Search results for: Privacy Preserving Data Publication (PPDP)

Authors: Chuping Lo

Abstract:

This paper presents a simple model demonstrating that ceteris paribus countries with lower barriers to accessing global data tend to earn higher incomes than other countries. Therefore, large countries that inherently have greater data resources tend to have higher incomes than smaller countries, such that the former may be more hesitant than the latter to liberalize cross-border data flows to maintain this advantage. Furthermore, countries with higher artificial intelligence (AI) intensity in production technologies tend to benefit more from economies of scale in data aggregation, leading to higher income and more trade as they are better able to utilize global data.

Keywords: digital intensity, digital divide, international trade, scale of economics

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Authors: G. R. Navaneesh, E. Nagarajan, C. H. Rajam Raju

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Nowadays the multimedia data are used to store some secure information. All previous methods allocate a space in image for data embedding purpose after encryption. In this paper, we propose a novel method by reserving space in image with a boundary surrounded before encryption with a traditional RDH algorithm, which makes it easy for the data hider to reversibly embed data in the encrypted images. The proposed method can achieve real time performance, that is, data extraction and image recovery are free of any error. A secure transmission process is also discussed in this paper, which improves the efficiency by ten times compared to other processes as discussed.

Keywords: secure communication, reserving room before encryption, least significant bits, image encryption, reversible data hiding

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: Okafor Calistus Chibuzor

Abstract:

Preserving African architectural heritage is a multifaceted endeavor that intersects with socio-cultural, economic, and environmental factors. Despite growing recognition of the importance of safeguarding these invaluable cultural assets, numerous challenges persist, hindering effective preservation efforts across the continent. This paper investigates the underlying factors impeding the preservation of African architectural heritage, aiming to provide insights for addressing this critical issue. The study begins with an exploration of the historical background and significance of African architectural heritage, highlighting its rich diversity and cultural significance. The study acknowledges that there is an urgent need to address the threats facing these heritage sites, including urbanization, rapid development, lack of funding, inadequate legal protection, and insufficient public awareness. The primary aim of this research is to identify and analyze the key factors contributing to the deterioration and loss of African architectural heritage, with the objective of formulating strategies to mitigate these challenges. A mixed-use research methodology combining archival research, field surveys, stakeholder interviews, and case studies is employed to gather comprehensive data and insights. The findings reveal a complex interplay of socio-economic, political, and institutional factors shaping the preservation landscape in Africa, including issues related to funding, governance, community engagement, and capacity building. The paper concludes by highlighting the urgent need for coordinated efforts among government agencies, heritage organizations, local communities, and international stakeholders to address the identified challenges and develop sustainable preservation strategies. Recommendations are provided for enhancing legal frameworks, promoting community involvement, fostering public awareness, and mobilizing resources to safeguard Africa's rich architectural heritage for future generations.

Keywords: African architectural heritage, preservation challenges, preservation strategies, factors

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Authors: Joshefina Bengoechea Fernandez, Alex Bell

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

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

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Authors: R Palson Kennedy, P.Kiran Sai

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This article introduces machine learning (ML) researchers to the hurdles that geoscience problems present, as well as the opportunities for improvement in both ML and geosciences. This article presents a review from the data life cycle perspective to meet that need. Numerous facets of geosciences present unique difficulties for the study of intelligent systems. Geosciences data is notoriously difficult to analyze since it is frequently unpredictable, intermittent, sparse, multi-resolution, and multi-scale. The first half addresses data science’s essential concepts and theoretical underpinnings, while the second section contains key themes and sharing experiences from current publications focused on each stage of the data life cycle. Finally, themes such as open science, smart data, and team science are considered.

Keywords: Data science, intelligent system, machine learning, big data, data life cycle, recent development, geo science

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Authors: L. Edirisinghe, P. Mukherjee, H. Edirisinghe

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Virtual Container Yard (VCY) is a modern concept that helps to reduce the empty container repositioning cost of carriers. The concept of VCY is based on container interchange between shipping lines. Although this mechanism has been theoretically accepted by the shipping community as a feasible solution, it has not yet achieved the necessary momentum among container shipping lines (CSL). This paper investigates whether there is any legal influence on this industry myopia about the VCY. It is believed that this is the first publication that focuses on the legal aspects of container exchange between carriers. Not much literature on this subject is available. This study establishes with statistical evidence that there is a phobia prevailing in the shipping industry that exchanging containers with other carriers may lead to various legal implications. The complexity of exchange is two faceted. CSLs assume that offering a container to another carrier (obviously, a competitor in terms of commercial context) or using a container offered by another carrier may lead to undue legal implications. This research reveals that this fear is reflected through four types of perceived components, namely: shipping associate; warehouse associate; network associate; and trading associate. These components carry eighteen subcomponents that comprehensively cover the entire process of a container shipment. The statistical explanation has been supported through regression analysis; INCO terms were used to illustrate the shipping process.

