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This paper explores the integration of artificial intelligence (AI) technologies with human rights considerations in plastic waste recycling, focusing on the context of Nigeria. Using an explanatory design and a basic review of the literature, it examines how AI can enhance human rights protection among workers in plastic waste recycling firms. The paper emphasizes the role of government policies and regulations in ensuring human rights protection, the need for ethical guidelines for AI use, and the potential of AI to improve worker safety and reduce environmental pollution in recycling facilities. Key recommendations for future research include enhancing AI capabilities for waste sorting, integrating Internet of Things (IoT) devices for real-time monitoring, and prioritizing ethics in AI development. Collaboration between stakeholders is identified as crucial, with multi-stakeholder partnerships and policy coherence essential for the effective implementation of AI technologies in plastic waste recycling. In conclusion, integrating AI with human rights considerations in plastic waste recycling is pivotal for enhancing efficiency, reducing pollution, and ensuring sustainable waste management practices. This paper contributes to the growing body of literature on AI and human rights in waste management, offering insights for policymakers, industry stakeholders, and researchers in Nigeria and beyond. [ABSTRACT FROM AUTHOR]

Due to the increasing presence of artificial intelligence (AI) in developed countries, this paper examines the adoption of AI for effective library services in academic libraries in Nigeria. The paper defines artificial intelligence while chronicling its history. He also identified the advantages of adopting artificial intelligence in academic libraries, which include ease of use, endless functionality, and the ability to perform complex work, among others, and the challenges faced by library management towards adopting artificial intelligence, which include financial uncertainty, job loss, and technological defects, among others. The paper concluded that adoption of AI in academic libraries sets a new level of efficient and effective library service delivery, but adoption in developing countries such as Nigeria is low due to some identified challenges. The paper recommended that government and library management should come together to suggest the way forward for academic libraries in terms of meeting the latest standard for the use of AI in libraries; library staff must undergo training and retraining in the use of artificial intelligence in providing library services, among other things. [ABSTRACT FROM AUTHOR]

There is problem of adoption and adapting to disruptive technologies key drivers. This failure of adoption and adapting to disruptive technologies key drivers could have created the problem of institutional inefficiency among accounting practitioners and accounting professional institutes in Nigeria. Accounting professional institutes in Nigeria may not achieve efficiency in accounting service delivery as most accounting professional institutes do not have in-depth knowledge of disruptive technologies, because it is a new development in the global community. Therefore, this study evaluates the effect of disruptive accounting technology on institutional efficiency of professional accounting institutes in Nigeria. The study employed a primary data distributed among the professional members of Institute of Chartered Accountant of Nigeria and the Association of National Accountants of Nigeria. Artificial Intelligence (AI), Robotic Technology (RT), Cloud Accounting (CA), Blockchain Technology (BCT), and QuickBook Technology (QBT) were used as proxies for disruptive accounting technology and it is represented as the independent variable while institutional efficiency is used as the dependent variable. Structural equation modelling was adopted for data analysis. The paper establishes that AI, CA, and QBT have a significant effect on institutional efficiency at P < 0.05 (5% significance level). The paper, therefore, recommends that accounting institute must be a force for change. The disrupt, innovate, and energize worried that the pull of the past would prevent accountants from chaining to meet the future. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) applications and machine learning models have extended beyond merely solving computer-related problems to tackle environmental sustainability issues. One such case is countermanding the demand and supply of illegal forest and wildlife products. In Nigeria, the challenges of improving its ability to combat the high rate of wildlife and forest crimes within its borders remain daunting. Despite existing laws, Nigeria remains both a source and a key intermediary for wildlife smuggling and crimes involving protected species. This paper analyses the potential of AI as a tool for strengthening the existing legal framework on wildlife crimes in Nigeria. The findings of this paper demonstrate that the current framework for preventing forest and wildlife crime is being breached due to a lack of resources available to enforcement authorities. Thus, leveraging AI's potential presents innovative solutions to strengthen compliance with these laws. [ABSTRACT FROM AUTHOR]

Due to the growing presence of artificial intelligence (AI) in developed countries, this paper looks at the adoption of artificial intelligence for effective library services in academic libraries in Nigeria. The paper describes the concept of artificial intelligence while tracing its origin. It further established the advantage of adopting artificial intelligence in academic libraries which include user-friendly, infinite functions, ability to take complex work among others; and the challenges faced by library management towards the adoption of artificial intelligence which include financial uncertainty, job loss, technological disadvantages among others. The paper concluded that the adoption of AI in academic libraries is setting a new level of efficient and effective library service delivery but the adoption in developing countries such as Nigeria is low due to some of the identified challenges. The paper recommended that government and library management must come together to proffer the way forward for academic libraries in terms of meeting up with the latest standard of the use of AI in libraries; Library staff should be exposed to training and retraining in the use of artificial intelligence in delivering of libraries' services; among others. [ABSTRACT FROM AUTHOR]

Educational technology is a discipline that has a lot of roles to play in the global education system yet, its services had been neglected over the years in Nigeria. The new global reality that was occasioned by the upsurge of COVID-19 has made educational technology a very consequential discipline with conspicuous roles to play in the face of such a global pandemic. COVID-19 has halted many human activities across the globe. Its effect in the education system has resulted to re-adjustment in the school calendar, prolonged graduation dates, and reduced research output. To combat this, many education systems now adopt the services of educational technology thereby changing the old norm. But for this new norm to be sustainable, this paper argues that the education system must show a pragmatic attitude towards the adoption of such innovation rather than a conservative attitude. Therefore, using the diffusion theory of innovation, this paper argues that necessity called for compulsory adoption of innovation in the Nigerian education system. This new opportunity, however, looks bleak as many educational practitioners lack the required skills and attitude to adopt the innovation. It, therefore, concludes that educational practitioners need in-service training to be part of these changes. The government is suggested to apply a systematic approach in procuring and installing ICT facilities that will enhance the diffusion of this innovation into the school system. [ABSTRACT FROM AUTHOR]

