The Construction of Adolescence on Social Media

The recent use of internet enabled technology has significantly impacted the way adolescents use social media. Once they are confined to a computer, laptop or mobile phone with internet accessibility, these adolescents are able to explore over a wider range on social media. However, attention has not been drawn to the impact of social media on adolescence. This research proposal examines the construction of adolescence on social media. It also seeks to identify the effects of social media on social behavior and academic performance of students in Senior High Schools with a focus on Oti Boateng Senior High School in Koforidua. In this research study, I intend using the Social Learning Theory and Uses of Gratification Theory as my theoretical framework. The study would employ quantitative method for data collection involving questionnaire administration. Keywords: Adolescence, Social media, Facebook, Questionnaire, Academic Performance DOI: 10.7176/JEP/10-9-08 Publication date:March 31st 201

Adopting Competitive Strategies in the Telecommunications Industry

The landscape of the Ghanaian Telecommunication industry has seen dramatic changes in the last two decades. During these period new companies both local and foreign emerged some as start-ups others through mergers or acquisitions. The liberalized economic environment lead to the influx of operators hence the need to assess their performance and the effectiveness of competitive strategies adopted.  This paper will evaluate the strategies adopted by mobile telecommunication operators to gain competitive advantage in the industry with particular reference to the Ghanaian market. Our study revealed that to have a competitive advantage and improve on performance a sustain investments in the area of infrastructure, human capital, technology, sales and marketing activities and essential resources were critical. Keywords: Telecommunications industry, Customer targets, Strategic management, competitive advantag

Text Analytics to Predict Time and Cause of Death from Verbal Autopsies

This thesis describes the first Text Analytics approach to predicting Causes of Death (CoD) from Verbal Autopsies (VA). VA is an alternative technique recommended by the World Health Organisation for ascertaining CoD in low and middle-income countries (LMIC). CoD information is vitally important in the provision of healthcare. CoD information from VA can be obtained via two main approaches: manual, also referred to as the physician-review and automatic. The automatic-based approach is an active research area due to its efficiency and cost effectiveness over the manual approach. VA contains both closed responses and open narrative text. However, the open narrative text has been ignored by the state-of-art automatic approaches and this remains a challenge and an important research issue. We hypothesise that it is feasible to predict CoD from the narratives of VA. We further contend that an automatic approach that could utilise the information contained in both narrative and closed response text of VA could lead to an improved prediction accuracy of CoD. This research has been formulated as a Text Classification problem, which employs Corpus and Computational Linguistics, Natural Language Processing and Machine Learning techniques to automatically classify VA documents according to CoD. Firstly, the research uses a VA corpus built from a sample collection of over 11,400 VA documents collected during a 10 year period in Ghana, West Africa. About 80 per cent of these documents have been annotated with CoD by medical experts. Secondly, we design experiments to identify Machine Learning techniques (algorithm, feature representation scheme, and feature reduction strategy) suitable for classifying VA open narratives (VAModel1). Thirdly, we propose novel methods of extracting features to build a model that predicts CoD from VA narratives using the annotated VA corpus as training and testing set. Furthermore, we develop two additional models: only closed responses based (VAModel2); and a hybrid of closed and open narrative based model (VAModel3). Our VAModel1 performs reasonably better than our baseline model, suggesting the feasibility of predicting the CoD from the VA open narratives. Overall, VAModel3 performance was observed to achieve better performance than VAModel1 but not significantly better than VAModel2. Also, in terms of reliability, VAModel1 obtained a moderate agreement (kappa score = 0.4) when compared with the gold standard– medical experts (average annotation agreement between medical experts, kappa score= 0.64). Furthermore, an acceptable agreement was obtained for VAModel2 (kappa score =0.71) and VAModel3 (kappa score =0.75), suggesting the reliability of these two models is better than medical experts. Also, a detailed analysis suggested that combining information from narratives and closed responses leads to an increase in performance for some CoD categories whereas information obtained from the closed responses part is enough for other CoD categories. Our research provides an alternative automatic approach to predicting CoD from VA, which is essential for LMIC. Therefore, further research into various aspects of the modelling process could improve the current performance of automatically predicting CoD from VAs

Financial Literacy and Firm performance The moderating role of financial capital availability and resource flexibility.

Financial literacy, financial capital availability and resource flexibility are typically modelled as separate antecedents of firm performance. However, the boundary conditions for such models are less examined in a developing country context where financial literacy has been argued to be weak. Accordingly, drawing on RBV, we examined the performance implications of financial capital availability and resource flexibility on the financial literacy-firm performance relationship of entrepreneurial firms operating in a less developed market setting. Using a survey-based approach and employing OLS, we examined 298 entrepreneurial firms operating Ghana, a sub-Saharan African country. Our findings indicate that financial literacy improves firm performance and particularly so when resources are flexible and entrepreneurs are able to access finance with eas

Crime Analysis and Conventional Policing Strategies: Evidence from a Community in the Western Region, Ghana

