Peer-reviewed international research papers published open-access with EOI assignment and global indexing across engineering, computer science, environmental science, social sciences, and more.
This study examines the effects of the African Continental Free Trade Area on economic integration in Africa, with a particular focus on the Democratic Republic of the Congo. Using a mixed-methods approach based on secondary data from the World Bank and African Export-Import Bank, the analysis highlights a still limited but significant increase in intra-African trade. The findings show that, despite the substantial potential of the AfCFTA, its effects remain constrained by low economic diversification, infrastructure deficits, and structural asymmetries among member countries. This study contributes to the literature by emphasizing the limitations of regionalism in extractive economies and proposes policy recommendations aimed at enhancing the effectiveness of regional economic integration.
This article explores the application of Commercicometry to optimize the distribution of local products in Kinshasa, DRC. Using data analysis and route optimization, the study identifies consumption patterns and reduces transport costs by 15%. The results show potential benefits for businesses and consumers, highlighting opportunities for data-driven commerce in Africa.
Healthcare data analytics has been a critical and efficient means of ensuring improvements in care, patient outcomes, disease management, operational efficiency, and data-driven decisions in healthcare. The research focused on patient risk stratification in healthcare by benchmarking six clustering algorithms, such as K-Means, Density-Based Spatial Clustering of Applications with Noise (DBSCAN), Hierarchical Clustering, Gaussian Mixture Model (GMM), Spectral Clustering, and Deep Clustering. The PIMA India diabetes public health dataset available in Kaggle and UCI machine learning was used for the experiments. Some data preprocessing techniques, such as removing unwanted features, handling missing values, and feature scaling, were implemented prior to applying clustering.
These algorithms were evaluated with these metrics: silhouette score, Davies-Bouldin index, computational efficiency, scalability, interpretability, and ability to tolerate noise. It has been found that among the conventional clustering algorithms, DBSCAN provided the highest clustering accuracy in terms of a Silhouette Score of 0.39 and Davies-Bouldin index of 0.76, whereas deep clustering provided high clustering accuracy with a Silhouette Score of 0.37 and Davies-Bouldin index of 0.91. While K-Means failed to provide the highest clustering accuracy, it performed excellently in terms of computational efficiency, scalability, simplicity, and interpretability. It can be concluded that K-Means continues to be the most practical, fast, and scalable clustering algorithm for healthcare analytics.
This experiment focused on determining the effect of auditory stimuli on biological growth and the bioelectricity of the plant named Ocimum basilicum, otherwise known as basil. The research work covered three different auditory stimuli; that is, Islamic Adhan call for prayers, sonata from the violin by the famous composer Johann Sebastian Bach whose frequency tone was 432 Hz, and natural sound from the environment. The purpose of conducting this study was to determine the effect of auditory stimuli on the bioelectric activities and the growth of leaves of the basil plants. This study involved the use of quantitative approach in research whereby real-time data was obtained from the plants over a period of three weeks or four weeks. In this experiment, the fifteen plants were evenly divided into three groups and exposed to various auditory stimuli every day for fifteen minutes. In order to measure bioelectrical signals in the plant, the Plant SpikerBox device was employed while measuring the growth of the leaves was done every three days. From this study, it is evident that the plants exposed to violin sonata and Islamic Adhan had higher bioelectrical activities and leaf growth as compared to those exposed to environmental sounds. The results obtained from this experiment agree with previous research in which vibrations produced in the sound waves can serve as stimuli for the environment with an effect on the physiology and electricity of the plants.