This paper expounds the application and perceived impact of Artificial Intelligence (AI) in academic libraries in Nigeria. Libraries especially in developing countries may become moribund in the 21 century unless they begin to harness new, smart and intelligent technologies for improved operations and service delivery. This research adopted a literature-based approach to x-ray the applications and perceived impact of Artificial Intelligence (AI) in academic libraries in Nigeria. Through a systematic analysis and review of literature, the study brought to limelight the current state of AI integration in academic libraries in Nigeria and its possible impact on library services, collections, users, professionals and general library operations and services. The application of Artificial Intelligence (AI) in academic libraries has the potential to revolutionize library operations and services. Some of the identifies AI tools include: Natural Language Recognition, Robotics, Big Data, Data Mining, Chatbot, Machine Learning, Pattern Recognition and Expert system. Findings from the study revealed that the application of AI in academic libraries have the potentials to increases productivity, improved customer satisfaction through personalization, easy availability and accessibility of information, easy collaboration and knowledge sharing, virtual assistance and chatbots, and ultimately increase overall operational effectiveness. This paper also explored some of the challenges associated with the application of AI technologies in academic libraries in Nigeria such as poor ICT skills and technical expertise, high initial costs of implementation, phobia for job displacement, epileptic power supply, poor maintenance culture, resistance to change, poor network connectivity, privacy and ethical implications, etc. To maximize the potential benefits of AI applications in academic libraries in Nigeria, it is crucial for these libraries to implement appropriate planning, guidelines and regulations on AI use as well as training and retraining of academic librarians to acquire the required ICT skills, knowledge and competence in order to adapt in the present digital and changing library environment. [ABSTRACT FROM AUTHOR]

One of the pivotal decision-making tools for sustainable management of water resources for various uses is accurate prediction of water quality. In the present paper, multiple linear regression (MLR), radial basis function neural network (RBF-NN), and multilayer perceptron neural network (MLP-NN) models were developed for the monitoring and management of irrigation water quality (IWQ) in Ojoto area, southeastern Nigeria. This paper is the first to integrate and simultaneously implement these predictive methods for the modeling of seven IWQ indices. Moreover, two modeling scenarios were considered. Scenario 1 represents predictions that utilized the specific physicochemical parameters for calculating the IWQ indices as input variables while Scenario 2 represents predictions that utilized pH, EC, Na+, K+, Mg2+, Ca2+, Cl-, SO42-, and HCO3- as inputs. In terms of salinity hazard, most of the water resources are unsuitable/poor for irrigation. However, in terms of carbonate and bicarbonate impact and magnesium hazard, majority of the samples have good and excellent IWQ. Seven agglomerative Q-mode dendrograms spatiotemporally classified the water resources based on the IWQ indices. Model validation metrics showed that the MLR, RBF-NN, and MLP-NN models developed in the two scenarios performed well in both scenarios, with minor variations. [ABSTRACT FROM AUTHOR]

Food security has gained international attention in recent years and Nigeria, with its abundant human and natural resources, is not exempted from this, as improving food security requires a strong focus on agricultural development. Innovations like precision agriculture tools and other advancements in modern agriculture provide farmers worldwide with the tools and expertise to improve workers' productivity in the agricultural sector and combat food insecurity. This paper examined the state of food security in Nigeria and how precision agriculture enhances workers' productivity in Nigeria. The study adopted a systematic review of relevant literature on the various issues addressed in the research. The paper revealed that there is a high level of food insecurity in Nigeria, with estimates of more than 65% of the Nigerian population being food insecure, and the average productivity of Nigerian farmers is several times lower compared to farmers in a developed economy. The study revealed that precision agriculture boosts workers' productivity by utilizing cutting-edge sensor and analysis techniques, increasing agricultural yields, and assisting management decisions which boost output, shorten labor hours, and guarantee efficient control of irrigation and fertilizer systems. Therefore, the paper recommends that Nigeria's farming sector incorporate precision agriculture equipment and technology, including drones, remote sensing, and artificial intelligence tools. Additionally, workers must be trained to use these innovative instruments and procedures to boost worker productivity and improve food security. [ABSTRACT FROM AUTHOR]

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Purpose: Boreout is a psychological state of intense boredom and apathy. Characterized by the absence of mental stimuli (i.e. menial tasks) required to keep employees conscious about their environment, and this incessant decline in mental stimuli may turn employees into "professional zombies." The diversity in work needs and preferences across generations has become a key organizational factor, generational differences have been studied in Western countries, not much information is available about generational cohorts and satisfaction (i.e. career, life and job satisfaction) in developing countries. The purpose of this paper is to provide more insights on these phenomena. Design/methodology/approach: Drawing upon conservation of resources theory, this paper examines the potential effects of boreout on important job outcomes (i.e. career, life and job satisfaction) conditioned by generation (Gen-Xers and Gen-Yers) in the service industry. Data analyses with Artificial Intelligence technique (i.e. artificial neural network) and structural equation modeling were conducted with data collated from Nigerian service employees. Findings: Results revealed that boreout has a negative impact on career, life and job satisfaction. The hypothesized relationships were significantly moderated by generation cohorts as Gen-Xers and Gen-Yers were found to be distinct cohorts. Originality/value: This paper advocates that non-western organizations should avoid utmost service standardization and rigid stylization of work processes and procedures. [ABSTRACT FROM AUTHOR]

The main purpose of this paper is to investigate the level of adoption of artificial intelligence(AI) to support library services delivery in university libraries in Africa. Qualitative research method was adopted to collect data. A preliminary survey of 102 university libraries in English speaking countries in Africa was conducted to identify the university libraries that have adopted AI in their libraries. Content analysis was used to analyse the responses. The study found that the only few university libraries in Africa have adopted AI technologies such as Chatbot, ChatGPT, LibKey from ThirdIron, robots, RFID technology and Grammarly. These AI technologies are used to render different library services like answering of directional and ready reference questions posed by library users, serving as a knowledge base for cataloguing information of library materials, self-check-out machine for books, used as a marketing tool for the library, tool for statistics evaluation and recommendations, assisting in the charging and discharging of library materials, etc. Lack of funds to acquire the AI tools, training of librarians, and lack of full knowledge of AI were the most mentioned challenges associated with adoption of AI in the libraries. The study recommended a formulation of policy to guide the adoption of new technologies such as AI, and training and re-training of librarians through workshops equip librarians with skills needed to effectively use the AI technologies. [ABSTRACT FROM AUTHOR]

