bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Malicious Spatial-Domain Steganography Over Noisy Channels
Authors: Shankar Prasad Swaroop , Hadar Ofer , Polian Ilia
Published: May 2021

Steganographic channels can be abused for malicious purposes, thus raising the need to detect malicious embedded steganographic information (steganalysis). This chapter will cover the little-studied problem of steganography and steganalysis over a noisy channel, providing a detailed modeling for the special case of spatial-domain image steganography. It will approach these issues from both a theoretical and a practical point of view. After a description of spatial-domain image steganography, the impact of Gaussian noise and packet loss on the steganographic channel will be discussed. Characterization of the substitution-insertion-deletion (SID) channel parameters will be performed through experiments on a large number of images from the ALASKA database. Finally, a steganalysis technique for error-affected spatial-domain image steganography using a convolutional neural network (CNN) will be introduced, studying the relationship between different types and levels of distortions and the accuracy of malicious image detection.
Secure Text Extraction From Complex Degraded Images by Applying Steganography and Deep Learning
Authors: Pandey Binay Kumar , Mane Deepak , Nassa Vinay Kumar Kumar , Pandey Digvijay , Dutta Shawni , Ventayen Randy Joy Magno , Agarwal Gaurav , Rastogi Rahul
Published: May 2021

This work's primary goal is to secure the transmission of text hidden within the cover image using steganography over a public network of computers. Steganography is a powerful tool for concealing information within a cover image so that the concealed message remains undetectable. As a result, steganography refers to concealed writing. The secure transmission of information over a public network communication channel using steganography occurs in two stages, the first on the sender side and the second on the receiver side. In the first phase, steganography is normally applied to conceal the encrypted information within the image as a cover. The encrypted data is implanted inside the cover image using an improved least significant bit steganography method. The secret key obtained by the embedding algorithm is shared with the message retrieval algorithm on the receiver side to retrieve the message. Finally, the embedded text message is identified using a hybrid convolution regression adaptive integrated neural network (CRAINN) approach.
An Integration of Keyless Encryption, Steganography, and Artificial Intelligence for the Secure Transmission of Stego Images
Authors: Pandey Digvijay , Nassa Vinay Kumar , Jhamb Ayushi , Mahto Dashrath , Pandey Binay Kumar , George A. S. Hovan , George A. Shaji , Bandyopadhyay Samir Kumar
Published: May 2021

Protected stored data as well as transfer in this virtual environment have been a significant thing since this world wide web has been used for information exchange. The need for data security rises as the level of personal data exchanged on the web is becoming more susceptible. To protect information from malicious use as well as alteration, services like confidential information but also data integrity have been needed. So many traditional cryptographic methods have been proposed by numerous studies throughout recent times to maintain multimedia data communicated over public networks. The chapter proposes a novel keyless picture encryption algorithm focused on a chaotic map. Almost every picture element is encoded by shuffling pixel values, which would be measured by an adapted cat map. In this suggested technique, steganography is used to transfer keyless encrypted information using a cover picture with encrypted information inserted in picture, audio, and video files.
Impact of the Evolution of Smart Phones in Education Technology?
Authors: Al-Jenaibi Badreya Nasser , Almansoori Alyazi
Published: May 2021

In this chapter, the researchers investigate the different effects of smartphones on the youth of the United Arab Emirates through an integrated questionnaire among 12 doctors that were randomly sampled and selected about the smartphone use of the youth in the country. Through a qualitative research design by using structured questionnaires, the researcher found out that smartphone usage affects the youth in UAE both in a positive and negative way. Despite the developments posited in the adoption of smart phones including data-driven solutions and education, the smart phones have been related to negative impacts on mental health and physical connection through the youth in the society. Moreover, smartphone usage may lead to negative health issues among the youth including obesity. Additionally, parents present a fear of extreme exposure and cultural deterioration in the presence of these phones. Also, it was concluded that parents should play a role in limiting the number of hours that youth should use their smartphones to a maximum of 3 hours a day.
A Comprehensive Review of Mobile Technology-Assisted English Learning
Authors: Yu Liheng , Yu (于) Zhonggen (中根)
Published: May 2021

Mobile English language learning has drawn global attention. This study systematically examined the literature in the past 11 years. It visualized the general trend of the number of related publications in a decade, discussed the attitudes of teachers and learners toward mobile device-assisted English learning, explored the effect of motivation on mobile device assisted English learning, discussed the influence of mobile device-assisted English learning on output and input English language skills, presented the influence of mobile device-assisted English learning on vocabulary knowledge acquisition, demonstrated the factors influencing the effectiveness of mobile English language learning, showed the general learning outcomes in mobile device-assisted English learning, together with the disadvantages of mobile technology-assisted English learning and co-citations of publications. When designing mobile devices, designers could include and optimize learning functions based on the findings.
Development of Transferable Knowledge
Authors: Chisita Collence T. , Enakrire Rexwhite Tega , Muziringa Masimba C. , Chikonzo Agnes
Published: May 2021

