Comparative Costs and Returns Pattern of Small-scale Groundnut Milling of RMP-12 and Ex-dakar Varieties in Gombe Metropolis, Gombe State Nigeria

The study determined the costs and returns involved in small-scale groundnut oil processing of two varieties in Gombe metropolis. Twelve markets were purposively selected for their popularity in groundnut oil processing, where 90 processors were selected by simple random sampling technique. Data were collected using structured questionnaires and were analysed using farm budget model, profitability index and t-test analysis. The results revealed that Cost of shelled groundnut constituted the major (92.3% and 91.6%) components of processing costs (P<0.01) for RMP-12 and Ex-dakar respectively. The  gross ratios, fixed ratios and operating ratios of the two groundnut varieties were < 1, meaning that the business was profitable. Also, the returns per naira invested of the respective groundnut varieties was ₦ 0.17 ($0.0006) and ₦ 0.25 ($ 0.0009) significant (P<0.01). Although, the RMP-12 variety gave higher gross income, but the Ex-dakar variety gave higher profit of ₦ 7,428.80 ($ 26.20) per tonne per week (P<0.01). To achieve higher profit, the traders should embark on Ex-dakar variety as the main resource input. They should also have access to formal loans so as to improve productivity and efficiency. Keywords: Comparative costs, Groundnut, Small-scaleJEL Classification: D24; D6

Load frequency control in variable inertia systems

Conventional load frequency control primarily relies on large synchronous generation units to ensure regulation of the system frequency. However, its performance deteriorates as the system parameters, including inertia and droop coefficients, deviate from original system design. This letter proposes an augmented load frequency control (ALFC) to ensure robust frequency regulation under diurnal variations in system parameters that are expected in the future, renewables-rich power system. The superior performance of ALFC is demonstrated by several case studies, and its stability is assessed by small-signal analysis

Relationship between types of organization with the quality of soft-scape construction work in Malaysia

This paper intends to focus on the relationship between types of organisations with the issues of quality of soft-scape construction work. The types of organizations are consultant, contractor, developer, government agency, and educational institution. This research will be using the mix method approach. Chi-square analysis was also performed to find the significant level of relationship between the respondents. Respondents of the survey are among Landscape Architects listed in ILAM directory. The study managed to conduct the questionnaire on 225 persons. This paper was identified the significant difference of the respondents from different type of organisations with the issues of soft-scape construction quality

An Efficient and Secure Energy Trading Approach with Machine Learning Technique and Consortium Blockchain

In this paper, a secure energy trading mechanism based on blockchain technology is proposed. The proposed model deals with energy trading problems such as insecure energy trading and inefficient charging mechanisms for electric vehicles (EVs) in a vehicular energy network (VEN). EVs face two major problems: finding an optimal charging station and calculating the exact amount of energy required to reach the selected charging station. Moreover, in traditional trading approaches, centralized parties are involved in energy trading, which leads to various issues such as increased computational cost, increased computational delay, data tempering and a single point of failure. Furthermore, EVs face various energy challenges, such as imbalanced load supply and fluctuations in voltage level. Therefore, a demand-response (DR) pricing strategy enables EV users to flatten load curves and efficiently adjust electricity usage. In this work, communication between EVs and aggregators is efficiently performed through blockchain. Moreover, a branching concept is involved in the proposed system, which divides EV data into two different branches: a Fraud Chain (F-chain) and an Integrity Chain (I-chain). The proposed branching mechanism helps solve the storage problem and reduces computational time. Moreover, an attacker model is designed to check the robustness of the proposed system against double-spending and replay attacks. Security analysis of the proposed smart contract is also given in this paper. Simulation results show that the proposed work efficiently reduces the charging cost and time in a VEN.publishedVersio

Relationship between Types of Organization with the Quality of Soft-scape Construction Work in Malaysia

This paper intends to focus on the relationship between types of organisations with the issues of quality of soft-scape construction work. The types of organizations are consultant, contractor, developer, government agency, and educational institution. This research will be using the mix method approach. Chi-square analysis was also performed to find the significant level of relationship between the respondents. Respondents of the survey are among Landscape Architects listed in ILAM directory. The study managed to conduct the questionnaire on 225 persons. This paper was identified the significant difference of the respondents from different type of organisations with the issues of soft-scape construction quality.Keywords: Quality Standard; Soft-scape Construction; Organization.eISSN 2398-4279 © 2018. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning &amp; Surveying, Universiti Teknologi MARA, Malaysia.