That AI has permeated all aspects of human endevour is a statement of fact. Indeed, the applications of AI technology will be the finest technology to give a boost to core sectors and help Nigeria for a fastest digitization. This study on the adoption of artificial intelligence (AI) in library parlance: issues and benefits focuses on the concept of artificial intelligence, artificial intelligence in library operations such as applications of expert systems in reference service, cataloguing, classification, indexing, and acquisition; applications of natural language processing in library activities, application of pattern recognition in library activities, applications of robotics in the library activities. The paper also looks at issues with artificial intelligence in libraries such as financial uncertainty, emerging skill gaps, resistance to change in workflow processes and adoption of new technologies including the fear of AI's possible risks among others. Furthermore, the benefits derivable by the adoption of AI in library operations which include but not limited to improve operational efficiency, engage larger audiences through better user experience and new services, help librarians achieve their new goals, establish a strong foothold for libraries in the new scholarly information landscape among others are discussed. Finally, a conclusion with a call for libraries to re-position themselves to take relative advantage of artificial intelligence was advanced. [ABSTRACT FROM AUTHOR]

This paper explained the influence of technological readiness on adoption of artificial intelligence technology, using data collected through Google form from 52 librarians in Nigeria. The study adopted descriptive survey research design and adapted the Technological Readiness Index 2.0 to design structured questionnaire on level of technological readiness among librarians in Nigeria. In addition, data was collected on demographic factors and prevalent artificial intelligent technologies adopted by the librarians. Findings reveal that Google Assistant is the prevalent artificial intelligence technology adopted by the librarians in Nigeria. Also, the librarians agreed more on the motivating factors than inhibiting factors for level of librarians' technological readiness in Nigeria. However, findings from the study indicate that there is no significant relationship between technological readiness and adoption of artificial intelligence among librarians in Nigeria. Hence, the study suggests that other factors could contribute to the adoption of artificial intelligence among librarians in Nigeria. [ABSTRACT FROM AUTHOR]

Greenhouse (GH) technology has been employed in the production of selected crops under a controlled environment for maximum yield. Most often, flowers, medicinal plants and short-duration arable crops are most favoured for cultivation in greenhouses for research and commercial production purposes. Greenhouse is beginning to gain acceptance and usage in crop production in Nigeria in particular. This paper focused on the: origin of greenhouse, type of GH, general research trend in GH development/technology, adaptable irrigation type for GH farming, design criteria for GH, trends in smart GH/farming and GH development and utilization across the globe to produce food crops sufficiently and for future food scarcity. Site selection is a key factor for profitable and sustainable greenhouse production where factors like climate, topography, irrigation water, soil characteristics, flooded areas, air pollution, expansion, labour availability, communications network and orientation affect the utilization of greenhouses for research and production purposes. The types, styles, materials selection and uses, sizes of greenhouses, should be considered in conjunction with factors that determine the siting of greenhouses. Existing localized irrigation methods commonly utilized for crop cultivation include surface (Sprinkler), subsurface (Drip, emitter). The selection of types of GH and irrigation method depends on influencing factors. [ABSTRACT FROM AUTHOR]

Digitalization of agriculture has been identified as panacea to the problem of food security to teeming population, although its uses for agricultural extension services is still evolving and challenging among extension professionals. This study examined the opportunities and challenges of using AI-based digital tools for agricultural extension services in Nigeria; the study described the socioeconomic characteristics of extension professionals and identified the effects of its usage on extension service delivery. An online questionnaire was used to gather primary data from 131 agricultural extension professionals drawn across the states in Nigeria. Frequency counts, percentages and means were used to analyse and summarize the data collected. The result reveals that majority (75.6%) were male with a mean age of 48.1±15.8 years. The respondents mostly identified provision for real-time insights into the farms and landscape (97.7%) and provision of reliable farm data (75.6%) as the major opportunities for AI-based Digital tools for agricultural extension service, while lengthy technology adoption Process (94.7%) and higher technical skills (70.2%) were the major challenges identified with the use of AI-based digital tools for agricultural extension services by the respondents. The study also reveals that respondents mostly indicated timely enhancement of communication (88.5%) and provision of an update on best practices globally (64.1%) as the key effects of AIbased digital for agricultural extension services. The study recommends that capacity building of extension professionals and farmers; involvement of farmers and other agriculture value chain stakeholders in the development of digital technologies; as well as provision of digital infrastructures and enablers which are germane for digitalization and utilisation of AI-based digital tools for agricultural extension service delivery in Nigeria. [ABSTRACT FROM AUTHOR]

The notion of human security has become a dominant theme in international political discussions. This is partly explained by the fact that the production of arms and ammunition does guarantee security. Economic, food, health, environmental, and personal safety are all components of human security. In Nigeria, the country is grappling with security hitches cutting across the six geo-political regions. Kidnapping, banditry, robbery, murder, and wanton killings are common items in the daily news. More worrying is that, despite huge resources being injected into the defense sector, the Nigerian government seems unable to curb this menace that has been troubling the nation's well-being. The government, security agencies, and intelligence organizations, on the other hand, appear to be caught off guard by the atrocities committed by terrorists, herders, and instances of interethnic violence pointing to the fact that Nigeria is prone to anarchy. Against this background, this paper contextualized the lawlessness in Nigeria with specific reference to human security. The paper employs the qualitative method of data collection that utilizes secondary sources such as newspapers, the internet, and extant scholarly works. Based on findings, the rate at which schools are closing, frequent jailbreaks, rising food prices, citizen apathy toward the government, the obvious inability of the government to uphold its own end of the social contract it made with its subjects, and failure of all security containment strategies are all overt signs of a failing state. It is submitted that there is a need for government to be conscious of its primary goals, which include welfare and the protection of people's lives and property. The article suggests that Nigeria should employ artificial intelligence to combat the threat to the nation's status as a sovereign republic, which is being posed by groups that have taken over the numerous ungoverned spaces that dot the country's territory. Nigeria should also invest in digital learning methods and coordinate its numerous security agencies. The political order, authority, law, and structures must all be rebuilt because they have all fallen apart. [ABSTRACT FROM AUTHOR]

