bluuebunny/crossref_metadata_2025 huggingface dataset:
Personalized Computer Support of Performance Rates and Education Process in High School: Case Study of Engineering Students
Authors: Zhiyenbayeva Nadezhda , Belyanova Elvira , Petunina Irina , Dmitrichenkova Svetlana , Dolzhich Elena
Published: March 2021

To date, the existing principles of a unified approach to schooling do not meet the requirements of a fundamental socio-economic transition characterized by personalization and customization of products and services that concern all areas, including education. The paradigm of education systems is being restructured in many countries towards a new approach of personalized learning that is adapted to students' needs, allows them to choose individual educational trajectories, and respects unique skills and qualities. The study aimed to determine the impact of personalization on the academic performance of engineering students in physics. The experiment on personalized student support was conducted during the academic year 2018-2019 at I.T. Trubilin Kuban State Agrarian University. The sample covered 78 students. The starting point of the research was the assessment of students' skills in mathematics, as the study of physics is based on mathematical analysis and interpretation. Test in physics and the criterion of alpha Kronbach (test reliability is determined with a coefficient of 0.87) were used as a toolkit for research. Besides, the statistical tools and covariance analysis of data processing were employed. The research was supported by the SPSS Statistics software package. According to the results obtained, higher post-test scores were recorded for students in the experimental group. The personalized learning has been found to have a significant impact on the academic performance of students. Those with low and medium ability in mathematics demonstrated higher growth in academic achievement than students with recorded high aptitude scores. A correlation between learning methods and mathematical skills to achieve high academic performance has been established. The influence of personalization in the learning process was determined to be moderately high (determinacy coefficient of 72.6%). The study is relevant for the development of constructive approaches that could help teachers improve their approach to learning and students improve academic achievements. The results may be of interest to researchers of educational technology, educators, and university administration management.
« Où est la frontière? »
Authors: Pârlea Vanezia
Published: March 2021

À l’époque des redéfinitions de l’interculturalité et des migrations mondialisées, une déconstruction de la notion de frontière comme celle proposée par Isabelle Eberhardt – que le présent article s’emploie à analyser – s’avère féconde, en préfigurant l’essor des « littératures migrantes » d’aujourd’hui. Fruit de multiples déplacements – identitaires, spatiaux, interculturels et idéologiques qui, bien que consubstantiels, seront analysés séparément, selon leur spécificité – la pensée eberhardtienne, empreinte de la logique d’une hybridation continuelle, en vient ainsi à construire une perspective dynamique de la frontière, envisagée non plus comme coupure ou barrière, mais comme pont, comme passage entre les cultures. En même temps, loin de toute idéalisation, cette sagesse de l’hybridité léguée par Isabelle Eberhardt n’est pas sans rappeler les écueils de la transculturalité qu’un être hybride, « déplacé », se doit d’affronter.
De l’Amérique à l’Europe des années 1920
Authors: Peloux Gérald
Published: March 2021

Les récits de voyage de l’écrivain japonais Tani Jōji (1900-1935) rédigés entre 1925 et 1930 sont caractéristiques d’une littérature japonaise de l’entre-deux-guerres qui connait une première mondialisation, avec des écrivains de plus en en plus cosmopolites voyageant à l’étranger. Tani Jōji a vécu en tant que travailleur itinérant de 1920 à 1924 dans le Midwest et à New York, puis a effectué un long périple européen de treize mois avec son épouse à la toute fin des années 1920. Il en rapporte chaque fois des récits au format moderniste, en complète osmose avec les recherches littéraires de l’époque. Ses textes sont actuellement plutôt étudiés du point de vue de l’immigration, des rapports interethniques. Notre article se propose d’analyser la question du déplacement dans ses récits viatiques, la manière dont celui-ci est présenté, mais aussi quelle influence ce paradigme a pu avoir sur son écriture.
Égypte, terre du Nil (1939) de Fernand Leprette : exemplarité du livre d’un intellectuel au service de deux pays, l’Égypte et la France
Authors: Lançon Daniel
Published: March 2021

L’étude porte sur Égypte, terre du Nil (1939) de Fernand Leprette, inspecteur français auprès du Ministère de l’Instruction Publique égyptien, poète, conférencier, mentor des écrivains francophones d’Égypte. Ce récit de vingt années de séjour en Égypte montre un écrivain humaniste, sensible, altruiste, porte-parole des hommes et des femmes du peuple, surtout des campagnes, passionné par sa « seconde patrie. » Le livre de cet intellectuel au service de deux pays, l’Égypte nation nouvelle se réappropriant sa personnalité orientale tout en s’ouvrant aux modernités européennes et la France, est le témoignage littéraire exemplaire d’un décentrement ayant abouti à l’accueil d’une altérité devenue intérieure.
« Marcher le plus longtemps possible ».Fantasmes et expériences du déplacement dans la poésie d’Iman Mersal (Égypte)
Authors: Dampierre-Noiray Ève de
Published: March 2021

