant research gap by examining the real-world effects of integrating AI into urban design and management. The main objective is to outline a framework for integrating AI to transform urban settings. The study employs an urban design framework to effectively navigate complicated urban environments, emphasize the need for urban management, and provide efficient planning and design strategies. Taking Gangtok's informal settlements as a focal point, the study employs AI methodologies such as machine learning, predictive analytics, and generative AI to tackle issues of 'urban informality'. The insights garnered not only offer valuable perspectives but also unveil AI's transformative potential in addressing contemporary urban challenges.

Keywords: urban design, artificial intelligence, urban challenges, machine learning, urban informality

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Authors: Ibtissem Talbi

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During the last decade, a variety of chaos-based cryptosystems have been investigated. Most of them are based on the structure of Fridrich, which is based on the traditional confusion-diffusion architecture proposed by Shannon. Compared with traditional cryptosystems (DES, 3DES, AES, etc.), the chaos-based cryptosystems are more flexible, more modular and easier to be implemented, which make them suitable for large scale-data encyption, such as images and videos. The heart of any chaos-based cryptosystem is the chaotic generator and so, a part of the efficiency (robustness, speed) of the system depends greatly on it. In this talk, we give an overview of the state of the art of chaos-based block ciphers and we describe some of our schemes already proposed. Also we will focus on the essential characteristics of the digital chaotic generator, The needed performance of a chaos-based block cipher in terms of security level and speed of calculus depends on the considered application. There is a compromise between the security and the speed of the calculation. The security of these block block ciphers will be analyzed.

Keywords: chaos-based cryptosystems, chaotic generator, security analysis, structure of Fridrich

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Authors: Pitak Keawbunsong, Sathaporn Promwong

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This paper presents an investigation on the efficiency of the optimized Davison path loss model in order to look for a suitable path loss model to design and planning DTTV propagation for small and medium urban areas in southern Thailand. Hadyai City in Songkla Province is chosen as the case study to collect the analytical data on the electric field strength. The optimization is conducted through the least square method while the efficiency index is through the statistical value of relative error (RE). The result of the least square method is the offset and slop of the frequency to be used in the optimized process. The statistical result shows that RE of the old Davidson model is at the least when being compared with the optimized Davison and the Hata models. Thus, the old Davison path loss model is the most accurate that further becomes the most optimized for the plan on the propagation network design.

Keywords: DTTV propagation, path loss model, Davidson model, least square method

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Authors: Jadwiga Fila, Mateusz Jezowski, Pawel Poszytek

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The outbreak of the global COVID-19 pandemic started the times of crisis full of uncertainty, especially in the field of transnational cooperation projects based on the international mobility of their participants. This is notably the case of Erasmus+ Program for higher education, which is the flagship European initiative boosting cooperation between educational institutions, businesses, and other actors, enabling students and staff mobility, as well as strategic partnerships between different parties. The aim of this abstract is to study whether competences 4.0 are able to empower Erasmus+ project leaders in sustaining their international cooperation in times of global crisis, widespread online learning, and common project disruption or cancellation. The concept of competences 4.0 emerged from the notion of the industry 4.0, and it relates to skills that are fundamental for the current labor market. For the aim of the study presented in this abstract, four main 4.0 competences were distinguished: digital, managerial, social, and cognitive competence. The hypothesis for the study stipulated that the above-mentioned highly-developed competences may act as a protective shield against the pandemic challenges in terms of projects’ sustainability and continuation. The objective of the research was to assess to what extent individual competences are useful in managing projects in times of crisis. For this purpose, the study was conducted, involving, among others, 141 Polish higher education project leaders who were running their cooperation projects during the peak of the COVID-19 pandemic (Mar-Nov 2020). The research explored the self-perception of the above-mentioned competences among Erasmus+ project leaders and the contextual data regarding the sustainability of the projects. The quantitative character of data permitted validation of scales (Cronbach’s Alfa measure), and the use of factor analysis made it possible to create a distinctive variable for each competence and its dimensions. Finally, logistic regression was used to examine the association of competences and other factors on project status. The study shows that the project leaders’ competence profile attributed the highest score to digital competence (4.36 on the 1-5 scale). Slightly lower values were obtained for cognitive competence (3.96) and managerial competence (3.82). The lowest score was accorded to one specific dimension of social competence: adaptability and ability to manage stress (1.74), which proves that the pandemic was a real challenge which had to be faced by project coordinators. For higher education projects, 10% were suspended or prolonged because of the COVID-19 pandemic, whereas 90% were undisrupted (continued or already successfully finished). The quantitative analysis showed a positive relationship between the leaders’ levels of competences and the projects status. In the case of all competences, the scores were higher for project leaders who finished projects successfully than for leaders who suspended or prolonged their projects. The research demonstrated that, in the demanding times of the COVID-19 pandemic, competences 4.0, to a certain extent, do play a significant role in the successful management of Erasmus+ projects. The implementation and sustainability of international educational projects, despite mobility and sanitary obstacles, depended, among other factors, on the level of leaders’ competences.

