International Journal of Computer (IJC - Global Society of Scientific Research and Researchers, GSSRR)
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Examining the Advantages of Artificial Intelligence Alongside Its Potential Risks on Human Wellbeing, Data Privacy, and National Security
Full text linkThis study seeks to comprehensively analyze the benefits and risks of artificial intelligence and discuss strategies and policies to balance them. The paper assesses AI\u27s positive impact on four industries - healthcare, finance, transportation, and education – juxtaposed with its negative welfare, privacy, and security effects. The study utilizes a semi-systematic review methodology to explore diverse narratives surrounding AI\u27s societal implications. Key findings suggest AI can improve decision-making, productivity, and quality of life but risks exacerbating bias, unemployment, and insecurity if not developed responsibly. The paper discusses practical strategies, policies, and regulatory interventions to help balance AI\u27s pros and cons, including human-centered design, explainable AI, and governance frameworks. It also suggests actionable recommendations for individual, organizational, and national stakeholders. Suggestions for future research include developing robust AI resilient to attacks, increasing AI transparency and accountability, assessing long-term societal impacts, and addressing legal and ethical dilemmas. This timely study contributes a measured perspective to current debates on AI and provides a framework to help appropriate its advantages while mitigating its perils.
A Validity of in-Vehicle Networks Using CAN-FD
Full text linkThe most common communication interface for automotive electronic control units is CAN (Controller Area Network). Since CAN was first introduced in Daimler vehicles in 1991, all automotive manufacturers have adopted CAN communication for in-vehicle networks. However, as the number of electronic control units connected to the CAN network grows rapidly, the CAN protocol is reaching its technological limits. To overcome this limitation, Bosch has introduced a new communication protocol, CAN-FD (Flexible Data-rate). In this paper, we analyse the characteristics and limitations of CAN-FD communication according to the topology under the in-vehicle wiring harness environment designed based on the existing classic CAN communication
Assessing Basic School Teachers’ Competence in the Application of Information and Communications Technology in Teaching: Implications for the New Ghanaian Curriculum
Full text linkInformation and Communications Technology (ICT) provides access to information through telecommunication technologies to interact in the digital world and continues to evolve to bring remarkable changes in the educational system. ICT integration in teaching is quite complicated and challenging because teachers need to be equipped with the right competencies for teaching practices. Therefore, the purpose of this study was to assess basic school teachers’ competence in the application of Information and Communications Technology in teaching. The study used descriptive survey design by which simple random sample was used to select 285 teachers from Tano South municipality of Ahafo Region, Ghana. Data collection was done using closed-ended questionnaire. Data analysis was done with Statistical Package for Social Sciences (SPSS version 25). The study results revealed that teachers are instruments of change in educational establishments. They play significant roles in the implementation of ICT in education. Teachers’ competence in integration of ICT in the classroom would bring new, stimulating and fulfilling learning experiences to policy makers, educators and learners. Based on these findings, it was recommended that teachers should be provided with administrative support to enable them integrate ICT into classroom activities in order to promote student learning. Teachers should be given regular-based ICT training workshops to possess the requisite knowledge and skills so that they can effectively support their students’ ICT usage in classrooms. Also, provision of ICT infrastructure and resources in schools should be given maximum premium since access is a necessary condition to the integration of ICT in education
Machine Learning and AI in Business Intelligence: Trends and Opportunities
Full text linkThe integration of machine learning and artificial intelligence (AI) in business intelligence has brought forth a plethora of trends and opportunities. These cutting-edge technologies have revolutionized how businesses analyze data, gain insights, and make informed decisions. One prominent trend is the rise of predictive analytics. Machine learning algorithms can sift through vast amounts of historical data to identify patterns and trends, enabling businesses to make accurate predictions about future outcomes. This empowers organizations to optimize operations, anticipate customer needs, and mitigate risks. By leveraging business intelligence, companies can uncover hidden patterns, identify opportunities for growth and improvement, optimize business processes, and ultimately make informed decisions that drive their success. Another trend is the adoption of AI-powered chatbots and virtual assistants. The opportunities presented by machine learning and AI in business intelligence are extensive. From automated data analysis and anomaly detection to demand forecasting and dynamic pricing, these technologies empower businesses to optimize processes, reduce costs, and identify new revenue streams. In conclusion, the integration of machine learning and AI in business intelligence offers promising trends and abundant opportunities. By leveraging these technologies, businesses can gain a competitive edge, drive innovation, and unlock new levels of success in the digital era
Formulation of a Computational Model for Predicting Drug Reactions Using Machine Learning
Full text linkIn the rapidly evolving landscape of healthcare, the efficient detection of drug reactions is of paramount importance to ensure patient safety and optimize treatment outcomes. This article presents the formulation of a computational model for the prediction of drug reactions in clinical settings using machine learning techniques. Our research leverages state-of-the-art machine learning algorithms to extract valuable insights from health records and prescription data. By systematically analyzing the relationships between prescribed medications and observed patient reactions, our computational model will be able to identify potential drug reactions emanating from drug prescription in clinical a clinical setting