Prenant comme perspective de départ la place occupée par le poème « Le Seuil » dans l’œuvre de la poétesse égyptienne Iman Mersal (née en 1966), texte phare à la fois par sa situation dans le parcours d’écriture, par sa portée poétique et politique, et par ses rapports structurels avec les images et motifs de l’ensemble de l’œuvre, l’article s’intéresse à la pensée du déplacement et à ses images, au seuil de l’expérience de l’émigration. Il tente de montrer par quels moyens poétiques est mise en scène une crise du lieu et du langage qui projette le sujet lyrique et le lecteur dans l’obsession du déplacement (errance frénétique dans l’espace autochtone, fatalité du départ à l’étranger), dans une impossible sédentarité ici comme là-bas, et dans une amertume politique, fantôme qui hante celui ou celle qui peut se définir comme un individu postcolonial.
Ezra Pound : Tel quel !
Authors: Contini Jean Christophe
Published: March 2021

Entre pardon inconditionnel et condamnation imprescriptible, la réception d’Ezra Pound en France est marquée par de nombreux paradoxes et de multiples zones d’ombre propres à l’identité et l’histoire du champ poétique et littéraire français. Soulignant son intérêt pour une étude comparatiste, cet article rappelle quelques éléments de cette réception qui débute véritablement au milieu des années 1960, notamment avec la publication du double Cahier de l’Herne impulsé par Dominique de Roux, mais également grâce aux textes de plusieurs acteurs de la revue Tel Quel comme Denis Roche, Philippe Sollers, Marcelin Pleynet.
Towards a Secure, Distributed, and Reliable Cloud-Based Reference Architecture for Big Data in Smart Cities
Authors: Kohler Jens , Specht Thomas
Published: March 2021

Current revolutions with respect to big data affect people's everyday life more and more. New ways of living, communication, and knowledge sharing have been created under the smart city umbrella. Information and communication technologies (ICT) are used to improve urban services. Examples are car sharing, energy consumption, adaptive traffic management, etc. A closer look at these services reveals that data, produced and consumed by people (or automatically by devices), are the cornerstone for working and reliable urban services. For this, large volumes of data with a great variety have to be processed at a high velocity which is commonly known as big data. This chapter designs a secure, distributed, and reliable cloud-based reference architecture that logically separates confidential data and distributes them to various databases in different clouds. It increases the reliability of the distributed data with high-availability mechanisms to protect data against various threads (e.g., hackers, terrorists, data collecting companies, etc.).
IoT Big Data Architectures, Approaches, and Challenges
Authors: Sarabia-Jácome David , Gonzalez-Usach Regel , Palau Carlos E.
Published: March 2021

The internet of things (IoT) generates large amounts of data that are sent to the cloud to be stored, processed, and analyzed to extract useful information. However, the cloud-based big data analytics approach is not completely appropriate for the analysis of IoT data sources, and presents some issues and limitations, such as inherent delay, late response, and high bandwidth occupancy. Fog computing emerges as a possible solution to address these cloud limitations by extending cloud computing capabilities at the network edge (i.e., gateways, switches), close to the IoT devices. This chapter presents a comprehensive overview of IoT big data analytics architectures, approaches, and solutions. Particularly, the fog-cloud reference architecture is proposed as the best approach for performing big data analytics in IoT ecosystems. Moreover, the benefits of the fog-cloud approach are analyzed in two IoT application case studies. Finally, fog-cloud open research challenges are described, providing some guidelines to researchers and application developers to address fog-cloud limitations.
Selection of Cloud Delivery and Deployment Models
Authors: Eid Mustafa I.M. , Al-Jabri Ibrahim M. , Sohail M. Sadiq
Published: March 2021

Research interests on cloud computing adoption and its effectiveness in terms of cost and time has been increasing. However, one of the challenging decisions facing management in adopting cloud services is taking on the right combinations of cloud service delivery and deployment models. A comprehensive review of literature revealed a lack of research addressing this selection decision problem. To fill this research gap, this article proposes an expert system approach for managers to decide on the right combination of service delivery and deployment model selection. The article first proposes a rule-based expert system prototype, which provides advice based on a set of factors that represent the organizational conditions and requirements pertaining to cloud computing adoption. Next, the authors evaluate the system prototype. Lastly, the article concludes with a discussion of the results, its practical implications, limitations, and further research directions.
Fault Tolerance Model for Efficient Actor Recovery Paradigm in WSAN
Authors: Mahjoub Reem Khalid , Elleithy Khaled
Published: March 2021

Wireless sensor and actor networks (WSAN) is an area where sensors and actors collaborate to sense, handle and perform tasks in real-time. Thus, reliability is an important factor. Due to the natural of WSAN, actor nodes are open to failure. Failure of actor nodes degrades the network performance and may lead to network disjoint. Thus, fault tolerance techniques should be applied to insure the efficiency of the network. In an earlier work, the authors proposed an efficient actor recovery paradigm (EAR) for WSAN which handles the critical actor node failure and recovery while maintaining QoS. EAR is supported with node monitoring and critical node detection (NMCND), network integration and message forwarding (NIMF), priority-based routing for node failure avoidance (PRNFA) and backup selection algorithms. In this article, the authors extend the work by adding a fault tolerance mathematical model. By evaluating the model, EAR shows to manage fault tolerance in deferent levels. To evaluate the effectiveness, the EAR fault tolerance is evaluated by simulation using OMNET++ Simulation. In addition, EAR reliability is measured and compared with RNF, DPCRA, ACR, and ACRA.
An Enhanced Task Scheduling in Cloud Computing Based on Deadline-Aware Model
Authors: Alworafi Mokhtar A. , Mallappa Suresha
Published: March 2021