The world is rapidly changing due to technological advancement, which is affecting how organizations operate and impacting on corporate performance. "Artificial intelligence" is an emerging topic that has gotten a lot of attention globally. However, there is scarcity of literature on the subject, particularly in developing countries. This paper seeks to investigate the effect of "artificial intelligence" (AI) on employee performance (EP) of the commercial banks in Nigeria, using intellectual capital (human capital) as a moderator. A survey questionnaire was administered to 312 bank employees randomly. SPSS was employed to carry out a demographic statistic to have a better understanding and summary of the data. Additionally, a structural equation model (PLS-SEM) was employed and SmartPLS 3 professional version is employed for the analyses and testing of the formulated hypotheses. Findings prove a positive and significant correlation between artificial intelligence and employee performance. Also, intellectual capital (human capital) positively and significantly moderates the nexus between artificial intelligence and employee performance. [ABSTRACT FROM AUTHOR]

This study focuses on agriculture, which is the main source of economic growth in many West African countries. In recent years, conventional agriculture has undergone a remarkable evolution and digital technologies are widely used for different purposes. While the world is rapidly using advanced digital technologies to grow their agriculture, Africa seems to be lagging behind, especially West Africa. To know how to contribute effectively, it is important to know what is being performed about this issue. The objective of this study is to examine the state of digital agriculture in five countries, namely, Benin, Burkina Faso, Côte d'Ivoire, Ghana, and Nigeria. The study consisted of an analysis of the scientific contributions of these countries and the cases of actual deployment. This is carried out by means of a bibliometric study based on data collected from the Web of Science and a comparative review of the technologies used in the target countries using data from several sources, such as IEEE, Scopus, Science Direct, Google Scholar, etc. The bibliometric analysis based on 3249 publications revealed that research interests have increased significantly since 2014. Climate change, machine learning (ML), and adoption have been the hottest topics of discussion and most of the organizations working on the topic are academic bodies. Moreover, a considerable amount of the scientific input was obtained from Nigeria, which is the most populous of the five countries considered. The survey on digital farming showed that publications in Nigeria that address deployment cases were focused on the internet of things (IoT), wireless sensor networks, blockchain, and artificial intelligence (AI) technologies. In Ghana, practical cases of blockchain, AI, and big data deployment were observed, while Burkina Faso focused on IoT and AI. In Côte d'Ivoire and Benin, the deployment cases generally focused on AI. [ABSTRACT FROM AUTHOR]

This paper argues for the role of technology, such as artificial intelligence, which includes machine learning, in managing conflicts between herders and farmers in Nigeria. Conflicts between itinerant Fulani herders and farmers over the years have resulted in the destruction of lives, properties, and the displacement of many indigenous communities across Nigeria, with devastating social, economic and political consequences. Over time, the conflicts have morphed into ethnic stereotypes, allegations of ethnic cleansing, forceful appropriation and divisive entrenchment of labels that are inimical to national existence. The reality of climate change and increased urbanization suggest that conflicts are likely to exacerbate over shrinking resources in the near future. Finding solutions to the conflicts, therefore requires innovative thinking capable of addressing the limits of past approaches. While mindful of the human and political dimension of the conflicts, I argue using the method of philosophical analysis that technology possesses the capacity for social transformation, and make a case for the modernization of grazing culture and the curbing of crossborder grazing through machine learning (ML) and other forms of artificial intelligence. Machine Learning represents a transformative technology that addresses the security challenges of irregular migration, accommodates the nomadic and subsistent mode of farming associated with the conflicting parties while enabling a gradual but stable transition to full modernization. I conclude that machine learning holds many prospects for minimizing conflicts and attaining social cohesion between herders and farmers when properly complemented by other mechanisms of social cohesion that may be political in nature. [ABSTRACT FROM AUTHOR]

Purpose: Given that managers play a crucial role in developing and deploying AI for marketing financial services, this study was aimed at better understanding their awareness regarding AI and the challenges they are facing in providing the attendant technologies, as well as highlighting key stakeholders and their collaborative efforts in providing financial services. Design/methodology/approach: Exploratory, inductive research design. The data was gathered through semi-structured interviews with 47 bank managers in both developed and developing countries, including the United Kingdom, Canada, Nigeria and Vietnam. Findings: Managers are aware of the prospects of AI and are making efforts to address AI as a business need but find that there often exist certain challenges in accelerating AI adoption. The study also presents a conceptual framework of AI in relation to financial service marketing, which captures and highlights the interactions among the customers, banks and external stakeholders, as well as the regulators. Research limitations/implications: Banks must understand their business objectives, the available resources and the needs of their customers. Managers should keep the ethical implications of their working relationships in mind when selecting a team or collaborating with partners. In addition, managers should be trained and assisted in comprehending AI in relation to financial services, while the regulators must be involved in the development of AI for financial service marketing. Finally, it is critical to communicate the prospects for AI to consumers. Originality/value: This study provides empirical insight into the opportunities, prospects and challenges pertaining to the use of AI in the area of financial service marketing. It also specifically calls into question certain preconceptions regarding AI and its role in financial services, the chatbots adopted for financial service delivery and the role of marketing managers in developing AI. [ABSTRACT FROM AUTHOR]

Human-computer interaction artificial intelligent system has become more necessary in the African region especially in Nigeria. Local innovative capabilities experience challenges with awareness, non-functionality of the system, and local professional teams carrying out local innovations. However, current human-computer interaction (HCI) guidelines are limited in their applicability to local needs. The paper aims to improve the interactions between users and designed technologies through the user interface. The objectives are to promote usability and maintain the HCIAI system (robot) efficiently; to create awareness of the functionality of HCI in our daily use; and to increase local innovative capabilities and develop the fundamental concepts within our environment. This paper describes an intuitive interaction process with specific attributes allowing interactions between humans and the intelligent system as well as eliciting target experience and making it more appealing to user interface designers as a tool. [ABSTRACT FROM AUTHOR]

Sub-Saharan Africa's low access to electricity and high vulnerability to climate change can be anticipated to constrain the region's future human and economic development prospects. The need for energy conservation, especially electricity, is of crucial importance as it is an economic solution to the problem of energy shortage and atmospheric carbon reduction. The role of Artificial intelligence (AI) has also been displayed by researchers in the promotion of energy management. Most of the past literature in the line of energy management strategies proposed various energy management models based on smart grid and smart meter technology, demand side management, home energy management schemes and management based on AI. This paper proposes an AI-based energy management for households in Nigeria. Genetic algorithm was used on smart meter-like data to optimize the energy consumption of households for 24 hours on a weekday and weekend. To achieve this aim, we determine the typical load profile of a mini-grid setting (for household and commercial load profile), develop a simulation of smart meter-like data and develop an energy management system to optimize electricity consumption during a weekday and weekend in a household. We corroborate our theoretical model with numerical results showing the energy (and consumption) saved during these periods. The algorithm will assist electricity consumers in rural communities to effectively manage their usage by avoiding wastage and the unnecessary payment for energy waste. [ABSTRACT FROM AUTHOR]

