ISSN:2320-9186
Impact Factor:4.1
ISSN:2320-9186 Impact Factor:4.1
ABSTRACT This study aimed to examine the grammatical competence of Grade 7 learners at Candon National High School through syntactic analysis of their journal reflection entries. Anchored in Chomsky’s Universal Grammar, Davidson’s Semantics, Error Analysis, and Syntactic Analysis, the research examined recurring syntactic errors to determine learners’ developmental patterns in grammar acquisition. Using qualitative content analysis and a developmental research design, the study analyzed 96 journal entries collected through simple random sampling. Errors were categorized using Corder’s taxonomy; omission, addition, misformation, and misordering, revealing persistent challenges in subject–verb agreement, tense consistency, sentence structure, and word order. Findings showed that subject–verb agreement was the most frequent and foundational difficulty, often co-occurring with other syntactic issues. Based on these results, an interactive intervention material titled SVA Mastery Toolkit was developed using the ADDIE model and was validated using the DepEd LRMDS Evaluation Rating Sheet for Non-print Mate-rials. The study concludes that explicit, interactive, and feedback-rich instruction can significantly address learners’ syntactic difficulties. It rec-ommends integrating the SVA Mastery Toolkit into grammar and writing instruction and conducting further research on interventions target-ing additional areas such as tense consistency and article usage. Keywords: grammatical competence, intervention material, journal reflections, syntactic analysis, subject–verb agreement, Universal Grammar
In the electronic world we live in today, data is saved, retrieved, and utilized in a variety of ways. While text contains a vast amount of valuable information, its lack of organization poses challenges and consumes a significant amount of time when attempting to extract valuable insights. The brand’s writing style is informative, professional, and direct, with a focus on clarity and simplicity. The tone is helpful and empowering, using second-person pronouns for a conversational feel. Use clear, straightforward language to explain complex concepts. Break down processes into step-by-step instructions. Text categorization is crucial for efficient information retrieval and analysis. It helps in organizing large volumes of unstructured text into meaningful categories, enabling easier access to relevant information. The classification of Amharic text involves the utilization of both conventional and machine learning methods. One major challenge in classifying Amharic text is the limited availability of labeled data for training machine learning models. Advancements in natural language processing (NLP) techniques specifically tailored for Amharic text are expected to address these challenges. As more annotated datasets become available and NLP models are fine-tuned for Amharic, the accuracy and efficiency of text classification will improve significantly. We proposed model that uses dynamic fast text to generate text vectors to represent semantic meaning of texts and solve the problem of traditional methods. The text vectors matrix is then fed into the embedding layer of a convolutional neural network (CNN), which automatically extracts features. We conduct experiments on a data set with six news categories, and our approach produced a classification accuracy of 94.21%. We compared our method to well-known machine learning algorithms such as support vector machine (SVM), Naive bayes (NB), Decision Tree (DT). Key Words: Text classification, Deep learning, CNN and dynamic wordembedding.
Two known terpenoids, Lupeol (1) and 2-oxokolavenic acid (2) were isolated for the first time from the fruits of Xylopia villosa. together with two known sterols, β-sitosterol and stigmasterol. The structures of these compounds were established by using various spectroscopic methods including 1D NMR (1H NMR and 13C NMR) and 2D NMR (COSY, HMQC and HMBC) in conjunction with mass spectrometry and by the comparison with literature data. The dichloromethane-methanol (1 :1) extract and the two terpenoids compounds were evaluated for their anticonvulsant effects on pentylenetetrazole , picrotoxin or becuculine induced convulsions in mice. All the tested treatments showed anticonvulsant effects on experimental models of epileptic seizures chemically induced in mice. Lupeol (1) showed up to 66.66 % protection of animals against convulsions, the 2-oxokolavenic acid (2) produced a maximum of 33.33 % protection and the dichloromethane-methanol (1 :1) extract showed a maximum of 83.33 % protection.
