World Academy of Science, Engineering and Technology

Authors: Job Bapyibi Guyson, Bangripa Kefas

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The advent of social media has no doubt provided platforms that facilitate the spread of fake news. The devastating impact of this does not only end with the prevalence of rumours and propaganda but also poses potential impact on individuals’ mental well-being. Therefore, this study on examining the impact of fake news on the mental health of residents in Jos metropolis among others interrogates the impact of exposure to fake news on residents' mental health. Anchored on the Cultivation Theory, the study adopted quantitative method and surveyed two the opinions of hundred (200) social media users in Jos metropolis using purposive sampling technique. The findings reveal that a significant majority of respondents perceive fake news as highly prevalent on social media, with associated feelings of anxiety and stress. The majority of the respondents express confidence in identifying fake news, though a notable proportion lacks such confidence. Strategies for managing the mental impact of encountering fake news include ignoring it, fact checking, discussing with others, reporting to platforms, and seeking professional support. Based on these insights, recommendations were proposed to address the challenges posed by fake news. These include promoting media literacy, integrating fact-checking tools, adjusting algorithms and fostering digital well-being features among others.

Keywords: fake news, mental health, social media, impact

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Authors: Musab Isah

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This paper presents a longitudinal analysis of Internet speed data in the Gulf Cooperation Council (GCC) region, focusing on the most populous cities of each of the six countries – Riyadh, Saudi Arabia; Dubai, UAE; Kuwait City, Kuwait; Doha, Qatar; Manama, Bahrain; and Muscat, Oman. The study utilizes data collected from the Measurement Lab (M-Lab) infrastructure over a five-year period from January 1, 2019, to December 31, 2023. The analysis includes downstream and upstream throughput data for the cities, covering significant events such as the launch of 5G networks in 2019, COVID-19-induced lockdowns in 2020 and 2021, and the subsequent recovery period and return to normalcy. The results showcase substantial increases in Internet speeds across the cities, highlighting improvements in both download and upload throughput over the years. All the GCC countries have achieved above-average Internet speeds that can conveniently support various online activities and applications with excellent user experience.

Keywords: internet data science, internet performance measurement, throughput analysis, internet speed, measurement lab, network diagnostic tool

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Authors: Shehroz Mukhtar, Maqsood Ahmed, Abdullah Mukhtar, Choudhry Shahid, Waqar Javaid

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Code switching is a common phenomenon, generally observed in multilingual communities across the globe. A critical look at code-switching literature reveals that mostly code-switching has been studied in the classrooms in learning and teaching contexts, while code-switching outside the classroom in settings such as café, hostels and so on has been the least explored areas. The current research investigated the reasons for code-switching in the interactive practices of students and their perceptions regarding the same outside the classroom settings. This paper is the study of the common practice that prevails in the Universities of Sialkot that bilinguals mix two languages when they speak in different classroom situations. In Pakistani classrooms where Multilingual is in abundance, i.e. they can speak two or more two languages at the same time, code-switching or language combination is very common. The teachers of Sialkot switch from one language to another consciously or unconsciously while teaching English in the classrooms. This phenomenon has not been explored in Sialkot’s teaching context. In Sialkot, private educational institutes do not encourage code-switching, whereas public or government institutes use it frequently. The crux of this research is to investigate and identify the importance of code-switching by taking its users into consideration. The survey research method and survey questionnaire will be used to get exact data from teachers and students. We will try to highlight the functions and importance of code switching in foreign language classrooms of Sialkot and will explore why this trend is emerging in Sialkot.

Keywords: code switching, foreign language classrooms, bilingual context, use of L1, importance of L2.

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Authors: Driss Kettani

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ICT4D actors are naturally attempted to include AI in the range of enabling technologies and tools that could support and boost the Development process, and to refer to these as AI4D. But, doing so, assumes that AI complies with the very specific features of ICT4D context, including, among others, affordability, relevance, openness, and ownership. Clearly, none of these is fulfilled, and the enthusiastic posture that AI4D is a natural part of ICT4D is not grounded and, to certain extent, does not serve the purpose of Technology for Development at all. In the context of Development, it is important to emphasize and prioritize ICT4D, in the national digital transformation strategies, instead of borrowing "trendy" waves of the IT Industry that are motivated by business considerations, with no specific care/consideration to Development.

