bluuebunny/crossref_metadata_2025 huggingface dataset:
Existence and controllability of Hilfer fractional neutral differential equations with time delay via sequence method
Authors: Kavitha Krishnan , Vijayakumar Velusamy , Nisar Kottakkaran Sooppy , Shukla Anurag , Albalawi Wedad , Abdel-Aty Abdel-Haleem
Published: May 2022

This paper deals with the existence and approximate controllability outcomes for Hilfer fractional neutral evolution equations. To begin, we explore existence outcomes using fractional computations and Banach contraction fixed point theorem. In addition, we illustrate that a neutral system with a time delay exists. Further, we prove the considered fractional time-delay system is approximately controllable using the sequence approach. Finally, an illustration of our main findings is offered.
A new characterization of hyperbolic cylinder in anti-de Sitter space $ \mathbb{H}_1^{5}(-1) $
Authors: Qi Xuerong , Shi Chunxia
Published: May 2022

By investigating complete Willmore maximal spacelike hypersurfaces with constant scalar curvature in anti-de Sitter space $ \mathbb{H}_{1}^{5}(-1) $, we give a new characterization of hyperbolic cylinder $ \mathbb{H}^{2}(-2)\times\mathbb{H}^{2}(-2) $ in $ \mathbb{H}_{1}^{5}(-1) $.
Fractional-order coronavirus models with vaccination strategies impacted on Saudi Arabia's infections
Authors: Batiha Iqbal M. , Al-Nana Abeer A. , Albadarneh Ramzi B. , Ouannas Adel , Al-Khasawneh Ahmad , Momani Shaher
Published: May 2022

Several newly nonlinear models for describing dynamics of COVID-19 pandemic have been proposed and investigated in literature recently. In light of these models, we attempt to reveal the role of fractional calculus in describing the growth of COVID-19 dynamics implemented on Saudi Arabia's society over 107 days; from 17 Dec 2020 to 31 March 2021. Above is achieved by operating two fractional-order differential operators, Caputo and the Caputo-Fabrizio operators, instead of the classical one. One of expanded SEIR models is utilized for achieving our purpose. With the help of using the Generalized Euler Method (GEM) and Adams-Bashforth Method (ABM), the numerical simulations are performed respectively in view of the Caputo and Caputo-Fabrizio operators. Accordance with said, the stability analysis of the two proposed fractional-order models is discussed and explored in view of obtaining the equilibrium points, determining the reproductive number ($ R_0 $) and computing the elasticity indices of $ R_0 $. Several numerical comparisons reveal that the fractional-order COVID-19 models proposed in this work are better than that of classical one when such comparisons are performed between them and some real data collected from Saudi Arabia's society. This inference together with the cases predictions that could easily deduced from the proposed fractional-order models can allow primary decision makers and influencers to set the right plans and logic strategies that should be followed to face this pandemic.
A complex network model for a society with socioeconomic classes
Authors: Licciardi Jr. A. N. , Monteiro L. H. A.
Published: May 2022

People's attitudes and behaviors are partially shaped by the socioeconomic class to which they belong. In this work, a model of scale-free graph is proposed to represent the daily personal contacts in a society with three social classes. In the model, the probability of having a connection between two individuals depends on their social classes and on their physical distance. Numerical simulations are performed by considering sociodemographic data from France, Peru, and Zimbabwe. For the complex networks built for these three countries, average values of node degree, shortest-path length, clustering coefficient, closeness centrality, betweenness centrality, and eigenvector centrality are computed. These numerical results are discussed by taking into account the propagation of information about COVID-19.
L’épave de Saint-Satur dans la Loire moyenne : un transport d’ardoises interrompu à la charnière du Moyen Âge et de la période moderne
Authors: Foucher Marion , Dumont Annie , Moyat Philippe , Lavier Catherine , Steinmann Ronan
Published: May 2022

Au droit du village de Saint-Satur (Cher), les opérations archéologiques menées en 2015 et 2017 ont révélé l’un des plus anciens bateaux fouillés en Loire. Le naufrage, estimé par dendrochronologie aux dernières années du xve siècle ou aux premières décennies du xvie siècle, a préservé une cargaison de pierres et d’ardoises, offrant de ce fait un potentiel d’étude inédit en termes de transport et d’économie des matériaux de construction. Le lot d’ardoises en particulier offre plusieurs pistes d’investigation riches, concernant leur morphologie et leur gabarit, leur origine et surtout leur association à un stock de pierres de taille d’origine et de destination différente. Au regard des comptabilités contemporaines, ces divers aspects permettent de discuter de l’existence de chaînes d’approvisionnement complexes, intégrant des intermédiaires entre les lieux d’extraction et ceux de la mise en œuvre, et d’évoquer la normalisation des productions ardoisières.
A Compass to Drive Collaborative Design Practices within Private Organisations
Authors: Rossi Martina
Published: May 2022