Keywords: virtual container yard, legal, maritime law, inventory

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Authors: Monika Gałwa-Widera, Anna Kwarciak–Kozłowska, Lucyna Sławik-Dembiczak

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Issues relating to management of sewage sludge from small and medium-sized wastewater treatment plants is a vital issue, which deal with such scholars as well as those directly involved in the issue of wastewater treatment and management of sedimentary. According to the Law on Waste generating waste is responsible for such processing to the product obtained impacted on the environment minimally. In small and medium-sized wastewater treatment plants have to deal with the technology of sludge management technology is far from drying and incineration of sewage sludge. So here you can use other technologies. One of them is the composting of sewage sludge. It is a process of processing and disposal of sewage sludge that effectively their disposal. By composting, we can obtain a product that contains significant amounts of organic matter to assess the fertilizing qualities. Modifications to the ongoing process in biological reactors allow for more rapid receipt of a wholesome product. The research presented and discussed in this publication relate to assist the composting process of sewage sludge and biomass structural material in the shares of rates: 35% biomass, 55% sludge, 10% structural material using a method which involves the re-spawning batch composting physical methods leachate from the composting process.

Keywords: biomass, composting, industry, sewage sludge

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Authors: Marc Bachelet, Abhijit Kumar Chatterjee, José Manuel Avila

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Data quality is a key component of any data-driven organization. Without data quality, organizations cannot effectively make data-driven decisions, which often leads to poor business performance. Therefore, it is important for an organization to ensure that the data they use is of high quality. This is where the concept of data mesh comes in. Data mesh is an organizational and architectural decentralized approach to data management that can help organizations improve the quality of data. The concept of data mesh was first introduced in 2020. Its purpose is to decentralize data ownership, making it easier for domain experts to manage the data. This can help organizations improve data quality by reducing the reliance on centralized data teams and allowing domain experts to take charge of their data. This paper intends to discuss how a set of elements, including data mesh, are tools capable of increasing data quality. One of the key benefits of data mesh is improved metadata management. In a traditional data architecture, metadata management is typically centralized, which can lead to data silos and poor data quality. With data mesh, metadata is managed in a decentralized manner, ensuring accurate and up-to-date metadata, thereby improving data quality. Another benefit of data mesh is the clarification of roles and responsibilities. In a traditional data architecture, data teams are responsible for managing all aspects of data, which can lead to confusion and ambiguity in responsibilities. With data mesh, domain experts are responsible for managing their own data, which can help provide clarity in roles and responsibilities and improve data quality. Additionally, data mesh can also contribute to a new form of organization that is more agile and adaptable. By decentralizing data ownership, organizations can respond more quickly to changes in their business environment, which in turn can help improve overall performance by allowing better insights into business as an effect of better reports and visualization tools. Monitoring and analytics are also important aspects of data quality. With data mesh, monitoring, and analytics are decentralized, allowing domain experts to monitor and analyze their own data. This will help in identifying and addressing data quality problems in quick time, leading to improved data quality. Data culture is another major aspect of data quality. With data mesh, domain experts are encouraged to take ownership of their data, which can help create a data-driven culture within the organization. This can lead to improved data quality and better business outcomes. Finally, the paper explores the contribution of AI in the coming years. AI can help enhance data quality by automating many data-related tasks, like data cleaning and data validation. By integrating AI into data mesh, organizations can further enhance the quality of their data. The concepts mentioned above are illustrated by AEKIDEN experience feedback. AEKIDEN is an international data-driven consultancy that has successfully implemented a data mesh approach. By sharing their experience, AEKIDEN can help other organizations understand the benefits and challenges of implementing data mesh and improving data quality.