This study examined the environmental and socioeconomic effects of informal settlements in Gasabo District, Kigali City, Rwanda, to address the challenges of rapid, unregulated urban expansion. Utilizing a descriptive mixed-methods design, quantitative data were gathered from 398 households across Gatsata, Gisozi, Kinyinya, and Remera sectors, alongside qualitative insights from 15 key informants. Empirical findings revealed high prevalence levels for unplanned housing (Mean = 4.26), poor infrastructure (Mean = 4.26), land encroachment (Mean = 4.18), and inadequate waste management (Mean = 4.28). These structural deficits generate severe environmental hazards, notably solid waste pollution (Mean = 4.29) and seasonal flooding (Mean = 4.27), which directly exacerbate socioeconomic vulnerabilities including poor livelihoods (Mean = 4.28) and restricted service access (Mean = 4.25). Correlation analysis confirmed a profound, positive relationship between environmental degradation and socioeconomic precarity (r = 0.82, p < 0.01). Furthermore, the multiple linear regression model demonstrated high explanatory power (R2 = 0.72, p < 0.001), with a lack of waste management emerging as the strongest predictor of adverse socio-environmental outcomes (β = 0.36), followed by poor infrastructure (β = 0.32). The study concludes that structural deficits in informal settlements manufacture a compounding vulnerability loop where environmental risks directly reinforce household poverty. To break this cycle, municipal authorities must transition from reactive relief to integrated, climate-resilient settlement upgrading programs. Policy interventions must prioritize executing structural drainage upgrades, establishing formal waste collection systems, enforcing zoning regulations against hazard-zone encroachment, and regularizing land tenure to foster long-term urban sustainability and resilience.
Cette étude examine le décalage entre les besoins réels des enseignants du primaire en didactique du français et l’offre institutionnelle de formation continue à Kisangani. Elle adopte une approche quantitative descriptive et repose sur un questionnaire administré à 294 enseignants issus des communes de Makiso, Kabondo, Kisangani, Mangobo et Tshopo. Les résultats montrent que les enseignants expriment des besoins marqués en appropriation de l’approche par situation, en disponibilité de matériels didactiques, en usage des outils numériques, en accès aux manuels scolaires et en construction d’outils d’évaluation. Ils considèrent également que ces besoins sont rarement pris en compte dans les formations continues, lesquelles restent souvent déconnectées des réalités de la classe. L’étude met en évidence une prédominance de supports classiques dans l’enseignement du français et un faible recours aux démarches interactives. Ces constats conduisent à recommander une formation continue plus contextualisée, plus participative et mieux alignée sur les besoins professionnels des enseignants
Cette étude analyse les besoins réels et les contraintes de la formation continue des enseignants du primaire à Kisangani en didactique du français, à partir des perceptions des inspecteurs et conseillers pédagogiques. Elle adopte une approche quantitative descriptive et s’appuie sur un questionnaire administré à 45 sujets sélectionnés par recensement exhaustif. Les résultats montrent que les formations continues sont perçues comme insuffisamment adaptées aux besoins réels des enseignants. Les difficultés les plus fréquemment signalées concernent la faible maîtrise didactique du français, l’application des approches pédagogiques modernes, la rareté des formations continues et l’insuffisance des supports didactiques. Les répondants soulignent aussi des contraintes financières, institutionnelles, matérielles et humaines. En conclusion, l’étude recommande une formation continue contextualisée, fondée sur l’observation de classe, le suivi post-formation, l’implication des enseignants et l’adaptation des contenus aux réalités du terrain.
Cette recherche examine l’incidence des dépenses publiques de santé et d’éducation sur le développement de la République Démocratique du Congo, en mobilisant une approche méthodologique mixte articulant analyses qualitatives et quantitatives. Elle met en évidence le rôle structurant de ces secteurs dans la formation du capital humain et dans la consolidation des capacités productives nationales. L’éducation, en tant que vecteur de compétences et de comportements favorables à la santé, et la santé, en tant que condition préalable à l’apprentissage et à la productivité, apparaissent comme des piliers indissociables du développement humain. Toutefois, l’étude souligne que l’efficacité des investissements demeure entravée par des disparités provinciales, des contraintes institutionnelles et des chocs exogènes, limitant ainsi leur portée réelle sur l’amélioration des conditions de vie.
Sur le plan analytique, l’utilisation de modèles de régression multiple permet d’évaluer la relation entre les dépenses publiques et l’évolution de l’indice de développement humain. Les résultats révèlent une corrélation positive mais relativement faible, suggérant que les dépenses de santé et d’éducation, bien qu’essentielles, ne suffisent pas à elles seules à expliquer les dynamiques du développement. D’autres facteurs structurels – tels que la gouvernance, la sécurité et les politiques macroéconomiques – exercent une influence déterminante. L’étude conclut à la nécessité d’une gestion plus efficiente des ressources publiques et d’une intégration des politiques sectorielles dans une stratégie globale, afin de renforcer la résilience et d’assurer un développement durable et inclusif.
