Computer and Information Science

Journal Information
ISSN / EISSN : 19138989 / 19138997
Current Publisher: Canadian Center of Science and Education (10.5539)
Total articles ≅ 817
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Sergey Voronin
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p80

Abstract:Many situations arise where data is collected continuously across multiple channels or over multiple similar subjects. In many cases, transmission of the data across all channels is necessary, but the process can be made more efficient by making use of present similarity between data across different channels. We present here a combined compression approach which exploits approximate linear dependence and high correlation coefficient values between pairs of transformed and sorted channel data vectors. By exploiting this similarity, substantial compression gains can be achieved compared to compression of data per each individual channel.
Chris Lee
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p90

Abstract:Reviewer Acknowledgements for Computer and Information Science, Vol. 13, No. 1, 2020
Derek Hall, Timothy Sands
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p72

Abstract:The nuclear inventory of Russia and the USA currently comprises 12,685 warheads in a large network of vehicles; and the interconnected network is managed by a command and control communication system. This command and control communication system (C3) must also relay information from numerous airborne, space-born, and ground sensors throughout the network in potentially degraded environments and are nonetheless meant to securely hold transmissions that must be held to the highest standards of encryption. C3 systems are also arguably one of the most challenging systems to develop, since they require far more security, reliability, and hardening compared to typical communication systems, because they typically must (absolutely) work while other systems fail. Systems used for C3 are not always cutting-edge technology, but they must be upgraded at crucial junctures to keep them at peak performance. This manuscript outlines a blueprint of a way to embed current and future systems with revolutionary encryption technology. This will transform the security of the information we pass to our C3 assets adding redundancy, flexibility, and enhanced speed and insure vehicles and personnel in the system receive network message traffic. Quantum key distribution (QKD) has the potential to provide nearly impregnable secure transmissions, increased bandwidth, and additional redundancy for command and control communication (C3). While QKD is still in its adolescence, how QKD should be used or C3 must be charted out before it can be engineered, tested, and implemented for operations. Following a description QKD functionality, its pros and cons, we theorize the best implementation of a QKD system for C3.
Yijie Han, Hemasree Koganti, Nikita Goyal
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p51

Abstract:We show that n integers in {0, 1, …, m-1} can be sorted into a linked list in constant time using nlogm processors on the Priority CRCW PRAM model, and they can be sorted into a linked list in O(loglogm/logt) time using nt processors on the Priority CRCW PRAM model.
Saloua Bennani, Iliass Ait El Kouch, Mahmoud El Hamlaoui, Sophie Ebersold, Bernard Coulette, Mahmoud Nassar
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p58

Abstract:Complex systems are typically designed collaboratively by stakeholders from different domains. This multi viewpoints paradigm promotes the separation of concerns since separate teams, from different business viewpoints, build partial models describing the system. These partial models are naturally heterogeneous. So, it is difficult to ensure their intermodel consistency if kept separately. For that, we propose a collaborative approach that combines Group Decision Making (GDM) and Model-Based Engineering (MBE). This paper highlights the GDM part of our approach and especially the concept of decision policy that enables coming up with collective decisions in group decision-making contexts.
Fahad Omar Alomary
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p34

Abstract:Several years ago Key Performance Indicators (KPIs) becoming a best measurement practiced by the government sectors. The Ministry of Higher Education in Saudi Arabia opens up to new technology, opportunities, and improved ways to acquire and disseminate scientific teaching and research to bring quality at par with the international standards. KPIs provide quality assurance to the scientific research and higher education. The KPIs are variable and designed specifically for a particular entity such as education, research, finance, operation management etc. Scientific research in Saudi Arabia needs special attention from governing bodies and those who are already involved in scientific research. In case of Al-Imam Muhammad Ibn Saud Islamic University (IMAMU), performance indicators are implemented but with skepticism. In future research, the Ministry of Higher Education, Saudi Arabia should provide the best indicators to measure the performance of Saudi universities by putting some value added in implementation of KPIs. Furthermore, third parties such as government servant and stakeholders should togetherness in performing their jobs to make sure everybody is complying with KPIs sets by its agencies.
Satish Gajawada, Hassan M. H. Mustafa
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p41