Keywords: AI, ICT4D, technology for development, position paper

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Authors: Niina Meriläinen

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Digital platforms are arenas for dialogue, various kinds of political debates, information and news gathering, policymaking, and social change processes. Human rights serve as examples of social and political issues that are universally noted as principles and yet often violated on digital platforms as well as in the analog world. Digital platforms in this study are different Internet sites, blogs, discussion platforms, social media apps, and gaming. Various actors, from human rights activists and non-governmental organizations to individual people, governments, and corporations, use digital platforms along with analog arenas to discuss and defend human rights, while violators can find new victims and continue violating rights on the same platforms. Digital platforms create opportunities for various women and minorities to empower themselves and others and to be active in various arenas of society and policymaking. At the same time, digital platforms pose threats to human rights globally, especially to women, girls, and minorities. The results of this meta-study of n=120 academic case studies indicate that more research is needed to determine the framework of human rights and human rights on digital platforms. A broad discussion must be had on what human rights require in the digital realm and how ICTs may enhance or threaten our ability to respect, protect, and fulfill a wide variety of human rights while various digital platforms pose multiple threats to human rights. This relates to the willingness of political decision-makers to act upon various crimes committed on and with online platforms. More research is needed to determine the framework of digital human rights and human rights on digital platforms in relation to political communication and decision-making. It is important to develop a framework in which these are defined. It must be discussed who participates in this process: those whose rights are violated, companies that profit by selling our personal data, activists, governments, and some unknown actors. In the end, the question comes back to who has the power to define what we talk about, when, and where. This use of power plays a big role. Digital platforms illustrate the darker side of technological progress, which, on the one hand, has given various people the possibility to engage in society, empower themselves, and take ownership of their rights globally. At the same time, the platforms enable others to use the same platforms to find victims, abuse them, and exploit them. Bullying, harassment, and violence are rampant on various digital platforms, where minorities and people with limited support are victims. There is indeed a need for a discussion of normative values in the era of fake news, the power of influencers, Trumpism, and institutionalized disregard for human rights, gender equality, and the elimination of gender-based violence online. Attention and obligations must be placed on politicians and internet architecture, such as corporations, and their roles in human rights and their violations online.

Keywords: human rights, digital platforms, violations, internet, social media

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Authors: Aneesh Mathew, Arunab K. S., Atul Kumar Sharma

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The uncontrolled rise in population has led to unplanned, swift, and unsustainable urban expansion, causing detrimental environmental impacts on both local and global ecosystems. This research delves into a comprehensive examination of the Urban Heat Island (UHI) phenomenon in Bengaluru and Hyderabad, India. It centers on the spatial and temporal distribution of UHI and its correlation with air pollutants. Conducted across summer and winter seasons from 2001 to 2021 in Bangalore and Hyderabad, this study discovered that UHI intensity varies seasonally, peaking in summer and decreasing in winter. The annual maximum UHI intensities range between 4.65 °C to 6.69 °C in Bengaluru and 5.74 °C to 6.82 °C in Hyderabad. Bengaluru particularly experiences notable fluctuations in average UHI intensity. Introducing the Urban Thermal Field Variance Index (UTFVI), the study indicates a consistent strong UHI effect in both cities, significantly impacting living conditions. Moreover, hotspot analysis demonstrates a rising trend in UHI-affected areas over the years in Bengaluru and Hyderabad. This research underscores the connection between air pollutant concentrations and land surface temperature (LST), highlighting the necessity of comprehending UHI dynamics for urban environmental management and public health. It contributes to a deeper understanding of UHI patterns in swiftly urbanizing areas, providing insights into the intricate relationship between urbanization, climate, and air quality. These findings serve as crucial guidance for policymakers, urban planners, and researchers, facilitating the development of innovative, sustainable strategies to mitigate the adverse impacts of uncontrolled expansion while promoting the well-being of local communities and the global environment.

Keywords: urban heat island effect, land surface temperature, air pollution, urban thermal field variance index

Procedia PDF Downloads 28

Authors: Zhang Songning, Guan Zheng, Ci Yan, Ding Gangyi

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The application of physical simulation engines in collaborative editing systems has an important background and role. Firstly, physical simulation engines can provide real-world physical simulations, enabling users to interact and collaborate in real time in virtual environments. This provides a more intuitive and immersive experience for collaborative editing systems, allowing users to more accurately perceive and understand various elements and operations in collaborative editing. Secondly, through physical simulation engines, different users can share virtual space and perform real-time collaborative editing within it. This real-time sharing and collaborative editing method helps to synchronize information among team members and improve the efficiency of collaborative work. Through experiments, the average model transmission speed of a single person in the collaborative editing system has increased by 141.91%; the average model processing speed of a single person has increased by 134.2%; the average processing flow rate of a single person has increased by 175.19%; the overall efficiency improvement rate of a single person has increased by 150.43%. With the increase in the number of users, the overall efficiency remains stable, and the physical simulation engine running status collaborative editing system also has horizontal scalability. It is not difficult to see that the design and implementation of a collaborative editing system based on physical simulation engines not only enriches the user experience but also optimizes the effectiveness of team collaboration, providing new possibilities for collaborative work.

Keywords: physics engine, simulation technology, collaborative editing, system design, data transmission

Procedia PDF Downloads 32

Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov

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Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.