Cette étude analyse l’efficacité de la politique monétaire dans un contexte de forte dollarisation en République Démocratique du Congo (RDC) sur la période allant de 2002 à 2024. L’objectif principal est d’évaluer dans quelle mesure la dollarisation affecte la transmission des instruments de politique monétaire et la capacité de la Banque Centrale du Congo (BCC) à stabiliser le niveau général des prix.
À travers une approche méthodologique combinant l’analyse théorique et l’économétrie, cette étude examine les relations entre l’inflation, la masse monétaire, le taux de change et le degré de dollarisation. Les résultats mettent en évidence que la forte prédominance du dollar américain dans les transactions et l’épargne réduit considérablement l’efficacité des instruments traditionnels de politique monétaire, notamment le taux directeur et les opérations d’open market.
Enfin, le travail propose des recommandations visant à renforcer la crédibilité de la politique monétaire, améliorer le cadre institutionnel, promouvoir l’inclusion financière et favoriser une dédollarisation progressive de l’économie congolaise, condition indispensable pour une stabilité macroéconomique durable.
Many constant false alarm rate (CFAR) detection algorithms that have certain robustness for non-homogeneous clutter have been proposed. These algorithms can be classified into: Spatial CFAR, in which the threshold level is estimated by using the returns from the resolution cells, which are adjacent to the cell of interest. Temporal CFAR, in which the returns are gathered from previous scans in the same cell of interest to estimate the threshold value. Most of CFAR algorithms consider spatial CFAR, which uses the sliding-window CFAR technique, which slides in the reference cells in the period between two successive radar pulses. For the sliding-window technique, the set of reference cells comprises the neighbouring cells around the test cell in the range-Doppler (RD) map of the current radar scan. the spatial CFAR is classified into two groups: standalone CFAR, and combined CFAR. Based on the three radar field environments, the detection process formed the adaptive threshold required to detect the received radar cell signal. Many algorithms are used to design this adaptive threshold to satisfy a Constant False Alarm Rate (CFAR) according to the detection criteria used in the specified environment, in non-homogenous, homogenous, or multi-target environments.
Internal control systems play an important role in improving operational efficiency, supporting reliable financial reporting, and reducing fraud risks within organizations (COSO, 2013). Recently, fraud prevention and fraud detection have become major concerns for small and medium-sized enterprises (SMEs) in Oman due to increasing financial irregularities and weaknesses in internal control practices (ACFE, 2022). This study aims to examine the impact of internal control systems on fraud prevention and fraud detection in SMEs in Oman. The objectives of this study are to explore the relationship between internal control systems and fraud prevention, investigate the relationship between internal control systems and fraud detection, and evaluate the effectiveness of internal control practices in reducing fraud risks (Albrecht et al., 2019). The study adopts a quantitative research approach using primary data collected through a structured questionnaire distributed to employees working in SMEs in Oman, including accountants, financial managers, internal auditors, and administrative staff (Saunders et al., 2019). A total of 30 responses are collected and analyzed using Microsoft Excel through descriptive statistics, correlation analysis, and regression analysis (Hair et al., 2010). The findings indicate that internal control systems have a strong positive relationship with both fraud prevention and fraud detection. The regression results also show that internal control systems significantly influence fraud prevention and fraud detection in SMEs in Oman. This research contributes to improving understanding of the role of internal control systems in strengthening financial reliability, reducing fraud risks, and supporting better governance practices within SMEs.