Keywords: Competences 4.0, COVID-19 pandemic, Erasmus+ Program, international education, project sustainability

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Authors: Wilaiwan Jongwilaikasaem, Phatteera Sarakornborrirak

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While Thai television producers feel anxious about digital disruption, Love Destiny, Thai television period drama became smash hit in Thailand in 2018. Audience throughout the country not only watched the drama both offline and online but also spread the content of the drama on social media and followed cultural trends from the protagonist. Thus, the main purpose of this article is to examine the secret behind the success of Love Destiny. Data were collected from content analysis and in-depth interview. The result shows that the key success of the drama is from earned media phenomenon from the audience and marketers’ engagement. As Love Destiny has full-flavored content with traditional challenged plot, delicate production, and presentation of Thainess in a positive and tangible way; audience and marketers are enthusiastic about building up the popular trend of Love Destiny on social media and also coming back home to watch televisions when the drama was on the air.

Keywords: Thai drama, earned media, Love Destiny, television

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Birmohan Singh, V.K.Jain

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Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Masses and microcalcifications, architectural distortions are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support Vector Machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and accuracy of 96% for the detection of abnormalities with mammogram images collected from Digital Database for Screening Mammography (DDSM) database.

Keywords: architecture distortion, mammograms, GLCM texture features, GLRLM texture features, support vector machine classifier

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Authors: Assma Azeroual, Karim Afdel, Mohamed El Hajji, Hassan Douzi

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Key frame extraction methods select the most representative frames of a video, which can be used in different areas of video processing such as video retrieval, video summary, and video indexing. In this paper we present a novel approach for extracting key frames from video sequences. The frame is characterized uniquely by his contours which are represented by the dominant blocks. These dominant blocks are located on the contours and its near textures. When the video frames have a noticeable changement, its dominant blocks changed, then we can extracte a key frame. The dominant blocks of every frame is computed, and then feature vectors are extracted from the dominant blocks image of each frame and arranged in a feature matrix. Singular Value Decomposition is used to calculate sliding windows ranks of those matrices. Finally the computed ranks are traced and then we are able to extract key frames of a video. Experimental results show that the proposed approach is robust against a large range of digital effects used during shot transition.

Keywords: FSDWT, key frame extraction, shot detection, singular value decomposition

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Authors: Chia Yen Li, Wen Huei Chou, Mieko Ohsuga, Tsuyoshi Inoue

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The evolution of the digital age has led to people’s lives being pervaded by both facts and misinformation, challenging media literacy (ML). Middle-aged and elderly persons (MEPs) are prone to disseminating large amounts of misinformation, which often endangers their lives due to erroneously believing such information. At present, several countries have actively established fact-checking platforms to combat misinformation, but they are unable to keep pace with the rapid proliferation of such information on social media. In this study, the questionnaire survey method was used to collect data on MEPs’ behavior, cognition, attitudes, and concepts of social media when using a mobile instant messaging app called LINE; analyze their behavioral patterns and reasons for sharing misinformation; and summarize design strategies for improving their ML. The findings can serve as a reference in future related research.