Keywords: communication, multi-agent systems, protocols, consensus

Procedia PDF Downloads 33

Authors: Jun Liu

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This paper introduces a new bipartite key agreement (2PKA) protocol which provides unconditionally security and lightweight. The unconditional security is stemmed from the known impossibility of distinguishing a particular solution from all possible solutions of an underdetermined system of equations. The indistinguishability prevents an adversary from inferring to the common secret-key even with the access to an unlimited amount of computing capability. This new 2PKA protocol is also lightweight because that the calculation of a common secret-key only makes use of simple modular arithmetic. This information-theoretic 2PKA scheme provides the desired features of Key Confirmation (KC), Session Key (SK) security, Know-Key (KK) security, protection of individual privacy, and uniformly distributed value of a common key under prime modulus.

Keywords: bipartite key agreement, information-theoretic cryptography, perfect security, lightweight

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Authors: Lawal Kado

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This paper investigates the perceptions of academic staff at Umaru Musa Yar’adua University regarding the influences of librarians and working colleagues on the awareness and use of electronic databases. The study aims to provide insights into the effectiveness of these influences and suggest strategies to improve the usage of electronic databases. Research aim: The aim of this study is to determine the perceptions of academic staff on the influence of librarians and working colleagues towards the awareness and use of electronic databases in Umaru Musa Yar’adua University, Katsina. Methodology: The study adopts a quantitative method and survey research design. The survey questionnaire is distributed to 110 respondents selected through simple random sampling from a population of 523 academic staff. The collected data is analyzed using the Statistical Package for Social Sciences (SPSS) version 23. Findings: The study reveals a high level of general awareness of electronic databases in the university, largely influenced by librarians and colleagues. Librarians have played a crucial role in making academic staff aware of the available databases. The sources of information for awareness include colleagues, social media, e-mails from the library, and internet searching. Theoretical importance: This study contributes to the literature by examining the perceptions of academic staff, which can inform policymakers and stakeholders in developing strategies to maximize the use of electronic databases. Data collection and analysis procedures: The data is collected through a survey questionnaire that utilizes the Likert scaling technique. The closed-ended questions are analyzed using SPSS 23. Question addressed: The paper addresses the question of how librarians and working colleagues influence the awareness and use of electronic databases among academic staff. Conclusion: The study concludes that the influence of librarians and working colleagues significantly contributes to the awareness and use of electronic databases among academic staff. The paper recommends the establishment of dedicated departments or units for marketing library resources to further promote the usage of electronic databases.

Keywords: awareness, electronic databases, academic staff, unified theory of acceptance and use of technology, social influence

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Authors: Lin Xie, Yang Wang

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An extensive body of research studies suggest that students, teachers, and supervisors can enhance the likelihood of reaching their goals by improving their communication skills. It is highly important to learn how and when to provide different kinds of feedback, e.g. anticipatory, corrective and positive) will gain better result and higher morale. The purpose of this mixed methods research is twofold: 1) To find out what factors affect effective communication among different stakeholders and how these factors affect student learning 2) What are the good practices for improving communication among different stakeholders and improve student achievement. This presentation first begins with an introduction to the recent research on Marshall’s Nonviolent Communication Techniques (NVC), including four important components: observations, feelings, needs, requests. These techniques can be effectively applied at all levels of communication. To develop an in-depth understanding of the relationship among different techniques within, this research collected, compared, and combined qualitative and quantitative data to better improve communication and support student learning.

Keywords: communication, education, language learning, goal achievement, academic success

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Authors: Adrian-Gabriel Chifu, Sebastien Fournier

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One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

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Authors: Amirhossen Zare Rahvard

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Freemium games based on the gacha mechanic have proven highly successful in recent years - games with simple graphics and simple gameplay systems but with a highly profitable market. Attempts at developing gacha games have even been made in Iran. Since gacha games are both profitable and easy to develop, they seem to be a suitable starting point for establishing a video game market in underdeveloped countries. This article aims to review the gacha games' approach to gaining revenue by studying the case of Arknights game in order to draw an outline of how simple games have led to great markets.

Keywords: gacha games, game’s economy, underdeveloped countries and games, arkngihts

Procedia PDF Downloads 74

Authors: Ali Momeni

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Visual media has had a significant impact on the mental structure and behaviors of humanity. One interactive platform that has played a major role in this is Instagram. In Islamic countries, particularly Iran, many Muslims have embraced this interactive media platform for various reasons. Instagram has also provided an opportunity for individuals to become famous and gain micro-celebrity status through its semi-algorithmic features. A notable group of Iranian women who have gained fame through Instagram are religious Muslim women who have transitioned into bloggers. These Iranian religious women bloggers (IRWB) have garnered a large following by showcasing different models of hijab and their private lives. This research aims to qualitatively study the representation of femininity and religiosity of these women. The main question addressed in this study is the acceptance of Instagram activity by IRWB among religious women. Drawing on concepts such as 'The Society of the Spectacle' and 'Celebrity Online', this study utilized the netnography method to analyze 14 pages of IRWB. Data was collected in two phases, with the first phase involving the analysis of religious women's comments on posts related to these themes. The second phase included interviews with religious women students who view or follow these pages. A total of 120 comments and 14 interviews were thematically analyzed. The results revealed that the reception of these pages by religious women fell into four main themes: the spectacle of femininity, the commercialization of religiosity, the distortion of Islam, and the construction of religiosity and femininity. Ultimately, religious women did not find these pages to be reflective of their own experiences of female and religious life.