Keywords: Internal Control Systems, Fraud Prevention, Fraud Detection, SMEs, Internal Audit, Financial Control, Oman
Financial planning is increasingly recognized as an essential managerial practice that enhances organizational performance and sustainability, particularly among Small and Medium Enterprises (SMEs). Effective financial planning supports organizations in managing financial resources efficiently, improving decision-making processes, controlling expenditures, and achieving long-term financial stability. Despite its importance, many SMEs continue to face difficulties in implementing effective financial planning practices due to limited financial expertise, inadequate financial systems, and resource constraints. Therefore, this study examines the impact of financial planning on the financial performance of SMEs in Oman. The study specifically aims to understand financial planning practices in Omani SMEs, determine the key components of financial planning, analyses the impact of financial planning on financial performance, and examine the challenges faced by SMEs in implementing effective financial planning practices. A quantitative research approach was adopted, and primary data were collected using a structured questionnaire distributed electronically through Google Forms. Purposive sampling was employed, and data were obtained from 34 respondents working in SMEs across Oman. The collected data were analyzed using Microsoft Excel through descriptive statistics, correlation analysis, and regression analysis. The findings revealed that financial planning practices, including budgeting, forecasting, cash flow management, and financial analysis, are widely adopted among SMEs and positively influence profitability, financial stability, and organizational effectiveness. However, challenges such as limited expertise, financial constraints, and business uncertainty continue to affect implementation. The study concludes that effective financial planning significantly contributes to improving the financial performance and sustainability of SMEs in Oman.
This article examines the applicability of the non-communicability clause to fruits and movable assets. It starts with a theoretical and practical analysis of how the clause operates across different property regimes. The article highlights its succession and patrimonial implications. It also discusses the main challenges and solutions related to its application. The effectiveness of the clause depends on careful wording, an express provision for subrogation (if applicable), and organized documentation. The study adopts a deductive method and a bibliographic procedure, drawing on doctrine, jurisprudence, and legislation. Despite its legal validity, the clause’s effects often become significant only when conflicts are established. These conflicts include divorce proceedings, dissolution of a stable union, or an inventory. When drafted well, the non-communicability clause is an effective tool for planning and asset protection, provided it is applied with skill, clarity, and proper legal support.
This article presents a case study of a Brazilian company in which the commercial and financial departments conducted in an internal negotiation concerning the restoration of a client’s credit after the settlement of a substantial outstanding debt. The central tension in the case involved the commercial department’s objective of increasing sales and preserving a strategic client relationship, while the financial department’s objective was to avoid risk. The negotiation dynamics were examined by characterizing the parties’ positions and interests. The space of possible agreements, the parties’ options and their alternatives were also analyzed. The findings of this case study support the view that, in order to reach a mutually beneficial agreement and enable the parties to return to the negotiation process and gradually restore the client's credit, the organization’s stability can be preserved by shifting from a positional bargaining to an interest-based negotiation approach. The case study presented here makes a valuable contribution to the study of negotiation, highlighting the importance of internal negotiations within organizations and showing how the use of a structured framework and an interest-driven approach can generate value for the organization despite divergent interests among departments.
Energy consumption during neural network training and inference has become a significant challenge due to the growing complexity of deep learning models and the rapid expansion of AI applications in edge and cloud environments. This research explores ways to reduce the energy demand of neural networks while maintaining an acceptable level of model accuracy. The main issue being addressed is the excessive energy consumption caused by high multiply-accumulate (MAC) operations, frequent memory access, and inefficient use of hardware resources, which raise operational costs and hinder sustainable deployment. The study used mathematical energy modeling and optimization techniques to measure energy consumption, including decomposition of computation-memory energy, training energy estimation, and inference energy assessment. Additionally, pruning, quantization, and compression techniques were applied to simplify models. Hardware-aware efficiency was assessed through dynamic energy modeling based on voltage, frequency, and capacitance, as well as throughput-per-watt evaluation of accelerators. The energy-performance trade-offs were examined using energy-delay products (EDP) and a multi-objective sustainability cost function. The results showed that Transformer models consumed the most energy (39.6 J) and had the highest EDP (7.13 J·s), while DNN3 had the lowest EDP (0.97 J·s), with an energy consumption of 12.1 J and an inference time of 0.08 s. Pruning improved efficiency but lowered accuracy—CNN accuracy decreased from 94% to 91% as pruning ratios increased from 0.33 to 0.54. Voltage scaling also reduced power from 30W to14 W by lowering the voltage from 1.1 V to 0.7 V. The findings suggest that energy-conscious AI policies should encourage model compression, hardware-efficient accelerators, and sustainability-focused deployment metrics to reduce carbon emissions and lower operational costs.