Oral Reading Fluency Can Be Estimated Across Languages with Text-To-Speech Software
Full text linkOral reading fluency (ORF) is a good index of the reading skill level, measured as the number of words read correctly per minute (WRPM). However, ORF tests are not available in many languages. This study tested if the mean of WRPM could be estimated in languages for which ORF tests have not been developed by using free text-to-speech software. Mean time taken by Google Translate (GT) to read out loud 10 texts in 16 languages from the International Reading Speed Texts was compared with the mean time taken by human participants. An English/Other languages ratio was obtained for both reading systems. Both ratios were highly similar, showing that GT is a valid tool to estimate mean WRPM in multiple languages
Performance Evaluation Of Quality Of Service Of A 4g Network In A Tropical Environment
Full text linkThe Nigerian Communications Commission (NCC), which is a communication regulatory Authority sets some key Performance Indications (KPIs) that the GSM network providers need to adhere to in order to deliver an efficient and quality network services in the country [1]. In this paper, Transverse Electromagnetic Wave Simulator (TEMS) was used in collecting data (Drive Tests) related to – call setup success rate (CSSR), call drop rate (CDR), paging success rate (PSR), grade of service (GOS), handover success rate (HOSR) etc; from 30 Base transceiver stations (BTS or BS) within Enugu metropolis during a specified period of fifteen working days. The Path Loss Exponent of the Test-Bed was verified to ascertain if it is in agreement with the environment of interest and the Operation and Maintenance Centre Resources (OMCR) statistics and drive test data gathered were analyzed using different graphs. The results of the Investigation of performance of Quality of Service offered by the network provider, Mobile Telecommunications Nigeria (MTN) in Enugu metropolis showed high performance as the network was deployed in the appropriate environment – Shadowed Urban Environment with Path Loss Exponent of 3.12
The Factors That Affect Undergraduates’ Attitudes Towards Computer-Based English Language Exams: A Case Study of An-Najah National University, Palestine
Full text linkThis paper investigates the impact of undergraduates’ gender, major, academic year level, computer skills, and level of English on their attitude towards computer-based English language exams at An-Najah National University. A simple random sample of 312 females and 201 males were chosen from all of the 49 classes of an English language core requirement course (English Language Course I) to fill in a paper-based group-administrated questionnaire consisting of 27 items. Five females and four males were randomly selected to participate in a focus group discussion. The data collected from the questionnaire was statistically analysed using the Statistical Package for the Social Sciences (SPSS), and a probability of p<0.05 was considered statistically significant. The data collected from the discussion was analysed thematically. While the statistical analyses revealed statistically significant differences in attitude towards computer-based English language exams due to gender, computer skills, major, and academic year level, no statistically significant differences were found due to their level of English. Female students, first-year students, those whose computer skills are low, and those who lack experience with computers need to receive more training in computer-based exams to reduce their anxiety and make the exams fairer to all groups
Artificial Intelligence in Electronic Commerce
Full text linkCompared to past years the way how the world functions today is very different. This is achieved as a result of several important improvements in the field of technology and internet. These improvements have influenced every aspect of our lives starting from the way we learn, the way we work, the way we travel, the way we shop and a lot of other activities. One of the fields that were drastically changed is the field of business and commerce. The purpose of this paper is to give information about the role and impact of artificial intelligence in electronic business. The readers of the paper will get familiar and gain solid information about the field of artificial intelligence and its implementation in electronic commerce
Algorithmic Decision-Making Concerns for Software: Non-Functional Requirement Elicitation as a Solution
Full text linkReference [1,2] Millions of software are lunched yearly and this software depend on data to produce required output. Personal data privacy and security has been a source of public concern for some time, and is usually interpreted in terms of data obtained from interaction with software. It is difficult to know whether a software system\u27s decisions are fair and what considerations were put in place in the system\u27s internal decision-making process if the system\u27s decisions are opaque. This has the potential to cause injustice and bias. In addition, a lack of openness may lead to a decrease in user acceptance and happiness. Algorithmic data-driven decision-making systems are becoming more automated, and they\u27ve had a lot of success in a lot of different applications. The General Data Protection Regulation of the European Union and other regulations limits algorithmic use of personal data and has fueled the dispute over the right to disclosure. This research adapted a crowd requirements elicitation model to develop a framework for the proper elicitation non-functional requirement. The developed model uses natural language processing integrated into a chatbot and a document extraction strategy since non-functional requirement exist also as government regulations and industrial standards. Proper and comprehensive elicitation of non-functional requirements will give accurate information on how the system performs its required task and such documents are best in terms of openness to the use of data by algorithms to avoid algorithm decision making concerns.