Benjamin Ghansah

A Comprehensive Review of Particle Swarm Optimization

Particle swarm optimization (PSO) is a heuristic global optimization method. PSO was motivated by the social behavior of organisms, such as bird flocking, fish schooling and human social relations. Its properties of low constraint on the continuity of objective function and the ability to adapt various dynamic environments, makes PSO one of the most important swarm intelligence algorithms and ostensibly the most commonly used optimization technique. This survey presents a comprehensive investigation of PSO and in particular, a proposed theoretical framework to improve its implementation. We hope that this survey would be beneficial to researchers studying PSO algorithms and would also serve as the substratum for future research in the study area, particularly those pursuing their career in artificial intelligence. In the end, some important conclusions and possible research directions of PSO that need to be studied in the future are proposed.

A Review of Deep Machine Learning

The rapid increase of information and accessibility in recent years has activated a paradigm shift in algorithm design for artificial intelligence. Recently, deep learning (a surrogate of Machine Learning) have won several contests in pattern recognition and machine learning. This review comprehensively summarises relevant studies, much of it from prior state-of-the-art techniques. This paper also discusses the motivations and principles regarding learning algorithms for deep architectures.

Research on the Virtualization Technology in Cloud Computing Environment

Virtualization and Cloud computing are two popular research directions in recent times. Today, Virtualization is being used by a growing number of organizations to reduce power consumption, Server Consolidation, Testing and Development, Dynamic Load Balancing and Disaster Recovery, Virtual Desktops and Improved System Reliability and Security. Virtualization also provides high availability for critical applications, and streamlines application deployment and migrations. Through cloud computing, Information Technology resources can be delivered as services over the Internet to the end user. Virtualization is one of such important core technologies of cloud computing. In this paper, we present a detailed review on virtualization. Furthermore, three technologies for x86 CPU virtualization and the architecture of Xen are introduced. Specifically, we propose an architecture of the cloud computing platform based on virtualization. Finally, we discuss the performance evaluation of server virtualization in saving cost, time and energy consumption.

Using Social Media as a Marketing Tool in Tertiary Institutions: A Case Study of Data Link University, Ghana

Social media has provided the platform for producers of goods and services to publicize their products and also to be more competitive through the provision of consumer feedback. In recent times, businesses and business owners are becoming more comfortable with including social media as part of their integrated marketing communications and strategies. This paper examines the role of social media as a marketing tool in stimulating demand for commodities, specifically using social media as a marketing tool to influence prospective candidates in their bid to apply to a particular tertiary institution. We examine the current marketing mix being used by Data Link University College, a private tertiary institution located in Ghana and how the inculcation of social media marketing strategies can help improve the system.

Distributed Information Retrieval: Developments and Strategies

Opposed to centralized search where Websites are crawled and indexed, Distributed Information Retrieval (DIR), also known as Federated Search, is a powerful way to comprehensively search multiple databases in real-time simultaneously. DIR is preferred to centralized search environments in a number of ways, characteristically among them are: 1. the diversity of resources that are made available; 2. improving scalability and reducing server load and network traffic; 3. the leverage of accessing the hidden or deep Web.There are three major phases/tasks of a DIR (i) resource description or collection representation (ii) resource selection and (iii) result merging. This paper aims at providing a comprehensive review on the various phases of DIR and also some current strategies being recommended in enhancing and improving the smooth implementation of a DIR system.

Group sparse based locality – sensitive dictionary learning for video semantic analysis

Sparse Representation-based Classifier (SRC) and Dictionary Learning (DL), have significantly impacted greatly on the classification performance of image recognition in recent times. In video semantic analysis, the locality structure of video semantic data containing more discriminative information is very essential for classification. However, this has not been fully considered by the current sparse representation-based approaches. Furthermore, similar coding outcomes are not being realized from video features with the same video category. To handle these issues, we propose a novel DL method, called Group Sparsity Locality-Sensitive Dictionary Learning (GSLSDL) for video semantic analysis. In the proposed GSLSDL, a discriminant loss function for the video category based on group sparse coding of sparse coefficients, is introduced into the structure of the Locality-Sensitive Dictionary Learning (LSDL) method. After solving the optimized dictionary, the sparse coefficients for the testing video feature samples are obtained. The classification result for video semantic is then realized by minimizing the error between the original and reconstructed samples. The experiment results show that, the proposed GSLSDL significantly improves the performance of video semantic detection compared with the competing methods, and robust in various diverse environments of video.