Zimbabwe has adopted Education 5.0 which is an educational transformation typified by five missions of Teaching, Community Outreach, Research, Innovation and Industrialization. The Education 5.0 seeks to produce relevant and cost effective knowledge products that results in the production of new goods and services towards the modernization and industrialization of Zimbabwe. Electronic Thesis and Dissertations (ETDs) are at the core of knowledge production by universities in Zimbabwe. ETD's are important data sets for research and development and are critical in the knowledge creation and production that must lead to innovation and industrialization driven by academic institutions. The management of e-scholarship underpins the success of academic institutions to cause the industrialization and modernization of Zimbabwe under the new transformation. The chapter explores the opportunities in managing ETDs in Zimbabwe. The chapter explored how ETD's are transforming scholarly communication landscape through knowledge creation and sharing for industrialization and modernization. The chapter highlights new transformation by academic institutions in creating and developing ETD's to be linked with innovation hubs. Furthermore, the chapter explored the extent to which academic libraries are grappling with the emerging genres of ETD's for example the use of linked data to enhance discoverability. The chapter suggested strategies to enhance the ETD's culture.
The Unheard Story of Organizational Motivations Towards User Privacy
Authors: Senarath Awanthika , Arachchilage Nalin Asanka Gamagedara
Published: May 2021

There could be numerous reasons that drive organizations to provide privacy protections to end users in the applications they develop and maintain. Organizational motivations towards privacy affects the quality of privacy received by end users. Understanding these motivations and the approaches taken by organizations towards privacy protection would assist the policymakers and regulators to define effective frameworks encouraging organizational privacy practices. This study focuses on understanding the motivations behind organizational decisions and the approaches they take to embed privacy into the software applications. The authors analyzed 40 organizations different in size, scope, scale of operation, nature of data used, and revenue. they identified four groups of organizations characterized by the approach taken to provide privacy protection to their users. The taxonomy contributes to the organizational perspective of privacy. The knowledge presented here would help addressing the challenges in the domain of user privacy in software applications and services.
A Secure Protocol for High-Dimensional Big Data Providing Data Privacy
Authors: Anitha J.  , Prasad S. P.
Published: May 2021

Due to recent technological development, a huge amount of data generated by social networking, sensor networks, internet, etc., adds more challenges when performing data storage and processing tasks. During PPDP, the collected data may contain sensitive information about the data owner. Directly releasing this for further processing may violate the privacy of the data owner, hence data modification is needed so that it does not disclose any personal information. The existing techniques of data anonymization have a fixed scheme with a small number of dimensions. There are various types of attacks on the privacy of data like linkage attack, homogeneity attack, and background knowledge attack. To provide an effective technique in big data to maintain data privacy and prevent linkage attacks, this paper proposes a privacy preserving protocol, UNION, for a multi-party data provider. Experiments show that this technique provides a better data utility to handle high dimensional data, and scalability with respect to the data size compared with existing anonymization techniques.
A Privacy-Preserving Feature Extraction Method for Big Data Analytics Based on Data-Independent Reusable Projection
Authors: Ravindran Siddharth , G. Aghila
Published: May 2021

Big data analytics is one of the key research areas ever since the advancement of internet technologies, social media, mobile networks, and internet of things (IoT). The volume of big data creates a major challenge to the data scientist while interpreting the information from raw data. The privacy of user data is an important issue faced by the users who utilize the computing resources from third party (i.e., cloud environment). This chapter proposed a data independent reusable projection (DIRP) technique for reducing the dimension of the original high dimensional data and also preserves the privacy of the data in analysis phase. The proposed method projects the high dimensional input data into the random low dimensional space. The data independent and distance preserving property helps the proposed method to reduce the computational complexity of the machine learning algorithm. The randomness of data masks the original input data which helps to solve the privacy issue during data analysis. The proposed algorithm has been tested with the MNIST hand written digit recognition dataset.
Privacy Preserving Classification of Biomedical Data With Secure Removing of Duplicate Records
Authors: Tarik Boudheb , Zakaria Elberrichi
Published: May 2021

Classifying data is to automatically assign predefined classes to data. It is one of the main applications of data mining. Having complete access to all data is critical for building accurate models. Data can be highly sensitive, such as biomedical data, which cannot be disclosed or shared with third party, because it can harm individuals and organizations. The challenge is how to preserve privacy and usefulness of data. Privacy preserving classification addresses this problem. Collaborative models are constructed over networks without violating the data owners' privacy. In this article, the authors address two problems: privacy records deduplication of the same records and privacy-preserving classification. They propose a randomized hash technic for deduplication and an enhanced privacy preserving classification of biomedical data over horizontally distributed data based on two homomorphic encryptions. No private, intermediate or final results are disclosed. Experimentations show that their solution is efficient and secure without loss of accuracy.
Evaluation of Reliable Data Storage in Cloud Using an Efficient Encryption Technique
Authors: Sarkar Saswati , Kundu Anirban , Banerjee Ayan
Published: May 2021