Cloud computing is the latest in distributed computing technology. The delivery mechanism between the service provider and users depends on Service Level Agreement (SLA). SLA contains Quality of Service (QoS), which has some constraints such as deadline to achieve user satisfaction. In this article, the authors propose a Deadline-Aware Priority Scheduling (DAPS) model to minimize the average makespan, and maximize resource utilization under deadline constraint. In the proposed model, the tasks are sorted based on length priority in ascending order and labeling the VM's state as successful which achieves the deadline constraint, and then mapping the tasks to the suitable VM that has minimum processing time. The authors compared their proposed model to the existing algorithms GA, Min-Min, SJF and Round Robin. The proposed model outperforms other algorithms by reducing the average of makespan, mean of total average response time, number of violations, violation ratio, and failure ratio, while increasing resource utilization, and guarantee ratio for tasks that meet deadline constraint.
A Conceptual Model for Cloud-Based E-Training in Nursing Education
Authors: Samra Halima E. , Li Alice S. , Soh Ben , AlZain Mohammed A.
Published: March 2021

In specific fields, such as e-training in nursing, involving computer-intensive training scenarios, there is an increased demand to deliver training services to a larger number of learners, and with it, the need for cloud services. However, to date there has been a lack of a formalized framework relating to the use of cloud computing for on-demand interactive e-training resources in nursing education. To this end, this chapter formalizes a conceptual framework for a cloud-based e-training system in nursing education. The conceptualization takes into consideration nursing e-training system requirements, with a focus on applying cloud computing technologies to ensure the dynamic scalability of virtual distributed services and computing power while maintaining QoS and security.
A Framework for Collaborative and Convenient Learning on Cloud Computing Platforms
Authors: Sharma Deepika , Kumar Vikas
Published: March 2021

The depth of learning resides in collaborative work with more engagement and fun. Technology can enhance collaboration with a higher level of convenience and cloud computing can facilitate this in a cost effective and scalable manner. However, to deploy a successful online learning environment, elementary components of learning pedagogy must be embedded in the technology framework. A cloud computing technology based learning platform built on the proven learning pedagogies will be most successful attempt to facilitate collaborative and convenient learning. Such platform will support the learners to connect and coordinate the online resources in a more efficient, effective and practical way. This paper proposes a new theoretical framework for collaborative and convenient learning on cloud computing technology by reviewing various learning theories and integrating them with the technology framework. Architectural details of the framework have been presented with suitable examples for a better understanding. The work has a lot of significance for deploying cloud computing based collaborative learning solutions in the educational institutions.
A Hierarchical Hadoop Framework to Handle Big Data in Geo-Distributed Computing Environments
Authors: Tomarchio Orazio , Di Modica Giuseppe , Cavallo Marco , Polito Carmelo
Published: March 2021

Advances in the communication technologies, along with the birth of new communication paradigms leveraging on the power of the social, has fostered the production of huge amounts of data. Old-fashioned computing paradigms are unfit to handle the dimensions of the data daily produced by the countless, worldwide distributed sources of information. So far, the MapReduce has been able to keep the promise of speeding up the computation over Big Data within a cluster. This article focuses on scenarios of worldwide distributed Big Data. While stigmatizing the poor performance of the Hadoop framework when deployed in such scenarios, it proposes the definition of a Hierarchical Hadoop Framework (H2F) to cope with the issues arising when Big Data are scattered over geographically distant data centers. The article highlights the novelty introduced by the H2F with respect to other hierarchical approaches. Tests run on a software prototype are also reported to show the increase of performance that H2F is able to achieve in geographical scenarios over a plain Hadoop approach.
Image-Based 3D Reconstruction on Distributed Hash Network
Authors: Zhong Jin Hua , Fang Wan
Published: March 2021

In order to optimize the workflow of iterative 3D reconstruction and support the goal of massive image data processing, high performance and high scalability, this article proposes an image distributed computing framework FIODH. It is a distributed computing framework based on distributed hash algorithm, which accomplishes the task of storing, calculating and merging the image data in multiple nodes. A SIFT algorithm is used to extract feature points from the original images which are distributed on the hash nodes. During the process of image clustering computation, the agent nodes are responsible for task management and intermediate result calculation. The clustering results in hierarchical trees which can be converted into computational tasks and assigned to the appropriate nodes. The experimental analysis shows that the algorithm has achieved satisfactory results in efficiency and error adjustment. In a large amount of experiment data, the advantage of the algorithm is more obvious.
Big Data Processing on Cloud Computing Using Hadoop Mapreduce and Apache Spark
Authors: Samadi Yassir , Zbakh Mostapha , Haouari Amine
Published: March 2021