Keywords: data culture, data-driven organization, data mesh, data quality for business success

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Authors: Ryan Kelvin Ford

Abstract:

For individuals and organizations, significant potential benefits were assured by sharing the data in a secure, trusted, and standardized environment. Technical trust and standards help each participant to use data space securely to share and access data. Sharing data in a safe environment helps acquire new business opportunities. Data sovereignty, interoperability, and trust were considered key factors to evaluate data spaces. Businesses and policymakers assure a fair data economy by integrating data space in organizations. A collaborative environment was needed to facilitate data sharing among organizations, satisfied with the implementation of different architectures using data spaces such as Eclipse Data Space Components (EDC), International Data Space Association (IDSA), Gaia-X, and Gaia-X Federation Services (GXFS). The last 15 years of application were reviewed and compared based on the architectures and implementations of different data spaces such as IDSA, EDC, Gaia-X and GXFS, EDC framework, IDSA, GXFS, data connector, data space architecture, characteristics of data space connectors, federated data spaces initiatives, data spaces overview, eclipse data space connector, designing data spaces, building data spaces based on technical overview, European future digital ecosystem based on Gaia-Vision and strategy of Gaia-Architecture. Empirical research based on an organized view was conducted. The current discussion elaborates on the systematic review of the impact of data space technology from various perspectives. The systematic review uses multiple databases such as IEEE Explore, Taylor & Francis, Science Direct, and Google Scholar to pursue publications on the impact of Data space from January 2019 to December 2024. The search results showcased a comparative review of 150 articles, out of which 20 were related to the IDSA, Gaia‑X, and EDC architecture and implementation.

Keywords: IDSA, Gaia-X, Gaia-X architecture, EDC, EDC architecture, GXFS architecture, IDSA, data space connector

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Authors: Zeinab Mirabulqasemi, Gholamali Hatam

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The article discusses the rich tradition of mural art in Gilan, Iran, particularly focusing on its religious and cultural significance, with a specific emphasis on tombs and Imamzadehs (descendants of imams). It examines the presence of animals and supernatural beings in these murals, such as horses, lions, birds, snakes, and angels, each carrying symbolic meanings within the religious narratives depicted. It discusses the multifaceted symbolism of these creatures and their portrayal in various scenes, enriching the narrative and conveying spiritual themes. Moreover, the article delves into the geographical and cultural context of the Gilan region, where many of these murals are found, and the challenges posed by environmental factors on their preservation. The article concludes by emphasizing the importance of preserving these artworks as valuable cultural heritage and calls for further research into their social, religious, and artistic dimensions. It utilizes a multifaceted research approach involving library research, image analysis, field investigations, and interviews with local inhabitants to gain a deeper understanding of the significance of these murals.

Keywords: cultural ritual, Shiite imams, mural, belief foundations, religious paintings

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Authors: C. M. Cebola, V. H. Ferreira

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In the past decade mediation has been legally implemented in European legal systems, especially after the publication by the European Union of the Directive 2008/52/EC on certain aspects of mediation in civil and mercantile matters. Developments in international trade and globalization in this new century have led to an increase of the number of litigations, often cross-border, and the courts have failed to respond adequately. We do not advocate that mediation should be promoted as the solution for all justice problems, but as a means with its own specificities that the parties may choose to consider as the best way to resolve their disputes. Thus, the implementation of mediation should be based on the advantages of its application. From the economic point of view, competitive negotiation can generate negative external effects in social terms. A solution reached in a court of law is not always the most efficient one considering all elements of society (economic social benefit). On the other hand, the administration of justice adds in economic terms transaction costs that can be mitigated by the application of other forms of conflict resolution, such as mediation. In this paper, the economic benefits of mediation will be analysed in the light of various studies on the functioning of justice. Several theoretical arguments will be confronted with empirical studies to demonstrate that mediation has significant positive economic effects. The objective is to contribute to the dissemination of mediation between companies and citizens, but also to demonstrate the cost to governments and states of still limited use of mediation, particularly in the current economic crisis and propose actions to develop the application of mediation.