Collaboration has currently become a must within design practices. Ranging from public to private sector, from social to business, the design activity is no longer commissioned ‘for’ the client, but is carried out ‘with’ the client and with all the stakeholders involved. This tendency introduces a reflection on the shift in design practice and the role of the designer within the community with which she is designing.This article focuses on collaborative design practices within the private sector, providing a set of case studies analysed through variables that define the main qualities of such activities.Those variables become lenses through which it is possible to zoom in on the peculiarity of the session and ultimately draw an evaluation. The correlations of the variables represent a first draft of a compass aimed at building awareness and providing guidelines for future practices.
Patient-centered healthcare service development: a literature review
Authors: Ramos Mayara , Forcellini Fernando Antônio , Ferreira Marcelo Gitirana Gomes
Published: May 2022

Patient centred services and patient experiences have increasingly been related to service quality and efficiency of care. As a way to have patient centred services, healthcare organizations started involving patients in service improvement. Proper service design is another factor that influences service quality. Healthcare services, however, have presented issues in this aspect. Human Centred Design approaches can be a way for healthcare organisations to properly design services and deliver patient centred care. In this paper, we investigate through a literature review, what methods have been used to design or improve healthcare services and how they contributed to patient centred care. With literature analysis, we identified that Service Design, co-design and other design related approaches were used to bring patient participation, and highlighted improvements and barriers involved in their use. Although these processes faced some barriers, they had positive effects to services being patient centred, improving patient satisfaction and care. Despite the effort of using structured approaches to patient participation and service improvement, the organizations might still be (re)designing their services with inadequate processes.
Influence Factors on Industrial Handmade Products Designed from Sugar Palm Fibers
Authors: Egwutvongsa Songwut E.
Published: May 2022

The objective of this research was to study the results of a fibers transformation procedure from sugar palm leaves into product designs. The population group included the customer group that visited the exhibition at Chulachomklao Royal Military Academy in Nakorn Nayok province, Thailand with a total of 1,398 people, and the Multistage Random Sampling with 5-point Rating Scale questionnaires was used in this research. Additionally, the Cronbach’s Alpha Coefficient value was analyzed for the Variance at the level of 0.85 in One-Way or Single-Factor ANOVA. In this case, it was found that the customers had the satisfaction with the products based on five attributes at the most suitable level, (Mean= 4.044, S.D. = 0.837), and in the comparative pairs, there were the differences with the significance of .05, except for the unique factors and the suitable applied factors having strong relationships and the significant connections to one another.
The usage of scenarios in the search for innovation regarding the model of rare disease associations: an empirical experience and its findings
Authors: Bittencourt Gustavo Berwanger , Freire Karine de Mello
Published: May 2022

Considering the challenge of organizational innovation in the rare disease associations, we propose the usage of Design Orienting Scenarios under the scope of a Strategic Design project. Such empirical experience generates reflections on the usage of scenarios for it stimulates both the participation of actors involved with the strategy and the expression of their visions and potentialities in a broad and democratic sense.
Combating Misinformation in the Open Access Era
Authors: Shakeri Shadi , Hawamdeh Suliman
Published: May 2022

Since the early 21st century, the scholarly community has struggled with the rising cost of scientific publications and issues related to the accessibility and dissemination of scientific work and research results to the wider community. Maintaining a high quality of scientific publications and lowering the cost led to the emergence of the open access (OA) movement. OA has appeared as an essential resource to make scholarly publications available to a broader audience in the last two decades, aiming to improve access to scientific knowledge. However, the onset of the internet and social media has given rise to a tide of misinformation, resulting in diminishing trust in science. This chapter discusses the importance of OA as a trusted source in combating misinformation and adopting strategies for sustaining the OA business models. Additionally, this chapter draws on the social psychology literature and the “inoculation theory” to reason why OA as a credible source of information can protect us against misinformation.
Best Practices and Navigating the Effects of Open Access Journals in Scholastic Publication
Authors: Sankar Mallika , Nagarathinam Aishwarya , Paramasivan Senthilmurugan , Chellasamy Aarthy
Published: May 2022

Open access (OA) journals have transformed the academic publication to a different realm, which was unfathomable years ago. The early 1990s witnessed OA journals founded by individual scholars which are now in the hands of major publication players using them as another disruptive business model. The benefits of an OA system outweigh its disadvantages. Growth in accessibility, visibility, citations, and impact on research work are some of the promising outcomes of OA. Though it has been contemplated as an inevitable element in scholastic writing for a long time, there are many misconceptions loaded with open access. The present study aims to navigate into the perceptions of open access journals among researchers intriguing into the fine clauses established in the scholarly publication arena. The chapter also intends to examine the features of major publishing houses in a global perspectives and probe into the best practices of open access from different publishing houses in an effort to enhance the overall capacity of the open access and to create a knowledge-based economy.
Negotiating Open Access
Authors: Srinivas Vijayalaya , Jayagopalan Gaana
Published: May 2022