Size of the data used by enterprises has been growing at exponential rates since last few years; handling such huge data from various sources is a challenge for Businesses. In addition, Big Data becomes one of the major areas of research for Cloud Service providers due to a large amount of data produced every day, and the inefficiency of traditional algorithms and technologies to handle these large amounts of data. In order to resolve the aforementioned problems and to meet the increasing demand for high-speed and data-intensive computing, several solutions have been developed by researches and developers. Among these solutions, there are Cloud Computing tools such as Hadoop MapReduce and Apache Spark, which work on the principles of parallel computing. This chapter focuses on how big data processing challenges can be handled by using Cloud Computing frameworks and the importance of using Cloud Computing by businesses
An Ant-Colony-Based Meta-Heuristic Approach for Load Balancing in Cloud Computing
Authors: Dam Santanu , Mandal Gopa , Dasgupta Kousik , Dutta Parmartha
Published: March 2021

This book chapter proposes use of Ant Colony Optimization (ACO), a novel computational intelligence technique for balancing loads of virtual machine in cloud computing. Computational intelligence(CI), includes study of designing bio-inspired artificial agents for finding out probable optimal solution. So the central goal of CI can be said as, basic understanding of the principal, which helps to mimic intelligent behavior from the nature for artifact systems. Basic strands of ACO is to design an intelligent multi-agent systems imputed by the collective behavior of ants. From the perspective of operation research, it's a meta-heuristic. Cloud computing is a one of the emerging technology. It's enables applications to run on virtualized resources over the distributed environment. Despite these still some problems need to be take care, which includes load balancing. The proposed algorithm tries to balance loads and optimize the response time by distributing dynamic workload in to the entire system evenly.
Enhanced Security for Electronic Health Care Information Using Obfuscation and RSA Algorithm in Cloud Computing
Authors: Gautam Pratiksha , Ansari Mohd. Dilshad , Sharma Surender Kumar
Published: March 2021

Recently, the electronic heath record (EHR) has become the chosen method to maintain a patient's health information. The advancement of cloud computing enables users to access their data with flexibility, providing large storage capability at low costs, which encourages EHR maintainers to consider shifting from their own storage to the cloud. In cloud computing, it is no doubt that securing EHRs poses a gigantic challenge. Various security properties like access control, data privacy, and scalable access between different clouds needs to be satisfied. This article presents a secure and efficient blueprint for securing data confidentiality on cloud computing storage. The proposed framework is carried out for EHR confidential data on cloud storage. Moreover, the proposed approach combines the obfuscation and RSA encryption together to enforce confidentiality and authentication. Through this framework, the data confidentiality and authentication scheme on EHR information can be enforced on clouds storage.
From Cloud Computing to Fog Computing
Authors: Ahuja Sanjay P. , Deval Niharika
Published: March 2021

This article describes how in recent years, Cloud Computing has emerged as a fundamental computing paradigm that has significantly changed the approach of enterprises as well as end users towards implementation of Internet technology. The key characteristics such as on-demand resource provision, scalability, rapid elasticity, higher flexibility, and significant cost savings have influenced enterprises of all sizes in the wide and successful adoption of Cloud Computing. Despite numerous advantages, Cloud Computing has its fair share of downsides as well. One of those major concerns is latency issues which has relevance to the Internet of Things (IoT). A new computing paradigm has been proposed by Cisco in early 2014 and termed 'Fog Computing'. Fog Computing otherwise known as Edge Computing is the integration of Cloud Computing and IoT. Being located in close proximity to the IoT devices, the Fog assists with latency requirements of IoT related applications. It also meets the data processing needs of IoT devices which are resource constrained by bringing computation, communication, control and storage closer to the end users. Clouds continue to offer support for data analytics. One can think of the IoT-Fog-Cloud as being part of a continuum. This article surveys the current literature on Fog Computing and provides a discussion on the background, details and architecture of Fog Computing, as well as the application areas of Fog Computing. The article concludes with some recommendations in the areas of future research.
An Efficient Data Replication Algorithm for Distributed Systems
Authors: Panda Sanjaya Kumar , Naik Saswati
Published: March 2021

This article describes how data replication plays an important role in distributed systems. It primarily focuses on the redundancy of data at two or more nodes, to achieve both fault tolerance and improved performance. Therefore, many researchers have proposed various data replication algorithms to manage the redundancy of data. However, they have not considered the faults that are associated with the nodes, such as permanent, transient and intermittent. Moreover, they have not incorporated any recovery approach to rejoin the failed nodes. Therefore, the authors propose a data replication algorithm, called dynamic vote-based data replication (DVDR). The main contribution of DVDR is to consider all types of faults and rejoin the failed nodes. DVDR is based on dynamic vote assignment among the connected nodes, and referred as passive and non-hierarchical one. The authors perform rigorous analysis of DVDR and compare with an existing dynamic vote assignment algorithm. The result shows the efficacy of the proposed algorithm.
Cognitive Visual Analytics of Multi-Dimensional Cloud System Monitoring Data
Authors: Baciu George , Wang Yungzhe , Li Chenhui
Published: March 2021