Keywords: women, bloggers, instagram, IRWB, reception.

Procedia PDF Downloads 33

Authors: Qazi Mahdia Ghyas

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Electronic Government Procurement (e-GP) has implemented in Bangladesh to ensure the good Governance. e-GP has transformed Bangladesh's procurement process electronically. But, to our best knowledge, there is no study to understand the key features of e-GP in Bangladesh. So, this study tries to identify the features of performance improvement after implementing an e-GP system that will help for further improvements. Data was collected from the PROMIS Overall Report (Central Procurement Technical Unit website) for the financial year from Q1 _July- Sep 2015-16 to Q4 _Apr- Jun 2021-22. This study did component factor analysis on KPIs and found nineteen KPIs that are statistically significant and represent time savings, efficiency, accountability, anti-corruption and compliance key features in procurement activities of e-GP. Based on the analysis, some practical measures have been recommended for better improvement of e-GP. This study has some limitations. Because of having multicollinearity issues, all the 42 KPIs (except 19) did not show a good fit for component factor analysis.

Keywords: public procurement, electronic government procurement, KPI, performance evaluation

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Authors: Suleiman Aliyu

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Integrating IoT applications with Fog systems presents challenges in optimization due to diverse environments and conflicting objectives. This study explores achieving Pareto optimal deployments for Fog-based IoT systems to address growing QoS demands. We introduce Pareto optimality to balance competing performance metrics. Using the FogTorch optimization framework, we propose a hybrid approach (Backtracking search with branch and bound) for scalable IoT deployments. Our research highlights the advantages of Pareto optimality over single-objective methods and emphasizes the role of FogTorch in this context. Initial results show improvements in IoT deployment cost in Fog systems, promoting resource-efficient strategies.

Keywords: pareto optimality, fog application deployment, resource allocation, internet of things

Procedia PDF Downloads 38

Authors: Chan Ka Lok Sobel

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The rapid evolution of digital media platforms has given rise to new forms of narrative engagement, particularly through multi-channel storytelling. This research focuses on exploring the teaching pedagogy and effectiveness of multi-channel storytelling for social media, cinema, games, and streaming platforms. The study employs case studies of the popular series "Squid Game" to investigate the diverse pedagogical approaches and strategies used in teaching multi-channel storytelling. Through qualitative research methods, including interviews, surveys, and content analysis, the research assesses the effectiveness of these approaches in terms of student engagement, knowledge acquisition, critical thinking skills, and the development of digital literacy. The findings contribute to understanding best practices for incorporating multi-channel storytelling into educational contexts and enhancing learning outcomes in the digital media landscape.

Keywords: digital literacy, game-based learning, artificial intelligence, animation production, educational technology