Q-V modal analysis was used to predict voltage instability in the existing south-south/south-east 330KV grid network. The application of NEPLAN 555 software package was used in the modelling of the south-south 330KV grid system. The violation of the simulated network was compensated using static var compensator (SVC) for improving deviation of loading margin of the buses close to the point of voltage collapse. This method was used because of the direct relation of the node voltage and reactive power changes which plays significant role in the analysis of voltage stability, the node voltage and reactive power change are also related to eigenvalues that give more accurate result for determining participation factors, this account for the prediction of weak buses that may consequently leads to voltage instability. The existing 330Kv grid consist of seven (7) generating station, twenty (20) transmission lines and eleven (11) load buses. The most critical node is identified by the least eigenvalues and from the selection once least eigenvalues are identified, they are evidently recommended as weak node for probable solution. Following the criteria of ranking, the critical buses of the network exhibited higher participation factor particularly, bus-12 (New-heaven) with 35.5598 mar/% followed by bus-18 (Ugwaji). These buses are selected as candidate buses targeted for intervention that required reactive power support for enhance system stability and prevent voltage collapse. Essentially, these buses are selected criteria and ranked as candidate’s buses targeted for probable consideration in order to avoid system outages. Similarly, the Nigeria 330KV grid, 48 buses were also modelled using electrical transient analysers program (ETAP 19.0.1) on the view to assess the evaluation of five (5) predictive analyser for the examination of system operating condition for immediate remedial action. This 330Kv grid 48-buses provided the flexibility for the assessment and evaluation of five (5) predictive-indexes, including fast voltage stability index (FVSI), line stability index (LMN), line stability factor (LQP), Voltage stability index (LD) and novel line stability index (NLSI) are presented to predict the proximity of the line close to voltage collapse. These voltage stability indices are based on active and reactive power injection into the network configuration for system evaluation and performance measurement. The five (5) predictive indices actually examined and evaluated prediction of line voltage profile for the 330Kv transmission network, 48-buses. This study particularly engaged twenty-four (24) cases for each analysis of FVSI, LMN, LQP, LD and NLSI respectively which are graphically as contained in figure 4. Which show the predictive pattern, evidently, three (3) of the five (5) predictive indices including NLSI, LMN, and FVSI captured and investigated the predictive behaviour as line close to instability while the other two (2) (LQP, LD) do not have good predictive capacity for system collapse. That is LD and LQP are very slow to the prediction of system collapse. Qualitatively, in the case of line 1, the predictive value of the indices are: FVSI (0.895), LMN (0.89456), NLSI (1.04077.35) while LQP and LD are: (0.002975 and 0.00151002) this means that LQP and LD has slower property for the predictions of the line voltage instability order investigation. Consequently, the Nigerian 330Kv integrated power system is currently consisting of existing network, national independent power project (NIPP), and independent power producer (IPP). It contained generation stations, transmission line and buses. This complex network is highly challenging on daily basis to be attended to and given serious attension in the event of the unlikely to ensure quick restoration to allow the grid to gain synchronism to avoid system collapse using the study case as research-tool to enhanced reliable power supply.
This study analyzes vehicle-related CO2 emissions across various regions in Kuwait from 2019 to 2024, focusing on identifying significant fluctuations in emissions and understanding the factors influencing these changes. Data collected from multiple monitoring stations revealed substantial variability in CO2 levels, with certain areas, such as Al-Shuaiba and Al-Ahmadi, recording consistently high emissions. The research highlights the strong correlation between traffic density and CO2 emissions, particularly in major urban areas. Significant seasonal peaks in emissions were observed, likely driven by increased vehicle activity and industrial operations. Conversely, some regions, like Al-Salam, demonstrated a slight decrease in emissions, suggesting the effectiveness of local factors such as improved vehicle efficiency and reduced traffic. The findings underscore the need for targeted environmental management strategies in high-emission areas, including stricter emissions regulations and the promotion of cleaner transportation technologies. While the study provides valuable insights into CO2 emissions in Kuwait, it is limited by its focus on CO2 alone and the five-year timeframe. Future research should expand to include other greenhouse gases and longer-term data to capture more comprehensive trends. The study’s conclusions offer actionable recommendations for policymakers, emphasizing the importance of region-specific interventions to mitigate the environmental impact of vehicle emissions. This research contributes to a better understanding of CO2 emissions in Kuwait and provides a foundation for developing effective environmental policies in the region. Keywords: CO2 emissions; Traffic density; Kuwait air quality; Seasonal emission trends; Environmental management strategies