Vehicle theft is continuously being reported as a global prevalent crime. It often aids the perpetuation of other related crimes such as kidnapping, armed robbery, terrorism and human trafficking. The traditional mode of combating vehicle theft crime is faced with abnormallies hindering accurate, timely prediction and recovery of stolen vehicles from criminals. This paper presents a computational Artificial Intelligence (A.I) technique known as Ensemble Neuro- Fuzzy modeled system with the aim of minimizing investigation time and number of deployed security operatives towards achieving a high successful rate in the prediction, detection and recovery of stolen cars. A collection of data collected from the Criminal Investigation Department of the Nigeria Police Force, were further analyzed through Dimensionality Reduction formula and Routine Activity Approach (RTA) to extract the most significant features. Dataset were sub-divided into 60, 20 and 20% for training, testing and validating the model respectively. A significant result of 92.91% obtained with this model showed that it is most efficient in predicting, detecting and recovering of stolen vehicles as compared with other machine learning algorithms such as Random Tree, Naïve Bayes, J48 and Decision Rule of prediction accuracy of 86.51%, 71.24%, 67.68% and 55.73% respectively. [ABSTRACT FROM AUTHOR]

In predicting human age, several approaches have been used and tested on different datasets, in this paper, we implemented an age estimation system from facial images using Rotation Invariant Local Binary Pattern Descriptor (RILBD) feature, this was combined with Principal Component Analysis (PCA) for feature high dimensional data and the Support Vector Machine (SVM) algorithm was used for classification. The facial images were grouped into four classes namely; class1 (0-10 years), class 2 (11-20 years), class 3 (21-35 years), and class 4 (above 35 years). To test the performance of the proposed method, experiments were carried out on the Local dataset captured within Kaduna metropolis in the Northern part of Nigeria and the FGNET dataset which is publicly available online. The system achieved an overall accuracy result of 95.0% and 95.7% on the two datasets. This system will be of immense benefit to law enforcement systems (to levy underage drivers), age-specific Human-Computer Interaction (HCI), age-specific access control systems, etc. [ABSTRACT FROM AUTHOR]

Despite the growing momentum of data analysis in Africa, scholarly attention has largely overlooked the promotion of data-driven content for enhanced audience engagement. Grounded in the sociology of news paradigm, this study examines engagement practices of online news platforms in Nigeria and explores the potential influence of audience engagement metrics on editorial decision-making. The in-depth interview research method was adopted for the study. Heads of data journalism units in four purposively selected online news media platforms in Nigeria with established data journalism practices were sampled as respondents for the study. The study identifies six innovative strategies being adopted by online news media in Nigeria to enhance audience engagement. Findings also confirm the centrality of audience engagement metrics to news-making decisions, but with the understanding to also consider the potential societal impact of stories in determining issues to produce data-driven content on. The implication for data journalism practice in Nigeria and its positioning for greater societal impact is discussed. [ABSTRACT FROM AUTHOR]

The need for the adoption of systematic land titling (SLT) in Nigeria cannot be overemphasised. Nonetheless, the problems of speed and cost of geospatial data acquisition, as well as identification of non-surveyed boundaries, remain unresolved, impeding the effectiveness of SLT for non-surveyed boundaries. The integration of language into Artificial Intelligence (AI) has allowed Natural Language Parsing (NLP) to effectively serve as a tool for communication between humans and computer systems. This study presents preliminary results of testing a prototype application that utilises NLP to convert textual descriptions into graphic sketches as a tool towards the production of a-priori sketches that can aid SLT in non-surveyed boundaries. The study determines that NLP alone cannot be used to achieve the required accuracy in geospatial data for SLT; however, the study concludes that NLP can be integrated alongside other ancillary information to enhance SLT in peri-urban regions. [ABSTRACT FROM AUTHOR]

This study investigated the factors influencing science teachers' 'Artificial Intelligence' (AI) utilization by using the 'Technology Acceptance Model' (TAM). The factors investigated alongside TAM variables were teachers' data like; age, sex, and residence type. TAM items that were correlated in this study included; self-esteem, stress and anxiousness, ease of utilization, behavioural intention, attitude towards AI usage, and expected benefits. The population of this study comprised all science teachers (170) in the Calabar Education Zone of Cross River State, Nigeria. The sample was made up of 79 science teachers comprising (58.22%) 46 females and (41.77%) 33 males. The descriptive and analytical research design was used in this study. A questionnaire named ' Approval of Artificial Intelligence: The Teachers' Eye' Questionnaire (AAITEQ) was used for the study. This study raised 3 research questions. The reliability for AAITEQ was from 0.72 to 0.81 using Cronbach's alpha. Findings indicated that the approval for the utilization of AI was high with an overall mean score of 3.00. The highest predicting value for behaviour intent using TAM variables was the ease of usage r =.789. Science teachers' sex (t, 77 = 1.988; p =.060, (p ˃.05), age F (2, 76) =.547; p =.581 (p ˃.05) and teachers' residence location (t,.77 =.533; p = −.062 (p ˃.05) did not influence the behaviour of science teachers' intention of the utilization of AI. It was recommended that both in-service and pre-service teachers be trained on the utilization of AI. [ABSTRACT FROM AUTHOR]

Globally, artificial intelligence (AI) technology spans various industries, but relatively little attention is given to the use of AI technologies by telecommunication industries. This study evaluated the effect of AI on the service quality of telecommunications companies in Nigeria, specifically the effect of data mining, machine learning, and chatbots on the service quality of these firms. The research employed a survey research design, and its population was heterogeneous. A sample size of 400 participants was chosen using Taro Yamane's formula, and the Cronbach alpha test yielded an average of 75%, confirming the reliability of the instrument. To analyze the data collected, descriptive and ordinary least squares regression methods were used. The study revealed that data mining and chatbots exhibited a significant positive effect while machine learning showed a negative relationship to the service quality of the telecommunications industry. Based on these findings, it is concluded that artificial intelligence affects service quality in Nigeria, with strong reference to data mining and chatbot, which enhance the quality of service to customers in Nigeria. It is therefore recommended that telecommunication firms in Nigeria should embrace the philosophy of AI to improve their quality of service. [ABSTRACT FROM AUTHOR]