Keywords: media literacy, middle-aged and elderly persons, social media, misinformation

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Authors: Anna Veres

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People’s ability to adapt to a constantly changing environment is essential. Career adaptability is central to Career Construction Theory, where proper adaptation to new situations, changing environments, and jobs require adequate career development. Based on current career theories and the possibilities offered by digital technology, the primary goal of this study is to develop career adaptability through an online tool. Its secondary goal is to apply for an online career intervention program and explore its developmental possibilities. A total of 132 university students from the bachelor program took part in the study, from which 65 students received a four-week online career intervention, while 67 participants formed the control group. Based on the results, it can state that career adaptability can be developed, and there is a great demand and interest from university students to use career-related programs on online platforms. Career interventions should be performed online as well if there is suitable software and a well-constructed program. Limitations and further implications are discussed.

Keywords: career adaptability, career development, online career intervention, university students

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Authors: Gizelle K. Vianna, Gustavo S. Oliveira, Gabriel V. Cunha

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The use of decision support systems in agriculture may help monitoring large fields of crops by automatically detecting the symptoms of foliage diseases. In our work, we designed and implemented a decision support system for small tomatoes producers. This work investigates ways to recognize the late blight disease from the analysis of digital images of tomatoes, using a pair of multilayer perceptron neural networks. The networks outputs are used to generate repainted tomato images in which the injuries on the plant are highlighted, and to calculate the damage level of each plant. Those levels are then used to construct a situation map of a farm where a cellular automata simulates the outbreak evolution over the fields. The simulator can test different pesticides actions, helping in the decision on when to start the spraying and in the analysis of losses and gains of each choice of action.

Keywords: artificial neural networks, cellular automata, decision support system, pattern recognition

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Authors: Ahmed Shuhaiber

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The explosion of the World Wide Web and the electronic trend of university teaching have transformed the learning style to become more learner-centred, Which has popularized the digital delivery of mediated lectures as an alternative or an adjunct to traditional lectures. Despite its potential and popularity, virtual lectures have not been adopted yet in Jordanian universities. This research aimed to fill this gap by studying the factors that influence student’s willingness to accept virtual lectures in one Jordanian University. A quantitative approach was followed by obtaining 216 survey responses and statistically applying the UTAUT model with some modifications. Results revealed that performance expectancy, effort expectancy, social influences and self-efficacy could significantly influence student’s attitudes towards virtual lectures. Additionally, facilitating conditions and attitudes towards virtual lectures were found with significant influence on student’s intention to take virtual lectures. Research implications and future work were specified afterwards.

Keywords: E-learning, student willingness, UTAUT, virtual Lectures, web-based learning systems

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Authors: Y. Laib Dit Leksir, S. Bouhouche

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Analysis and processing of data bases resulting from infrared thermal measurements made on the electrical installation requires the development of new tools in order to obtain correct and additional information to the visual inspections. Consequently, the methods based on the capture of infrared digital images show a great potential and are employed increasingly in various fields. Although, there is an enormous need for the development of effective techniques to analyse these data base in order to extract relevant information relating to the state of the equipments. Our goal consists in introducing recent techniques of modeling based on new methods, image and signal processing to develop mathematical models in this field. The aim of this work is to capture the anomalies existing in electrical equipments during an inspection of some machines using A40 Flir camera. After, we use binarisation techniques in order to select the region of interest and we make comparison between these methods of thermal images obtained to choose the best one.