Stick-slip vibration is one of the largest causes of drill bit wear, tool failure and less drilling efficiency during rotary drilling activities. Though they are effective in detecting the downhole vibrations, they are expensive and not always available in drilling campaigns. The study introduces a complete package of stick-slip detection using only the measurements of the surface, torque and rotary speed (RPM), without relying on the expensive downhole sensors. This methodology uses the supervised machine learning classification models that are trained using labelled surface data to differentiate between stick-slip and normal drilling. An artificial dataset with a calibration to drilling activities at the North Sea was created, consisting of 172800 samples (48 hours at 1 Hz) where 15 injected stick-slip events involving torsional oscillations (0.15-0.45 Hz) were characteristic of the databank. There were 21 time-domain and frequency-domain features per 60-second window in feature extraction; comprising the statistical moments, spectral energy in torsional bands (0.1-0.5 Hz) and dominant frequency content. The training and testing of three supervised classifiers, including Logistic Regression, Support Vector Machine (SVM) and Random Forest were systematically trained and tested with stratified 80-20 train-test splits. The three models were found to perform perfectly on the test set, with all of accuracy, precision, recall, F1-score, and ROC-AUC being equal to 1.000 and proving the feasibility of surface-data-based stick-slip detection. The analysis of feature importance named RPM stick-slip energy ratio (0.1-0.5 Hz band), torque standard deviation and spectral features as the most discriminative features. Random Forest model was also better in terms of interpretability with feature importance ranking whereas Logistic Regression was used when there was a need to deploy a model in real time. This study confirms a cheap, surface-data-driven, early warning mechanism, that can be integrated together with any existing rig monitoring assets, so that proactive mitigation of stick-slip can be conducted without the use of downhole monitoring. Keywords: Stick-Slip Vibration, Machine Learning Classification, Surface Drilling Data, Torque Oscillation, Feature Extraction, Random Forest, Vibration Detection, Drilling Optimisation
The telecommunications sector is presently undergoing a paradigmatic transition from reactive network management to Level 4 Autono-mous Networks (AN), necessitating the integration of user-centric Quality of Experience (QoE) metrics with advanced cognitive architec-tures. Despite the availability of extensive telemetry, a persistent dissonance—designated as the "Watermelon Effect"—remains, wherein aggregated Key Performance Indicators (KPIs) mask localized subscriber dissatisfaction. Presented herein is a comprehensive review of related literature, synthesized to propose a unified framework wherein Grid-Level Spatio-Temporal modeling serves as the foundational perception layer for Agentic Artificial Intelligence. Through the synthesis of research concerning Spatio-Temporal Graph Neural Networks (ST-GNN) and the Perceive-Reason-Act-Learn (PRAL) cognitive loop, it is posited that the adoption of a 50m x 50m Grid-based granularity is a requisite condition for Agentic systems to autonomously identify and resolve latent dissatisfaction prior to its crystallization into churn.).
Technical writing skill is one of the basic skills that a learner must master in terms of writing, specifically in research. It enhances communication in academic context and real-life setting. However, some learners struggle in these skills due to their lack of mastery in technical writing. This study aims to identify the specific technical writing needs of learners in composing a Review of Related Literature (RRL). Using a qualitative content analysis, data were collected at Candon National High School through the RRL output, interview questionnaire, and journal entries of 20 Grade 10 learners in the researcher’s advisory class. These were used to explore their experiences, challenges, and technical difficulties in writing RRL. Findings revealed that learners commonly encounter challenges in organizing ideas coherently, synthesizing information from multiple sources, applying proper citation and using appropriate academic language. These results highlight the need for targeted instructional strategies and an intervention program that would address these gaps, including scaffolding techniques, guided practice, and explicit instruction in technical writing conventions. This approach would encourage active participation in writing future research-based and academic texts. The study underscores the importance of equipping learners with essential writing competencies to improve their academic performance and prepare them for future research tasks. Future studies that would examine whether improvements in technical writing skills are sustained over time and how they transfer to other academic writing tasks are highly encouraged.