Cloud-based reliable and protected data storage technique is proposed in this chapter. The proposed technique encrypts and protects data with less time consumption. Power consumption of storage is dependent upon capacity of storage and physical size of storage. Time analysis is presented graphically in this chapter. Reliable data storage is represented in cloud based proposed approach. Data is encrypted with minimum time complexity due to usage of proposed cloud-based reliable data storage. The competent ratio of time complexity is graphically observed in proposed data storage technique. Power consumption of storage has been typically dependent on the basis of capacity of storage and amount of storage. A ratio of power consumption and capacity of storage is presented in cloud-based approach. An efficient usage of energy is shown depending on current consumption and voltage in proposed reliable approach.
Data Backup and Recovery With a Minimum Replica Plan in a Multi-Cloud Environment
Authors: Alshammari Mohammad M. , Alwan Ali A. , Nordin Azlin , Abualkishik Abedallah Zaid
Published: May 2021

Cloud computing has become a desirable choice to store and share large amounts of data among several users. The two main concerns with cloud storage are data recovery and cost of storage. This article discusses the issue of data recovery in case of a disaster in a multi-cloud environment. This research proposes a preventive approach for data backup and recovery aiming at minimizing the number of replicas and ensuring high data reliability during disasters. This approach named Preventive Disaster Recovery Plan with Minimum Replica (PDRPMR) aims at reducing the number of replications in the cloud without compromising the data reliability. PDRPMR means preventive action checking of the availability of replicas and monitoring of denial of service attacks to maintain data reliability. Several experiments were conducted to evaluate the effectiveness of PDRPMR and the results demonstrated that the storage space used one-third to two-thirds compared to typical 3-replicas replication strategies.
Misuse of ‘Break-the-Glass' Policies in Hospitals
Authors: Stark Benjamin , Gewald Heiko , Lautenbacher Heinrich , Haase Ulrich , Ruff Siegmar
Published: May 2021

This article describes how the information about an individual's personal health is among ones most sensitive and important intangible belongings. When health information is misused, serious non-revertible damage can be caused, e.g. through making intimidating details public or leaking it to employers, insurances etc. Therefore, health information needs to be treated with the highest degree of confidentiality. In practice it proves difficult to achieve this goal. In a hospital setting medical staff across departments often needs to access patient data without directly obvious reasons, which makes it difficult to distinguish legitimate from illegitimate access. This article provides a mechanism to classify transactions at a large university medical center into plausible and questionable data access using a real-life data set of more than 60,000 transactions. The classification mechanism works with minimal data requirements and unsupervised data sets. The results were evaluated through manual cross-checks internally and by a group of external experts. Consequently, the hospital's data protection officer is now able to focus on analyzing questionable transactions instead of checking random samples.
Security and Privacy Challenges of Deep Learning
Authors: Onesimu J. Andrew , J. Karthikeyan , Viswas D. Samuel Joshua , Sebastian Robin D
Published: May 2021

Deep learning is the buzz word in recent times in the research field due to its various advantages in the fields of healthcare, medicine, automobiles, etc. A huge amount of data is required for deep learning to achieve better accuracy; thus, it is important to protect the data from security and privacy breaches. In this chapter, a comprehensive survey of security and privacy challenges in deep learning is presented. The security attacks such as poisoning attacks, evasion attacks, and black-box attacks are explored with its prevention and defence techniques. A comparative analysis is done on various techniques to prevent the data from such security attacks. Privacy is another major challenge in deep learning. In this chapter, the authors presented an in-depth survey on various privacy-preserving techniques for deep learning such as differential privacy, homomorphic encryption, secret sharing, and secure multi-party computation. A detailed comparison table to compare the various privacy-preserving techniques and approaches is also presented.
An Efficient Privacy-preserving Approach for Secure Verifiable Outsourced Computing on Untrusted Platforms
Authors: Olakanmi Oladayo Olufemi , Dada Adedamola
Published: May 2021

In outsourcing computation models, weak devices (clients) increasingly rely on remote servers (workers) for data storage and computations. However, most of these servers are hackable or untrustworthy, which makes their computation questionable. Therefore, there is need for clients to validate the correctness of the results of their outsourced computations and ensure that servers learn nothing about their clients other than the outputs of their computation. In this work, an efficient privacy preservation validation approach is developed which allows clients to store and outsource their computations to servers in a semi-honest model such that servers' computational results could be validated by clients without re-computing the computation. This article employs a morphism approach for the client to efficiently perform the proof of correctness of its outsourced computation without re-computing the whole computation. A traceable pseudonym is employed by clients to enforce anonymity.
Big Data and the Internet of Things
Authors: Pingo Zablon , Narayan Bhuva
Published: May 2021