Keywords: infrared thermography, defect detection, troubleshooting, electrical equipment

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Authors: Patrick Mbassegue, Mickael Gardoni

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In a market environment centered more and more on services and the digital economy, knowledge management becomes a framework that can help organizations to create value and to improve their overall performance. Based on an optimal allocation of scarce resources, managers are interested in demonstrating the added value generated by knowledge management projects. One of the challenges faced by organizations is the difficulty in measuring impacts and concrete results of knowledge management initiatives. The present article concerns the measure of concrete results coming from knowledge management projects based on balance scorecard model. One of the goals is to underline what can be done based on this model but also to highlight the limits associated. The present article is structured in five parts; 1-knowledge management projects and organizational impacts; 2- a framework and a methodology to measure organizational impacts; 3- application illustrated in two case studies; 4- limits concerning the proposed framework; 5- the proposal of a new framework to measure organizational impacts.

Keywords: knowledge management, project, balance scorecard, impacts

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Authors: Tony Cripps, Larry Kimber

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This paper will begin by briefly explaining how blockchain technology works. Then, after highlighting a few of the ways it promises to heavily impact all aspects of the digital landscape, the focus will shift to Blockchain in the field of education, with specific emphasis placed on practical applications in foreign language education. Blockchain is a decentralized Internet-based software application that guarantees truth in transactions. This means whenever two parties engage in a transaction using Blockchain, it is time-stamped, added to a block of other transactions, and then permanently attached to an unalterable ‘chain’ of blocks. The potential for developing applications with Blockchain is therefore immense, since software systems that ensure the impossibility of outside tampering are invaluable. Innovative ideas in every imaginable domain are presently being entertained and Blockchain in education is no exception. For instance, records kept within and between institutions of students’ grade performance, academic achievement and verification of assignment/course completion are just a few examples of how this new technology might potentially be used to revolutionize education. It is hoped that this paper will be of use to all educators interested in the application of technology in the field of education.

Keywords: blockchain, disruption, potential, technology

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Authors: Laetitia Lemiere, Marie Gosme, Gerard Subsol, Marc Jaeger

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Agroforestry is recognized as a way of developing sustainable and resilient agriculture that can fight against climate change. However, the number of species combinations, spatial configurations, and management options for trees and crops is vast. These choices must be adapted to the pedoclimatic and socio-economic contexts and to the objectives of the farmer, who therefore needs support in designing his system. Participative design workshops are a good way to integrate the knowledge of several experts in order to design such complex systems. The design of agroforestry systems should take into account both spatial aspects (e.g., spacing of trees within the lines and between lines, tree line orientation, tree-crop distance, species spatial patterns) and temporal aspects (e.g., crop rotations, tree thinning and pruning, tree planting in the case of successional agroforestry). Furthermore, the interactions between trees and crops evolve as the trees grow. However, agroforestry design workshops generally emphasize the spatial aspect only through the use of static tokens to represent the different species when designing the spatial configuration of the system. Augmented reality (AR) may overcome this limitation, allowing to visualize dynamic representations of trees and crops, and also their interactions, while at the same time retaining the possibility to physically interact with the system being designed (i.e., move trees, add or remove species, etc.). We propose an ergonomic digital solution capable of assisting a group of agroforestry experts to design an agroforestry system and to represent it. We investigated the use of web-based marker-based AR that does not require specific hardware and does not require specific installation so that all users could use their own smartphones right out of the pocket. We developed a prototype mobilizing the AR.js, ArToolKit.js, and Three.js open source libraries. In our implementation, we gradually build a virtual agroforestry system pattern scene from the users' interactions. A specific set of markers initialize the scene properties, and the various plant species are added and located during the workshop design session. The full virtual scene, including the trees positions with their neighborhood, are saved for further uses, such as virtual, augmented instantiation in the farmer fields. The number of tree species available in the application is gradually increasing; we mobilize 3D digital models for walnut, poplar, wild cherry, and other popular species used in agroforestry systems. The prototype allows shadow computations and the representation of trees at various growth stages, as well as different tree generations, and is thus able to visualize the dynamics of the system over time. Future work will focus on i) the design of complex patterns mobilizing several tree/shrub organizations, not restricted to lines; ii) the design of interfaces related to cultural practices, such as clearing or pruning; iii) the representation of tree-crop interactions. Beside tree shade (light competition), our objective is to represent also below-ground competitions (water, nitrogen) or other variables of interest for the design of agroforestry systems (e.g., predicted crop yield).