In this chapter, the authors interrogate the discursive terrain of the open access phenomenon to position the processual as well as the discourse communities that open access is inevitably enmeshed in. The essay explores the current climate of open access and investigates the ethical dilemmas that its subversive sibling of guerrilla open access foregrounds. Further, the essay also recommends a viable model that can be deployed by state players as an exemplar of academic socialism that is flexible, accommodative, and a true reflection of the open-access philosophy which also counters the development of otherwise illegal and ‘pirate' models of open access.
Unraveling Governance Issues in Global Sourcing of Accounting Services
Authors: Aman Aini , Said Suzana Muhamad , Dastane Omkar
Published: May 2022

As global accounting services continues to increase; firms need to be equipped with proper governance framework. The need for governance of global sourcing activities is being emphasized practically as well as academically. This study aims to understand governance issues along with the mechanisms used to overcome such issues in a global sourcing of accounting services by using the migratory governance path framework. The study employs interpretive case study research approach. The fundamental issues of governance in global sourcing of accounting services were found to be related to coordination and communication aspects. Findings show that several governance mechanisms were implemented to overcome such issues. Theoretically, this study enhances the understanding of governance issues in global sourcing by providing further evidence on the importance of governance in global sourcing of accounting services. The study has practical implications in terms of offering best practices of good governance for global sourcing.
A Real-Time System for a Safer Society in the Era of the COVID-19 Pandemic Using New Configurations of YOLO and MobileNet
Authors: Bouarara Hadj Ahmed , Cheimaa Bentadj
Published: May 2022

To create a secure environment that supports public safety, the proposed solution called I3S-Covid19 (Intelligence system for a safer society in covid-19) which consists of several parts: 1) extract foreground objects in videos received from surveillance camera. 2) Detect whether a person is wearing a mask or not through the use of data augmentation, transfer learning and new configuration of several models (such as MobileNet and YOLOV3). 3) Calculate the distance between people circulating in public or private places using MobileNet-SSD and YOLOV3 with the Euclidean distance measure. Finally, after evaluating the different solutions in different contexts and on different benchmark datasets, the results obtained represent an empirical validation of the benefit derived from the use of deep learning, the internet of things, and computer vision to minimize the spread of COVID-19.
Hybrid Genetic Fuzzy System for Modeling Consumer Behavior
Authors: Sajja Priti Srinivas
Published: May 2022

Understanding consumer behavior is beneficial to a business in various aspects such as prediction of manufacturing quantity, new product launch, and aids in lock-in customers and lock-out competitors. The task is highly complex and traditional models do not help in absence of generalized decision making logic. Further such domains handle large amount of data in unstructured format. This article presents an intelligent system for modeling consumer behavior via a hybrid genetic fuzzy system from large source of data. The paper justifies and presents a literature survey with common observations. A four phase generic architecture of genetic fuzzy system presented for the modeling of consumer behavior. Detailed discussion on the architecture is also provided with an experiment. Technical details, fuzzy membership functions used in experiment, encoding strategy, genetic operators, and evaluation of rules using fitness function are also discussed in detail along with results. At end, applications of the research work in other domains are enlisted with possible future enhancements.
Framework for Plastic Waste Management
Authors: Khan Rohan Ullah , Siddiqi Marium , Mahmood Hira , Asghar Muhammad Abrar
Published: May 2022

Plastic pollution has become a global problem. Around 3.3 million tons of plastic are wasted annually, with an annual plastic product usage growth rate of 15%. The recycling sector is unstructured, policies at the state level are non-existent to address plastic waste management. Pakistan, as a developing country is also turning towards circular economy practices to benefit businesses and the environment. This case study is done with support from SPEL and aims to perform a systematic literature review, analyzing the present frameworks followed by developed countries for the implementation of CE in developing countries, its critical analysis for the gaps to achieve sustainability in view of UN SDGs 2030 along with the study of factors impacting PWM. The findings showed that the current system is primarily focused on garbage collection and transportation with very little focus on its management. Religion, culture, educational awareness, and psychology can play moderating roles in implementing CE practices. It will provide a conceptual framework that can be implemented by SPEL.
Consumer Social Responsibility (CnSR) in the Circular Economy of Global Value Chains
Authors: Karimova Guli-Sanam , Arthur LeMay Stephen
Published: May 2022

