Search

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]

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]

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]

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]

Copyright of Folia Toruniensia is the property of Nicolus Copernicus Public Provincial Library in Torun and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

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]

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]

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]

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]

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]

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]

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 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]

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]

Copyright of Analisi: Quaderns de Comunicacio i Cultura is the property of Universitat Autonoma de Barcelona and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]