Keywords: agroforestry system design, augmented reality, marker-based AR, participative design, web-based AR

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Authors: Shireen Simon

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Cyberbullying among schoolchildren and teenagers became a hot issue discussed by Malaysian society. Cyberbullying is a new age of bullying because it uses the modern digital technology intentionally to hurt and degrade someone in the cyber world. Cyberbullying is a problem affecting many teenagers as they embrace online communication and interaction whereby virtual world with no borders. By adopting a qualitative approach, this study has captured 8 cyberbullied victims’ school experience. Even years after leaving school, these 8 cyberbullied victims remember how it feels to be bullied in the cyber world. The principal investigator also tries to identify the possibility factors that contribute to cyberbullying among these 8 victims. The result shows that these victims were bullied differently in cyber world. This study not just primarily focuses on cyberbullying issues among schoolchildren and teenagers; it also addresses the motives and causes of cyberbullying. Lastly, this article will be served as guidance for school teachers, parents and teenagers to prepare to tackle cyberbullying together. Cyberbullying is no laughing matter in our community, and it is time to spread the seeds of peace inspires others to do the same.

Keywords: cyberbullying, cyber victimization, internet, school experience, teenagers

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Authors: Aliasghar Baziar, Hassan Masoumi, Alireza Ale Saadi

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The control of the response of electric motors plays a significant role in the damping of transient responses. In this regard, this paper presents a static VAR compensator (SVC) based on a fuzzy logic which is applied to an industrial power network consisting of three phase synchronous, asynchronous and DC motor loads. The speed and acceleration variations of a specific machine are the inputs of the proposed fuzzy logic controller (FLC). In order to verify the effectiveness and proficiency of the proposed Fuzzy Logic based SVC (FLSVC), several non-linear time-domain digital simulation tests are performed. The proposed fuzzy model can properly control the response of electric motors. The results show that the FLSVC is successful to improve the voltage profile significantly over a wide range of operating conditions and disturbances thus improving the overall dynamic performance of the network.

Keywords: fuzzy logic controller, VAR compensator, single cage asynchronous motor, DC motor

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Authors: Alberto Alcalá-Alvarez, Pablo Padilla-Longoria

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The present paper describes a framework for constructing mathematical networks encoding relevant musical information from a music score for structural analysis. These graphs englobe statistical information about music elements such as notes, chords, rhythms, intervals, etc., and the relations among them, and so become helpful in visualizing and understanding important stylistic features of a music fragment. In order to build such networks, musical data is parsed out of a digital symbolic music file. This data undergoes different analytical procedures from Graph Theory, such as measuring the centrality of nodes, community detection, and entropy calculation. The resulting networks reflect important structural characteristics of the fragment in question: predominant elements, connectivity between them, and complexity of the information contained in it. Music pieces in different styles are analyzed, and the results are contrasted with the traditional analysis outcome in order to show the consistency and potential utility of this method for music analysis.

Keywords: computational musicology, mathematical music modelling, music analysis, style classification

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Authors: Andrea Macruz

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This paper explores computation as a process for design by examining how computers can become more than an operative strategy in a designer's toolkit. It documents this, building upon concepts of neuroscience and Antonio Damasio's Homeostasis Theory, which is the control of bodily states through feedback intended to keep conditions favorable for life. To do this, it follows a methodology through algorithmic drawing and discusses the outcomes of three multi-sensory design installations, which culminated from a course in an academic setting. It explains both the studio process that took place to create the installations and the computational process that was developed, related to the fields of algorithmic design and tangible computing. It discusses how designers can use computational range to achieve homeostasis related to sensory data in a multi-sensory installation. The outcomes show clearly how people and computers interact with different sensory modalities and affordances. They propose using computers as meta-physical stabilizers rather than tools.