Antimicrobial resistance (AMR) is the resistance possessed by microorganisms such as bacteria to survive against drugs that are normally effective in killing them. This problem is increasing at global scale and is considered one of the major public health concerns of the 21st century because microbes have developed resistance against many of broad spectrum commonly used antibiotics like penicillin, methicillin, and ampicillin by their various adaptive mechanisms and resistance conferring proteins. Two important proteins involved in this process are Beta lactamase TEM-type (BlaTEM) and Penicillin-Binding Protein 2a (PBP2a). BlaTEM hydrolyzes β-lactam antibiotics such as ampicillin, while PBP2a enables methicillin-resistant Staphylococcus aureus (MRSA) continue cell wall synthesis even in the presence of methicillin. Such mechanisms allow bacteria to survive and spread infections that are difficult to treat.
If no action is taken, AMR could become a silent pandemic by 2050, leading to millions of deaths worldwide . Researcher worldwide are working on it in both laboratory studies and computational approaches. Bioinformatics is significantly contributing to this field by identifying resistance genes, studying protein structures, and predicting drug-protein interactions through molecular docking and other in silico methods. These strategies support the design of new drugs and can help reduce the impact of antimicrobial resistance in the future.
Standard software engineering practices - like Agile, Scrum, and DevOps—are built on the premise of deterministic systems. They work because we expect the same input to produce the same output every single time. However, these methodologies struggle when applied to autonomous agents powered by Large Language Models (LLMs), which are inherently probabilistic, emergent, and highly sensitive to context. This paper introduces the LLM Agent Development Lifecycle (LADL), a specialized nine-phase engineering framework designed specifically for these unpredictable autonomous systems. LADL brings together requirement engineering, prompt architecture, tool and memory integration, safety and alignment, probabilistic testing, human-in-the-loop (HITL) validation, observability, drift monitoring, and continuous alignment into one cohesive workflow. The framework draws on an interdisciplinary mix of the Cynefin Framework, Statistical Process Control, AI alignment theory, and prompt engineering research. By analyzing where Agile falls short and synthesizing existing frameworks, this paper identifies six major gaps in current literature and shows how LADL fills them through its unique phases and governance. We also introduce Prompt Signature Hashing (PSH), a new governance tool that uses cryptographic methods to ensure prompt traceability, versioning, and auditing. To show how LADL works in practice, we apply it to the development of a healthcare triage agent. Finally, we evaluate LADL as a design science research artifact based on its utility, completeness, theoretical depth, and internal consistency. This paper offers AI engineers a rigorous, structured lifecycle for building and governing reliable, production-ready autonomous agents.
Cet article analyse les déterminants structurels de l’inefficacité du financement des entreprises en RDC, caractérisé par une dépendance exclusive à l’intermédiation bancaire à court terme. En mobilisant une approche comparative avec la côte d’ivoire qui pivot la Bourse Régionale des Valeurs Mobiliers (BRVM), cette étude examine du point de vue de la gestion financière les conditions de microstructure, de gouvernance et de tarification des risques nécessaires à l’émergence d’un marché financier efficient en RDC.
Ce travail démontre que la transition d’une économie d’endettement vers une économie de marchés de capitaux en RDC requiert une réduction du risque de contrepartie par l’indépendance de la compensation, une incitation au dual-listing des firmes extractives, et une gestion rigoureuse du risque de change induit par la dollarisation structurelle des bilans.
Mots-clés : structure du capital, micro structure des marchés, coût du capital, Gestion des risques, Dollarisation, RDC, BRVM, etc.
Autonomous vehicles depend on the development of a reliable perception system that can perceive surrounding obstacles and provide appropriate guidance during autonomous driving. However, single-sensing perception models pose various challenges regarding environment conditions, depth prediction, and object localization. The current research paper focuses on the analysis of the efficiency of deep learning-based multi-sensor fusion in improving the perception process in autonomous driving. In this research, three perception models were analyzed—the camera-based YOLOv8, the LiDAR-based PointPillars, and the multi-sensing fusion model, BEVFusion. The methodology of the current research is quantitative and utilizes the Python programming language to train and analyze perception models. The efficiency of each perception model was measured by mean average precision (mAP), nuScenes detection score (NDS), precision, recall, false positive rate, and localization error. As a result, BEVFusion demonstrated the best performance among other models, achieving mAP = 0.691, NDS = 0.742, Precision = 0.782, Recall = 0.735, and Localiza-tion Error = 0.308 m. The results indicate that multi-sensor fusion provides substantial improvements in terms of detection precision and robustness, which makes multi-sensor fusion one of the best solutions for future autonomous driving systems.