The privacy construct is an important aspect of internet of things (IoT) technologies as it is projected that over 20 billion IoT devices will be in use by 2022. Among other things, IoT produces big data and many industries are leveraging this data for predictive analytics to aid decision making in health, education, business, and other areas. Despite benefits in some areas, privacy issues have persisted in relation to the use of the data produced by many consumer products. The practices surrounding IoT and Big Data by service providers and third parties are associated with a negative impact to individuals. To protect consumers' privacy, a wide range of approaches to informational privacy protections exist. However, individuals are increasingly required to actively respond to control and manage their informational privacy rather than rely on any protection mechanisms. This chapter highlights privacy issues across consumers' use of IoT and identifies existing responses to enhance privacy awareness as a way of enabling IoT users to protect their privacy.
Achieving Cloud Security Using a Third Party Auditor and Preserving Privacy for Shared Data Over a Public Cloud
Authors: Gutte Vitthal Sadashiv , Devulapalli Sita
Published: May 2021

Correctness of data and efficient mechanisms for data security, while transferring the file to and from Cloud, are of paramount importance in today's cloud-centric processing. A mechanism for correctness and efficient transfer of data is proposed in this article. While processing users request data, a set of attributes are defined and checked. States with attributes at different levels are defined to prevent unauthorized access. Security is provided while storing the data using a chunk generation algorithm and verification of chunks using lightweight Third-Party Auditor (TPA). TPA uses digital signatures to verify user's data that are generated by RSA with MD5 algorithms. The metadata file of generated chunks is encrypted using a modified AES algorithm. The proposed method prevents unauthorized users from accessing the data in the cloud environment, in addition to maintaining data integrity. Results of the proposed cloud security model implementation are discussed.
Consumer Value Trumps Perceived Privacy Risk
Authors: Kukard Wesley A. , Wood Lincoln C.
Published: May 2021

This chapter reviews past radio frequency identification (RFID) literature within the fast-moving consumer goods (FMCG) industry and the impact of consumer benefits on the perceived risks of item-level RFID. Two new categories are used to measure this impact; the separation of consumers' interactions with the technology to in-store and after-sales allows the consumers expectation of privacy to changes depending on the surrounding environment. A quantitative survey on primary household grocery purchasers within the USA revealed that while consumers are aware of the associated privacy risks after sale, they would be willing to use the technology, given sufficient benefits. This important step in RFID literature changes the conversation from a privacy risk management focus to a balanced integration of the technology, focusing on consumer benefits to manage the roll-out within the FMCG industry.
Ambiguities in the Privacy Policies of Common Health and Fitness Apps
Authors: Sen Devjani , Ahmed Rukhsana
Published: May 2021

With a growing number of health and wellness applications (apps), there is a need to explore exactly what third parties can legally do with personal data. Following a review of the online privacy policies of a select set of mobile health and fitness apps, this chapter assessed the privacy policies of four popular health and fitness apps, using a checklist that comprised five privacy risk categories. Privacy risks, were based on two questions: a) is important information missing to make informed decisions about the use of personal data? and b) is information being shared that might compromise the end-user's right to privacy of that information? The online privacy policies of each selected app was further examined to identify important privacy risks. From this, a separate checklist was completed and compared to reach an agreement of the presence or absence of each privacy risk category. This chapter concludes with a set of recommendations when designing privacy policies for the sharing of personal information collected from health and fitness apps.
Erosion by Standardisation
Authors: Christofi Athena , Dewitte Pierre , Ducuing Charlotte , Valcke Peggy
Published: May 2021

This chapter examines the interplay between the GDPR and parallel private regulation in the form of privacy-related standards adopted by the International Organisation for Standardisation (ISO). Focusing on the understanding of ‘risks' in the GDPR and ISO respective ecosystems, it compares the GDPR requirement for Data Protection Impact Assessments (DPIAs) with ISO/IEC 29134:2017, a private standard on Privacy Impact Assessment explicitly referred to by EU Data Protection Authorities as relevant in the context of DPIA methods. The resulting gap analysis identifies and maps misalignments, critically reflecting on whether the parallel form of ISO regulation, in the context of DPIAs, could support or rather blurs GDPR's objective to protect fundamental rights by embracing a risks-based approach.
Critical Cybersecurity Threats
Authors: Al-Alawi Adel Ismail , Al-Bassam Sara Abdulrahman , Mehrotra Arpita A.
Published: May 2021