Mathematics entered physics as a tool but little by little it transformed to be the master. In previous articles entitled How to Generate New Mathematics-Parts I, II and III we discussed how to apply the statistical theory of Cairo techniques to generate new laws and rules in most fields of classical and quantum physics, statistics, and pure mathematics. In this article, we use the same theory to extend our previous statistical analysis by introducing and analysing new important and urgent six questions:1- Is it true that separation of variables is the most absurd idea inhistory?2- Is the West losing the battle of the century?3-Can we find the stationary energy levels of the Bohr hydrogenatom without using Bohr's hypothesis E=nhf, n=1,2,3,... up to infinity? 4-Did Einstein go through ten years of confusion and loss of knowledge in physics just before presenting his theory of general relativity?5-Can complex Markov chains be solved using Cairo techniques? 6-What are the allowed and forbidden transitions in quantummechanics?Thanks to the statistical theory of Cairo techniques the answer to all the above questions is generated as yes and furthermore new rules and theorems have been generated. This striking fact is the subject of this article. Finally, it should be clarified that this article is not intended to minimize the major contributions of great physicists and mathematicians such as Einstein, Schrödinger, Heisenberg, Minkowski, Hilbert, and Riemann, among others, but rather to address the main slips and limitations of their theories, where applicable. Note: If you are not familiar with the universal laws of physics, please stop reading. This article is not intended for you
The increasing frequency of oil spills globally has highlighted the need for efficient and cost-effective methods for hydrocarbon remediation. Hydrocarbon spills severely affect marine ecosystems and surrounding environments, posing significant risks to both ecological and human health. This study investigates the potential of locally sourced clays modified with alkyl ammonium surfactants as adsorbents for hydrocarbon contamination, with a specific focus on the Niger Delta region. Organoclays, synthesized by modifying natural clays with surfactants, have gained attention for their high adsorption capacity due to their hydrophobic surfaces. The objective of this study was to develop and evaluate locally produced organoclays for the removal of organic contaminants such as benzene, toluene, and xylene (BTX) from aqueous solutions. The clay samples were sourced from Kono Boue, Khana Local Government Area, Rivers State, Nigeria, and modified using Hexadecyl Trimethyl Ammonium Bromide (HDTMABr) as a surfactant. Batch adsorption studies were conducted to assess the effects of various factors, including initial concentration, adsorbent dosage, pH, and contact time, on the adsorption efficiency. The results indicated that the adsorption efficiency increased with adsorbent dosage, with the modified clays showing significant improvements over unmodified clays. For example, benzene removal efficiency for modified clays ranged from 56.58% to 96.73%, compared to 58.63% for unmodified bentonite. Toluene removal efficiency ranged from 58.85% to 95.69%, and xylene removal ranged from 57.73% to 97.11%. pH played a crucial role, with optimal performance observed at pH 5 for most modified clays, where benzene removal peaked at 95.76%. Contact time also significantly affected adsorption, with maximum removal efficiencies reached at approximately 90 minutes. This study demonstrates that locally sourced and modified clays offer a promising, sustainable, and cost-effective solution for hydrocarbon remediation in the Niger Delta, contributing to more efficient and environmentally friendly methods for addressing petroleum pollution.
This study developed a real-time, webcam-based Human–Computer Interaction (HCI) system using a Modular Multi-Task (MMT) CNN architecture capable of estimating gaze direction, head pose, and facial Action Units (AUs). The system was designed to support hands-free interaction for users with motor limitations while remaining lightweight and cloud-accessible. System performance will be evaluated through accuracy, angular error, F1 scores, latency, and real-time responsiveness using both quantitative metrics and qualitative observations. Overall, this study aims to show that a low-cost, cloud-supported CNN system can provide reliable multimodal input for practical, accessible, and hands-free HCI applications.