What does it mean for global consumers to be 'socially responsible' in the context of sustainable supply chains? Why should Consumer Social Responsibility (CnSR) in the sustainable value chains matter? In this paper, we examine global consumers' responsibilities in the context of the United Nations' Sustainable Agenda 2030, Goal 12. Goal 12 addresses sustainable production and consumption. We explore CnSR from normative and descriptive standpoints. We look explicitly at the consumers' duties and responsibilities to influence global production and supply networks. To accomplish this purpose, we apply philosophical theories to the importance of sustainable value chains, especially to the meaning of 'value' in a sustainable supply chain. Consumers can and should influence corporations with global supply chains to produce goods sustainably while still meeting consumers' needs worldwide. We also look at why consumers should be willing to live up to these responsibilities in the context of sustainable supply chains.
Innovative Revenue Collection Practices in South European Countries and the Case of Hellenic Independent Authority for Public Revenue
Authors: Papageorgiou Konstantinos , Stavropoulos Angelos Stavros , Derleres Konstantinos , Milioris Konstantinos , Papagrigoriou Aristidis
Published: May 2022

Developed country governments have sought ways to offer a better service and some of them have already turned to a form of semi-autonomous service in order to achieve improvements in tax collection, better service to taxpayers and businesses as well as more flexible human resource management options. The South European countries have faced the most severe consequences from the recent economic crisis. Therefore, the need for reformation has been highlighted as imperative in these cases. These reformations were designed in order to emend previous pathologies, aiming to intensify efficiently the collection of public revenues and reduce operating costs. Nevertheless, the outcome of these restructures appears to offer a significant service to the citizens and facilitates conduction of business.
Investigating CSR Practice and SERVQUAL Model for Customer Attitudinal and Behavioral Loyalty in a Banking Context
Authors: Ahmad Bilal , Akbar Muhammad Imad ud Din
Published: May 2022

The quality of service delivery is considered one of the most important success indicators in the banking sector. Therefore, this research aims to investigate the impact of corporate social responsibility (CSR) on the SERVQUAL model in the retail banking sector, taking into account the serial mediation of customer satisfaction and affective commitment. A sample of 313 retail banking customers was employed for the final analysis. The authors validate a measurement model using structural equation modeling (SEM). The findings of this research suggest that corporate social responsibility (CSR) has a significant relationship with SERVQUAL dimensions. Furthermore, results showed potential effects of SERVQUAL dimensions on customer satisfaction and affective commitment. Consequently, corporate social responsibility (CSR) has a strong indirect association with attitudinal and behavioral loyalty. The theoretical contributions of these results for managerial practices are also discussed.
How Perceived Risk and Suspicion Moderates the Relationship Between Information Source, eWOM, and Purchasing Decision
Authors: Truong Giang Nu To , Nguyen Phuong Minh Binh , Truong Giang Le Ngoc
Published: May 2022

This research aimed to examine the customer behavior in online shopping by measuring product characteristics, information sources, perceived risk, electronic word-of-mouth, suspicion, and purchase decision with the moderation effect. The research data were collected using convenience sampling method. Respondents of 312 customers who conducted shopping online have been analysed, and research hypotheses were assessed by employing partial linear square structural equation modelling (PLS-SEM) and hierarchy regression analysis. The study found that there is a relationship among different variables and perceived risk, and suspicion moderates the relationship between information sources, electronic word-of-mouth, and purchase decision. Since the issues of online shopping were still subject to further validation, this study provided an important reference for marketers to develop marketing strategies as well as the theoretical base for further empirical validation.
An Intelligent Model for DDoS Attack Detection and Flash Event Management
Authors: Tinubu Oreoluwa Carolyn , Sodiya Adesina Simon , Ojesanmi Olusegun Ayodeji , Adeleke Emmanuel Oyeyemi , Timehin Ahmad Alfawwaz
Published: May 2022

Distributed Denial of Service (DDoS) attacks are the foremost security concerns on the Internet. DDoS attacks and a similar occurrence called Flash Event (FE) signify anomalies in the normal network traffic, requiring intelligent interventions. This study presents the design and implementation of an intelligent model for the detection of application-layer DDoS attacks and the prevention of service degradations during FE. A Multi-Layer Perceptron (MLP) classifier was used for detecting DDoS attacks on application servers. The FE management system consists of asynchronous processing of requests on a First-In, First-Out (FIFO) basis. A demo application was set up wherein HTTP flood attack was launched and a Flash Event was simulated. The experimental results clearly show that the MLP classifier in comparison with other machine learning classifiers performs best in terms of speed and accuracy. Also, the evaluation of the FE management system shows a great reduction in service degradation. This reflects that the designed model is capable of averting service unavailability on the web.
A Model Study on Hierarchical Assisted Exploration of RBAC
Authors: Chen Wan , Han Daojun , Zhang Lei , Xiao Qi , Li Qiuyue , Xiang Hongzhen
Published: May 2022