In this study, an experimental investigation was conducted to determine the thermal performance of a spherical dimple corrugated plate solar air heater (SDCPSAH) at distinctive environmental conditions (by varying mass flow rate). The experiments were performed for air flow rates of 0.009kg/s, 0.014kg/s, 0.020 kg/s, 0.024 kg/s and 0.028 kg/s. The result showed that a higher heat transfer coefficient can be obtained by SDCPSAH with a U-turn airflow pattern. The presented solar air heater requires less surface area than that of a flat plate solar air heater for the same input of solar radiation. The heat transfer rate is higher due to turbulence of the air in the spherical dimple. Thermal boundary layers are disrupted by vortex flow.
Peningkatan kesejahteraan sosial masyarakat merupakan tujuan utama pembangunan nasional yang memerlukan intervensi terencana dan berkelanjutan. Artikel ini mengkaji peran penyuluh sosial dalam implementasi program Sekolah Rakyat (SR) sebagai salah satu instrumen peningkatan kesejahteraan sosial masyarakat. Penelitian ini bertujuan untuk menganalisis kontribusi penyuluh sosial dalam memfasilitasi program SR agar dapat secara efektif memberdayakan masyarakat, dengan meninjau melalui lensa teori kesejahteraan sosial dan pemberdayaan masyarakat. Metode penelitian yang digunakan adalah studi literatur kualitatif dengan pendekatan deskriptif analitis terhadap berbagai sumber pustaka relevan. Hasil penelitian menunjukkan bahwa penyuluh sosial memiliki peran krusial sebagai fasilitator, motivator, edukator, dan mediator dalam penyelenggaraan SR. Mereka mengidentifikasi kebutuhan spesifik masyarakat, merancang kurikulum SR yang adaptif, serta memonitor dan mengevaluasi dampak program. Melalui program SR, masyarakat memperoleh peningkatan pengetahuan, keterampilan, dan akses pada sumber daya, yang secara kolektif berkontribusi pada peningkatan kapasitas diri dan kemandirian, sejalan dengan prinsip-prinsip kesejahteraan sosial dan pemberdayaan. Peran kolaboratif penyuluh sosial dengan berbagai pemangku kepentingan juga menjadi kunci keberhasilan program ini.
Kata Kunci: penyuluh sosial; Sekolah Rakyat; kesejahteraan sosial; pemberdayaan masyarakat; pendidikan non formal.
Today, countries all over the world are seeking sustainable economic growth, factors that contribute to this growth (e.g., employment creation, higher per capita income and equitable distribution of wealth) are important targets for development. Of particular interest, is the fact that small units are playing a very important role in entrepreneurship development and thus in economic development to a large extent. The study aimed to explore the contribution of entrepreneurship towards the economic transformation in Owerri community, Imo State. Specifically, the study aimed at finding out: (i) the contribution of entrepreneurship to the creation of employment in the region; (ii) the role of entrepreneurship in the improvement of per capita income of the region and (iii) the effect of entrepreneurship on the generation of income equity in the region. The population of 160 people was purposively selected and a total of 150 people were selected for the study. The data collected were then expressed in tables and simple percentage and the Multiple Regression Analysis was also conducted to test the hypotheses in SPSS 21. The results showed that there has been a significant effect on the creation of employment opportunities as the venture businesses have contributed to the improvement of the income per capita and increased equity of the residents of Owerri. The results are proof of the strategic role of entrepreneurship in supporting the development of the regions.
Cette étude analyse l’effet des institutions et de la gouvernance sur la croissance économique en République Démocratique du Congo sur la période 2006-2024. L’objectif principal est d’évaluer l’influence de la qualité institutionnelle et de la gouvernance publique sur l’évolution du taux de croissance du PIB réel.
