Somalia and Somaliland are usually presented as competitors in a zero-sum sovereignty dispute. This article develops a different proposition: internationally recognized Somaliland statehood could also advance Somalia's stabilization and state-building. The "buy one get one free" formulation describes a potential dual peace dividend rather than an automatic result. The study combines qualitative, theory-guided historical and policy analysis with in-depth expert interviews and focus group discussions. Five theoretical mechanisms are proposed. Recognition could clarify the territorial scope of Somalia's federal project, reduce political investment in forceful reunification and redirect resources toward reconciliation and public authority. It could also support security and economic cooperation with Hargeisa and reduce regional threat perceptions that complicate external support for Mogadishu. Interview participants linked the unresolved status dispute to constitutional ambiguity, nationalist mobilization, diplomatic tensions, and diverted state-building attention. The article therefore recommends a negotiated settlement covering borders, citizenship, public assets and debts, security cooperation, freedom of movement, and minority protections. If Somalia is unwilling or unable to accept separation, the international community should step in to mediate the deadlock . With these arrangements, recognition could strengthen Somaliland’s statehood and help Somalia develop a more coherent, legitimate, and governable federal state. Read more

This study examined the relationship between transactional leadership approach (TLA) and employee commitment (EC) using secondary school teachers as a case study. The study considered contingency punishment and contingency reward disintegrated into recognition/appreciation as well as promotion and salary increase as dimensions of TLA. The study adopted the descriptive survey research design and used a 20-item closed-ended, validated and structured questionnaire as an instrument for data collection from a sample of 189 employees of private secondary schools in Ukwuani and Ethiope East Local Government Areas of Delta State. Out of the 189 questionnaires administered, only 171 were retrieved, valid, and used for the analysis to make inferences and final generalizations. Descriptive and inferential statistical tools were employed with the aid of the Statistical Package for the Social Sciences (SPSS). The descriptive statistical tools of percentage and mean rating were used to analyze the demographic data and data relating to research questions, respectively. While the inferential statistics of Pearson Correlation and multiple regression were used to test the hypotheses at the 0.05 alpha level. The study based on the analysis revealed that the influence of TLA on the commitment of employees is positive and significant(R = 0.717, P=0.000). Specifically, it showed with β = 0.229, P=0.009 < 0.05, that appreciation/recognition of employees for doing their jobs well influence EC positively and significantly. With β = 0.510, P = 0.000 < 0.05, that promotion and salary increase positively and significantly influence EC and with β = 0.185, P= 0.017 < 0.05 that contingency punishment for not performing well have a positive and slightly significant influence on EC. Based on the findings of this study, it is recommended that school management should supplement disciplinary or correctional systems with motivational as well as supportive strategies so as to realize sustained EC Read more

This study investigates the effect of Key Audit Matters (KAM) disclosure on market capitalisation, of listed Deposit Money Banks (DMBs) in Nigeria. Adopting an ex-post facto research design, the study utilized panel data from 12 DMBs over a 16-year period (2009–2024), divided into pre-KAM (2009–2016) and post-KAM (2017–2024) periods. Secondary data were extracted from audited financial statements using a standardized disclosure checklist covering four KAM dimensions: Financial Instruments Valuation (FIVD), Loan Impairments (LIPD), Revenue Recognition (RERD), and Litigation and Contingencies (LCOD). The study employed a mixed-effects regression model with Restricted Maximum Likelihood (REML) estimation to assess the relationship between KAM disclosures and market capitalisation, while accounting for unobserved heterogeneity across banks. Descriptive and diagnostic statistics confirmed data suitability and regression assumptions. The findings reveal that FIVD, RERD, and LCOD disclosures significantly and positively influenced market capitalisation, suggesting that transparency in these areas strengthens investor confidence and firm valuation. Conversely, LIPD exhibited a significant negative effect, indicating investor sensitivity to disclosures signaling credit risk. The post-KAM period showed a significant improvement in market valuation, affirming the overall positive influence of mandatory audit transparency reforms. The study concludes that while audit transparency generally enhances investor confidence, the specific content and perceived implications of KAMs determine their market impact. It recommends that banks and regulators enhance the quality, clarity, and context of KAM disclosures to optimize investor understanding and market response. The study contributes to audit disclosure literature and informs regulatory policy on financial reporting in emerging capital markets. Read more

This study examined the effect of entrepreneurial processes proxied by opportunity recognition and resource mobilization on SME performance in Nasarawa State. A survey research design was adopted, and data were collected through a structured questionnaire designed on a five-point Likert scale. The collected data was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM. The study findings revealed that both opportunity recognition (Beta = 0.224, p < 0.05) and resource mobilization (Beta = 0.598, p < 0.001) significantly influence SME performance, with resource mobilization exerting a stronger effect. The results suggest that SMEs that effectively identify market opportunities and mobilize resources are more likely to improve their growth and sustainability in a volatile environment. Based on these findings, the study recommends that SMEs invest in capacity-building to enhance their opportunity sensing and resource management capabilities and that policymakers provide support through training programs, access to finance, and networking platforms, to foster innovation and resource efficiency among SMEs for sustainable development. Read more