Procedia PDF Downloads 47

Authors: Brennan Lodge

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Cybersecurity professionals have long been embroiled in a digital arms race, confronting increasingly sophisticated threats with innovative solutions. The field of cybersecurity is in an unending race against malicious adversaries. As threats evolve in complexity, the tools used to defend against them need to advance even faster. Burdened with a vast arsenal of tools and an expansive scope of threat intelligence, analysts frequently navigate a complex web, trying to discern patterns amidst information overload. Herein lies the potential of Retrieval Augmented Generation (RAG). By combining the capabilities of Large Language Models (LLMs) with a generative AI facet, RAG brings to the table an unparalleled ability for real-time cross-referencing, bridging the gap between raw data and actionable insights. Imagine an analyst named Sarah working at a global Fortune 500 company. Every day, Sarah navigates a maze of diverse knowledge bases, real-time threat intelligence, and her company's vast proprietary data, from network specifics to intricate technical blueprints. One day, she's challenged by a potential breach through a personal device due to the company's global "Bring Your Own Device" policy. With the clock ticking, Sarah has mere minutes to trace the malware's origin, all while considering complex regional regulations. As she races against the benchmark of Mean Time To Resolution (MTTR), she wonders: Could "Cozy Bear" with its notorious malware tactic, HAMMERTOSS, be behind this? Balancing policy intricacies, global network considerations, and ever-emerging cyber threats, Sarah's role epitomizes the intense challenges faced by today's cybersecurity analysts. While analysts grapple with this array of intricate, time-sensitive challenges, the necessity for precision and efficiency is key. RAG technology—a cutting-edge advancement in Gen AI—is a promising solution. Designed to assimilate diverse data sources such as cyber advisory notices, phishing email sentiment, secure and insecure code examples, information security policy documentation, and the MITRE ATT&CK framework, RAG equips analysts with real-time querying capabilities through a vector database and a cross referenced concise response from a Gen AI model. Traditional relational databases often necessitate a tedious process of filtering through numerous entries. Now, with the synergy of vector databases and Gen AI models, analysts can rapidly access both contextually or semantically akin data points. This augmented approach equips analysts with a comprehensive understanding of the prevailing cyber threats, elevating the robustness of cybersecurity defenses and upskilling the analyst and team, too. Vector databases underpin the knowledge translation in Gen AI. They bridge the gap between raw data and translation into meaningful insights, ensuring that analysts are equipped with comprehensive and relevant information. This superior capability of the RAG framework, with its impressive depth and precision, finds application across a broad spectrum of cybersecurity challenges. Let's delve into some use cases where its potential becomes particularly evident: Phishing Email Sentiment Analysis: Phishing remains a predominant vector for cybersecurity breaches. Leveraging RAG's capabilities, analysts can not only assess the potential malevolence of an email but can also understand the context behind it. By cross-referencing patterns from varied data sources in real-time, the detection process evolves from a mere content evaluation to a holistic understanding of attacker tactics, behaviors, and evolving profiles. This allows for the identification of nuanced phishing strategies that might otherwise go undetected. Insecure Code Analysis: Software vulnerabilities form a critical entry point for cyber adversaries. With RAG, the process of code evaluation undergoes a transformation. Instead of manual code reviews, the system pulls insights from vector databases and historical code snippets marked as insecure, enabling detection of vulnerabilities based on historical patterns, emerging threat vectors, and even predictive threat modeling. This ensures that even the most obfuscated or embedded vulnerabilities are identified, and corrective measures can be promptly implemented. Vulnerability and Upskill Advisory: In the fast-paced world of cybersecurity, staying updated is paramount. Through RAG's capabilities, analysts are not only made aware of real-time vulnerabilities but are also guided on the necessary skills and tools needed to combat them. By dynamically sourcing data through vulnerability advisories, news on advanced persistent threats, and tactics to defend, RAG ensures that analysts are not only reactive to threats but are also proactively upskilled, thereby bolstering their defense mechanisms. Information Security Policies for Compliance Teams: Compliance remains at the heart of many organizational cybersecurity strategies. However, with ever-shifting regulatory landscapes, staying compliant becomes a moving target. RAG's ability to source real-time data ensures that compliance teams always have access to the latest policy changes, guidelines, and best practices. This not only facilitates adherence to current standards but also anticipates future shifts, assists with audits, and ensures that organizations remain ahead of the compliance curve. Fusing a RAG architecture with platforms like Slack amplifies its practical utility. Slack, known for its real-time communication prowess, seamlessly evolves into more than just a messaging platform in this context. Cybersecurity analysts can pose intricate queries within Slack and, almost instantaneously, receive comprehensive feedback powered by the harmonious interplay of RAG and Gen AI. This integration effectively transforms Slack into an AI-augmented chatbot-like assistant for cybersecurity professionals, always ready to provide informed insights on-demand, making it an indispensable ally in the ever-evolving cyber battlefield. Navigating the vast landscape of cybersecurity, analysts often encounter unfamiliar terminologies and techniques., analysts require tools that not only detect or inform them of threats, like CISA (U.S Cybersecurity Infrastructure Security Agency) Advisories, but also interpret and communicate them effectively. Consider a junior cybersecurity analyst named Alex, who comes across the term "Kerberoasting" while reviewing a network log. Unfamiliar with its intricacies, Alex turns to Slack to pose a query: "chat explain is Kerberoasting, using CISA." Almost instantaneously, Slack, powered by the harmonious interplay of RAG and Gen AI, provides a detailed response, cross-referencing a recent cyber advisory on the technique. It explains how attackers can exploit the Kerberos Ticket Granting Service to decipher service account passwords, potentially compromising a network. In this dynamic realm of cybersecurity, the blend of RAG and Generative AI represents more than just a technological leap. It embodies a paradigm shift, promising a future where human expertise and AI-driven precision join forces. As cyber threats continue their relentless advance, this synergy ensures that defenders are equipped with an arsenal that's not just reactive, but also profoundly insightful. No longer should analysts be submerged in a deluge of data without direction. Instead, they should be empowered, to discern, act, and preempt with unparalleled clarity and confidence. By harmoniously intertwining human discernment with AI capabilities, we should chart a path towards a future where cybersecurity is not just about defense, but about achieving a strategic advantage, paving the way for a safer, informed and a more secure digital horizon.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

