Volume-12 , Issue-1 , Mar 2025, ISSN 2348-635X

• Open Access   Article

  Using Hybrid Convolutional Neural Network and Random Forest (CNN-RF) Algorithms to Address Non-Technical Losses in Power Distribution Systems

  Babawale Bunmi Folajinmi, Emmanuel Majiyebo Eronu, Seyi Josiah Fanifosi

  Research Paper | Journal-Paper (WAJES)

  Vol.12 , Issue.1 , pp.1-8, Mar-2025

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  Abstract
  The electricity distribution sector experiences substantial financial losses due to non-technical losses (NTLs) including electricity theft, faulty meters, and commercial losses. This research introduces a combined Convolutional Neural Network and Random Forest (CNN-RF) approach to detect NTLs using metered customer electricity consumption data from the Abuja Electricity Distribution Company. The dataset, covering February 1, 2021, to January 31, 2022, was cleaned, preprocessed, and used to train the model. The CNN part uses a multi-layer design with convolutional layers for automatic feature extraction, followed by dropout layers to mitigate overfitting. Early stopping mechanisms were introduced to optimize training efficiency and prevent model degradation. The RF component was trained on the automatically extracted features by the CNN component and classifies consumers into "energy loss" and "no energy loss" categories. The GridSearchCV algorithm facilitated the RF’s hyperparameters fine-tuning to achieve optimal configurations. The proposed model demonstrated a classification accuracy of 97% with a low false positive rate, thereby surpassing the effectiveness of manual inspections in detecting NTLs. This model can enhance the inspection hit rate and serve as an effective tool for detecting NTL activities in the electricity distribution sector.

  Key-Words / Index Term
  Non-Technical Loss Detection, Random Forest, Machine Learning, Deep Learning, Energy Consumption, Convolution Neural Network

  References
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  [15] Z. A. Khan, M. Adil, N. Javaid, M. N. Saqib, M. Shafiq, and J. G. Choi, “Electricity theft detection using supervised learning techniques on smart meter data,” Sustain., Vol.12, No.19, pp.1–25, 2020.
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  Citation
  Babawale Bunmi Folajinmi, Emmanuel Majiyebo Eronu, Seyi Josiah Fanifosi, "Using Hybrid Convolutional Neural Network and Random Forest (CNN-RF) Algorithms to Address Non-Technical Losses in Power Distribution Systems," World Academics Journal of Engineering Sciences, Vol.12, Issue.1, pp.1-8, 2025

• Open Access   Article

  Enhancing Client Satisfaction in Design Build Project in Nigeria

  Nathan Ikoja, M.M. Muktar, Nuru Gambo

  Research Paper | Journal-Paper (WAJES)

  Vol.12 , Issue.1 , pp.9-16, Mar-2025

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  Abstract
  Client satisfaction is closely linked to performance within the construction sector. Organizations that consistently achieve high levels of client satisfaction are better positioned to enhance their competitiveness in the industry. However, many clients often express dissatisfaction with the outcomes of their projects. Consequently, this study aims to explore how Design-Build contractors address these challenges. A total of 300 respondents, including clients, contractors, and consultants involved in completed design-build projects, were purposefully selected for the survey. Data analysis was conducted using IBM SPSS Version 22 and Warp PLS SEM 3.0v. The results highlighted that effective time management, a clear understanding of the performance brief, the attitudes of project managers, and the adoption of advanced technology are critical factors in achieving client satisfaction. Furthermore, the study emphasized the significance of trust, collaboration, and adopting a client-focused approach to ensure project success.

  Key-Words / Index Term
  Design-Build (DB), Client Requirement (CR) and Client satisfaction

  References
  [1] Adamtey, S. “A Case Study of Performance Analysis of Design-Build Integrated Project Delivery”, IJCER, Vol.2, Issue.1, pp.1-17, 2019.
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  [17] Walker, A. “Project management in construction”. New Jersey: John Wiley & Sons, 2015.

