Classification is a data mining (machine learning) technique used to predict group membership for data instances. There are several classification techniques that can be used for classification purpose. In this paper, we present the basic classification techniques. Later we discuss some major types of classification method including Bayesian networks, decision tree induction, k-nearest neighbor classifier and Support Vector Machines (SVM) with their strengths, weaknesses, potential applications and issues with their available solution. The goal of this study is to provide a comprehensive review of different classification techniques in machine learning. This work will be helpful for both academia and new comers in the field of machine learning to further strengthen the basis of classification methods.
Smart Grid (SG) is an emerging paradigm of the modern world to upgrade and enhance the existing conventional electrical power infrastructure from generation to distribution to the consumers in a two-way communication fashion to automate the electrical power demand and supply and make this a cyber-physical system. SG infrastructure key elements, such as smart meters, circuit breakers, transformers, feeders, substations, control centers, grid stations, are required well-formed communication network architectures. SG infrastructure is divided into three main communication networks architectures, such as HAH, NAN, and WAN. Each of these communication network architectures requires reliable, stable, secure, high data rate at real-time with the help of different wireline and wireless communication technologies from HAN to WAN networks. To understand the complete concepts about SG, a concise review is presented and it will help the readers to get foundations of communication network architectures and technologies of SG.
An Intelligent Tutoring System (ITS) is a computer software that help students in learning educational or academics concepts in customized environment. ITSs are instructional systems that have capability to facilitate user by providing instantaneous feedback and instructions without any human intervention. The advancement of new technologies has integrated computer based learning with artificial intelligence methods with aim to develop better custom-made education systems that referred as ITS. One of the important factors that affect students learning process is self-learning; all students cannot have similar experience of learning scholastic concepts from same educational material. Because students have individual differences that make some topics difficult or easy to understand regarding taken subjects. These systems have capability to improve teaching and learning process in different educational domains while respecting individual learning needs. In this study an attempt is made to review the research in field of ITSs and highlight the educational areas or domains in which ITSs have been introduced. Techniques, delivering modes and evaluation methodologies that have been used in developed ITSs have also been discussed in this work. This work will be helpful for both academia and new comers in the field of ITSs to further strengthen basis of tutoring systems in educational domains.
Cloud computing is one of the fastest growing internet based technology that facilitates users to utilize services by making use of large poll of resources without installation of any software. Adoption of this technology is increasing rapidly because of many advantages including reduction of cost and IT load. Despite the popularity of cloud computing, it faces many difficulties such as security that is one of the major inhibitors in the growth of cloud computing. Data confidentiality is at the top of the list of security concern for this technology. Many methods have been introduced to overcome this issue; encryption is one of them and widely used method to ensure the data confidentiality in cloud environment. In this study, an attempt is made to review the encryption techniques used for the data confidentiality. The results of review are classified on the basis of type of approach and the type of validation used to validate the approach.
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