La méthodologie repose sur l’approche ARDL ainsi que sur le modèle à correction d’erreur (ECM). Les données utilisées proviennent principalement des bases World Development Indicators (WDI) et Worldwide Governance Indicators (WGI) de la Banque mondiale. Les variables explicatives retenues sont la qualité institutionnelle, la gouvernance, la formation brute du capital fixe et l’inflation.
Les résultats montrent que la qualité institutionnelle influence significativement la croissance économique en RDC, tandis que la gouvernance présente un effet positif mais non significatif. En revanche, la formation brute du capital fixe exerce un effet positif et significatif sur la croissance économique. Les résultats du test de cointégration et du modèle ECM confirment l’existence d’une relation de long terme entre les variables étudiées.
Cette étude met en évidence l’importance du renforcement des institutions, de l’amélioration de la gouvernance publique et de la promotion des investissements productifs pour soutenir durablement la croissance économique en République Démocratique du Congo.
Voice Assistance Technology (VAT) has experienced significant growth and integration across consumer devices globally due to its convenience and hands-free interaction capabilities. However, despite widespread availability and technological advancement, VAT adoption among tertiary students in Ghana remains below expectations, with many exhibiting resistance toward sustained usage. The present study investigates consumer barriers toward the intentions to use and recommend VAT through the lens of Innovation Resistance Theory (IRT). We developed a research model based on IRT and tested it using a cross-sectional study with 1,342 tertiary students from major universities in Ghana. Study findings suggest that usage, value, and risk barriers are negatively associated with intentions to use VAT, while usage and value barriers show negative associations with users' intention to recommend VAT. The tradition and image barriers did not share significant associations with user intentions among this cohort. The study offers theoretical and practical implications for researchers and practitioners in understanding consumer resistance to voice-based digital assistants in the Ghanaian context.
Purpose - This study builds on a conceptual model by integrating voice assistance technology (VAT) features (Domain knowledge and Query capabilities) while extending expectation confirmation theory (ECT) factors (interaction quality, confirmation, and user experience) to evaluate the continued intention to use of voice assistance technology among tertiary students in Ghana.
Design/methodology/approach - Data were collected through an online questionnaire administered to 1,124 tertiary students across universities in Ghana. The data were further analysed, and the presented hypotheses were evaluated using partial least squares structural equation modelling (PLS-SEM).
Findings - The research indicates that domain knowledge and query capabilities predict interaction quality. Interaction quality significantly impacts expectation confirmation, user experience, and the continuous intention to use voice assistance technology. VAT design will become a fundamental factor; thus, all interactions should be user-friendly, efficient, and reliable, and the successful implementation of voice assistants in educational contexts will largely depend on VAT features.
Originality/value - This study is the first to demonstrate the effectiveness of a VAT-ECT model for voice assistance technology among tertiary students in Ghana. The user continuance intention to use voice assistants in the educational context has not yet been studied in the Ghanaian setting. These findings further enrich the literature on voice assistance technology, digital learning, and information systems by focusing on the domain knowledge and query capabilities variables in educational technology adoption.
This research investigates the problem of insufficient investment awareness among citizens of the Sultanate of Oman and explores various factors affecting their engagement with financial markets. Despite numerous measures implemented under Oman Vision 2040 aimed at economic diversification and financial inclusivity, many citizens lack sufficient knowledge of investment mechanisms, including stocks, bonds, and mutual funds — particularly among middle-class individuals and youth. The study adopts a positivist philosophy with a deductive approach, using a quantitative research design. Data were collected through a structured questionnaire administered to 58 randomly selected respondents in both online and paper formats. Findings reveal that a majority of respondents rated their investment knowledge as average, that traditional investment instruments were most widely recognised, and that social media serves as the primary source of financial information. The research identifies a lack of formal financial education and fear of financial risk as the dominant barriers preventing individuals from participating in investment markets. The study concludes that targeted financial literacy programmes, integration of investment education into the academic curriculum, and greater public awareness campaigns are essential to improving investment participation in Oman. These findings contribute to existing knowledge and offer practical recommendations for policymakers, educators, and financial institutions seeking to advance financial inclusion in Oman.