One common reason for cybercrime is the goal of damaging a business by hacking or destroying important information. Another such reason is the criminal's goal of gaining financially from the hack. This chapter analyzes Bahraini organizations' vulnerability to digital security threats. It has used qualitative research to analyze industry performance. Moreover, with the support of secondary research, it has also explored cybersecurity threats faced by such organizations. The discussion based on secondary data analysis has explored two major aspects of Bahraini organizations and the cybersecurity threats they face. Firstly, the data and finances of both sectors are at huge risk in Bahraini organizations. Secondly, one important aspect of exploration has been to identify the most frequently encountered forms of cybercrime. Its analysis reveals that the kind of cybersecurity threat that a business is most likely to face is cyberwarfare. This may affect two rival businesses while they are competing with each other. Competitors' data may be destroyed or hacked—leading to long-term losses.
Embracing Cybersecurity Risk Management in the Industry of Medical Devices
Authors: Lam Maria Lai-Ling , Wong Kei Wing
Published: May 2021

The promises of Industry 4.0 in the medical device industry needs to be built on sound cybersecurity infrastructures, polices, and practices. During 2011-2017, the authors interviewed many manufacturers of medical devices in China, Germany, Israel, Japan, Taiwan, and U.S. about their attitude towards cybersecurity. Many manufacturers are not committed to cybersecurity risk management because they pursue lower cost and shorter product life cycles; do not have sufficient knowledge of operating environments of hospitals; have defensive attitude toward vulnerability disclosure; and reap quick benefits from the low-trust level among stakeholders and unequal power between manufacturers and distributors. Only a few large U.S. manufacturers of medical devices have set up robust secure platforms and interoperable optimal standards which benefit the users. As cybersecurity is a shared responsibility, many small and medium-sized enterprises need to be empowered through the support of international organizations and local government policies.
Investigating E-Wallet Adoption in India
Authors: Singh Surabhi , Ghatak Sanchita
Published: May 2021

This study aims to investigate the customer adoption of e-wallets in India. The paper further seeks to explore the significant relationships amongst the constructs of TAM in explaining consumer intention to use the digital wallet. The present study employs an extended TAM framework. The variables of the study are risk, cost, compatibility, usefulness, ease of use, behavioral intention to use, actual usage, etc. for exploring digital wallet usage intentions in Indian consumers. The sample considered was North Indian customers to understand their plan to use a mobile wallet. A standardized scale was used for the present study. The data was collected using a questionnaire with variables of external factors, perception, preference, and usage. Structured equation modeling has been was used to check the model fit of the proposed model, and path analysis revealed the correlations between the endogenous and exogenous variables of the study.
A Descriptive 3D City Information Model Built From Infrastructure BIM
Authors: Pereira Augusto Pimentel , Buzzo Marcio , Zimermann Ingrid , Neto Frederico Huckembeck , Malgarezi Hellisson
Published: May 2021

This study developed a descriptive 3D city information model (CIM) using only infrastructural building modeling tools to create maps and analyzed the model according to needs identified in interviews with public-sector actors and a bibliometric analysis. The interviews assessed the challenges of implementing CIM in the Brazilian city of Curitiba, while the literature study determined that current academic production reflects the current reality, calling attention to relevant issues. The experimental software solution successfully created 3D informational modeling of cities for passive use as well as maps to support decision making, although it did not offer advanced parametric tools for urban analysis. Still, this model provides a flexible approach to overcoming the challenges reported by interviewees, which included financial limitations and organizational culture.
A Hybrid Approach to Identify Code Smell Using Machine Learning Algorithms
Authors: Patnaik Archana , Padhy Neelamdhab
Published: May 2021

Code smell aims to identify bugs that occurred during software development. It is the task of identifying design problems. The significant causes of code smell are complexity in code, violation of programming rules, low modelling, and lack of unit-level testing by the developer. Different open source systems like JEdit, Eclipse, and ArgoUML are evaluated in this work. After collecting the data, the best features are selected using recursive feature elimination (RFE). In this paper, the authors have used different anomaly detection algorithms for efficient recognition of dirty code. The average accuracy value of k-means, GMM, autoencoder, PCA, and Bayesian networks is 98%, 94%, 96%, 89%, and 93%. The k-means clustering algorithm is the most suitable algorithm for code detection. Experimentally, the authors proved that ArgoUML project is having better performance as compared to Eclipse and JEdit projects.
Quantitative Software Change Prediction in Open Source Web Projects Using Time Series Forecasting
Authors: Rhmann Wasiur
Published: May 2021

Software change prediction (SCP) is used for the prediction of changes earlier in the software development life cycle. It identifies the files that are change prone. Software maintenance costs can be reduced with the help of accurate prediction of change-prone files. Most of the literature of SCP deals with the identification of a class as change prone or not change prone. In the present work, the amount of change in a web project in terms of line of code added (loc_added), line of code deleted (loc_deleted), and lines of code (LOC) are predicted using time series forecasting method of machine learning. Data of web projects is obtained from GIT repository using Pydriller Python package extractor. The obtained result showed that support vector machine (SVM) is good for prediction of loc_added and loc_removed while the random forest is good for the prediction of LOC. Results advocate the use machine learning techniques for forecasting changes amount in web projects.
Co-Shaping Smart Cities
Authors: Baccarne Bastiaan , De Marez Lieven
Published: May 2021