Role-based access control(RBAC) system has been widely used in data security because of its good flexibility and security, wherein RBAC dominates the field of access control. However, the process of establishing RBAC roles is complex and time-consuming, which hinders the development and application of this field. Recently, the introduction of expert interactive q&a algorithm based on attribute exploration has greatly reduced the complexity and time-consuming of RBAC role building process. However, when attributes increases, algorithm will face challenges that the time complexity will explode exponentially with the increase of attributes. To cope with above problems, this paper proposes a hierarchical assisted exploration model of RBAC under attribute-based exploration expert interactive q&a algorithm framework from the view of reducing time-consuming of overall and single role engineering. This model not only avoids time-consuming process of single role requirements, but also reduces time-consuming process of whole role establishment from the overall architecture perspective.
SRGM Decision Model Considering Cost-Reliability
Authors: Jiang Wenqian , Zhang Ce , Liu Di , Liu Kaiwei , Sun Zhichao , Wang Jianyuan , Qiu Zhongyin , Lv Weigong
Published: May 2022

Aiming at the current software cost model and optimal release research, which does not fully consider the actual faults in the testing phase, a cost-reliability SRGM evaluation and selection algorithm SESABCRC is proposed. From the perspective of incomplete debugging, introducing new faults, and considering testing effort, the imperfect debugging SRGM is established. The proposed SRGM can be used to describe the testing process of the software through the actual failure data set verification, and is superior to other models. Based on the proposed SRGM, the corresponding cost function is given, which explicitly considers the impact of imperfect debugging on the cost. Furthermore, an optimal release strategy is proposed when given restricted reliability target requirements and when considering the uncertainty that the actual cost may exceed the expected cost. Finally, an experimental example is given to illustrate and verify the optimal publishing problem, and parameter sensitivity analysis is carried out.
A Novel IDS Securing Industrial Control System of Critical Infrastructure Using Deception Technology
Authors: Zhang Shaobo , Liu Yuhang , Yang Dequan
Published: May 2022

The Industrial Control System (ICS) has become the key concept in the modern industrial world, enabling process monitoring and system control for general industrial systems and critical infrastructures. High-skilled hackers can invade an imperfect ICS by existing vulnerabilities without much effort. Conventional defenses (such as encryption and firewall) to keep invaders away are getting less and less effective when an attack is carried out by exploiting an array of particular vulnerabilities. Under this circumstance, a new-type intrusion detection system (IDS) based on deception strategy using honeypot technique is proposed, which is of dramatic effectiveness in protecting ICSs of critical infrastructures. In this honeypot-based model, we capture malicious Internet flows and system operations. We analyze the collected data before alerting and preventing the intrusion alike when it affects the system in the future. This paper deals with the model's concept, architecture, deployment, and what else can be achieved in the field of Critical Infrastructure Cybersecurity (CIC).
A Privacy Protection Scheme for Cross-Chain Transactions Based on Group Signature and Relay Chain
Authors: Liang Xiubo , Zhao Yu , Wu Junhan , Yin Keting
Published: May 2022

Recently, with the rapid development of blockchain technology, the information interaction and value transfer problems between different blockchains have become the focus of research. The cross-chain technology is to solve the cross-chain operation problems of assets and data between different chains. However, the existing cross-chain technology has the problem of identity privacy leakage. Therefore, this article proposes a cross-chain privacy protection scheme for consortium blockchains based on group signature, certificate authority and relay chain. The scheme is divided into three cross-chain service layers, called the management layer, the transaction layer, and the group layer. The management layer is responsible for the forwarding of cross-chain transactions, the transaction layer includes the blockchains that actually participate in cross-chain transactions, and the group layer is responsible for group signature related work. Through this scheme, the identity privacy of both parties to the transaction can be protected during the cross-chain transaction process.
Audio Tampering Forensics Based on Representation Learning of ENF Phase Sequence
Authors: Zeng Chunyan , Yang Yao , Wang Zhifeng , Kong Shuai , Feng Shixiong
Published: May 2022

This paper proposes an audio tampering detection method based on the ENF phase and BI-LSTM network from the perspective of temporal feature representation learning. First, the ENF phase is obtained by discrete Fourier transform of ENF component in audio. Second, the ENF phase is divided into frames to obtain ENF phase sequence characterization, and each frame is represented as the change information of the ENF phase in a period. Then, the BI-LSTM neural network is used to train and output the state of each time step, and the difference information between real audio and tampered audio is obtained. Finally, these differences were fitted and dimensionally reduced by the fully connected network and classified by the Softmax classifier. Experimental results show that the performance of this method is better than the state-of-the-art approaches.
Smartphones and the Perception of Space
Authors: Kaisar Marilia
Published: May 2022