Hardware virtualization has enabled large scale computational service delivery models with high cost leverage and improved resource utilization on cloud computing platforms. This has completely changed the landscape of computing in the last decade. It has also enabled large–scale data analytics through distributed high performance computing. Due to the infrastructure complexity, end–users and administrators of cloud platforms can rarely obtain a full picture of the state of cloud computing systems and data centers. Recent monitoring tools enable users to obtain large amounts of data with respect to many utilization parameters of cloud platforms. However, they fail to get the maximal overall insight into the resource utilization dynamics of cloud platforms. Furthermore, existing tools make it difficult to observe large-scale patterns, making it difficult to learn from the past behavior of cloud system dynamics. In this work, the authors describe a perceptual-based interactive visualization platform that gives users and administrators a cognitive view of cloud computing system dynamics.
Quality Evaluation of Cloud and Fog Computing Services in 5G Networks
Authors: Kitanov Stojan , Popovski Borislav , Janevski Toni
Published: March 2021

Because of the increased computing and intelligent networking demands in 5G network, cloud computing alone encounters too many limitations, such as requirements for reduced latency, high mobility, high scalability, and real-time execution. A new paradigm called fog computing has emerged to resolve these issues. Fog computing distributes computing, data processing, and networking services to the edge of the network, closer to end users. Fog applied in 5G significantly improves network performance in terms of spectral and energy efficiency, enable direct device-to-device wireless communications, and support the growing trend of network function virtualization and separation of network control intelligence from radio network hardware. This chapter evaluates the quality of cloud and fog computing services in 5G network, and proposes five algorithms for an optimal selection of 5G RAN according to the service requirements. The results demonstrate that fog computing is a suitable technology solution for 5G networks.
Perspectives of the Adoption of Cloud Computing in the Tourism Sector
Authors: Palos-Sanchez Pedro R. , Correia Marisol B.
Published: March 2021

This chapter aims to expose the current situation of the adoption of cloud computing in companies in general and in enterprises of the tourism sector in particular. For this, a review of the literature has been carried out to establish the conceptual framework of technology and of the new economic model that underlies its adoption. Cloud computing is one of the technologies less known to many organizations and especially users, as it is a new technology based on the Internet, through which information is stored on servers, is provided as a service and on clients' demand. Therefore, the main theories of adoption that have been used to explain the different adoption models are presented, as well as, the different solutions that are being used in the tourist industry.
Can Interlending and Document Supply Be Undervalued
Authors: Enakrire Rexwhite Tega
Published: March 2021

The multifarious task of information services, which academic libraries are saddled with, continues to require the support of interlending and document supply from other libraries, in order to meet users' increasing information needs. The rationale that spurs this drive was the shifting nature of operations from traditional to virtual/technological platforms. This article employed the qualitative research approach grounded on documents/textual content analysis of literature extracted from databases of Scopus, Science Direct, and LISTA. Findings revealed that academic libraries should utilize interlending and document supply to fulfill growing and diverse demands for information. The ability to fulfill information needs requires diverse knowledge and the skills of librarians, information resources, and infrastructure to strengthen interlending and document supply. The study recommends the adaptation of grey literature as part of the collection development, cooperation with library associations and securing funding for academic libraries in Nigeria as the way forward.
Security of Wireless Sensor Networks
Authors: Qabulio Mumtaz , Malkani Yasir Arfat , Memon Muhammad S. , Keerio Ayaz
Published: March 2021

Wireless sensor networks (WSNs) are comprised of large collections of small devices having low operating power, low memory space, and limited processing capabilities referred to as sensor nodes. The nodes in WSNs are capable of sensing, recording, and monitoring environmental conditions. Nowadays, a variety of WSNs applications can be found in many areas such as in healthcare, agriculture, industries, military, homes, offices, hospitals, smart transportation, and smart buildings. Though WSNs offer many useful applications, they suffer from many deployment issues. The security issue is one of them. The security of WSNs is considerable because of the use of unguided medium and their deployment in harsh, physically unprotected, and unattended environments. This chapter aims to discuss various security objectives and security attacks on WSNs and summarizes the discussed attacks according to their categories. The chapter also discusses different security protocols presented to prevent, detect, and recover the WSNs from various security attacks.
Solving Job Scheduling Problem in Computational Grid Systems Using a Hybrid Algorithm
Authors: Ghosh Tarun Kumar , Das Sanjoy
Published: March 2021