This paper studies participation divides on civic crowdsourcing platforms in a smart city context, hybrid applications of distributed urban innovation management, and new modes of digital citizenship, often applied to co-shape future urban environments. However, the emergence of new participatory instruments also brings new digital inequalities, as their adoption is not distributed equally. Hence, from an explicitly interdisciplinary perspective, this article explores the role of civic engagement, digital inequalities, and opinion leadership in understanding differences in participatory behavior on such platforms. Using a regression model (N = 178), this study shows that participation differences on civic crowdsourcing platforms are explained by opinion leadership and political engagement, but not by community engagement, traditional digital inequalities. This reveals that such platforms are used most by those who were already participating and have high levels of expertise, which sheds a light on the potential empowerment of such platforms and its democratic implications.
Exploring Factors Determining Chinese College Students' Satisfaction With E-Government Services
Authors: Mensah Isaac Kofi , Luo Chuanyong
Published: May 2021

This study explored the factors determining students' satisfaction with electronic government services. The population of the study was 411 college students in Ganzhou City, Jiangxi Province, China. The technology acceptance model (TAM) was used as the research model and structural equation modeling (SEM) using Smart PLS 3.0 for the statistical analysis. The results showed that perceived usefulness, perceived ease of use, student trust, content quality, and service quality were significant determinants of student satisfaction with e-government services. Both content quality and service quality were significant predictors of the perceived usefulness of e-government services. Importantly, the study revealed that student satisfaction with e-government services was significant in influencing student intention to recommend e-government services adoption. The managerial consequences of these research outcomes on the development and diffusion of electronic government are deliberated.
QR Digital Payment System Adoption by Retailers
Authors: Jiang Yun , Ahmad Hassan , Butt Asad Hassan , Shafique Muhammad Nouman , Muhammad Sher
Published: May 2021

The acme of this paper was to examine the QR code payment services adoption by retailers in Pakistan. An all-inclusive review of the literature and data analysis has justified the purpose to use this inventive technology. The study established that innovation diffusion theory (IDT) dimensions and convenience impacted the usefulness of QR code payment services which are well-thought-out critical antecedents of accepting future technologies. The inferences of this research work provide valuable acumens for banks, financial institutions, and the government to develop a platform about digital payment for the retailers, wholesalers, and the end consumers. Further, the study approves that QR code payment services will aid to advance the business operations in Pakistan in the COVID-19 pandemic.
TRAM-Related TLR4 Pathway Antagonized by IRAK-M Mediates the Expression of Adhesion/Coactivating Molecules on Low-Grade Inflammatory Monocytes
Authors: Pradhan Kisha , Geng Shuo , Zhang Yao , Lin Rui-Ci , Li Liwu
Published: May 2021

Low-grade inflammatory monocytes critically contribute to the pathogenesis of chronic inflammatory diseases such as atherosclerosis. The elevated expression of coactivating molecule CD40 as well as key adhesion molecule CD11a is a critical signature of inflammatory monocytes from both human patients with coronary artery diseases as well as in animal models of atherosclerosis. In this study, we report that subclinical superlow-dose LPS, a key risk factor for low-grade inflammation and atherosclerosis, can potently trigger the induction of CD40 and CD11a on low-grade inflammatory monocytes. Subclinical endotoxin-derived monocytes demonstrate immune-enhancing effects and suppress the generation of regulatory CD8+CD122+ T cells, which further exacerbate the inflammatory environment conducive for chronic diseases. Mechanistically, subclinical endotoxemia activates TRAM-mediated signaling processes, leading to the activation of MAPK and STAT5, which is responsible for the expression of CD40 and CD11a. We also demonstrate that TRAM-mediated monocyte polarization can be suppressed by IRAK-M. IRAK-M–deficient monocytes have increased expression of TRAM, elevated induction of CD40 and CD11a by subclinical-dose endotoxin, and are more potent in suppressing the CD8 regulatory T cells. Mice with IRAK-M deficiency generate an increased population of inflammatory monocytes and a reduced population of CD8 T regulatory cells. In contrast, mice with TRAM deficiency exhibit a significantly reduced inflammatory monocyte population and an elevated CD8 T regulatory cell population. Together, our data reveal a competing intracellular circuitry involving TRAM and IRAK-M that modulate the polarization of low-grade inflammatory monocytes with an immune-enhancing function.
Une note sur la densité des zéros des sommes partielles de la fonction zeta de Dedekind sur un corps quadratique
Authors: Dubon Eric
Published: May 2021