A Survey of Advanced Marine Communication and Navigation Technologies: Developments and Strategies

Marine communication and navigation technologies go hand-in-hand in order to provide a safe and secure marine travel on those who are on board a vessel or a ship. These tools are used together to establish rapport between sea ports and nearby vessels, as well as determining a sea or ocean’s characteristics and weather patterns. Unmanned Surface Vehicle (USV) for maritime salvage is designed to mitigate the menaces associated with marine navigation. The technique involves intelligent navigation and communication, intelligent collision avoidance and intelligent rheostat systems. This paper seeks to explore the technological advancements in marine communication and navigation used in the maritime environment, with veneration to both hardware and software. This review would invariable serve as a source of information pool for further studies. We also present some current technological challenges the marine industry is antagonized with.

Corporate Social Responsibility: Institutional Behavior Differences in Extractive Industry

The developed countries’ institutional research undertaken on corporate social responsibilities (CSR) have shown a positive relationship between accessibility of financial related assets and CSR. Contentions that we classified as the Institutional Difference Hypothesis (IDH) drawn from the institutional writing, on the other hand, propose that institutional contrasts amid of developing and the developed economies are prone to result in diverse CSR propositions. Incorporating the rationale of IDH with understanding of knowledge from slack resource theory, we contend that there exists a negative relationship between fiscal resources accessibility and CSR investments for mining companies in Ghana, a sub-Saharan African developing economy. We utilize a well-protected data from the Ghana Investment Promotion Center (GIPC), Ghana Stock Exchange (GSE) and Ghana Chamber of mines (GCM) and find that Return on Ordinary Share, Return on Sales, and Net Profit were reliably connected with lower CSR disbursements. We highlight the ramifications of our discoveries for academics’ examination and corporate practitioners.

The Antecedents of Corporate Social Responsibility for Extractive Industries in the Governance Systems in Africa

The extractive industry gets huge international consideration because of the way they discharge their ecological and social obligations. Despite the fact that mining sector ventures have numerous points of interest, wrong mining operations have prompted emotional environment and resources exhaustion. To accomplish a parity of such operations, sustainable programs are an absolute necessity and ought to be trailed by the business. Of the different feasible practices, CSR (Corporate Social Responsibility) has picked up conspicuousness as of late. The developed nations, CSR is at a propelled level, yet in emerging economies particularly in Africa, CSR is in a preparatory stage, because of both known and obscure reasons. This study researches drivers for CSR usage in the mining business in Ghana, a developing country in Africa. A few studies concentrated on CSR issues however were constrained to industrial points of view without considering multi-partners. This paper endeavors to bridge the gap by dissecting CSR drivers from the viewpoints of numerous stakeholders, including media, government and social organizations. The researchers propose a model system, showed with a contextual investigation from a Ghana Investments Promotion Center (GIPC). In light of these findings, businesses can build their chances of honing quality CSR in modern business behaviors. This research augments the extent of this issue through changing multi-criteria decision making (MCDM) apparatuses and distinctive situations, for example, dim, fluffy, and different methodologies. The extra drivers can likewise be accepted with statistical interpretations.

Factors that Influence Students' Decision to Choose a Particular University: A Conjoint Analysis

Ghanaian universities have employed various marketing mix to stimulate demand for their services; particularly in recruitment and engagement of home and international students. This paper examines the relative influence of factors affecting the college choice decisions of students. It is based on a survey of 2,534 admitted students at a major university in Ghana, to which 39 percent of the sample responded. We used Factor analysis to rate 26 University borne attributes upon which student decisions are based. The outcome was used to build a five-scale preference measure, which were evaluated with a qualitative approach in analyzing gathered data using descriptive statistics, cross tabulation and chi square. The results revealed some marketing strategies that can be used in institutions of higher learning to boost students’ enrolment in their order of perceived effectiveness. The following were found to influence decisions: word of mouth (family and friends), proximity/nearness, accreditation/affiliation, affordability and lecturing Style.