Procedia PDF Downloads 44

Authors: Getaneh Berie Tarekegn

Abstract:

Wireless communication via unmanned aerial vehicles (UAVs) has drawn a great deal of attention due to its flexibility in establishing line-of-sight (LoS) communications. However, in complex urban and dynamic environments, the movement of UAVs can be blocked by trees and high-rise buildings that obstruct directional paths. With reconfigurable intelligent surfaces (RIS), this problem can be effectively addressed. To achieve this goal, accurate channel estimation in RIS-assisted UAV-enabled wireless communications is crucial. This paper proposes an accurate channel estimation model using long short-term memory (LSTM) for a multi-user RIS-assisted UAV-enabled wireless communication system. According to simulation results, LSTM can improve the channel estimation performance of RIS-assisted UAV-enabled wireless communication.

Keywords: channel estimation, reconfigurable intelligent surfaces, long short-term memory, unmanned aerial vehicles

Procedia PDF Downloads 46

Authors: Maryam Kiani

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In order to enhance the efficiency and stability of an electrocatalyst for formic acid electro-oxidation reaction (FAOR), we developed a method to create Pt/Ni nanoparticles with carbon black. These nanoparticles were prepared using a simple impregnation reduction technique. During the observation, it was found that the nanoparticles had a spherical shape. Additionally, the average particle size remained consistent, falling within the range of about 4 nm. This approach aimed to obtain a loaded Pt-based electrocatalyst that would exhibit improved performance and stability when used in FAOR applications. By utilizing the impregnation reduction method and incorporating Ni nanoparticles along with Pt, we sought to enhance the catalytic properties of the material. By incorporating Ni atoms into the Pt structure, the electronic properties of Pt are modified, resulting in a delay in the chemisorption of harmful CO intermediate species. This modification also promotes the dehydrogenation pathway of the formic acid oxidation reaction (FAOR). Through electrochemical analysis, it has been observed that the Pt3Ni-C catalyst exhibits enhanced performance in FAOR compared to traditional Pt catalysts. This means that the addition of Ni atoms improves the efficiency and effectiveness of the Pt3Ni-C catalyst in facilitating the FAOR process. Overall, the utilization of these alloy nanoparticles as electrocatalysts represents a significant advancement in fuel cell technology.

Keywords: electrocatalyst, impregnation reduction method, formic acid electro-oxidation reaction, fuel cells

Procedia PDF Downloads 61

Authors: Amrane Meriem, Oukid Salyha

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The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

Procedia PDF Downloads 42

Authors: Olakanmi Oladayo Olufemi, Bamifewe Olusegun James, Badmus Yaya Opeyemi, Adegoke Kayode

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The wireless sensor network (WSN) has made a significant contribution to the emergence of various intelligent services or cloud-based applications. Most of the time, these data are stored on a cloud platform for efficient management and sharing among different services or users. However, the sensitivity of the data makes them prone to various confidentiality and performance-related attacks during and after harvesting. Various security schemes have been developed to ensure the integrity and confidentiality of the WSNs' data. However, their specificity towards particular attacks and the resource constraint and heterogeneity of WSNs make most of these schemes imperfect. In this paper, we propose a secure variance-aware routing and authentication scheme with two-tier verification to collect, share, and manage WSN data. The scheme is capable of classifying WSN into different subnets, detecting any attempt of wormhole and black hole attack during harvesting, and enforcing access control on the harvested data stored in the cloud. The results of the analysis showed that the proposed scheme has more security functionalities than other related schemes, solves most of the WSNs and cloud security issues, prevents wormhole and black hole attacks, identifies the attackers during data harvesting, and enforces access control on the harvested data stored in the cloud at low computational, storage, and communication overheads.

Keywords: data block, heterogeneous IoT network, data harvesting, wormhole attack, blackhole attack access control

Procedia PDF Downloads 30

Authors: Alon Friedman, Antonio Sanchez Chinchon

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This bibliometric study takes an artistic and storytelling approach to explore the term ”information visualization.” Analyzing over 1008 titles collected from databases that specialize in data visualization research, we examine the titles of these publications to report on the characteristics and development trends in the field. Employing a qualitative methodology, we delve into the titles of these publications, extracting leading terms and exploring the cooccurrence of these terms to gain deeper insights. By systematically analyzing the leading terms and their relationships within the titles, we shed light on the prevailing themes that shape the landscape of ”information visualization” by employing the artist Mark Lombardi’s techniques to visualize our findings. By doing so, this study provides valuable insights into bibliometrics visualization while also opening new avenues for leveraging art and storytelling to enhance data representation.