The networked human moves across the city while consuming and reproducing representations of the places it encounters. This paper investigates how human engagement with the smartphone has created a shift in perception and embodiment that affects the relationship between the moving body and the city through rituals performed in everyday life. The smartphone becomes a pivotal point between the physical and virtual worlds, allowing the user to access and interfere with physical and virtual layers of space, continually transforming how the public understands the city. This paper uses media studies theory to read how the smartphone operates as an always-available extension of the body that functions as a screen, a camera, a map, and a small computer. In a new, data-enhanced world that has emerged, storytelling and the circulation of representations of the surrounding space affect the experience of the city. This paper explores how informational flows create new topologies, new embodied experiences, and new futures for cities.
The Impacts of Early Architectural Design Decisions on Building Performance
Authors: İşeri Orçun Koral , Dursun Onur
Published: May 2022

The early architectural design involves the most salient decisions. However, because of the large amount of variance, the decision-making is highly arduous. This article presents a methodology to enable the most effective design variables to be selected within the most effective value range by presenting a method that allows the measurement of output uncertainty depending on the impact of design decisions on outputs. The methodology was tested with different building functions and climate regions using two-phase sensitivity analysis. The values of design variables were generated with quasi-random sampling. They were sorted with factor prioritization. Ineffective variables were eliminated with factor fixing. Advanced global sensitivity analyses were performed for the total effect. Factor mapping was applied with the output weighting. The results were presented with Parallel Coordinate Plot (PCP). The designers can make selections from alternatives with PCP. Finally, the study demonstrated how climate and building functions should be considered for building performance.
An Imperfect Inventory Model for Multi-Warehouses Under Different Discount Policies With Shortages
Authors: Panwar Aastha , Pareek Sarla , Dhaka Vinti , Mittal Mandeep
Published: May 2022

A multi-warehouse inventory model with shortage has been developed where demand is taken as deterministic. In reality, during production, if the machine works for a long time there may be a random breakdown and the system shifts from controlled to out of the controlled situation, in this time production system produces defective items. The retailer offers an all-unit quantity discount on the selling price of the item who in return gets a quantity-based discount on the purchase price of the item. The motive of this model is to study a multi-warehouse model for imperfect items under a quantity-based discount, where the defectives can be screened and then can be sold in a single batch where the decision variables are set as optimal ordering quantity and optimal shortage quantity, to maximize the total profit of the retailer. A solution procedure is given to find the optimal solution and a numerical example is given to illustrate this study. Sensitivity analysis is also performed to study the effect of the changes in parameter values on the optimal solution.
Analyzing Cross-country E-entrepreneurship in a Framework of Transnational Digital Entrepreneurial Ecosystem: Evidence of Chinese E-platforms
Authors: Duan Carson
Published: May 2022

This paper examines the effects of digital platforms (e-platforms) on transnational e-entrepreneurship (TEE) through the lens of the digital entrepreneurial ecosystem framework. It propose that TEE research should be conducted in a transnational e-entrepreneurial ecosystem framework that combines the digital ecosystem and host- and home-country entrepreneurial ecosystems. Based on the experiences of twelve Chinese immigrants living in Australasia, the framework was validated through case studies of two Chinese digital platforms. The results show that e-platforms bridge host and home-country ecosystems in addition to playing roles in e-trading business. E-platforms enable micro, small and medium e-enterprises (MSME) owners to operate in the same manner as large enterprises in transnational markets. The author concludes that future research themes for TEE study should link e-entrepreneurs with e-platforms and dual (host- and home-country) entrepreneurial ecosystems. It suggests that researchers and policymakers need to emphasize the availability and functionalities of MSME.
Factors Affecting Techno-Entrepreneurship Innovation and Growth in Developing Economies
Authors: Shatat Ahmad , Keir Mohammed Abo , Mustafa Iaad , Zitouni Faiza , Almatrook Manal
Published: May 2022

In many countries, entrepreneurs witnessed a considerable concern by governments and individuals due to its positive impact on individual interest in particular and the economic growth in general. Many individuals rely on government to secure a job which impose a huge burden on the government sector. The adoption of techno-entrepreneurship as a solution to create new job opportunities experienced several challenges to grow-up. However, the Critical Success Factors (CSFs) enabled many individuals to startup a new venture or transform their business effectively into the virtual platform such as social media. A survey instrument was distributed to 250 entrepreneurs effectively using technology as a platform for their venture. Out of which 204 were completed and used in the analysis which determined 81% as the overall response rate. The results of the study reveal a positive and significant relationship between the 7 CSFs and the venture success, and that also indicates a notable impact of the CSFs on the startups.
An Architecture of the Semantic Meta Mining Assistant for Adaptive Domain-Oriented Data Processing
Authors: Jiafeng Yang , Zhukova Nataly , Lebedev Sergey , Tianxing Man
Published: May 2022