Keywords: economic impact, litigation costs, mediation, solutions

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Authors: Abubakar Abdulkareem, Nasir Haruna Soba

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This study investigates the non-utilization of AI tools for research and academic writing among academic staff in Nigerian universities using the perceived attribute of innovation theory by Rogers as a theoretical framework to guide the investigation. This study was framed in an interpretative research paradigm. A qualitative methodology and case study research design was adopted. Interviews were conducted with 20 academic staff. The study used a thematic analysis process to identify 115 narratives. The narratives are organized into five major categories and further collapsed into five theoretical constructs explaining the non-use of AI tools for research and academic writing. Findings from this study revealed some of the reasons for the non-utilization of AI tools for research and academic writing as lack of Awareness, perceived Complexity, trust and Reliability Concerns, cost and accessibility, ethical and Privacy concerns and, cultural and institutional factors, etc.

Keywords: non-utilization, AI tools, research and academic writing, academic staff

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Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

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It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels, so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to exponential growth of computation, this paper also proposes a key data extraction method, that only extracts part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: data augmentation, mutex task generation, meta-learning, text classification.

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Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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Authors: Abdulfatah A Raji

Abstract:

This paper started with the definitions of literature, Arabic literature, transformation and went further to highlight the components of educational transformation. The general history of Arabic literature was discussed with focus on how it undergoes some transformations from pre-Islamic period through Quranic era, Abbasid literature to renaissance period in which the modernization of Arabic literature started in Egypt. It also traces the spread of Arabic literature in Nigeria from the pre-colonial era during the Kanuri rulers to Jihad of Usman Dan Fodio and the development of literature which manifested to the Teacher’s Colleges and Bayero University in Northern Nigeria. Also, the establishment of primary and post-primary schools by Muslim organizations in many cities and towns of the Western part of Nigeria. Literary criticism was also discussed in line with Arabic literature. Poetry work of eminent poets were cited to show its importance in line with educational transformation in Nigerian literature and lessons from the cited Arabic poetry works were also highlighted to include: motivation to behave well and to tolerate others, better spirits of interaction, love and co-existence among different sexes, religion etc. All these can help in developing a better educational transformation in Nigeria which can in turn help in how to conduct researches for national development. The paper recommended compulsory Arabic literature at all levels of the nations’ educational system as well as publication of Arabic books and journals to encourage peace in this era of conflicts and further transform Nigeria’s educational system for better.

Keywords: Arabic, literature, peace, development, Nigeria

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Authors: Paula Simões, Isabel Natário

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This paper reviews a number of theoretical aspects for implementing an explicit spatial perspective in econometrics for modelling non-continuous data, in general, and count data, in particular. It provides an overview of the several spatial econometric approaches that are available to model data that are collected with reference to location in space, from the classical spatial econometrics approaches to the recent developments on spatial econometrics to model count data, in a Bayesian hierarchical setting. Considerable attention is paid to the inferential framework, necessary for structural consistent spatial econometric count models, incorporating spatial lag autocorrelation, to the corresponding estimation and testing procedures for different assumptions, to the constrains and implications embedded in the various specifications in the literature. This review combines insights from the classical spatial econometrics literature as well as from hierarchical modeling and analysis of spatial data, in order to look for new possible directions on the processing of count data, in a spatial hierarchical Bayesian econometric context.

Keywords: spatial data analysis, spatial econometrics, Bayesian hierarchical models, count data

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Authors: A. Abyar, R. Khavarzadeh

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The most basic and important decision-making tool for industrial and service managers is understanding the market and customer behavior. In this regard, the Apriori algorithm, as one of the well-known machine learning methods, is used to identify customer preferences. On the other hand, with the increasing diversity of goods and services and the speed of changing customer behavior, we are faced with big data. Also, due to the large number of competitors and changing customer behavior, there is an urgent need for continuous analysis of this big data. While the speed of the Apriori algorithm decreases with increasing data volume. In this paper, the big data PCA method is used to reduce the dimension of the data in order to increase the speed of Apriori algorithm. Then, in the simulation section, the results are examined by generating data with different volumes and different diversity. The results show that when using this method, the speed of the a priori algorithm increases significantly.

Keywords: association rules, Apriori algorithm, big data, big data PCA, market basket analysis

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Authors: Gueidi Afef, Gharsellaoui Hamza, Ben Ahmed Samir

Abstract:

This paper deals with the secret of the continual progression data that new data management solutions have been emerged: The NoSQL databases. They crossed several areas like personalization, profile management, big data in real-time, content management, catalog, view of customers, mobile applications, internet of things, digital communication and fraud detection. Nowadays, these database management systems are increasing. These systems store data very well and with the trend of big data, a new challenge’s store demands new structures and methods for managing enterprise data. The new intelligent machine in the e-learning sector, thrives on more data, so smart machines can learn more and faster. The robotics are our use case to focus on our test. The implementation of NoSQL for Robotics wrestle all the data they acquire into usable form because with the ordinary type of robotics; we are facing very big limits to manage and find the exact information in real-time. Our original proposed approach was demonstrated by experimental studies and running example used as a use case.