Keywords: bibliometrics analysis, Mark Lombardi design, information visualization, qualitative methodology

Procedia PDF Downloads 42

Authors: Shah Muhammad Butt

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The study aimed to investigate the factors influencing the adoption of e-governance in Pakistan's public universities and how that adoption has affected organizational performance. An online Likert scale survey was utilized to gather information from 350 participants from different public universities in Pakistan. The data were examined using descriptive statistics and correlation analysis. The findings suggest that organizational culture, infrastructure, and leadership support are among the elements impacting the adoption of e-governance at Pakistan's public sector universities. A further finding of the study was that e-governance adoption benefited organizational performance, including effectiveness, efficiency, and customer satisfaction. The study emphasizes the significance of e-governance adoption at public sector universities and the demand for successful policies and strategies to support its implementation. To increase organisational performance and raise the standard of higher education in Pakistan, policymakers and university administrators should use the study's findings to develop and practice e-governance policies and initiatives.

Keywords: e-governance, adoption, public sector universities, Pakistan, organizational performance, higher education, technology, ICT, factors, comparative analysis

Procedia PDF Downloads 43

Authors: Hamid R. Lashgarian Azad, Seyed N. Shetab Boushehri

Abstract:

Wireless sensor networks (WSN) have become progressively popular due to their wide range of applications. Wireless Sensor Network is made of numerous tiny sensor nodes that are battery-powered. It is a very significant problem to maximize the lifetime of wireless sensor networks. In this paper, we propose a two-stage protocol based on an imperialist competitive algorithm (2S-ICA) to solve a sensor network optimization problem. The energy of the sensors can be greatly reduced and the lifetime of the network reduced by long communication distances between the sensors and the sink. We can minimize the overall communication distance considerably, thereby extending the lifetime of the network lifetime through connecting sensors into a series of independent clusters using 2SICA. Comparison results of the proposed protocol and LEACH protocol, which is common to solving WSN problems, show that our protocol has a better performance in terms of improving network life and increasing the number of transmitted data.

Keywords: wireless sensor network, imperialist competitive algorithm, LEACH protocol, k-means clustering

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Authors: Malika Yaici, Soraya Aloui, Sara Semchaoui

Abstract:

This paper deals with human activity recognition from sensor data. It is an active research area, and the main objective is to obtain a high recognition rate. In this work, a recognition system based on expert systems is proposed; the recognition is performed using the objects, object states, and gestures and taking into account the context (the location of the objects and of the person performing the activity, the duration of the elementary actions and the activity). The system recognizes complex activities after decomposing them into simple, easy-to-recognize activities. The proposed method can be applied to any type of activity. The simulation results show the robustness of our system and its speed of decision.

Keywords: human activity recognition, ubiquitous computing, context-awareness, expert system

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Authors: E. Hegazy, S. Anderberg, J. Krook

Abstract:

The city's wire-based infrastructure systems (WBIS) are responsible for the delivery of electricity, telecommunications, sanitation, drainage, and district heating and are a necessity for sustainable modern urban life. Maintaining the functionality of these structures involves high costs and, brings disturbance to the local community and effects on the environment. One key reason for this is that the cables and pipes are placed under streets, making system parts easily worn and their service lifetime reduced, and all maintenance and renewal rely on recurrent needs for excavation. In Sweden, a significant part of wire-based infrastructure is already outdated and will need to be replaced in the coming decades. The replacement of these systems will entail massive costs as well as important traffic disruption and environmental disturbance. However, this challenge may also open a unique opportunity to introduce new, more sustainable technologies and management practices. The transformation of WBIS management for long-term sustainability and meeting maintenance and renewal needs does not have a comprehensive approach. However, a systemic approach may inform WBIS management. This approach considers both technical and non-technical aspects, as well as time-related factors. Nevertheless, there is limited systemic knowledge of how different factors influence current management practices. The aim of this study is to address this knowledge gap and contribute to the understanding of what factors influence the current practice of WBIS management. A case study approach is used to identify current management practices, the underlying factors that influence them, and their implications for sustainability outcomes. The case study is based on both quantitative data on the local system and data from interviews and workshops with local practitioners and other stakeholders. Linköping was selected as a case since it provided good accessibility to the water administration and relevant data for analyzing water infrastructure management strategies. It is a sufficiently important city in Sweden to be able to identify challenges, which, to some extent, are common to all Swedish cities. By uncovering current practices and what is influencing Linköping, knowledge gaps and uncertainties related to sustainability consequences were highlighted. The findings show that goals, priorities, and policies controlling management are short-termed, and decisions on maintenance and renewal are often restricted to finding solutions to the most urgent issues. Sustainability transformation in the infrastructure area will not be possible through individual efforts without coordinated technical, organizational, business, and regulatory changes.