Keywords: algorithmic drawing, Antonio Damasio, emotion, homeostasis, multi-sensory installation, neuroscience

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Authors: Yi Wang, Greg Hearn, Terry Flew

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In order to understand how cultural innovation occurs, this paper explores the interaction in Shenzhen of China between universities, creative industries, and government in creative economic using the Triple Helix framework. During the past two decades, Triple Helix has been recognized as a new theory of innovation to inform and guide policy-making in national and regional development. Universities and governments around the world, especially in developing countries, have taken actions to strengthen connections with creative industries to develop regional economies. To date research based on the Triple Helix model has focused primarily on Science and Technology collaborations, largely ignoring other fields. Hence, there is an opportunity for work to be done in seeking to better understand how the Triple Helix framework might apply in the field of creative industries and what knowledge might be gleaned from such an undertaking. Since the late 1990s, the concept of ‘creative industries’ has been introduced as policy and academic discourse. The development of creative industries policy by city agencies has improved city wealth creation and economic capital. It claims to generate a ‘new economy’ of enterprise dynamics and activities for urban renewal through the arts and digital media, via knowledge transfer in knowledge-based economies. Creative industries also involve commercial inputs to the creative economy, to dynamically reshape the city into an innovative culture. In particular, this paper will concentrate on creative spaces (incubators, digital tech parks, maker spaces, art hubs) where academic, industry and government interact. China has sought to enhance the brand of their manufacturing industry in cultural policy. It aims to transfer the image of ‘Made in China’ to ‘Created in China’ as well as to give Chinese brands more international competitiveness in a global economy. Shenzhen is a notable example in China as an international knowledge-based city following this path. In 2009, the Shenzhen Municipal Government proposed the city slogan ‘Build a Leading Cultural City”’ to show the ambition of government’s strong will to develop Shenzhen’s cultural capacity and creativity. The vision of Shenzhen is to become a cultural innovation center, a regional cultural center and an international cultural city. However, there has been a lack of attention to the triple helix interactions in the creative industries in China. In particular, there is limited knowledge about how interactions in creative spaces co-location within triple helix networks significantly influence city based innovation. That is, the roles of participating institutions need to be better understood. Thus, this paper discusses the interplay between university, creative industries and government in Shenzhen. Secondary analysis and documentary analysis will be used as methods in an effort to practically ground and illustrate this theoretical framework. Furthermore, this paper explores how are creative spaces being used to implement Triple Helix in creative industries. In particular, the new combination of resources generated from the synthesized consolidation and interactions through the institutions. This study will thus provide an innovative lens to understand the components, relationships and functions that exist within creative spaces by applying Triple Helix framework to the creative industries.

Keywords: cultural policy, creative industries, creative city, triple Helix

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Authors: Linnea Stenliden

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The aim of this paper is to understand emerging learning conditions, when a visual analytics is implemented and used in K 12 (education). To date, little attention has been paid to the role visual analytics (digital media and technology that highlight visual data communication in order to support analytical tasks) can play in education, and to the extent to which these tools can process actionable data for young students. This study was conducted in three public K 12 schools, in four social science classes with students aged 10 to 13 years, over a period of two to four weeks at each school. Empirical data were generated using video observations and analyzed with help of metaphors by Latour. The learning conditions are found to be distinguished by broad complexity characterized by four dimensions. These emerge from the actors’ deeply intertwined relations in the activities. The paper argues in relation to the found dimensions that novel approaches to teaching and learning could benefit students’ knowledge building as they work with visual analytics, analyzing visualized data.