Antiretroviral therapy (ART) is the common hope for HIV/AIDS-treated patients. Total commitments from individuals and the entire community are the major challenges faced during treatment. This study investigated the progress of ART in the Federal Teaching Hospital in Gombe state, Nigeria by using various records of patients receiving treatment in the ART hospital unit. We combined artificial intelligence (AI)-based models and correspondence analysis (CA) techniques to predict and visualize the progress of ART from the beginning to the end. The AI models employed are artificial neural networks (ANNs), adaptive neuro-fuzzy inference systems (ANFISs) and support-vector machines (SVMs) and a classical linear regression model of multiple linear regression (MLR). According to the outcome of this study, ANFIS in both training and testing outperformed the remaining models given the R2 (0.903 and 0.904) and MSE (7.961 and 3.751) values, revealing that any increase in the number of years of taking ART medication will provide HIV/AIDS-treated patients with safer and elongated lives. The contingency results for the CA and the chi-square test did an excellent job of capturing and visualizing the patients on medication, which gave similar results in return, revealing there is a significant association between ART drugs and the age group, while the association between ART drugs and marital status (93.7%) explained a higher percentage of variation compared with the remaining variables. [ABSTRACT FROM AUTHOR]

The means and the process of doing business have been revolutionized globally and deploying Artificial Intelligence has unlocked significant opportunities that would transform the business model design of SMEs. The need for artificial intelligence in SMEs with favorable technology increases the ease of doing business and encourages efficiency and effectiveness while impacting positively on the productivity outcome. The study dwells on the effect of artificial intelligence on SME Growth in Anambra State. A survey research design was adopted in the study. A population of 50 SME operators was randomly selected, which equally served as the sample size for the study. A structured questionnaire was the major instrument used for data collection in the study. Regression analysis was used to test the formulated hypotheses. The result revealed that the 21% change in the control variables BMD in SMEs is a result of the double effect of the artificial intelligence being experienced by the SMEs, this shows a positive and strong relationship between the variables and concludes that artificial intelligence has a significant influence on the business model design of SMEs in Anambra State. We recommended that SME operators need to adopt artificial intelligence as a working tool in their business operations because it increases efficiency, and effectiveness and reduces the cost of doing business which ultimately and positively affects productivity in the long run. [ABSTRACT FROM AUTHOR]

The article discusses the role of Information and Communication Technology (ICT) in libraries, emphasizing its impact on modernizing services and improving user experiences. It highlights the global adoption of ICT solutions in academic libraries, such as automated systems, digital repositories, and virtual reference services. Despite advancements, challenges like inadequate infrastructure and limited funding persist.

The study investigated how librarians working in various university libraries in Kwara State, Nigeria, adopt and use artificial intelligence. The study raised four research goals as well as four research questions. A descriptive survey method and random sampling techniques with 450 randomly selected librarians from Kwara State Universities, Nigeria, were used for the research. Five research assistants were trained on how to contact respondents and secure their consent before distributing the structured questionnaire designed by the researcher, who assisted in the tool distribution process. The researcher was able to retrieve 410 copies of the 450 questionnaires that were given to the respondents. However, the rate of return was 91%, which is a respectable amount. A self-designed questionnaire was used to elicit responses from the respondents, and a simple percentage was adapted for data analysis. The results showed that there was little adoption of AI in university libraries in Kwara State, Nigeria. The research also reveals that security scanning devices at the entrances and exits of university libraries are the most prevalent AI systems, while other AI systems such as bots, chatbots, face recognition, touch recognition, RFID technologies, humans, AI classification tools, machine-readable catalogs, and not smart AI features are still missing from the Kwara State University libraries. A self-designed questionnaire was used to elicit responses from the respondents, and a simple percentage ratio was adapted for data analysis. The findings revealed that AI has received minimal attention in university libraries in Kwara State, Nigeria. According to the study, the most common AIs are security scanning equipment at university library entrances and exits, followed by robotics, chatbots, face recognition, and touch recognition. RFID technologies, humanoids, AI classification tools, machine-readable catalogs, and AI smart features are still lacking in Kwara State's university libraries. The results of this study also indicate that librarians in a university library are aware of the many ways in which artificial intelligence can be applied to provide services. The results of the study indicate that obstacles to adoption include significant disruption caused by artificial intelligence in traditional library services, a lack of skills and a need for training prior to adoption, irregular power supply, and a lack of adequate infrastructure for adoption, among other problems. The study recommended the need to organize training for librarians to enhance their skills in using artificial intelligence to provide services, and the university administration and libraries should commit and provide the necessary support for the adoption of artificial intelligence by providing the necessary infrastructure to ensure its rapid implementation. [ABSTRACT FROM AUTHOR]

The study investigated how librarians working in the various university libraries in Southern Nigeria adopted and used artificial intelligence. The study raised four research objectives as well as four research questions. A survey design was used for the study with 848 librarians from university libraries in Southern Nigeria as the sample. The entire population was chosen for the study using the total enumeration sample method. Eight research assistants who had received training in how to contact respondents and secure their consent before distributing the structured questionnaire designed by the researcher assisted in the instrument distribution process. The researcher was able to retrieve 704 copies of the 848 questionnaires that were given to the responders. However, the return rate was 83%, which is a respectable amount. The descriptive statistics approach was used to analyse the data that the questionnaire produced. The results showed that there has been little adoption of AI in university libraries in Southern Nigeria. The research also reveals that security scanning devices at university libraries' entrances and exits are the most prevalent AIs, while other AIs like robots, chatbots, face recognition, touch recognition, RFID technologies, humanoids, AI classification tools, machine-readable catalogues, and AI smart features are still lacking in Southern Nigeria's university libraries. The results of this study also suggest that the university library's librarians are knowledgeable about the many ways that AI may be applied to provide services. The study's findings indicate that adoption hurdles include considerable disruption brought on by AI to conventional library services, a lack of skills and the need for training prior to adoption, erratic power supply, a lack of suitable infrastructure for adoption, among other problems. It was recommended in the study that training should be organized for librarians to boost their skills in the use of AI for service delivery and university and library management should be committed and give the needed support towards the adoption of AI by making available the needed infrastructure to ensure their swift implementation. [ABSTRACT FROM AUTHOR]