Grid computing is a high performance distributed computing system that consists of different types of resources such as computing, storage, and communication. The main function of the job scheduling problem is to schedule the resource-intensive user jobs to available grid resources efficiently to achieve high system throughput and to satisfy user requirements. The job scheduling problem has become more challenging with the ever-increasing size of grid systems. The optimal job scheduling is an NP-complete problem which can easily be solved by using meta-heuristic techniques. This chapter presents a hybrid algorithm for job scheduling using genetic algorithm (GA) and cuckoo search algorithm (CSA) for efficiently allocating jobs to resources in a grid system so that makespan, flowtime, and job failure rate are minimized. This proposed algorithm combines the advantages of both GA and CSA. The results have been compared with standard GA, CSA, and ant colony optimization (ACO) to show the importance of the proposed algorithm.
A Comparative Study and Algorithmic Analysis of Workflow Decomposition in Distributed Systems
Authors: Ali Ihtisham , Bagchi Susmit
Published: March 2021

Workflow is an essential mechanism for the automation of processes in distributed transactional systems, including mobile distributed systems. The workflow modeling enables the composition of process activities along with respective conditions, data flow and control flow dependencies. The workflow partitioning methods are used to create sub-partitions by grouping processes on the basis of activities, data flow and control flow dependencies. Mobile distributed systems consisting of heterogeneous computing devices require optimal workflow decomposition. In general, the workflow partitioning is a NP-complete problem. This article presents a comparative study and detailed analysis of workflow decomposition techniques based on graphs, petri nets and topological methods. A complete taxonomy of the basic decomposition techniques is presented. A detailed qualitative and quantitative analysis of these decomposition techniques are explained. The comparative analysis presented in this article provides an insight to inherent algorithmic complexities of respective decomposition approaches. The qualitative parametric analysis would help in determining the suitability of workflow applicability in different computing environments involving static and dynamic nodes. Furthermore, the authors have presented a novel framework for workflow decomposition based on multiple parametric parameters for mobile distributed systems.
An Overview of Cloud and Edge Computing Architecture and Its Current Issues and Challenges
Authors: Bhandari Guru Prasad , Gupta Ratneshwer
Published: March 2021

Edge computing is a technique of optimizing cloud computing systems by performing data processing at the edge of the network, near the source of the data in the systems. And, cloud computing is a service that delivers on-demand self-service, broad network access, resource pooling, rapid elasticity or expansion, which is trending in today's technology-driven world. With the advantage of flexibility, storage, sharing, and easy accessibility, cloud is being used by major players in IT (information technology). This chapter highlights cloud/edge computing architecture and its current issues and challenges from technological and organizational aspects. A brief introduction of edge computing architecture with similar technologies along with its service models is discussed. A few counterexamples of cloud computing architecture are showed. Organizational aspects of cloud computing architecture, as well as IBM and Oracle reference cloud architecture, are briefly presented. Some emerging issues and challenges associated with cloud/edge computing on its utilization are also elaborated.
Virtual Supercomputer Using Volunteer Computing
Authors: Shettar Rajashree , Niranjan Vidya , Reddy V. Uday Kumar
Published: March 2021

Invention of new computing techniques like cloud and grid computing has reduced the cost of computations by resource sharing. Yet, many applications have not moved completely into these new technologies mainly because of the unwillingness of the scientists to share the data over internet for security reasons. Applications such as Next Generation Sequencing (NGS) require high processing power to process and analyze genomic data of the order of petabytes. Cloud computing techniques to process this large datasets could be used which involves moving data to third party distributed system to reduce computing cost, but this might lead to security concerns. These issues are resolved by using a new distributed architecture for De novo assembly using volunteer computing paradigm. The cost of computation is reduced by around 90% by using volunteer computing and resource utilization is increased from 80% to 90%, it is secure as computation can be done locally within the organization and is scalable.
Associations of Plasma Glucagon Levels with Estimated Glomerular Filtration Rate, Albuminuria and Diabetic Kidney Disease in Patients with Type 2 Diabetes Mellitus
Authors: Huang Hua-Xing , Shen Liang-Lan , Huang Hai-Yan , Zhao Li-Hua , Xu Feng , Zhang Dong-Mei , Zhang Xiu-Lin , Chen Tong , Wang Xue-Qin , Xie Yan , Su Jian-Bin
Published: March 2021