En s’appuyant sur la notion d’équivalence au sens de Bohr entre polynômes de Dirichlet et sur le fait que sur un corps quadratique la fonction zeta de Dedekind peut s’écrire comme produit de la fonction zeta de Riemann et d’une fonction L, nous montrons que, pour certaines valeurs du discriminant du corps quadratique, les sommes partielles de la fonction zeta de Dedekind ont leurs zéros dans des bandes verticales du plan complexe appelées bandes critiques et que les parties réelles de leurs zéros y sont denses.
Аппроксимации по мере: задача Дирихле, универсальность и гипотеза Римана
Authors: Falco Javier , Gauthier Paul M
Published: May 2021

Аппроксимации по мере используются для решения асимптотической задачи Дирихле на произвольных открытых множествах, а также для демонстрации того обстоятельства, что многие функции, в том числе дзета-функция Римана, универсальны в смысле сходимости по мере. Выдвигается предположение о связи этих результатов с гипотезой Римана.
Библиография: 12 наименований.
О нижней оценке скорости сходимости многоточечных аппроксимаций Паде кусочно аналитических функций
Authors: Buslaev Viktor Ivanovich
Published: May 2021

В работе получена нижняя оценка скорости сходимости многоточечных аппроксимаций Паде функций, голоморфно продолжаемых с компакта в объединение областей, границы которых обладают определенным свойством симметрии. Полученная оценка смыкается с доказанной ранее верхней оценкой той же величины.
Библиография: 22 наименования.
Тау-функции решений солитонных уравнений
Authors: Domrin Andrei Victorovich
Published: May 2021

В рамках голоморфного варианта метода обратной задачи теории рассеяния показано, что определитель фредгольмова оператора тeплицева типа, возникающего при решении обратной задачи, является целой функцией от пространственной переменной для всех потенциалов, данные рассеяния которых принадлежат классу Жевре с номером, строго меньшим единицы. В качестве следствия установлено, что любое локальное голоморфное решение уравнения Кортевега-де Фриза является (с точностью до постоянного множителя) второй логарифмической производной некоторой целой функции от пространственной переменной. Обсуждается возможный порядок роста этой целой функции. Приведены аналогичные результаты для всех солитонных уравнений параболического типа.
Библиография: 24 наименования.
Собственные голоморфные отображения ограниченных двумерных областей Рейнхарта. I
Authors: Kruzhilin Nikolai Georgievich
Published: May 2021

Описана структура собственных голоморфных отображений кратности выше единицы ограниченных областей Рейнхарта в $\mathbb C^2$ на двумерные комплексные многообразия.
Библиография: 21 наименование.
Плоские алгебраические кривые в "причудливых" шарах
Authors: Kruzhilin Nikolai Georgievich , Orevkov Stepan Yur'evich
Published: May 2021

Буало и Рудольф [1] назвали ориентируемое зацепление $L$ в трехмерной сфере, которое реализуемо в виде пересечения алгебраической кривой $A$ в $\mathbb{C}^2$ с границей гладко вложенного замкнутого четырехмерного шара $B$, $\mathbb{C}$-границей. Они показали, что некоторые зацепления не являются $\mathbb{C}$-границами. Будем говорить, что $L$ - сильная $\mathbb{C}$-граница, если оно реализуется так со связным дополнением $A\setminus B$. В частности, все квазиположительные зацепления являются сильными $\mathbb{C}$-границами.
В настоящей статье мы приводим примеры неквазиположительных сильных $\mathbb{C}$-границ, а также примеры $\mathbb{C}$-границ, не являющихся сильными $\mathbb{C}$-границами. Мы даем полную классификацию (сильных) $\mathbb{C}$-границ с не более чем пятью пересечениями.
Библиография: 17 наименований.
Constitutional immunity clause and the fight against corruption in Nigeria
Authors: Fabamise Sesan
Published: May 2021

One of the most pressing debates in Nigeria today is on the continued retention, or removal, of the immunity clause enshrined in section 308 of the 1999 Constitution of the Federal Republic of Nigeria. Some scholars canvass for the removal of the immunity clause because its retention, they argue, appears ironic in view of the stance of the government to rid governance of corrupt practices, including misappropriation of public funds. Others have called for its retention while another set of scholars further ask that it be extended to the leadership of the National Assembly and the States Houses of Assembly. This latter group has said that the Senate President, the Deputy Senate President, the Speaker of the House of Representatives and the Deputy Speaker as well as the Speakers of the States Houses of Assembly and their Deputies should be granted immunity under the Constitution. This article discusses the immunity clause and its sphere, extent and limits as it relates to the officers protected, the arguments for and against its retention in the Constitution, as well as state practices in other jurisdictions.It concludes that it is expedient to retain the clause, but the call in some quarters to expand it to cover the leadership of the National Assembly and States Houses of Assembly is not viable.Keywords: Corruption, immunity, Constitution, sustainable development.
Trophy hunting: To ban or not to ban? Legal pathways for Zimbabwe in the aftermath of Cecil the lion
Authors: Makuyana Precious G.
Published: May 2021

