WoS
Permanent URI for this collectionhttps://hdl.handle.net/20.500.14411/18
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Article Citation - WoS: 21Citation - Scopus: 48Customer Relationship Management: Implementation Process Perspective(Budapest Tech, 2009) Mishra, Alok; Mishra, Deepti; Computer Engineering; Software EngineeringCustomer relationship management (CRM) can help organizations manage customer interactions more effectively to maintain competitiveness in the present economy. As more and more organizations realize the significance of becoming customer-centric in today's competitive era, they adopted CRM as a core business strategy and invested heavily. CRM, an integration of information technology and relationship marketing, provides the infrastructure that facilitates long-term relationship building with customers at an enterprise-wide level. Successful CRM implementation is a complex, expensive and rarely technical projects. This paper presents the successful implementation of CRM from process perspective in a trans-national organization with operations in different segments. This study will aid in understanding transition, constraints and the implementation process of CRM in such organizations.Article Citation - WoS: 11Citation - Scopus: 16Improving Baggage Tracking, Security and Customer Services With Rfid in the Airline Industry(Budapest Tech, 2010) Mishra, Deepti; Mishra, Alok; Computer Engineering; Software EngineeringRadio frequency identification (RFID) has been identified as one of the ten greatest contributory technologies of the 21(st) Century. This technology has found a rapidly growing market, and an increasing variety of enterprises are employing RFID to improve the efficiency of their operations and to gain competitive advantage. In the aviation industry, major airports/airlines have been looking for the opportunity to adopt RFID in the area of baggage handling for a long time. Many pilot tests have been done at numerous US., European, and Hong Kong airports. RFID tags were found to be far more accurate than bar codes, and their performance was also measured to be well above that of bar codes. This paper presents the state of RFID adoption planning, architecture and implementation at a major airline, with a special focus on improved services due to improved baggage handling, on increased airport/airline security and on frequent flier program services. This is accomplished by integrating RFID technology together with networking and database technologies.Article Citation - WoS: 4Citation - Scopus: 3A Legal Business Information System: Implementation Process Context(Budapest Tech, 2011) Mishra, Alok; Mishra, Deepti; Computer Engineering; Software EngineeringInformation Technology (IT) is fast becoming useful in implementing time, case, manpower and cost management strategies within judicial services. The legal system environment has adopted IT not just to save costs and time but also to give organizations a competitive edge and to ensure security as well. The Legal Business Information System is a fully operational and integrated system for a legal department. The mission of the department is to provide innovative and quality services in insolvency and trustee matters. Very few legal business information system implementations are documented in literature. Therefore this paper will facilitate understanding of system implementation in this sector.Article Citation - WoS: 5Citation - Scopus: 11Erp Project Implementation: Evidence From the Oil and Gas Sector(Budapest Tech, 2011) Mishra, Alok; Mishra, Deepti; Computer Engineering; Software EngineeringEnterprise Resource Planning (ERP) systems provide integration and optimization of various business processes, which can lead to improved planning and decision quality, and a smoother coordination between business units, resulting in higher efficiency and a quicker response time to customer demands and inquiries. This paper reports the challenges and opportunities and the outcome of an ERP implementation process in the Oil & Gas exploration sector. This study will facilitate the understanding of the transition, constraints, and implementation process of ERP in this sector and will also provide guidelines from lessons learned in this regard.Article Citation - WoS: 17Citation - Scopus: 24Iot Platform for Seafood Farmers and Consumers(Mdpi, 2020) Jaeger, Bjorn; Mishra, Alok; Jæger, BjørnThere has been a strong growth in aquatic products supported by the global seafood industry. Consumers demand information transparency to support informed decisions and to verify nutrition, food safety, and sustainable operations. Supporting these needs rests on the existence of interoperable Internet of Things (IoT) platforms for traceability that goes beyond the minimum "one up, one down" scheme required by regulators. Seafood farmers, being the source of both food and food-information, are critical to achieving the needed transparency. Traditionally, seafood farmers carry the costs of providing information, while downstream actors reap the benefits, causing limited provision of information. Now, global standards for labelling, data from IoT devices, and the reciprocity of utility from collecting data while sharing them represent great potential for farmers to generate value from traceability systems. To enable this, farmers need an IoT platform integrated with other IoT platforms in the value network. This paper presents a case study of an enterprise-level IoT platform for seafood farmers that satisfies consumers' end-to-end traceability needs while extracting data from requests for information from downstream actors.Review Citation - WoS: 74Citation - Scopus: 119Devops and Software Quality: a Systematic Mapping(Elsevier, 2020) Mishra, Alok; Otaiwi, ZiadoonQuality pressure is one of the factors affecting processes for software development in its various stages. DevOps is one of the proposed solutions to such pressure. The primary focus of DevOps is to increase the deployment speed, frequency and quality. DevOps is a mixture of different developments and operations to its multitudinous ramifications in software development industries, DevOps have attracted the interest of many researchers. There are considerable literature surveys on this critical innovation in software development, yet, little attention has been given to DevOps impact on software quality. This research is aimed at analyzing the implications of DevOps features on software quality. DevOps can also be referred to a change in organization cultures aimed at removal of gaps between the development and operations of an organization. The adoption of DevOps in an organization provides many benefits including quality but also