Includes bibliographical references.

Article 1. The Design of Power Security Defense System Based on Resource Pool Cloud Computing Technology -- Article 2. A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue: Join Minimum Loaded Queue -- Article 3. Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features -- Article 4. A Set of Usability Heuristics and Design Recommendations for Higher Education Institutions' Websites -- Article 5. Volumetric Estimation of the Damaged Area in the Human Brain from 2D MR Image -- Article 6.A Blur Classification Approach Using Deep Convolution Neural Network.

[Article Title: The Design of Power Security Defense System Based on Resource Pool Cloud Computing Technology / Dang Nan, p. 1-11]

Abstract: In order to realize the power system defense security, this article puts forward the idea and method of constructing power dispatching automation systems with a cloud computing architecture and realizes the unified management of distributed resources with server virtualization technology. Real-time online migration of each module of the scheduling system is realized by using the in-memory data transfer technology. The multi-node network heartbeat detection technology is used to realize the complete monitoring of the server cluster. In the form of an independent disk array, the fault node is removed, and the service is restored automatically. The whole disaster reserve of the system is realized by means of remote resource mapping. System analysis results show that compared with traditional architecture, the service interruption probability of the new scheduling automation system is effectively reduced. Fault redundancy capacity in the station is increased from a key module 2 node to multi-node protection of all modules.

https://doi.org/10.4018/IJISMD.2020010101

[Article Title: A Proficient Approach for Load Balancing in Cloud Computing-Join Minimum Loaded Queue: Join Minimum Loaded Queue / Minakshi Sharma, Rajneesh Kumar, and Anurag Jain, p. 12-36]

Abstract: Cloud load balancing is done to persist the services in the cloud environment along with quality of service (QoS) parameters. An efficient load balancing algorithm should be based on better optimization of these QoS parameters which results in efficient scheduling. Most of the load balancing algorithms which exist consider response time or resource utilization constraints but an efficient algorithm must consider both perspectives from the user side and cloud service provider side. This article presents a load balancing strategy that efficiently allocates tasks to virtualized resources to get maximum resource utilization in minimum response time. The proposed approach, join minimum loaded queue (JMLQ), is based on the existing join idle queue (JIQ) model that has been modified by replacing idle servers in the I-queues with servers having one task in execution list. The results of simulation in CloudSim verify that the proposed approach efficiently maximizes resource utilization by reducing the response time in comparison to its other variants.

https://doi.org/10.4018/IJISMD.2020010102

[Article Title: Multimodal Biometric Based on Fusion of Ridge Features with Minutiae Features and Face Features / Law Kumar Singh, Munish Khanna, and Hitendra Garg, p. 37-57]

Abstract: Multimodal biometrics refers to the exploiting combination of two or more biometric modalities in an identification of a system. Fingerprint, face, retina, iris, hand geometry, DNA, and palm print are physiological traits while voice, signature, keystrokes, gait are behavioural traits used for identification by a system. Single biometric features like faces, fingerprints, irises, retinas, etc., deteriorate or change with time, environment, user mode, physiological defects, and circumstance therefore integrating multi features of biometric traits increase robustness of the system. The proposed multimodal biometrics system presents recognition based on face detection and fingerprint physiological traits. This proposed system increases the efficiency, accuracy and decreases execution time of the system as compared to the existing systems. The performance of proposed method is reported in terms of parameters such as False Rejection Rate (FRR), False Acceptance Rate (FAR) and Equal Error Rate (EER) and accuracy is reported at 95.389%.

https://doi.org/10.4018/IJISMD.2020010103

[Article Title: A Set of Usability Heuristics and Design Recommendations for Higher Education Institutions' Websites / Bhim Sain Singla and Himanshu Aggarwal, p. 58-73]

Abstract: Usability evaluation of a website is a key element in identifying the areas where the end-users might experience problems while interacting with it. The usability parameter has a great impact on the performance of a website, an organization's image, user satisfaction, and their intention to revisit the site. In the recent past, there has been a tremendous increase in the use of websites for seeking requisite information about admission to various courses offered by higher education institutions. There has been a lack of an effective and efficient set of heuristics that can be used to evaluate the usability of these education institution websites. The present study differs from earlier studies by providing a new set of 43 usability heuristics and categorizing them into eight distinct factors on the basis of their empirical validation. These eight identified factors exhibit strong psychometric properties and are ease of navigation, design quality, information architecture, credibility, functionality quality, content quality, simplicity, and learnability. The findings of this study are highly useful for the website designers and evaluators of higher education institutions' websites, who are concerned with evaluating and improving the usability of these websites. The findings of this study have theoretical as well as practical implications.

https://doi.org/10.4018/IJISMD.2020010104

[Article Title: Volumetric Estimation of the Damaged Area in the Human Brain from 2D MR Image / P Naga Srinivasu, T Srinivasa Rao, and Valentina Emilia Balas, p. 74-92]

Abstract: In this article, we present a volumetric estimate of the mutilated part in the human brain from a typical 2D MR image that is directly rendered from the scanner, which is first of its kind in the field of medical imaging. The proposed concept necessitates segmentation of the MR image for the identification of dimensions in the damaged region. Once the dimensions are identified from the resultant segmented image, the volume of the damaged region is evaluated through the Gauss Derivation theorem. The pixel to the distance scaling, which is fed as an input for the Gauss Derivation is from an earlier medical diagnosis from another researcher. The proposed algorithm was experimented with real-time images and the obtained results were examined against the real-time scenarios and were observed to exhibit better accuracy.

https://doi.org/10.4018/IJISMD.2020010105

[Article Title: A Blur Classification Approach Using Deep Convolution Neural Network / Shamik Tiwari, p. 93-111]

Abstract: Computer vision-based gesture identification is designed to recognize human actions with the help of images. During the process of gesture image acquisition, images suffer various degradations. The method of recovering these degraded images is called restoration. In the case of blind restoration of such a degraded image where blur information is unavailable, it is essential to determine the exact blur type. This article presents a convolution neural network model for blur classification which categories a blur found in a hand gesture image into one of the four blur categories: motion, defocus, Gaussian, and box blur. The simulation results demonstrate the improved preciseness of the CNN model when compared to the MLP model.

https://doi.org/10.4018/IJISMD.2020010106