This article examines the legal framework and tools for achieving sustainable trophy hunting in Zimbabwe. Trophy hunting is part of wildlife tourism, in which wealthy tourists visit Zimbabwe to hunt for a unique, iconic wildlife with desirable phenotypic characteristics at a very high cost. The trophy hunting system was developed to achieve the tripartite objectives of conserving wildlife; providing local communities with economic opportunities and income; and incentivizing local communities to support environmental conservation initiatives. This article, however, highlights the blurred lines between the purported sustainable trophy hunting and its unsustainable implementation which now resembles “legal poaching.” This dichotomy was heightened by the killing of Cecil the Lion, a tourism icon in Zimbabwe when it was not listed under the quota system for trophy hunting. The wellintentioned legal frameworks on sustainable trophy hunting in Zimbabwe are weakened by broad exceptions that render them toothless to achieve the intended tripartite sustainability objectives. As demonstrated in this article, these tripartite objectives can be fulfilled by effective enforcement mechanisms that do not currently exist. Proposals are recommended to promote these objectives through reformation of the existing legal frameworks. The option to ban trophy hunting is examined through a socioeconomic analysis in Zimbabwe to determine whether it would be possible to support a complete ban. Zimbabwe’s current socioeconomic realities confirm that banning trophy hunting would be unlikely as doing so would devastate the tripartite objectives. Undertaking effective and sustainable policies is the more effective path for Zimbabwe at this time.Keywords: Sustainability, Trophy Hunting, CITES; CAMPFIRE, Zimbabwe
Utilization of cullets for the production of glass tiles through likn casting
Authors: Adjei K. , Opoku-Bonsu K. , Asiamah E. O.
Published: May 2021

The study explored the technique of kiln casting of glass as a means of recycling glass for aesthetic and functional purposes. Some disposed glass bottles were collected and processed through crushing, milling and sieving to particle sizes of 60, 80 and 120 mesh size. These particle sizes were batched and fired in an electric kiln to temperatures of 1050oc and 1180oc. The study revealed that the 60 mesh and 80 mesh specimens fired at 1180oc gave very good translucent effect with rich clear colour. It was observed that the sample that had addition of colouring oxides gave the best result when it was double fired. The results of the study revealed that the two major parameters that were investigated in this research, (temperature and particle sizes), had an effect on each other and that they were very important for the study. The study concludes that glass recycling through kiln casting presents an avenue for producing glass tiles for functional and aesthetic applications.Keywords: Cullets; kiln casting; glass tiles; recycling; melting temperature
Improving mechanical properties of aluminium alloy through addition of coconut shell-ash
Authors: Apasi A. , Yawas D. S. , Abdulkareem S. , Kolawole M. Y.
Published: May 2021

This paper investigates the microstructure and mechanical properties of aluminum alloy (Al-Si-Fe) reinforced with coconut shell-ash particulate. The aluminium (Al-Si-Fe) alloy composite was produced by a double-stir casting process at a speed of 700 rpm for 10 and 5 minutes at first and second stirring respectively. The samples produced from addition of 0-15 wt% coconut shellash particles (CSAp) were prepared and subjected to microstructural and mechanical properties testing. The results of the microstructural analysis of the composite reveal a fairly uniform distribution of the coconut shell-ash particles in the matrix with increase in volume fraction of CSAp. The mechanical property test results revealed that, hardness of the developed composite increased with increasing percentage weight of CSAp. Also the tensile and yield strength at 0.2% offset values of Al-Si-Fe/CSAp composite increased with percentage increase in CSAp up to 9% addition above which a little decrease in both tensile and yield strength was observed.Keywords: Matrix, coconut shell, mechanical properties, stir- casting, particulate, reinforcements
Shopping malls as catalyst for sub-urban development in Ghana
Authors: Quagraine V. K. , Oppong R. A. , Agyekum-Sah J.
Published: May 2021

The concentration of population in major cities is usually the consequence of the concentration of employment opportunities, goods and services in such cities. These goods and services act as pull factors to the regional population, especially from the suburban or rural areas, to densely populated cities. The resulting migration creates congestion of all kinds in the cities. Suburban communities are, thus, rendered unattractive for living. This situation is prevalent in Ghana where 75% of migrants into major cities are from suburban areas and the rate of urbanization is 4.1%. Decentralizing amenities to suburban areas would initiate re-distribution of population and thus development. This study investigated the possibility of using the Shopping Mall concept as catalyst to both help develop the suburbia and decongest cities in Ghana. The West Hills Mall at Dunkonah, a suburb near Accra was selected for the study. A mixed research method including  questionnaires, interviews, and observations was used for data collection. Out of a total of 1,642 house owners 328 were sampled and interviewed with questionnaire that delved into their origins, whether they are migrants, and the reasons behind their movement. The study concluded that shopping malls could act as catalysts for development.Keywords: Shopping Malls, Catalyst, Decongestion, Suburbanization, Amenities