brings challenges to an organization. This study presents systematic mapping of the impact of DevOps on software quality. The results of this study provide a better understanding of DevOps on software quality for both professionals and researchers working in this area. The study shows research was mainly focused in automation, culture, continuous delivery, fast feedback of DevOps. There is need of further research in many areas of DevOps (for instance: measurement, development of metrics of different stages to assess its performance, culture, practices toward ensuring quality assurance, and quality factors such as usability, efficiency, software maintainability and portability). (C) 2020 The Author(s). Published by Elsevier Inc.Article Citation - WoS: 12Citation - Scopus: 17A Novel Framework Using Deep Auto-Encoders Based Linear Model for Data Classification(Mdpi, 2020) Karim, Ahmad M.; Kaya, Hilal; Guzel, Mehmet Serdar; Tolun, Mehmet R.; Celebi, Fatih V.; Mishra, AlokThis paper proposes a novel data classification framework, combining sparse auto-encoders (SAEs) and a post-processing system consisting of a linear system model relying on Particle Swarm Optimization (PSO) algorithm. All the sensitive and high-level features are extracted by using the first auto-encoder which is wired to the second auto-encoder, followed by a Softmax function layer to classify the extracted features obtained from the second layer. The two auto-encoders and the Softmax classifier are stacked in order to be trained in a supervised approach using the well-known backpropagation algorithm to enhance the performance of the neural network. Afterwards, the linear model transforms the calculated output of the deep stacked sparse auto-encoder to a value close to the anticipated output. This simple transformation increases the overall data classification performance of the stacked sparse auto-encoder architecture. The PSO algorithm allows the estimation of the parameters of the linear model in a metaheuristic policy. The proposed framework is validated by using three public datasets, which present promising results when compared with the current literature. Furthermore, the framework can be applied to any data classification problem by considering minor updates such as altering some parameters including input features, hidden neurons and output classes.Article Citation - WoS: 47Citation - Scopus: 73Software architecture of the internet of things (IoT) for smart city, healthcare and agriculture: analysis and improvement directions(Springer Heidelberg, 2021) Gavrilovic, Nebojsa; Mishra, AlokInternet of things (IoT) enables organizations to automate the process and improves service delivery through Internet technology and transferring the data at the cloud level. IoT does not allow the use of a universal software architecture for different fields in which it is used, but needs to be adjusted according to the requirements of users. This paper presents an analysis of currently available types of software architectures of the IoT systems in the field of smart cities, healthcare, and agriculture. It provides a proposal for solutions and improvements of different software architecture types, interactions between identified software architecture elements that will provide better performance and simplicity. The novelty of the study is the analysis of different types of IoT software architecture such as: layered, service-oriented and cloud-based software architecture application in these areas of IoT. Based on the analysis, the study proposed the type of software architecture of the IoT system for the relevant area of application (smart city, healthcare, and agriculture). Specific points of research are: analysis of different types of software architecture applied in IoT systems, identification of functionalities available in IoT systems through different types of software architecture, the proposal for enhancement of the above functionalities, and proposal of software architecture that is most relevant to the IoT system of a particular area.Article Citation - WoS: 12Citation - Scopus: 20Algorithm for Adaptive Learning Process and Improving Learners' Skills in Java Programming Language(Wiley, 2018) Gavrilovic, Nebojsa; Arsic, Aleksandra; Domazet, Dragan; Mishra, AlokAdaptive approaches within distance learning systems enable adapting teaching process to the needs of each learner during the learning process. This paper presents an algorithm for creating an adaptive learning process that provides knowledge and skills improvement for learners in the Java programming language. Also, it presents the application of the tool that checks the learner's knowledge through solving practical tasks from the Java programming language. The adaptive learning process in this work leads the learner through teaching materials and practical tasks where the acquired knowledge is required to be applied. Also, the algorithm, based on the measurement of knowledge and time spent on a particular part of the learning process with detailed feedback and the demonstration of observed deficiencies, directs the learner to teaching materials that allow improving the demonstrated knowledge. Teaching materials are conceived as learning objects and, as such, allow for the application of adaptive approach. An analysis of the effectiveness of the algorithm and tool for practical knowledge testing from the Java programming language was done with a test group of learners who gave their opinions and grades.Article Citation - WoS: 21Citation - Scopus: 38Deep Learning-Based Computer-Aided Diagnosis (cad): Applications for Medical Image Datasets(Mdpi, 2022) Kadhim, Yezi Ali; Khan, Muhammad Umer; Mishra, AlokComputer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the best optimal features while reducing the amount of data. Lastly, diagnosis prediction (classification) is achieved using learnable classifiers. The novel framework for the extraction and selection of features is based on deep learning, auto-encoder, and ACO. The performance of the proposed approach is evaluated using two medical image datasets: chest X-ray (CXR) and magnetic resonance imaging (MRI) for the prediction of the existence of COVID-19 and brain tumors. Accuracy is used as the main measure to compare the performance of the proposed approach with existing state-of-the-art methods. The proposed system achieves an average accuracy of 99.61% and 99.18%, outperforming all other methods in diagnosing the presence of COVID-19 and brain tumors, respectively. Based on the achieved results, it can be claimed that physicians or radiologists can confidently utilize the proposed approach for diagnosing COVID-19 patients and patients with specific brain tumors.