This article investigates a physician shift-coverage negotiation method at a general hospital operating in Rio de Janeiro's de-manding healthcare market. The maternity department operates as the research unit because its uncontrolled shift changes threaten both patient safety and hospital operational performance. The research investigates how negotiation principles, in-cluding BATNA (Best Alternative to a Negotiated Agreement), ZOPA (Zone of Possible Agreement), and the positions-versus-interests analysis, help address workforce recruitment problems. The negotiation process used structured option-building to result in the adoption of variable remuneration through procedure-based payments. The intervention preserved its core ele-ments, leading to higher doctor retention rates and demonstrating healthcare management negotiation techniques. The re-search results demonstrate that organizations need to adopt comprehensive systems that foster employee commitment during periods of market competition.
Power plant planning and optimization for proper system management, system stability, and efficient operation all depend on power system load forecasts. Artificial Neural Networks (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) embedded in MATLAB/SIMULINK software were used to forecast the electrical load demand of the study site for 10 years from 2023 to 2032 using month and year data as inputs and load consumption as the output. The minimal mean squared error (MSE) for the training of ANFIS is 0.307983 and the training was completed at epoch 2 whereas, the MSE for ANN model is 0.3201 at epoch 10. The mean squared error showed that ANFIS model performed better in forecasting electrical load demand in Abuloma 33kV power network. Regression results for the ANN training, validation and testing were 0.9289, 0.9262 and 0.9501. The regression results showed that there is a close fit between the actual data and the neural network results. _x000D_ The actual power consumption data of Abuloma 33kV Injection Substation from 2010 to 2022, showed that there was an increase in power consumption from 4.9MW to 9.1MW and the predicted power consumption rose from 10.076MW in 2023 to 13.204MW in 2032 using ANFIS model.
The city of Bandundu is rich in both surface and groundwater resources. The issue of access to drinking water remains an urgent problem in the daily lives of the population. The objective of our study is to analyze the physicochemical parameters of the surface waters of the Kwilu River’s sand port. Parameter measurements were taken using a HANNA HI 991300 multiparameter probe and a Spectroquant pharo 300M spectrophotometer. The data underwent descriptive statistical analysis to characterize the studied parameters. The results show that the waters of the sand port are characterized by high concentrations of nitrite, nitrate, phosphate, and chemical oxygen demand. It is also important to note the high turbidity, total dissolved solids, and redox potential, which indicate that the environment is reducing. These results reveal surface water pollution at the sand port, indicating anthropogenic pressure on the Kwilu river.
This study develops a conceptual model examining the influence of staff competence and operational procedures on service performance, with information technology positioned as a mediating variable at PT. Pelayaran Lintas Optic. The research is motivated by a documented decline in service performance between 2022 and 2024, indicating the need to evaluate organizational and technological factors affecting performance outcomes. Using an analytical observational approach with a cross-sectional design, data were collected through questionnaires from 60 operational staff members and analyzed using path analysis techniques. The proposed model hypothesizes that staff competence and operational procedures directly influence both information technology and service performance, while information technology also mediates these relationships. The findings are expected to provide strategic insights for improving service quality and organizational performance through enhanced human resource capability and effective technology utilization.
This study examines the influence of customer expectations and competitor evaluations on contractor profit, with service quality positioned as a mediating variable, within the context of Indonesia’s increasingly competitive construction industry. Focusing on projects completed by the Infrastructure I Department of PT Adhi Karya (Persero) Tbk during 2016–2024, the research addresses the gap between relatively strong service quality performance and declining profit realization. Grounded in Expectancy Theory, Stakeholder Theory, Service Quality Theory (SERVQUAL), and project management perspectives, the study develops a conceptual model linking customer-related factors, service quality, and financial outcomes. Using a quantitative explanatory approach and secondary data from 105 completed projects, the hypotheses are tested through Structural Equation Modeling–Partial Least Squares (SEM-PLS) with SMARTPLS software. The findings are expected to provide empirical insights into how managing customer expectations and competitor evaluations through service quality can enhance contractor profitability and support strategic decision-making in construction companies.
This study examines the influence of Occupational Health and Safety (OHS) knowledge and reward–punishment systems on employee performance, with motivation serving as a mediating variable at PT Tri Energi Berkarya. Grounded in Performance Theory, Safety Knowledge and Behavior Theory, Reinforcement Theory, and major Motivation Theories, the research addresses inconsistent empirical findings regarding the relationships among safety knowledge, motivation, and performance. A quantitative approach was employed using saturation sampling of 52 employees, with data collected through questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings are expected to provide a clearer understanding of how OHS knowledge and managerial control mechanisms contribute to employee performance through motivational processes, particularly within the renewable energy sector.