Background: Type 2 diabetes mellitus (T2DM) is characterized by elevated fasting glucagon and impaired suppression of postprandial glucagon secretion, which may participate in diabetic complications. Therefore, we investigated the associations of plasma glucagon with estimated glomerular filtration rate (eGFR), albuminuria and diabetic kidney disease (DKD) in T2DM patients.Methods: Fasting glucagon and postchallenge glucagon (assessed by area under the glucagon curve [AUCgla]) levels were determined during oral glucose tolerance tests. Patients with an eGFR <60 mL/min/1.73 m2 and/or a urinary albumin-to-creatinine ratio (UACR) ≥30 mg/g who presented with diabetic retinopathy were identified as having DKD.Results: Of the 2,436 recruited patients, fasting glucagon was correlated with eGFR and UACR (r=–0.112 and r=0.157, respectively; P<0.001), and AUCgla was also correlated with eGFR and UACR (r=–0.267 and r=0.234, respectively; P<0.001). Moreover, 31.7% (n=771) presented with DKD; the prevalence of DKD was 27.3%, 27.6%, 32.5%, and 39.2% in the first (Q1), second (Q2), third (Q3), and fourth quartile (Q4) of fasting glucagon, respectively; and the corresponding prevalence for AUCgla was 25.9%, 22.7%, 33.7%, and 44.4%, respectively. Furthermore, after adjusting for other clinical covariates, the adjusted odds ratios (ORs; 95% confidence intervals) for DKD in Q2, Q3, and Q4 versus Q1 of fasting glucagon were 0.946 (0.697 to 1.284), 1.209 (0.895 to 1.634), and 1.521 (1.129 to 2.049), respectively; the corresponding ORs of AUCgla were 0.825 (0.611 to 1.114), 1.323 (0.989 to 1.769), and 2.066 (1.546 to 2.760), respectively. Additionally, when we restricted our analysis in patients with glycosylated hemoglobin <7.0% (n=471), we found fasting glucagon and AUCgla were still independently associated with DKD.Conclusion: Both increased fasting and postchallenge glucagon levels were independently associated with DKD in T2DM patients.
Genome-wide association analysis reveals regulation of at-risk loci by DNA methylation in prostate cancer
Authors: Liu Qiang , Liu Gang , Martin Darryl T , Xing Yu-Tong , Weiss Robert M , Qi Jun , Kang Jian
Published: March 2021

Epigenetic changes are potentially important for the ontogeny and progression of tumors but are not usually studied because of the complexity of analyzing transcript regulation resulting from epigenetic alterations. Prostate cancer (PCa) is characterized by variable clinical manifestations and frequently unpredictable outcomes. We performed an expression quantitative trait loci (eQTL) analysis to identify the genomic regions that regulate gene expression in PCa and identified a relationship between DNA methylation and clinical information. Using multi-level information published in The Cancer Genome Atlas, we performed eQTL-based analyses on DNA methylation and gene expression. To better interpret these data, we correlated loci and clinical indexes to identify the important loci for both PCa development and progression. Our data demonstrated that although only a small proportion of genes are regulated via DNA methylation in PCa, these genes are enriched in important cancer-related groups. In addition, single nucleotide polymorphism analysis identified the locations of CpG sites and genes within at-risk loci, including the 19q13.2–q13.43 and 16q22.2–q23.1 loci. Further, an epigenetic association study of clinical indexes detected risk loci and pyrosequencing for site validation. Although DNA methylation-regulated genes across PCa samples are a small proportion, the associated genes play important roles in PCa carcinogenesis.
When the State Imposes the “Commons”
Authors: Pons-Raga Ferran , Ferrer Lluís , Beltran Oriol , Vaccaro Ismael
Published: March 2021

After the brown bear reintroduction program was launched in the Pyrenees in 1996, the French and Spanish States fostered and funded a regrouping policy to protect the sheep flocks from the bear attacks. Drawing on a comparative analysis between two Catalan districts in north-eastern Spain (Val d'Aran and Pallars Sobirà) and the Ariège district in south-western France, this article scrutinises the extent to which the transformation of shepherding practices induced by the renewed presence of bears can be deemed as a return of the ‘commons’ to the Pyrenees. The emergence of public regrouped herds resembles an old and until then abandoned pastoral format, the communal herd. However, this iteration of collective action is promoted and tightly controlled by the State, whereas previously, local farmers used to manage the old communal system themselves. The regrouping policy mimics the morphology of locally generated models following historical property rights logic, while incorporating a modern form of public governmentality. The conceptualisation of property as a bundle of rights and the two ethnographic studies serve to critically engage with the notion of the commons and their return. The literature on environmentality and territorialisation allows us to read this State-driven policy through the lenses of imposition and dispossession.
Risk of chronic kidney disease and end-stage renal disease in patients with psoriasis
Authors: Yang Shang-Feng , Chen Ting-Hao , Tsai Shin-Hung , Chen Pei-En , Chi Ching-Chi , Tung Tao-Hsin
Published: March 2021

Background:

Previous studies showed a higher risk of renal disease among patients with psoriasis; however, this association has been inconsistent.

Objectives:

This study aimed to carry out a comparison in the probability from suffering renal diseases—including chronic kidney disease (CKD), end-stage renal disease (ESRD), IgA nephropathy (IgAN), glomerular disease (GD), and those resulting in death caused by other renal diseases—in patients with psoriasis.

Methods:

The systematic review and meta-analysis was conducted to identify cohort studies with reported hazard ratios (HRs) and a 95% confidence intervals (CIs) for the renal outcomes among patients with psoriasis. The meta-analysis was analyzed with the random-effects modeling and was further stratified by psoriasis severity.

Results:

Three studies were included. Compared to controls without psoriasis, patients with psoriasis had increased risks of CKD (HR: 1.53; 95% CI: 1.20–1.96) and ESRD (HR: 1.24, 95% CI: 1.06–1.46). The risks of CKD (HR: 1.91, 95% CI: 1.78–2.05) and ESRD (HR: 2.72, 95% CI: 1.71–4.34) were increased in servere psoriasis patients. Due to substantial heterogeneity across enrolled studies (I
2 = 95%), the risk of CKD in mild psoriasis was insignificant (HR: 1.14, 95% CI 0.87–1.48). Two studies identified severe psoriasis were related to higher risks of IgAN and GD, whereas one study found that mild psoriasis was associated with an increased risk of death from renal disease.