Data mining is applied in various domains for extracting knowledge from domain data. The efficiency of DM algorithms usage in practice depends on the context including data characteristics, task requirements, and available resources. Semantic meta mining is the technique of building DM workflows through algorithm/model selection using a description framework that clarifies the complex relationships between tasks, data, and algorithms at different stages in the DM process. In this article, an architecture of semantic meta mining assistant for domain-oriented data processing is proposed. A case study applied proposed architecture on time series classification tasks is discussed.
Unsupervised Learning and Online Anomaly Detection
Authors: Decker Leticia , Leite Daniel , Minarini Francesco , Tisbeni Simone Rossi , Bonacorsi Daniele
Published: May 2022

The Large Hadron Collider (LHC) demands a huge amount of computing resources to deal with petabytes of data generated from High Energy Physics (HEP) experiments and user logs, which report user activity within the supporting Worldwide LHC Computing Grid (WLCG). An outburst of data and information is expected due to the scheduled LHC upgrade, viz., the workload of the WLCG should increase by 10 times in the near future. Autonomous system maintenance by means of log mining and machine learning algorithms is of utmost importance to keep the computing grid functional. The aim is to detect software faults, bugs, threats, and infrastructural problems. This paper describes a general-purpose solution to anomaly detection in computer grids using unstructured, textual, and unsupervised data. The solution consists in recognizing periods of anomalous activity based on content and information extracted from user log events. This study has particularly compared One-class SVM, Isolation Forest (IF), and Local Outlier Factor (LOF). IF provides the best fault detection accuracy, 69.5%.
On a Solution Set to a Mathematical Programming Problem With a Fuzzy Set of Constraint Indices
Authors: Mashchenko Serhii O.
Published: May 2022

The present paper investigates a mathematical programming problem with a fuzzy set of constraint indices. To formalize the set of feasible alternatives, the concept of intersection of crisp sets with a fuzzy set of operands is used. The result of this operation is a type-2 fuzzy set (T2FS) (a fuzzy set whose membership function takes a fuzzy set of values). Furthermore, the corresponding membership function is given. It is shown that the T2FS of feasible alternatives can be represented in the form of the collection of T2FSs with constant secondary grades. The notion of the solution T2FS to the mathematical programming problem with a fuzzy set of constraint indices is proposed. The basic properties of the solution T2FS are investigated. The notion of a compromise maximizing solution is given. Several results are proved that make it possible to simplify its construction. Illustrative examples are given.
Application of Artificial Intelligence Techniques in Slope Stability Analysis
Authors: Bardhan Abidhan , Samui Pijush
Published: May 2022

Artificial intelligence (AI) techniques have become a trusted methodology among researchers in the recent decades for handling a variety of geotechnical and geological problems. Machine learning (ML) algorithms are distinguished by their superior feature learning and expression capabilities as compared to traditional approaches, attracting researchers from a variety of domains to their growing number of applications. Different ML models are extensively used in the field of geotechnical engineering to accounting for the inherent spatial variability of soils in slope stability assessments. This study presents a brief overview of the application of several AI techniques in the area of slope stability, including adaptive neuro-fuzzy inference system, artificial neural network, extreme learning machine, functional network, genetic programming, Gaussian process regression, least-square support vector machine, multivariate adaptive regression spline, minimax probability machine regression, relevance vector machine, and support vector machine. Additionally, a summary containing published literature, the corresponding reference cases with the type of input soil parameters, and the implemented ML algorithms was compiled. Recent applications of various hybrid ML models in slope stability assessment are also discussed. Furthermore, the challenges and future prospects of AI techniques development in solving slope stability problems are presented and discussed.
Estimation of Vs30 Bounds From Limited Soil Data Considering Uncertainty
Authors: Dauji Saha
Published: May 2022

According to design standards, uncertainty of dynamic foundation parameters are accounted in soil structure interaction (SSI) analysis by considering best estimate, upper and lower bounds. Site specific variability (coefficient of variation: Cv) cannot be directly established from limited site measurements. Codes prescribe a value of unity for such cases, which results in wide and often unrealistic range of foundation parameters for SSI. A Monte Carlo (MC) simulation based approach is proposed for calculation of site specific Cv from limited measurements. Along with 12% reduction of mean value, Cv could be reduced to 0.5, thereby enabling reduction of the aforementioned range. Adoption of code specified minimum Cv could accommodate 50% inaccuracy of input shear wave velocity, which justifies use of correlation equations (with inaccuracies reported between 20% and 35%) for generation of synthetic shear wave velocity profiles as substitute for or augmentation of site measurements.
Numerical Modeling of Quaternary Sediment Amplification
Authors: Parla Rajesh , Somala Surendra Nadh
Published: May 2022