Keywords: NoSQL databases, database management systems, robotics, big data

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Authors: Tonderai Muchenje, Mkhatshwa Phethile

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Humans living in this current situation know that communication with one another is necessary for themselves. There are many ways to communicate with each other; during unexpected natural disasters and outbreak of epidemics and pandemics, the need for online meeting platforms are considered most important. Apparently, the development in the telecommunication sector also played an important role. Therefore, the epidemic of the Covid-19 Pandemic and the new normal situation resulted in the overwhelming production of online meeting platforms to prevent the situation. This software is commonly used in business communications in the beginning. Rapidly the COVID-19 pandemic changed the situation. At present-day, these virtual meeting applications are not only used to have informal meetings with friends and relatives but also to be used to have formal meetings in the business and education (universities) sector. In this article, an attempt has been made to list out the useful secured ways for using online meeting platforms.

Keywords: virtual background, zoom, secure online algorithm, RingCentral, Pexip Pexip, TeamViewer, microsoft teams

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Authors: C. B. Le, V. N. Pham

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In modern data analysis, multi-source data appears more and more in real applications. Multi-source data clustering has emerged as a important issue in the data mining and machine learning community. Different data sources provide information about different data. Therefore, multi-source data linking is essential to improve clustering performance. However, in practice multi-source data is often heterogeneous, uncertain, and large. This issue is considered a major challenge from multi-source data. Ensemble is a versatile machine learning model in which learning techniques can work in parallel, with big data. Clustering ensemble has been shown to outperform any standard clustering algorithm in terms of accuracy and robustness. However, most of the traditional clustering ensemble approaches are based on single-objective function and single-source data. This paper proposes a new clustering ensemble method for multi-source data analysis. The fuzzy optimized multi-objective clustering ensemble method is called FOMOCE. Firstly, a clustering ensemble mathematical model based on the structure of multi-objective clustering function, multi-source data, and dark knowledge is introduced. Then, rules for extracting dark knowledge from the input data, clustering algorithms, and base clusterings are designed and applied. Finally, a clustering ensemble algorithm is proposed for multi-source data analysis. The experiments were performed on the standard sample data set. The experimental results demonstrate the superior performance of the FOMOCE method compared to the existing clustering ensemble methods and multi-source clustering methods.

Keywords: clustering ensemble, multi-source, multi-objective, fuzzy clustering

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Authors: Shahryar Eslamitabar

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Currently, the internet plays an important role in the various scientific, commercial and service practices. Thanks to information and communication technology, the healthcare industry via the internet, generally known as cyber-medicine, can offer professional medical service in a wider geographical area. Having some appealing benefits such as convenience in offering healthcare services, improved accessibility to the services, enhanced information exchange, cost-effectiveness, time-saving, etc. Tele-health has increasingly developed innovative models of healthcare delivery. However, it presents many potential hazards to cyber-patients, inherent in the use of the system. First, there are legal issues associated with the communication and transfer of information on the internet. These include licensure, malpractice, liabilities and jurisdictions as well as privacy, confidentiality and security of personal data as the most important challenge brought about by this system. Additional items of concern are technological and ethical. Although, there are some rules to deal with pitfalls associated with cyber-medicine practices in the USA and some European countries, yet for all developments, it is being practiced in a legal vacuum in many countries. In addition to the domestic legislations to deal with potential problems arisen from the system, it is also imperative that some international or regional agreement should be developed to achieve the harmonization of laws among countries and states. This article discusses some implications posed by the practice of cyber-medicine in the healthcare system according to the experience of some developed countries using a comparative study of laws. It will also review the status of tele-health laws in Iran. Finally, it is intended to pave the way to outline a plan for countries like Iran, with newly-established judicial system for health laws, to develop appropriate regulations through providing some recommendations.