This study aims to develop a conceptual model that examines the effect of internal and external in financing on construction poject performance, with financing as a mediating variable. This research uses a quantitative approach with a cross-sectional design. The sample consists of 60 respondents who are directly involved in planning, managing financing, and controlling the implementation of construction projects at PT. Adhi Karya (Persero) Tbk. Data are collected through questionnaires measured by a five-point Likert scale. The analysis method applied is Partial Least Squares–Structural Equation Modeling (PLS-SEM) to evaluate the measurement model and the structural relationships among variables, including the mediating role of financing. This study proposes that internal and external factors influence constructing project performance both directly and indirectly through financing. The conceptual model is expected to provide a clearer understanding about how internal and external factors contribute to improving constructing project performance.
Transhumance-related conflicts in the Logone region of Chad have become a growing challenge due to competition over limited resources, particularly land and water, between pastoralists and farmers. This article explores the potential of community-based resource management (CBRM) as a solution to these conflicts. Through a qualitative approach, including semi-structured interviews, focus group discussions, and document analysis, the study examines the causes of these conflicts, the effectiveness of community-driven management strategies, and the role of traditional knowledge in conflict resolution. Findings suggest that joint resource management, negotiation and mediation by local leaders, and community-based monitoring systems have been successful in mitigating tensions and fostering cooperation between pastoralists and farmers. The article concludes with recommendations for strengthening these solutions, including government support, partnerships with NGOs, and improved access to resources. It emphasizes the importance of institutionalizing community-driven approaches and ensuring their sustainability to address transhumance-related conflicts in the long term. Keywords: Transhumance, Conflict, Resource Management, Community-Based Solutions, Chad, Logone Region, Pastoralists, Farmers, Climate Change, Traditional Knowledge
This study explored the lived experiences of the oppressed suicide survivors in Ilocos Norte focusing on the factors that influenced the participants to commit suicide, the methods they used, the circumstances that led to the failure of their suicide attempts, and the personal realizations they developed after surviving the experience. The study employed a qualitative research method through a case study research design to collect data using a semi structured interview guide from the suicide survivors who were selected through purposive sampling based on the criteria that they had experienced repeated forms of oppression and had survived at least one suicide attempt. The study was conducted in selected municipalities of Ilocos Norte, namely Bacarra, Batac City, Dingras, Marcos, Solsona, and San Nicolas. Narrative analysis was utilized as the treatment of data to examine how participants constructed meaning from their experiences within their social and cultural contexts. The findings revealed that participants were influenced to attempt suicide by persistent experiences of oppression, including emotional neglect, family conflict, academic pressure, discrimination, humiliation, and feelings of worthlessness and hopelessness. The methods used by the participants varied and included medication overdose, self-inflicted cutting, and ingestion of toxic substances, often chosen based on accessibility and emotional impulsivity. Suicide attempts failed primarily due to timely intervention by family members, peers, or community members. After surviving their attempts, participants reported significant realizations, such as recognizing the value of life, strengthening faith and spirituality, developing self-worth, rebuilding relationships, and cultivating resilience despite ongoing challenges.
Le secteur minier en République Démocratique du Congo souffre de nombreuses faiblesses qui entravent son développement. Parmi celles-ci figurent le manque de qualifications adaptées, la faiblesse des salaires dans certaines entreprises et la précarité des conditions de travail. Les mineurs sont souvent confrontés à des environnements dangereux, marqués par une insécurité accrue et des horaires exigeants, ce qui affecte leur bien-être. Ils se sentent fréquemment sous-évalués et insuffisamment rémunérés pour leurs efforts. Par ailleurs, les services publics chargés de lutter contre la fraude et la contrebande minières se révèlent souvent inefficaces, laissant les travailleurs exposés à des risques pour leur santé et leur sécurité. Cette situation contribue à une démotivation générale et fragilise davantage la performance du secteur.