Keywords: case study, infrastructure, management, practice, Sweden

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Authors: Tesfaye Fenta Boka, Niu Zhendong

Abstract:

Recommender systems play a crucial role in connecting individuals with the items they require, as is particularly evident in the rapid growth of online grocery shopping platforms. These systems predominantly rely on user-centered recommendations, where items are suggested based on individual preferences, garnering considerable attention and adoption. However, our focus lies on the item-centered recommendation task within the grocery shopping context. In the reverse next item period recommendation (RNPR) task, we are presented with a specific item and challenged to identify potential users who are likely to consume it in the upcoming period. Despite the ever-expanding inventory of products on online grocery platforms, the cold start item problem persists, posing a substantial hurdle in delivering personalized and accurate recommendations for new or niche grocery items. To address this challenge, we propose a Graph Neural Network (GNN)-based approach. By capitalizing on the inherent relationships among grocery items and leveraging users' historical interactions, our model aims to provide reliable and context-aware recommendations for cold-start items. This integration of GNN technology holds the promise of enhancing recommendation accuracy and catering to users' individual preferences. This research contributes to the advancement of personalized recommendations in the online grocery shopping domain. By harnessing the potential of GNNs and exploring item-centered recommendation strategies, we aim to improve the overall shopping experience and satisfaction of users on these platforms.

Keywords: recommender systems, cold start item recommendations, online grocery shopping platforms, graph neural networks

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Authors: Claudia Mertens, Amanda Shufflebarger

Abstract:

Step one: What we know about effective learning for pupils with SEN: results of 2 systematic reviews: Before establishing principles and practices for teaching and learning of pupils with SEN, we need a good overview of the results of empirical studies conducted in the respective field. Therefore, two systematic reviews on the use of digital tools in inclusive and non-inclusive school settings were conducted - taking into consideration studies published in German: One systematic review included studies having undergone a peer review process, and the second included studies without peer review). The results (collaboration of two German universities) will be presented during the conference. Step two: Students’ results of a research lab on “inclusive media education”: On this basis, German students worked on “inclusive media education” in small research projects (duration: 1 year). They were “education majors” enrolled in a course on inclusive media education. They conducted research projects on topics ranging from smartboards in inclusive settings, digital media in gifted math education, Tik Tok in German as a Foreign Language education and many more. As part of their course, the German students created an academic conference poster. In the conference, the results of these research projects/papers are put into the context of the results of the systematic reviews. Step three: Global Classroom: The German students’ posters were critically discussed in a global classroom in cooperation with Indiana University East (USA) and Hamburg University (Germany) in the winter/spring term of 2022/2023. 15 students in Germany collaborated with 15 students at Indiana University East. The IU East student participants were enrolled in “Writing in the Arts and Sciences,” which is specifically designed for pre-service teachers. The joint work began at the beginning of the Spring 2023 semester in January 2023 and continued until the end of the Uni Hamburg semester in February 2023. Before January, Uni Hamburg students had been working on a research project individually or in pairs. Didactic Approach: Both groups of students posted a brief video or audio introduction to a shared Canvas discussion page. In the joint long synchronous session, the students discussed key content terms such as inclusion, inclusive, diversity, etc., with the help of prompt cards, and they compared how they understood or applied these terms differently. Uni Hamburg students presented drafts of academic posters. IU East students gave them specific feedback. After that, IU East students wrote brief reflections summarizing what they learned from the poster. After the class, small groups were expected to create a voice recording reflecting on their experiences. In their recordings, they examined critical incidents, highlighting what they learned from these incidents. Major results of the student research and of the global classroom collaboration can be highlighted during the conference. Results: The aggregated results of the two systematic reviews AND of the research lab/global classroom can now be a sound basis for 1) improving accessibility for students with SEN and 2) for adjusting teaching materials and concepts to the needs of the students with SEN - in order to create successful learning.

Keywords: digitalization, inclusion, inclusive media education, global classroom, systematic review

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Authors: Aofan Liu, Qianqian Tan, Burra Venkata Durga Kumar

Abstract:

Data security is of the utmost importance in the healthcare area, as sensitive patient information is constantly sent around and analyzed by many different parties. The use of federated learning, which enables data to be evaluated locally on devices rather than being transferred to a central server, has emerged as a potential solution for protecting the privacy of user information. To protect against data breaches and unauthorized access, federated learning alone might not be adequate. In this context, the application of blockchain technology could provide the system extra protection. This study proposes a distributed federated learning system that is built on blockchain technology in order to enhance security in healthcare. This makes it possible for a wide variety of healthcare providers to work together on data analysis without raising concerns about the confidentiality of the data. The technical aspects of the system, including as the design and implementation of distributed learning algorithms, consensus mechanisms, and smart contracts, are also investigated as part of this process. The technique that was offered is a workable alternative that addresses concerns about the safety of healthcare while also fostering collaborative research and the interchange of data.

Keywords: data privacy, distributed system, federated learning, machine learning

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