Keywords: analytical reasoning, complexity, data use, problem space, visual analytics, visual storytelling, translation

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Authors: Anyia Nduka, Aslan Bin Amad Senin, Ayu Azrin Binti Abdul Aziz

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Telemedicine is a rapidly developing discipline with enormous promise for better healthcare results for patients. To meet the demands of patients and the healthcare sector, medical providers must be proficient in telemedicine and also need government funding for infrastructure and core competencies. In this study, we surveyed general hospitals in Kuala Lumpur and Selangor to investigate patient’s impressions of both the positive and negative aspects of government funding for telemedicine and its level of acceptance. This survey was conducted in accordance with the Diffusion of Innovations (DOI) hypothesis; the survey instruments were designed through a Google Form and distributed to patients and every member of the medical team. The findings suggested a framework for categorizing patients' levels of technology use and acceptability, which provided practical consequences for healthcare. We therefore recommend the increase in technical assistance and government-backed funding of telemedicine by bolstering the entire system.

Keywords: technology acceptance, quality assurance, digital transformation, cost management.

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Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

Abstract:

Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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Authors: Chin-Shan Lu, Yi-Pei Liu

Abstract:

This study examines the factors influencing the adoption of MASS in Taiwan's shipping industry. Digital technology and unmanned vehicle advancements have enhanced efficiency and reduced environmental impact in the shipping industry. The IMO has set regulations to promote low-carbon emissions and autonomous ship technology. Using the TOE framework and DOI theory, a research model was constructed, and data from 132 Taiwanese shipping companies were collected via a questionnaire survey. A structural equation modeling (SEM) was conducted to examine the relationships between variables. Results show that technological and environmental factors significantly influence operators' attitudes toward MASS, while organizational factors impact their willingness to adopt. Enhancing technological support, internal resource allocation, top management support, and cost management are crucial for promoting adoption. This study identifies key factors and provides recommendations for adopting autonomous ships in Taiwan's shipping industry.

Keywords: MASS, technology-organization-environment, diffusion of innovations theory, shipping industry

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Authors: Zayar Phyo, Ei Chaw Htoon

Abstract:

In a New-LSB based Steganography method, the Fisher-Yates algorithm is used to permute an existing array randomly. However, that algorithm performance became slower and occurred memory overflow problem while processing the large dimension of images. Therefore, the Text-Based Shuffling algorithm aimed to select only necessary pixels as hiding characters at the specific position of an image according to the length of the input text. In this paper, the enhanced text-based shuffling algorithm is presented with the powered of GPU to improve more excellent performance. The proposed algorithm employs the OpenCL Aparapi framework, along with XORShift Kernel including the Pseudo-Random Number Generator (PRNG) Kernel. PRNG is applied to produce random numbers inside the kernel of OpenCL. The experiment of the proposed algorithm is carried out by practicing GPU that it can perform faster-processing speed and better efficiency without getting the disruption of unnecessary operating system tasks.

Keywords: LSB based steganography, Fisher-Yates algorithm, text-based shuffling algorithm, OpenCL, XORShiftKernel

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Authors: Berhane Tewelday Weldhiwot

Abstract:

This research investigates the pivotal role of modular forms in modern cryptographic systems, particularly focusing on their applications in secure communications and data integrity. Modular forms, which are complex analytic functions with rich arithmetic properties, have gained prominence due to their connections to number theory and algebraic geometry. This study begins by outlining the fundamental concepts of modular forms and their historical development, followed by a detailed examination of their applications in cryptographic protocols such as elliptic curve cryptography and zero-knowledge proofs. By employing techniques from analytic number theory, the research delves into how modular forms can enhance the efficiency and security of cryptographic algorithms. The findings suggest that leveraging modular forms not only improves computational performance but also fortifies security measures against emerging threats in digital communication. This work aims to contribute to the ongoing discourse on integrating advanced mathematical theories into practical applications, ultimately fostering innovation in cryptographic methodologies.

Keywords: modular forms, cryptography, elliptic curves, applications, mathematical theory

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