The usage of Liquefied Petroleum Gas in households has been to increase in recent years. The energy used by households has proved difficult to forecast due to the nature of the independent variables. In recent years, deep learning models has been broadly utilized in the machine learning area to model time series data. Most noticeable is in the field of forecasting. In this work, Neural Network Autoregressive model (NNETAR), Naive forecasting and the Autoregressive Integrated Moving Average (ARIMA) models were used to model the price of Liquefied Petroleum Gas prices(LPG) of 37 states (including the FCT) in Nigeria, with input variables in the form of the price of refilling LPG for 12.5 kg from January 2016 to April 2019 covering a 1480 data points. The Mean Absolute Percentage Errors was used to measure the performance of the model. The result shows that Naive produced lower MAPE for more states compare to NNETAR and ARIMA models. [ABSTRACT FROM AUTHOR]

Purpose: As disruptive technologies, such as the use of artificial intelligence (AI)-enabled customer relationship management (CRM) systems, alter the processes and strategies that banks use in service delivery models, the impact of such technologies on consumer acceptance and buying behavior must continue to be examined. This research studies the impact of technology usage and acceptance of AI-enabled banking CRM systems in Nigeria on consumer buying behavior via the mediation of customer satisfaction and service quality. The study also investigates the negative impact of technology downtime, a frequent phenomenon in the emerging market, which has not, to this point, been studied on a large scale. Design/methodology/approach: The authors collect quantitative data via a face-to-face administered questionnaire from four hundred customers of ten different Nigerian banks regarding their perceptions of technology use in the banking sector. Findings: While the research finds that technology usage has positive and direct effects on service quality, customer satisfaction and consumer buying behavior, service quality was found not to have a significant effect on consumer buying behavior. The study also establishes that technology downtime has a moderating effect on technology usage, consumer buying behavior and customer satisfaction in the banking context. Originality/value: Scant literature exists that explores the importance of culture in technology usage and acceptance, specifically in developing countries like Nigeria. This study explores the impact of technology usage along with acceptance in the Nigerian setting on Nigerian consumers and their resulting satisfaction. Technology usage has been known to impact customer satisfaction in various ways, but no study has looked specifically at how technology in the banking sector can further be of help or harm from a Nigerian perspective. This study explores the technology usage in banking sector of Nigeria and its impact on the consumer buying behaviour. No studies in our knowledge have been known to consider the role of technology downtime, a frequent phenomenon in emerging market, as a factor, which will affect the customer satisfaction and buying behavior. Thus, this study (1a) explores the negative outcomes of technology downtime on both service quality and customer satisfaction, (b) explores the moderating relationship of technology downtime on the technology usage and consumer-related outcomes. [ABSTRACT FROM AUTHOR]

This study examined the perspectives of librarians on the awareness and readiness of academic libraries to integrate artificial intelligence (AI) for library operations and services in Nigeria. Six libraries were drawn from the six geopolitical zones in Nigeria. An open-ended questionnaire posted to the respondents through the mail was used for data collection. Collected data was analyzed using thematic analysis. The findings reveal that the Nigerian academic libraries are aware of the integration of AI systems in libraries and how it is now being adopted and used in many academic libraries around the globe. However, this is not so in the Nigerian context. The findings also reveal that the librarians have mixed feelings about the readiness of academic libraries to integrate AI systems into library operations and services. Based on the librarian perception, the result implies that integration of AI in library operation and services will take the library to the next level by reducing human errors due to repetitiveness in library tasks, and if care is not taken, AI system might take their job role. The challenges reported that academic libraries in Nigeria may likely face the problem of funding, inadequate experts, limited power supply, limited budget to procure the technology and training personnel that will be in charge of the system maintenance. The study recommends the need for adequate funding for libraries to be able to procure, AI and other information and communication technology infrastructure; and recruitment of librarians with relevant requisite skills to work with the technology. [ABSTRACT FROM AUTHOR]

This study examined information professionals of the future and their prospects in the Fourth Industrial Revolution. The study employed a mixed method, where quantitative data were analysed using a percentage and frequency table, while qualitative data were analysed thematically. Alumni from all Nigerian library schools constituted the target population. The study gathered data through a semi-structured questionnaire distributed via Google Forms to several platforms, including WhatsApp, Telegram, and Facebook. A total of 150 filled questionnaires were received from participants in Nigeria's six geopolitical zones. The findings show that participants were fully aware of the emergence of the 4IR. They indicated the impact of the 4IR era on the future job market as driverless cars, the Internet of Things (IoT), Artificial Intelligence (AI), robot technology, metaverse, blockchain and soft skills. It is evident from the findings that these technologies have changed the landscape of all industries. Nigerian information professionals partially possess some 4IR skills, including active learning and learning strategies, and people management, and have good knowledge of skills required for current and future job markets. Challenges associated with the preparation of future information professionals are lack of motivation for trainers; lack of synergy between training schools and the industry; inadequate funding for training schools; lack of qualified personnel; and poor attitude by students to acquire new skills. The study concludes that poor preparation of future information professionals could result in job losses, economic disparities, unemployment, and underperformance in the workplace. The study recommends that training schools should develop a core curriculum for future information professionals that covers characteristics of the 4IR. [ABSTRACT FROM AUTHOR]

The necessity to confirm the effectiveness of ICT tax and FDI to government income from tax in Nigeria. The policy to levy ICT-based enterprises appears to raise firms' tax burdens, however it requires rigorous analysis to determine if this policy should be amended or supported. The purpose of this study is to look into the boost that ICT taxes and FDI inflows have brought to tax revenue collection in Nigeria. The study employs descriptive and inferential statistics, different diagnostic tests, and ordinary least squares techniques to analyze the efficacy of ICT taxes and FDI in increasing general tax income. The analysis shows that ICT tax has a positive and considerable impact on tax revenue, whereas FDI inflows have a somewhat favorable impact but have no effect on tax revenue. The global growth of ICT and the accompanying tax in Nigeria has certain economic and financial ramifications that have not been examined. Several researches on ICT and FDI have been published, however this unusual taxing feature has yet to be explored in the current studies. [ABSTRACT FROM AUTHOR]