Keywords: tele-health, cyber-medicine, telemedicine, criminal laws, legislations, time-saving

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Authors: Eui-Jin Kim, Hasik Lee, Su-Jin Park, Dong-Kyu Kim

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Smart-card data are expected to provide information on activity pattern as an alternative to conventional person trip surveys. The focus of this study is to propose a method for training the person trip surveys to supplement the smart-card data that does not contain the purpose of each trip. We selected only available features from smart card data such as spatiotemporal information on the trip and geographic information system (GIS) data near the stations to train the survey data. XGboost, which is state-of-the-art tree-based ensemble classifier, was used to train data from multiple sources. This classifier uses a more regularized model formalization to control the over-fitting and show very fast execution time with well-performance. The validation results showed that proposed method efficiently estimated the trip purpose. GIS data of station and duration of stay at the destination were significant features in modeling trip purpose.

Keywords: activity pattern, data fusion, smart-card, XGboost

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Authors: Stefano Fantin

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The present analysis outcomes from the research undertaken in the course of the European-funded project EUNITY, which targets the gaps in research and development on cybersecurity and privacy between Europe and Japan. Under these auspices, the research presents a study on the policy approach of Japan, the EU and a number of Member States of the Union with regard to the handling and discovery of software vulnerabilities, with the aim of identifying methodological differences and similarities. This research builds upon a functional comparative analysis of both public policies and legal instruments from the identified jurisdictions. The result of this analysis is based on semi-structured interviews with EUNITY partners, as well as by the participation of the researcher to a recent report from the Center for EU Policy Study on software vulnerability. The European Union presents a rather fragmented legal framework on software vulnerabilities. The presence of a number of different legislations at the EU level (including Network and Information Security Directive, Critical Infrastructure Directive, Directive on the Attacks at Information Systems and the Proposal for a Cybersecurity Act) with no clear focus on such a subject makes it difficult for both national governments and end-users (software owners, researchers and private citizens) to gain a clear understanding of the Union’s approach. Additionally, the current data protection reform package (general data protection regulation), seems to create legal uncertainty around security research. To date, at the member states level, a few efforts towards transparent practices have been made, namely by the Netherlands, France, and Latvia. This research will explain what policy approach such countries have taken. Japan has started implementing a coordinated vulnerability disclosure policy in 2004. To date, two amendments can be registered on the framework (2014 and 2017). The framework is furthermore complemented by a series of instruments allowing researchers to disclose responsibly any new discovery. However, the policy has started to lose its efficiency due to a significant increase in reports made to the authority in charge. To conclude, the research conducted reveals two asymmetric policy approaches, time-wise and content-wise. The analysis therein will, therefore, conclude with a series of policy recommendations based on the lessons learned from both regions, towards a common approach to the security of European and Japanese markets, industries and citizens.

Keywords: cybersecurity, vulnerability, European Union, Japan

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Authors: D. Baranova, E. Neborak

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Polyphenols, particularly flavonoids like quercetin, fisetin, and kaempferol, have gained significant attention in nutrition due to their antioxidant, senolytic, and anti-inflammatory properties. These compounds are commonly found in various plant-based foods and are represented by diverse subclasses, each with unique health benefits. Understanding their absorption, metabolism, and bioactivity within the human body is crucial for unlocking their full potential. Quercetin, for instance, exists in multiple forms, impacting its solubility and absorption in the intestine. Its intake, often derived from sources like apples, is affected by cooking methods, with medium heat retaining its potency. Fisetin, also present in fruits and vegetables, demonstrates neuroprotective qualities and stability under varied conditions compared to quercetin. Similarly, kaempferol, found in fruits and vegetables, displays antioxidative effects but is influenced by cooking techniques, with specific methods preserving its polyphenolic content better. Overall, these polyphenols offer promising health benefits, yet their optimal dosage and specific dietary recommendations warrant further research to harness their full nutritional potential.