Abstract:Nature Inspired Optimization Algorithms have become popular for solving complex Optimization problems. Two most popular Global Optimization Algorithms are Genetic Algorithms (GA) and Particle Swarm Optimization (PSO). Of the two, PSO is very simple and many Research Scientists have used PSO to solve complex Optimization Problems. Hence PSO is chosen in this work. The primary focus of this paper is on imitating God who created the nature. Hence, the term "Artificial God Optimization (AGO)" is coined in this paper. AGO is a new field, which is invented in this work. A new Algorithm titled "God Particle Swarm Optimization (GoPSO)" is created and applied on various benchmark functions. The World's first Hybrid PSO Algorithm based on Artificial Gods is created in this work. GoPSO is a hybrid Algorithm, which comes under AGO Field as well as PSO Field. Results obtained by PSO are compared with created GoPSO algorithm. A list of opportunities that are available in AGO field for Artificial Intelligence field experts are shown in this work.
Imane Haddar, Brahim Raouyane, Mostafa Bellafkih
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p20

Abstract:With the on-going trends of the telecom services, the number of service providers with similar functionalities is undergoing a rapid growth. The customers face the difficulty to decide which service provider can satisfy their needs and full their requirements. Negotiating contracts between involved parts, and hiding heterogeneity in the distributed network environment has been challenging for telecom operators and service providers. Different languages exist to describe the Service Level Agreement (SLA), which is a contract between a service provider and a customer. However, since each service provider expresses his SLA in his own way, it disrupts the customer's choice of the best service provider, and leads to a bad contract management. In this respect, we propose a novel architecture for service selection, and SLA management between different stakeholders in our network architecture. The idea is to set up a smart broker where we implemented a Multi-Criteria Decision Making (MCDM) method to maximize utility function so that the customer can choose services with required QoS performances. We also came up with the idea of settling a negotiation model for the SLA, and a context based SLA contract ontology in IP Multimedia Subsystem (IMS) network is also proposed to provide users with a clear model to express their requirements and preferences. Moreover, we used the New Generation Operations Systems and Software (NGOSS) Framework to model and analyze networks and services actions. To better understand the relationship and the projection of NGOSS Framework and IMS platform, we introduce an SLA management and monitoring architecture in IMS network.
Asmae Benali, Bouchra El Asri
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p10

Abstract:Day after day, the number of mobile applications deployed on cloud computing continues in increasing because of smartphone capabilities improvement. Cloud computing has already succeeded in the web-based application, for that reason, the demand for context-aware services provided by cloud computing increases. To customize a cloud service that takes into account the consumer requirements, which depend on information change, it brings to light many recent challenges to cloud computing about environment-aware, location-aware, time-aware. The cloud provider, moreover, has to manage personalized applications and the constraints of mobile devices in matters of interaction abilities and communication restrictions. This paper proposes a strategy for selecting automatically an appropriate cloud environment that runs out whole requirements, defines a configuration for the associated cloud environment and able to easily adapt to the change of the environment on either the user or the cloud side or both. This process builds on the principles of dynamic software product lines, Agent-oriented software engineering, and the MAPE-k model to select and configure cloud environments according to the consumer needs and the context change.
Awoyelu I. O., Ojo B. R., Aregbesola S. B., Soyele O. O.
Computer and Information Science, Volume 13; doi:10.5539/cis.v13n1p1

Abstract:This paper extracted features from region of interest of histopathology images, formulated a classification model for diagnosis, simulated the model and evaluated the performance of the model. This is with a view to developing a histopathology image classification model for oral tumor diagnosis. The input for the classification is the oral histopathology images obtained from Obafemi Awolowo University Dental Clinic histopathology archive. The model for oral tumor diagnosis was formulated using the multilayered perceptron type of artificial neural network. Image preprocessing on the images was done using Contrast Limited Adaptive Histogram Equalization (CLAHE), features were extracted using Gray Level Confusion Matrix (GLCM). The important features were identified using Sequential Forward Selection (SFS) algorithm. The model classified oral tumor diagnosis into tive classes: Ameloblastoma, Giant Cell Lesions, Pleomorphic Adenoma, Mucoepidermoid Carcinoma and Squamous Cell Carcinoma. The performance of the model was evaluated using specificity and sensitivity. The result obtained showed that the model yielded an average accuracy of 82.14%. The sensitivity and the specificity values of Ameloblastoma were 85.71% and 89.4%, of Giant Cell Lesions were 83.33% and 94.74%, of Pleomorphic Adenoma were 75% and 95.24%, of Mucoepidermoid Carcinoma were 100% and 100%, and of Squamous Cell Carcinoma were 71.43% and 94.74% respectively. The model is capable of assisting pathologists in making consistent and accurate diagnosis. It can be considered as a second opinion to augment a pathologist’s diagnostic decision.