The headways in Artificial Intelligence have impacted on every aspect of society especially communications which is a vital part of any civilisation. AI revolution in multimedia applications have now become a means of guaranteeing stress reduction, speed, performance and in the face of a pandemic such as the Covid-19 a safe avenue for journalists. But sadly as a result of the issues faced by developing countries such as Nigeria, journalists are not current with innovations that will lessen the load of seemingly routine duties in the newsroom and collaborate with new technologies in order to stay relevant. In light of this, the purpose of this research was to examine journalists' perception on how robot journalism can (or has) transformed journalism. Hinged on the mediamorphosis theory, the study utilised quantitative survey as 389 former and current media practitioners were chosen through a purposive sampling technique. The research discovered that most Nigerian journalists though familiar with the concept of robot journalism believe Nigerians are not adequately prepared for its adoption. It was established that automation is the way of the future, and Nigerian journalists cannot afford to be consigned to oblivion in the final shift to an automated world, so they must be acquainted to embrace robot journalism. This study recommends that while media practitioners try to grapple with the reality of automated journalism and with concerns on the uncertainties such as pandemics, practitioners need to keep up with technology as supportive techs in their jobs in light of the Covid-19 protocols, around social distancing, ban on travels to ensure they stay on top of major happening without becoming victims. [ABSTRACT FROM AUTHOR]

Poor management practices of road transport assets posed a challenge to the sustainable development of the transport system in developing countries like Nigeria. Studies in the past focused mainly on the performance of road construction process. However, few studies have evaluated the effect of the fourth Industrial Revolution (4.0IR) on the road transport assets in developing countries such as Nigeria. The current study aimed at assessing the effect of the 4.0IR towards improving the management practice of road transport assets. Survey instruments were administered to project and facility managers in the Nigerian road construction sector of the economy using a proportionate random sampling technique. Partial least square structural equation modelling was used for data analysis utilising the Warp 7.0 partial least squares-structural equation modelling (PLS-SEM) software algorithm. The software calculates p-values with WarpPLS based on non-parametric algorithms, resampling or stable algorithms and thus does not require that the variables to be normally distributed. The study concluded that the 4.0IR drivers have a moderate effect change on the management practice of road transport assets in Nigeria at the moment. The findings imply that management of road assets in Nigeria would moderately improve due to the 4.0IR technologies resulting in transport, safety and general efficiency and effectiveness of road networks in Nigeria. The study identified the 4.0IR drivers to include robotics, mobility, virtual and augmented reality, Internet of things and cloud computing, machine learning, artificial intelligence, blockchain, three-dimensional (3D) printing drones that are built with an attached 3D printer (the drone hangs a 3D printing nozzle that has fed plastic, concrete mix or other material from a tube connected to the top of the drone's printing path that precisely plotted by software, for a promised printing accuracy of 0.1 mm) and digital engineering. This study emanated from the government reports and past studies in the area of road transport asset management practice which the study investigated the major causes of poor practices and assessed the effect of the 4.0IR on the practice. [ABSTRACT FROM AUTHOR]

Due to the growing presence of artificial intelligence (AI) in developed countries, this study investigates the awareness and perception about artificial intelligence in the management of university libraries in Nigeria. The study is a survey design that is based on both qualitative and quantitative approaches. The population of the study comprised eighty academic librarians from eight purposively selected university libraries in the country. The finding of the study revealed that academic librarians are aware of the existence of AI usage in the university libraries and that the fear of job loss is the major constraint they face in the adoption of the technologies; even though they are aware that the innovative technologies will enable efficient user satisfaction. The study recommends the need for academic librarians to make themselves relevant in this era of the fourth industrial revolution, by acquiring necessary skills that are in line with the technologies. It is also critical that library management educate academic librarians to understand that the adoption of AI in the library does not translate to the loss of jobs. [ABSTRACT FROM AUTHOR]

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Background: Accurate forecasting model for under-five mortality rate (U5MR) is essential for policy actions and planning. While studies have used traditional time series modeling techniques (e.g., autoregressive integrated moving average (ARIMA) and Holt-Winters smoothing exponential methods), their appropriateness to predict noisy and non-linear data (such as childhood mortality) has been debated. The objective of this study was to model long-term U5MR with group method of data handling (GMDH)-type artificial neural network (ANN), and compare the forecasts with the commonly used conventional statistical methods-ARIMA regression and Holt-Winters exponential smoothing models.Methods: The historical dataset of annual U5MR in Nigeria from 1964 to 2017 was obtained from the official website of World Bank. The optimal models for each forecasting methods were used for forecasting mortality rates to 2030 (ending of Sustainable Development Goal era). The predictive performances of the three methods were evaluated, based on root mean squared errors (RMSE), root mean absolute error (RMAE) and modified Nash-Sutcliffe efficiency (NSE) coefficient. Statistically significant differences in loss function between forecasts of GMDH-type ANN model compared to each of the ARIMA and Holt-Winters models were assessed with Diebold-Mariano (DM) test and Deming regression.Results: The modified NSE coefficient was slightly lower for Holt-Winters methods (96.7%), compared to GMDH-type ANN (99.8%) and ARIMA (99.6%). The RMSE of GMDH-type ANN (0.09) was lower than ARIMA (0.23) and Holt-Winters (2.87). Similarly, RMAE was lowest for GMDH-type ANN (0.25), compared with ARIMA (0.41) and Holt-Winters (1.20). From the DM test, the mean absolute error (MAE) was significantly lower for GMDH-type ANN, compared with ARIMA (difference = 0.11, p-value = 0.0003), and Holt-Winters model (difference = 0.62, p-value< 0.001). Based on the intercepts from Deming regression, the predictions from GMDH-type ANN were more accurate (β0 = 0.004 ± standard error: 0.06; 95% confidence interval: - 0.113 to 0.122).Conclusions: GMDH-type neural network performed better in predicting and forecasting of under-five mortality rates for Nigeria, compared to the ARIMA and Holt-Winters models. Therefore, GMDH-type ANN might be more suitable for data with non-linear or unknown distribution, such as childhood mortality. GMDH-type ANN increases forecasting accuracy of childhood mortalities in order to inform policy actions in Nigeria. [ABSTRACT FROM AUTHOR]