Accounting practices play a central role in supporting effective financial decision-making within banking institutions. This study investigates the role of accounting practices in improving financial decision-making at the National Bank of Oman(NBO), focusing on four key dimensions: current accounting practices and IFRS alignment, financial reporting quality and its influence on decision-making, challenges in accounting integration, and strategies for enhancing accounting practices. The study adopts a quantitative research design grounded in a positivist philosophical paradigm, and primary data were collected through a structured questionnaire distributed to 104 employees at NBO, including financial managers, accountants, internal auditors, and senior executives. Data were analyzed using descriptive statistics, Pearson correlation analysis, and multiple regression analysis through JASP statistical software. The findings reveal that accounting practices (Q1)are the strongest predictor of financial decision-making quality(β = 0.590, p < .001), followed by strategies for enhancement (Q4)(β = 0.247, p = .003), while challenges in accounting integration (Q3)did not demonstrate a statistically significant direct effect on decision-making quality (p = .307). The overall regression model explained 78.0% of the variance in financial decision-making quality (R² = 0.780, F = 118.4, p < .001), confirming the strong influence of accounting practices on decision outcomes at NBO. The study concludes that while NBO employees broadly recognize the importance of accounting practices in supporting financial decision-making, notable gaps remain in full IFRS compliance, particularly in relation to IFRS 9 ECL modeling. Evidence-based recommendations are proposed for strengthening IFRS compliance, internal controls, staff training, inter-departmental communication, and digital transformation at NBO.
influençant le pronostic vital et neurodéveloppemental du nouveau-né. Contrairement aux anciennes croyances, le nouveau-né, y compris prématuré, perçoit la douleur de manière intense en raison de l’immaturité de ses mécanismes inhibiteurs.
En réanimation néonatale, l’exposition répétée à des gestes douloureux, sans prise en charge adéquate, entraîne des conséquences immédiates et des séquelles à long terme. La douleur constitue ainsi un enjeu éthique et médical incontournable.
Ce travail a montré que la douleur néonatale peut être évaluée grâce à des outils validés (PIPP, NIPS, CRIES, DAN) et efficacement prise en charge par une approche multimodale combinant méthodes non pharmacologiques et traitements médicamenteux.
À Lubumbashi, des défis persistent, notamment le manque de formation, l’absence de protocoles et les contraintes en ressources. Toutefois, une amélioration est possible grâce à la mise en place de stratégies simples : évaluation systématique, formation du personnel, protocoles adaptés et accès aux traitements essentiels.
The study investigated the effect of relationship marketing on customer retention of selected commercial banks in Owerri, Imo State, Nigeria. The study examined the relationship between trust and customer loyalty, communication and repeat patronage, and commitment and relationship continuity. The descriptive survey research design was used in this study. Population for the study consisted of 300 employees and active customers of selected commercial banks in Owerri, Imo State, Nigeria. Using Taro Yamane formula, 171 respondents were determined for the study. Out of 152 questionnaires that were retrieved for the study, valid questionnaires for the study were 152. The data for the study were collected through the use of structured questionnaires and analyzed using descriptive statistics and Pearson Product Moment Correlation and analyzed using Statistical Package for Social Sciences (SPSS) version 23. The findings of the study revealed that trust had significant positive relationship with customer loyalty (r = .787, p < .05). Similarly, the study found out that communication had significant positive relationship with repeat patronage (r = .788, p < .05). Furthermore, the study established that commitment had significant positive relationship with relationship continuity (r = .788, p < .05). These findings suggested that relationship marketing dimensions influenced customer retention of commercial banks’ customers positively. The study’s findings supported the Commitment–Trust Theory which posited that trust and commitment were very important for sustaining long-term customer relationships. Thus, the study concluded that relationship marketing practices affected customers’ retention positively through promoting customers’ loyalty, encouraging repeat patronage and sustaining relationship continuity.
This manuscript investigates the concept of the operator Bohr ra
dius within the framework of functional analysis, particularly in the
context of bounded linear operators on Banach and Hilbert spaces.
We extend classical Bohr-type inequalities to operator-valued analytic
functions and derive bounds for various operator classes including nu
clear and Hilbert–Schmidt operators. The study culminates in a sharp
characterization using the unilateral shift operator on ℓ2(N)
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