The main objective of this study is to understand the dependency of basin amplification on-site and source parameters employing high computational numerical simulations. This study mainly addresses the effect of fault dip, size of the basin, site classification, and position of the basin on wave amplification. Two dip angles are considered, 7 and 9 degrees, in this study to estimate the factor of amplification. Amplifications observed at the basin center and basin edge station for three different sizes of the basin are analyzed. Simulation results obtained from three different models with the ASCE site class C, D, and E basin sediment specifications compared. To analyze the effect of basin relative position on amplification, the authors studied a model with two different basins embedded in bedrock, back and forth of the fault. This study observed multiple peaks at different time periods in response spectra drawn to amplification ratio versus time periods.
An Online Service Performance Prediction Learning Method
Authors: Liang Hua , Wang Sha
Published: May 2022

In order to improve the quality of service operations, it is necessary to take the initiative to prevent service failures and service performance fluctuations, instead of triggering handlers when service errors occur. Effective prediction and analysis of the large-scale services performance is an effective and feasible proactive prevention tool. However, the traditional service performance prediction model mostly adopts the full batch training mode, it is difficult to meet the real-time requirements of large-scale service calculation. Based on the comprehensive trade-off between the method of full batch learning and the stochastic gradient descent method, a large-scale service performance prediction model is established based on online learning, and a service performance prediction method is proposed based on small batch online learning. Through properly setting the batch parameters, the proposed approach only need to train the sample data with small batches in one iteration, the time efficiency is improved for large-scale service performance prediction.
An Adaptive Push-Pull for Disseminating Dynamic Workload and Virtual Machine Live Migration in Cloud Computing
Authors: Naik K. Jairam
Published: May 2022

Adapting a dynamic load dissemination system for distributed computing pasture has become a hot spot problem of current research. In the instance of overloaded VM’s or node failure, the associated resources face difficult to determine which VM should be selected for load exchanging and/or how many VM’s should migrate to manage load imbalance. This work, introduces a Hierarchical Adaptive Push-Pull system for disseminating dynamic workload and live migration of VM’s among resources in the Cloud. Adhering to the Adaptive Push-Pull, Cloud Resources frequently pull’s the workload or through VM Managers based on load dynamics. In contrast, status information pertaining to Cloud Resources maintained by the Cloud Resource Managers that possess push capability to push the workload only to those VM’s which are capable enough to receive additional load. These two practices contain balancing possessions through efficient load management complications and simulation result addresses reduced load deviation and scalable resources utilization.
Evaluating the Presence of Hospitals on Social Media
Authors: AlHussainan Anwar F. , Jasem Zahraa A. , Alhuwail Dari
Published: May 2022

Today, adults are using social media to seek health information. Evidence suggests that hospitals using Instagram reported better patient engagement and in turn increased profit and reputation. Yet, little is known about how public and private hospitals are leveraging Instagram. This study aims to analyze the presence of hospitals on Instagram using Kuwait as a case study. Hospitals were identified using the Ministry of Health's website and Instagram. Posts collected from seven odd months were analyzed using the Constant Comparison method. A total of 3,439 posts were distributed across six categories: health advice and education, operations and services, current events, hospital community, seasonal occasions, and trivia. Public and private hospitals differed in their activity on Instagram in terms of health topics covered, post categories, and interactions. Hospitals should improve their presence on Instagram to promote healthy lifestyles, augment public health campaigns, and be a source of reliable and accessible health information online.
Digital Financial Inclusion
Authors: Srivastava Anushree
Published: May 2022

Digital financial inclusion is an issue which needs to be addressed in today's era. Its impact, reach and outcome were obvious at the time of corona. This paper highlights the significance of digital literacy and financial literacy and shows how the lack of these two can act as a roadblock in achieving digital financial inclusion along with demographic barriers. This paper highlights the factors relevant to achieve digital financial inclusion. For this primary data was collected from the respondents of the age group 18-60 having an education from intermediate to post graduate level coming from rural to metro regions working in an unorganized, contractual, self-job having an income base of 10000-40000. It was seen that digital and financial illiteracy varies along with education, income and regional boundaries. Financial and digital illiteracy was evident among many respondents due to lack of access, usage, aptitude and application. Proper financial training and knowledge can be a solution to this problem.
Meaning of New Means
Authors: Sharma Shudipta , Ahmed Salauddin , Hossain Md. Monjur
Published: May 2022

This paper aims to explore the economic impact of mobile banking on rural Bangladesh. It also tries to detect the rural people’s perception about this new financial phenomenon. To meet the goals this study involves both quantitative and qualitative investigation. To get the quantitative data a survey was conducted by a set questionnaire where 300 people from three villages participated. In the qualitative part, semi-structured in-depth interviews of 60 mobile bank users were conducted. Applying grounded theory and hermeneutics approaches, this study finds that since the service of mobile banking is easy and fast, rural people adopted it quickly and it affects positively in the socio-economic development in rural Bangladesh. Its impact on employment creation, business, savings behavior, remittance, expenditure, and agriculture is found good. However, it is also found that the mobile banking services are helping the criminals to do illegal economic activities such as forgery.