Keywords: polyphenols, flavonoids, absorption, quercetin, kaempferol, fisetin, senolytics, absorption, cooking method

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Authors: Haojie Wang, Xun Li, Rui Yin

Abstract:

In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Ibrahim Alsendid, Rob Sturman, Benjamin Sharp

Abstract:

In this paper, we consider a family of 2-dimensional nonlinear area-preserving transformations on the torus. A single parameter η varies between 0 and 1, taking the transformation from a hyperbolic toral automorphism to the “Cerbelli-Giona” map, a system known to exhibit multifractal properties. Here we study the multifractal properties of the family of maps. We apply a box-counting method by defining a grid of boxes Bi(δ), where i is the index and δ is the size of the boxes, to quantify the distribution of stable and unstable manifolds of the map. When the parameter is in the range 0.51< η <0.58 and 0.68< η <1 the map is ergodic; i.e., the unstable and stable manifolds eventually cover the whole torus, although not in a uniform distribution. For accurate numerical results, we require correspondingly accurate construction of the stable and unstable manifolds. Here we use the piecewise linearity of the map to achieve this, by computing the endpoints of line segments that define the global stable and unstable manifolds. This allows the generalized fractal dimension Dq, and spectrum of dimensions f(α), to be computed with accuracy. Finally, the intersection of the unstable and stable manifold of the map will be investigated and compared with the distribution of periodic points of the system.

Keywords: Discrete-time dynamical systems, Fractal geometry, Multifractal behaviour of the Perturbed map, Multifractal of Dynamical systems

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Authors: Chi-Hsuan Cheng

Abstract:

This research aims to evaluate public-private partnerships against cyberattacks by comparing the UK and Taiwan. First, the study analyses major cyberattacks and factors influencing cybersecurity in both countries. Second, it assesses the effectiveness of current cyber defence strategies in combating cyberattacks by comparing the approaches taken in the UK and Taiwan, while also evaluating the cyber resilience of both nations. Lastly, the research evaluates existing public-private partnerships by comparing those in the UK and Taiwan, and proposes recommendations for enhancing cooperation and collaboration mechanisms in tackling cyberattacks. Grounded theory serves as the core research method. Theoretical sampling is used to recruit participants in both the UK and Taiwan, including investigators, police officers, and professionals from cybersecurity firms. Semi-structured interviews are conducted in English in the UK and Mandarin in Taiwan, recorded with consent, and pseudonymised for privacy. Data analysis involves open coding, grouping excerpts into codes, and categorising codes. Axial coding connects codes into categories, leading to the development of a codebook. The process continues iteratively until theoretical saturation is reached. Finally, selective coding identifies the core topic, evaluating public-private cooperation against cyberattacks and its implications for social and policing strategies in the UK and Taiwan, which highlights the current status of the cybersecurity industry, governmental plans for cybersecurity, and contributions to cybersecurity from both government sectors and cybersecurity firms, with a particular focus on public-private partnerships. In summary, this research aims to offer practical recommendations to law enforcement, private sectors, and academia for reflecting on current strategies and tailoring future approaches in cybersecurity

Keywords: cybersecurity, cybercrime, public private partnerships, cyberattack

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Authors: Olurankinse Felix

Abstract:

Local governments in Ondo State Nigeria are the third tier of government saddled with the responsibility of providing governance and economic services at the grassroots. To be able to do this, the Constitution of the Federal Republic of Nigeria provided that a proportion of Federation Account be allocated to them in addition to their internally generated revenue. From the allocation and other incidental sources of revenue, the local governments are expected to provide basic infrastructures and other social amenities to better the lots of the rural dwellers. Nevertheless, local governments’ performances in terms of provision of social amenities are without questioning and quite not encouraging. Assessing the performance of local governments in this period of dearth and scarcity of resources is highly indispensable more so that the activities of local governments’ staff are bedeviled and characterized with fraud, corruption and mismanagement. Considering the direct impact of the consequences of their action on the living standard of the rural dwellers therefore calls for the need to evaluate their level of performances using capital budgeting approach. The paper being a time series study adopts the survey design. Data were obtained through secondary source mainly from the Annual financial statements and publication of approved budgets estimates covering the period of study (2008-2012). The use of ratio analysis was employed in analyzing the comparative level of performances of the local governments under study. The result of the study shows that less than 30% of the local governments were able to harness the budgetary allocation to provide amenities to the beneficiaries while majority of the local governments were involved in unethical conduct ranging from theft of fund, corruption, diversion of funds and extra-budgetary activities. Also, there is poor internally generated revenue to complement the statutory allocation and besides, the monthly withholding of larger portions of local government share by the state in the name of joint account were also seen as contributory factors. The study recommends the need for transparency and accountability in public fund management through the oversight function of the state house of assembly. Also local government should be made to be autonomous and independent of the state by jettisoning the idea of joint account.

Keywords: performance, transparency and accountability, capital budgeting, joint account, local government autonomy

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