Conclusion:

Patients with severe psoriasis have a higher risk of incident CKD, ESRD, and GD. However, we only identified two cohort studies that compared the risk of IgAN and GD in psoriasis patients to general populations. It is difficult to conclude that severe psoriasis was associated with higher risks of IgAN and GD. For mild psoriasis, the association with renal disease was less consistent.
A population-based observational morphologic measurements of anatomic landmarks in maxillary and mandibular molar
Authors: Agarwal Esha , Nikhil Vineeta
Published: March 2021

Aim:

The aim of this study is to study the morphological measurements of external and internal anatomic landmarks in human maxillary and mandibular molars and their correlation with critical pulp chamber morphology.

Materials and Methods:

A total of 200 mandibular and maxillary molar teeth of patients were evaluated. Teeth whose pulp chamber were not violated by caries, restoration, fracture crown, and those having closed apex were included in the study. Teeth were subjected to radiovisiography of bitewing projection and imaging tool was utilized for measuring-A: Distance from the pulp chamber floor to the furcation, B: Distance from the pulp chamber ceiling to the furcation, C: Distance from the buccal cusp tip to the furcation, D: Distance from the buccal cusp to the floor of the pulp chamber, E: Distance from the buccal cusp to the ceiling of pulp chamber, and F: Pulp chamber height. Differences in the measurements were examined using the Student's t-test and Pearson correlations. All results were considered statistically significant if P < 0.05.

Results:

There were significant differences found among the various measurements between young and old population groups (P < 0.05). The highest percentage variance was found for the height of the pulp chamber (P < 0.001).

Conclusions:

The knowledge of pulp chamber morphology should be integrated with preoperative radiograph and intraoperative tactile perception during endodontic access preparation.
A comparative evaluation of the shaping ability of four different single-file systems in severely curved mesiobuccal root canals of mandibular first molars
Authors: Pathak Vivek Kumar , Singhal Rajnish K , Jain Anurag , Mankeliya Saurabh , Singh Kaushal , Sharma Ashish
Published: March 2021

Aim:

The aim of this study was to compare the shaping ability of four different single-file systems in severely curved mesiobuccal root canals in extracted human mandibular first molars.

Materials and Methods:

Sixty extracted intact human mandibular first molars with at least one curved mesial root were collected and used for the study. The study samples (n = 60) were divided into four experimental groups (n = 15 each): WaveOne (WO) (Group I), WaveOne Gold (WOG) (Group II), OneShape (Group III), and F360 (Group IV). The working length was established. All the study samples were prepared with respective file systems according to manufacturer's instructions. Pre- and postinstrumentation radiographs were taken and images were transferred to AutoCAD 2016 to determine the radius of curvature of each root canal. The canal curvature was assessed as a difference between before and after instrumentation to determine canal straightening. The data obtained were subjected to statistical analysis using SPSS version 20.0.

Results:

The pre- and postinstrumentation readings were compared using one-sample t-test, and difference was found to be statistically significant (P < 0.05). The mean difference in root curvature was estimated by pre- and postinstrumentation readings. According to mean change in the root curvature, the order determined was Group IV < III < II < I. Intergroup comparison was conducted using ANOVA statistical analysis, and it was found to be statistically significant.

Conclusion:

WOG and WO reciprocating files showed a marked tendency to straighten the severely curved canals, whereas F360 and OneShape continuous files maintained the original canal curvatures well.
Comparative evaluation of antimicrobial efficacy of Asphaline Temp, Triple antibiotic Paste and Ultracal XS against Enterococcus faecalis – An in vitro study
Authors: Bandekar Siddhesh , Amin Aditi , Kshirsagar Shirin , Vathsala N , Chinmay Vyas , Sayyad Anjum
Published: March 2021

Aim:

This study aimed to evaluate and compare the antimicrobial efficacy of asphaline temp, triple antibiotic paste (TAP), and Ultracal Xs against Enterococcus faecalis – An in vitro study.

Materials and method:

A hundred and twenty freshly extracted, single-rooted human permanent teeth were instrumented and autoclaved. Samples were inoculated with the pure culture of E. faecalis and incubated. After incubation, colony-forming units (CFUs) were recorded before medication. Each group was further divided into three subgroups containing ten samples each for days – 1 day, 5 days, and 7 days. Group A – Asphaline Temp; Group B – TAP; Group C – Calcium hydroxide; and Group D – Normal saline (Control). The various time interval bacterial (CFU) within the group were compared by the Analysis of Variance followed by Tukey's Post hoc test.

Results:

The greater antimicrobial effects were observed in the samples treated with Asphaline temp (P < 0.005). No statistical antimicrobial difference was found between Asphaline temp and TAP.

Conclusion:

Asphaline temp demonstrated significant antimicrobial effectiveness against E. faecalis.