The study investigated the application of crime analysis at various police stations within the Tarkwa-Nsuaem Municipality in the Western Region of Ghana with the objective of understanding crime, crime analysis, crime control and crime information management and their implications on conventional policing strategies. Qualitative and quantitative research adopting the questionnaire and interview were conducted with crime analysts and specialized investigators/intelligence analysts through descriptive and explorative research design. The study had a dual purpose of generating operational crime management information in assisting crime prevention initiatives as well as identifying the strengths and weaknesses of current practices for improving performance, mainly focusing on the criminal activities of group offenders (organized crime related), repeat offenders and serial offenders

PRIVACY PRESERVATION FOR TRANSACTION INITIATORS: STRONGER KEY IMAGE RING SIGNATURE AND SMART CONTRACT-BASED FRAMEWORK

Recently, blockchain technology has garnered support. However, an attenuating factor to its global adoption in certain use cases is privacy-preservation owing to its inherent transparency. A widely explored cryptographic option to address this challenge has been ring signature which aside its privacy guarantee must be double spending resistant. In this paper, we identify and prove a catastrophic flaw for double-spending attack in a Lightweight Ring Signature scheme and proceed to construct a new, fortified commitment scheme using the signer’s entire private key. Subsequently, we compute a stronger key image to yield a double-spending-resistant signature scheme solidly backed by formal proof. Inherent in our solution is a novel, zero-knowledge-based, secured and cost-effective smart contract for public key aggregation. We test our solution on a private blockchain as well as Kovan testnet along with performance analysis attesting to efficiency and usability and make the code publicly available on GitHub

Institutional voids, international learning effort and internationalization of emerging market new ventures

Much of the existing scholarly works portray institutional voids (IVs) in emerging economies as impeding forces against the development of new ventures. However, little attention has been paid to how such voids generate positive outcomes in emerging market new ventures. Drawing on the institutional theory, we propose IVs as crucial enablers of new venture internationalization. In addition, we investigate both how and when IVs enhance the degree to which new ventures internationalize by examining international learning effort (ILE) as a mediator and two domestic market environmental factors (i.e., environmental dynamism and competitive intensity) as important contingencies. We test our moderated mediation model using primary data gathered from 211 new ventures from Ghana. We found that ILE mediates the relationship between IVs and new venture internationalization and that both environmental dynamism and competitive intensity moderate the indirect relationship between home-country IVs and new venture internationalization. We discuss the theoretical and practical implications of this study

Enhancing Security and Energy Efficiency in Wireless Sensor Network Routing with IOT Challenges: A Thorough Review

Wireless sensor networks (WSNs) have emerged as a crucial component in the field of networking due to their cost-effectiveness, efficiency, and compact size, making them invaluable for various applications. However, as the reliance on WSN-dependent applications continues to grow, these networks grapple with inherent limitations such as memory and computational constraints. Therefore, effective solutions require immediate attention, especially in the age of the Internet of Things (IoT), which largely relies on the effectiveness of WSNs. This study undertakes a comprehensive review of research conducted between 2018 and 2020, categorizing it into six main domains: 1) Providing an overview of WSN applications, management, and security considerations. 2) Focusing on routing and energy-saving techniques. 3) Reviewing the development of methods for information gathering, emphasizing data integrity and privacy. 4) Emphasizing connectivity and positioning techniques. 5) Examining studies that explore the integration of IoT technology into WSNs with an eye on secure data transmission. 6) Highlighting research efforts aimed at energy efficiency. The study addresses the motivation behind employing WSN applications in IoT technologies, as well as the challenges, obstructions, and solutions related to their application and development. It underscores that energy consumption remains a paramount issue in WSNs, with untapped potential for improving energy efficiency while ensuring robust security. Furthermore, it identifies existing approaches' weaknesses, rendering them inadequate for achieving energy-efficient routing in secure WSNs. This review sheds light on the critical challenges and opportunities in the field, contributing to a deeper understanding of WSNs and their role in secure IoT applications

Pfeiffer syndrome type 3 with FGR2 c.1052C>G (p.Ser351Cys) variant in West Africa: a case report

Pfeiffer syndrome is a rare genetic condition that includes anomalies of the head, hands, and feet. It was originally described by Rudolf Pfeiffer in 1964. As a result of varied clinical presentations, there is a low threshold for missing the diagnosis. Three (3) cases were found by the authors in the medical literature from the African continent, all of which lacked molecular studies. The main dysmorphic features we observed in our patient were; macrocephaly with widely gaped sagittal sutures, proptosis with ocular hypertelorism, ankylosed elbows, wide sandal gap and medially deviated broad great toes. In this case, sequence analysis using Illumina technology and deletion/duplication testing of 65 genes for variants associated with craniosynostosis syndromes was performed at Invitae Medical Genetic laboratory. A diagnosis of Pfeiffer syndrome type 3 with FGFR2 c.1052C>G (p.Ser351Cys) variant was made. In conclusion, this case will aid health care providers especially in areas of low accessibility to molecular studies to promptly identify, appropriately manage the condition as well as counselling the parents to offset the risk of abandonment of neonates with dysmorphic features