Optimization Parameters of Injection Moulding Machine For Reducing Warpage of Dog Bone Plastic Part

The optimization of processing parameters on warpage of polypropylene (PP) in the application of injection moulding machine was studied. The appropriate parameters were adjusted to reduce the warpage defect on the tensile test specimen of dog bone. The type of injection moulding machine used in this research is Arburg 420C 800-250C. Four parameters that have been investigated; injection pressure, clamping pressure, back pressure and holding pressure.A concept of design of experiment (DOE) has been applied using Taguchi method to determine the suitable parameters.To measure the warpage of the dog bone, digital height gauge was used to measure the flatness of the part surface.According the analysis of variance (ANOVA), the most significant factor that effect the warpage was holding pressure by 57.82%, followed with back pressure by 25.75%, clamping pressure by 16.27% and injection pressure by 0.16%. Itis found that the optimum parameters setting that have been obtained were injection pressure at 950 bar, clamping pressure at 600 kN, holding pressure at 700 bar and back pressure at 75 bar. The depreciation value of warpage minimum index in this experiment was decreased by 4.6% after confirmation run

Motion Capture Technologies for Ergonomics: A Systematic Literature Review

Muscular skeletal disorder is a difficult challenge faced by the working population. Motion capture (MoCap) is used for recording the movement of people for clinical, ergonomic and rehabilitation solutions. However, knowledge barriers about these MoCap systems have made them difficult to use for many people. Despite this, no state-of-the-art literature review on MoCap systems for human clinical, rehabilitation and ergonomic analysis has been conducted. A medical diagnosis using AI applies machine learning algorithms and motion capture technologies to analyze patient data, enhancing diagnostic accuracy, enabling early disease detection and facilitating personalized treatment plans. It revolutionizes healthcare by harnessing the power of data-driven insights for improved patient outcomes and efficient clinical decision-making. The current review aimed to investigate: (i) the most used MoCap systems for clinical use, ergonomics and rehabilitation, (ii) their application and (iii) the target population. We used preferred reporting items for systematic reviews and meta-analysis guidelines for the review. Google Scholar, PubMed, Scopus and Web of Science were used to search for relevant published articles. The articles obtained were scrutinized by reading the abstracts and titles to determine their inclusion eligibility. Accordingly, articles with insufficient or irrelevant information were excluded from the screening. The search included studies published between 2013 and 2023 (including additional criteria). A total of 40 articles were eligible for review. The selected articles were further categorized in terms of the types of MoCap used, their application and the domain of the experiments. This review will serve as a guide for researchers and organizational management

Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review

Coronavirus, or COVID-19, is a hazardous disease that has endangered the health of many people around the world by directly affecting the lungs. COVID-19 is a medium-sized, coated virus with a single-stranded RNA. This virus has one of the largest RNA genomes and is approximately 120 nm. The X-Ray and computed tomography (CT) imaging modalities are widely used to obtain a fast and accurate medical diagnosis. Identifying COVID-19 from these medical images is extremely challenging as it is time-consuming, demanding, and prone to human errors. Hence, artificial intelligence (AI) methodologies can be used to obtain consistent high performance. Among the AI methodologies, deep learning (DL) networks have gained much popularity compared to traditional machine learning (ML) methods. Unlike ML techniques, all stages of feature extraction, feature selection, and classification are accomplished automatically in DL models. In this paper, a complete survey of studies on the application of DL techniques for COVID-19 diagnostic and automated segmentation of lungs is discussed, concentrating on works that used X-Ray and CT images. Additionally, a review of papers on the forecasting of coronavirus prevalence in different parts of the world with DL techniques is presented. Lastly, the challenges faced in the automated detection of COVID-19 using DL techniques and directions for future research are discussed