  Citation
  Nathan Ikoja, M.M. Muktar, Nuru Gambo, "Enhancing Client Satisfaction in Design Build Project in Nigeria," World Academics Journal of Engineering Sciences, Vol.12, Issue.1, pp.9-16, 2025

• Open Access   Article

  Moderating Effect of Active Management by Exception on Relationship Between Information Elicitation and Design-Build Quality Delivery in Fct, Abuja

  Nathan Ikoja, M.M. Muktar, Alhassan Dahiru

  Research Paper | Journal-Paper (WAJES)

  Vol.12 , Issue.1 , pp.17-24, Mar-2025

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  Abstract
  An examination is conducted Of Design – Build delivery with a view of finding out if the relationship between inefficiently elicited stakeholders’ information and Design Build quality delivery can be moderated by the intervention of active manager by exception. Data were generated using a questionnaire and analysed using Warp PLS SEM algorithm with graphical interface. Results show that there is a nonlinear relationship between elicitation and quality delivery of Design Build delivery in the study area provided the interaction of a moderator is high. The study recommends the use of moderation as an emerging resource in Design Build delivery to ensure successful delivery.

  Key-Words / Index Term
  Design-Build (DB), Design-Build Delivery (DBD), Elicitation, Validation and Active management by exception (AME).

  References
  [1] Adamtey, S. “A Case Study of Performance Analysis of Design-Build Integrated Project Delivery”, IJCER, Vol.2, Issue.1, pp.1-17, 2019.
  [2] Aluko, O. R., Idoro, G. I., &Mewomo, M. C. “Relationship between perceived service quality and client satisfaction indicators of engineering consultancy services in building projects”. Journal of Engineering, Design and Technology, Vol. 19, Issue.2, pp. 557-577, 2021.
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  [5] Edum-Fotwe, F.T. and McCaffer, R. “Developing Project Management Competency: Perspectives from the construction industry”. International Journal of Project Management, Vol. 18, Issue.2, pp. 111-124. 2000.
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  [14] Raji, A. U. “Contractors Team Commitment Factors for Post-contract Transaction Minimization in Design-build (db) Projects”. ATBU Journal of Environmental Technology, Vol. 13, Issue.2, pp. 130-151, 2020.
  [15] Raji, M. N. “Issues around vocational and career counselling in Nigeria”. International Journal of Contemporary Management, Vol. 18, Issue.2, pp. 47-69, 2019.

  Citation
  Nathan Ikoja, M.M. Muktar, Alhassan Dahiru, "Moderating Effect of Active Management by Exception on Relationship Between Information Elicitation and Design-Build Quality Delivery in Fct, Abuja," World Academics Journal of Engineering Sciences, Vol.12, Issue.1, pp.17-24, 2025

• Open Access   Article

  Optimizing Phonetic Recognition and Computational Efficiency in Swahili Digraphs Using Feature Reduction Model with Multinomial Logistic Regression

  Tirus Muya Maina

  Research Paper | Journal-Paper (WAJES)

  Vol.12 , Issue.1 , pp.25-35, Mar-2025

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  Abstract
  Automatic Speech Recognition systems commonly rely on spectral acoustic features such as Linear Predictive Coding, Perceptual Linear Prediction, and Mel-Frequency Cepstral Coefficients. While these features capture essential spectral information, they often fall short in conveying detailed phonetic distinctions, especially for languages with complex phonological structures like Swahili. This paper introduces a novel approach to enhance Swahili digraph recognition by transforming high-dimensional MFCC feature vectors into a reduced set of probability-based features using Multinomial Logistic Regression (MLR), termed Feature reduction by Multinomial Logistic Regression (FRMLR). The FRMLR method reduces the feature dimensionality from 39 to 5, significantly decreasing computational complexity while preserving critical phonetic information. The proposed method improves recognition accuracy, achieving an accuracy of 92.5% and enhances computational efficiency, reducing training time from 45 minutes to 10 minutes and memory usage by 70%. The findings illustrate how effective FRMLR is at capturing the phonetic nuances of Swahili digraphs, leading to higher recognition accuracy and robustness against variability and noise. The FRMLR approach`s adaptability to other languages and potential applications in various ASR systems highlight its scalability and versatility. By addressing the limitations of traditional spectral features, FERMLR represents a significant advancement in ASR technology, particularly for languages with intricate phonological characteristics. This method holds promise for advancing ASR systems in multilingual environments, contributing to more inclusive and effective speech recognition technologies.

  Key-Words / Index Term
  Automatic Speech Recognition (ASR), Feature Extraction, Multinomial Logistic Regression (MLR), Swahili Digraphs, Dimensionality Reduction, Computational Efficiency, Mel-Frequency Cepstral Coefficients (MFCC).

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  Citation
  Tirus Muya Maina, "Optimizing Phonetic Recognition and Computational Efficiency in Swahili Digraphs Using Feature Reduction Model with Multinomial Logistic Regression," World Academics Journal of Engineering Sciences, Vol.12, Issue.1, pp.25-35, 2025