Crop diseases pose a significant challenge to global food security, adversely impacting agricultural output and resulting in considerable economic repercussions. The prompt and precise identification of these diseases is essential for effective intervention and sustainable agricultural practices. This study introduces a model based on Convolutional Neural Networks (CNNs) for the automated detection of crop diseases. The model employs advanced deep learning methodologies to recognize and categorize plant diseases through the analysis of leaf images. Our CNN framework is trained on an extensive dataset comprising both diseased and healthy plant images, employing multiple convolutional layers to extract intricate features, including texture, color variations, and patterns linked to specific diseases. The model demonstrates a high level of accuracy in identifying a variety of diseases across different crop species by learning from both overt symptoms and subtle cues. We evaluate the performance of the system using established metrics such as accuracy, and precision, thereby validating its efficacy in practical applications. The proposed system is designed for implementation in low-resource agricultural settings, offering farmers a cost-effective, dependable, and real-time solution for monitoring crop health. Read more

The study examined innovative behaviour and opportunity recognition of food and beverages firms in Port Harcourt. The study used a correlational research methodology, and the population consisted of 25 food and beverage businesses in Rivers State. The study used a census survey with a managerial staff focus in addition to its population of 25 food and beverage companies. One hundred twenty-five (125) copies of the questionnaire were made available in total. The data collected for this study were analyzed through descriptive and inferential statistics. The Spearman Rank-Order Correlation Technique was employed to test the various hypotheses formulated with the aid of the Statistical Package for Social Sciences (SPSS). From the data generated and analysed, it was empirically discovered that a positive and significant relationship exists between Innovative Behaviour and Opportunity Recognition of food and beverages firms in Port Harcourt. Problem solving and creativity showed a strong positive relationship with s opportunity recognition of food and beverages firms in Port Harcourt. The study concluded that engaging in innovative behaviour will achieve bumper success in many food and beverages firms. Following the conclusion above, the study therefore recommends that; Food and beverages firms in Port Harcourt should adopt problem solving approach to take advantage of market opportunities and improve sales and also food and beverages firms should be creative and innovative, especially through new product development, being first to market with new products. Read more

Organizations are striving to ensure an enabling working environment that motivates employees to feel engaged, acknowledged, retained, and respected. These promote efficiency, effectiveness, and organizational growth. The present study examined the relationship between employee recognition and organizational growth; and the survey was based on three selected oil service firms in Nigeria, with an accessible population of 90 staff of the selected oil service firms. Questionnaire copies were administered, and data was collected from the staff. Two hypotheses were formulated and tested, and the Pearson Product-Moment Correlation (PPMC) coefficient was used to test the strength and direction of the relationship between the variables. Findings revealed that employee recognition has a significant positive relationship with organizational growth. Thus, it was recommended that every organization should constantly ensure the recognition process as often as possible; they should employ the reward strategy, to increase their employee willingness and devotion to producing results; and Impactful rewards should be given to employees equitably for work inclusiveness and productivity. Read more

The study looked at the relationship between compensation policy and employee performance in Ado Local Government Area in Ekiti State. The study's goals were to examine the impact of promotion on employee performance, evaluate the impact of salary increases on employee performance, and analyze the extent to which recognition influences employee performance. When it came to safety management, a questionnaire was employed to collect data from the employees. The study's population and sample size were 350 people. Various sampling approaches were used. Because of the nature of the task, the study employed a survey research approach. The study included both primary and secondary data sources. The collected questionnaire was analyzed using correlation analysis. The study discovered that promotion had a considerable impact on employee performance based on the studies conducted. According to the survey, dedicated employees should have their salaries increased once in a while to indicate that their efforts are appreciated. Read more

There are plenty of home security cameras currently on the market, many allowing you to stream live footage over the internet and receive alerts whenever someone wanders past. This paper discusses the facial recognition attendance scheme on CCTV Cameras using OpenCV and Deep learning. Generally, Face Recognition is a method of identifying or verifying the identity of an individual by using their face. Various algorithms are there for face recognition but their accuracy might vary. In this paper, we discuss how we can do face recognition using deep learning. We used face embeddings to perform deep_metric_learning and the development steps of the scheme were; face detection, feature extraction, and lastly comparing faces. The legacy system used at IUEA Was firstly studied in more detail. More requirements for the proposed system were obtained and the system was developed. The interfaces for the new system were implemented using HTML, Bootstrap, and Django which is a high-level Python web framework. After the implementation, the new system was then tested, validated, and deployed for use. Read more

This research aimed at studying the current methods of attendance used at higher institutions of learning in Uganda and the feasibility of using facial biometrics as a new method of capturing attendance. Facial biometrics is distinct from other biometrics because it can be carried out without the consent of the person involved. As a result, the researcher developed a face recognition attendance system using OpenCV and Microsoft Azure CS. Questionnaires, interviews, and observations were used to capture data for the research. The data were analyzed using SPSS to get the requirements and systems functionalities. Object-Oriented Design tools were used to model the architecture of the system. Data Flow Diagram, Use-Case Diagram, Activity Diagram, and Flow Chart were used for processing whereas Entity Relation Diagram was used for data modeling. The system was designed to facilitate attendance management of a large number of attendees with ease. Efficiency and reliability were essential features of the system. Data visualization was provided to help management make informed and timely decisions on management matters that are related to attendance. The system was developed using python Tkinter, OpenCV, and Azure CS as mentioned above. The data (images) used by the system were stored in the cloud for accessibility by multiple users. The system was tested thoroughly using various testing types to uncover and fix errors and to minimize the severity of failures. Read more