International Journal of Advances in Applied Sciences
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Assessment of heavy metals concentration of Mapanuepe Lake, Zambales, Philippines
Get PDFDespite the absence of recent research, Mapanuepe Lake in the Philippines has been a significant environmental concern due to potential heavy metal contamination. Hence, the study assessed the heavy metal concentration of water and surface sediments and identified the other physicochemical properties of Mapanuepe Lake in San Marcelino, Zambales, Philippines. This descriptive research employed physical profiling and physicochemical characterization of water and surface sediments of the lake. Six sampling stations in the lake were selected based on their current land use and nearness to the point source of heavy metal pollution. The study found that the Mapanuepe Lake is a thriving place for algae and zooplankton. The heavy metal concentration of the lake water and sediment sample is within the standard limit. The water conductivity is considered to be within the standards. In terms of pH level, the sampling sites obtained a pH level within the acceptable limit. The concentration of heavy metals in the lake water and sediments is generally within the standard limit. Other physicochemical properties are also in the acceptable range. The community people and local government must collaborate to implement the crafted strategic environmental sustainability plan, which includes biodiversity conservation and ecotourism promotion. Likewise, the study provides updated and comprehensive data on the status of the lake's heavy metal concentration for policy formulation and further research
Batak Toba language-Indonesian machine translation with transfer learning using no language left behind
Get PDFThis study focuses on neural machine translation (NMT) for low-resource languages (LRLs) pair, Batak Toba-Indonesian (bbc↔ind). The Batak Toba language is a critically endangered dialect of an Indonesian ethnic group, Batak. Recent advances in machine translation offer potential solutions, with transfer learning emerging as a promising approach for this language pair. We used a publicly available bbc↔ind parallel corpora from the Hugging Face datasets hub and employed the NLLB-200's distilled 600M variant model as the baseline model. Our models achieved sacreBLEU scores as follows: i) for bbc→ind, it achieved a score of 37.10 (+25.67, up from 11.43) and ii) for ind→bbc, it achieved a score of 30.84 (+25.82, up from 5.02). These results outperform all previous works in the task bbc↔ind machine translation and prove the validity of our approach
Pyrolysis of biomass mixture of coconut fiber and rice husk waste with polypropylene plastic
Get PDFThis research aims to evaluate the effect of the composition ratio of oil from coconut fiber waste biomass and rice husks as well as polypropylene (PP) plastic which is not optimally utilized and can be used as an alternative fuel processed through the pyrolysis process. This research was conducted by mixing biomass of coconut fiber and rice husk with PP plastic in the form of refuse-derived fuel (RDF)-3 with compositional variations of 100:0%, 75:25%, 50:50%, 75:25%, and 0:100% for 60 minutes. The pyrolysis product in the form of oil was then distilled to separate the compounds contained in it and produce pure oil. Next, quantity (volume of pyrolysis oil and distilled oil) and quality (yield, density, viscosity, visual, and color) tests were carried out. The results of the study showed that there is an influence of the variation in the composition ratio of the mixture of biomass of coconut fiber and rice husk and PP plastic on its quantity and quality. The highest quantity was obtained from the 100% PP ratio and the best quality was obtained from the 100% PP ratio, which leads to the specifications of solar fuel oil
A brief on artificial intelligence in medicine
Get PDFThis review explores the transformative impact of artificial intelligence (AI) in medicine. It discusses the benefits of AI, its core technologies, integration processes, and diverse applications. AI enhances diagnostics, personalizes treatments, and optimizes healthcare operations. Machine learning and deep learning are key AI technologies, while explainable AI ensures transparency. The review emphasizes the integration journey and highlights AI applications, from image diagnosis to telemedicine. Ethical concerns, data privacy, regulations, and algorithmic bias are challenges. The future promises continued innovation, global health equity, and responsible AI application in medicine
A network-based mobile positioning system using an optimization model
Get PDFThe expansion of cellular network coverage facilitates the advancement of research on network-based positioning. We are interested in the signal fingerprinting method to predict the location of a mobile device. By this method, the device must be within the fingerprint coverage to have a successful location prediction. However, any disturbance in the signal propagation would decrease the prediction accuracy. We propose an optimization model based on generalized triangulation combined with a signal fingerprint which is treated more adaptively in responding to any signal disturbance. The triangulation method determines the most likely region where the device is located. The solution provides the estimated longitude and latitude of the device. An illustration of the implementation of the model is presented. The model is assessed using the Indosat cellular network in three distinct testbeds in Indonesia, which are: South Jakarta, a metropolitan area; South Tangerang, a buffer area adjacent to the metropolitan area; and Malang, a city surrounded by rural areas. The most favorable outcome yields an average prediction error of 39.6 m, a maximum error of 197.08 m, a minimum error of 0.05 m, and a standard deviation of error of 39.22 m
Enhancement performance of the Naïve Bayes method using AdaBoost for classification of diabetes mellitus dataset type II
Get PDFIn using technology, especially in health sciences, machine learning modeling can make it easier to predict disease treatment. Naïve Bayes optimization with AdaBoost is needed because even though Naïve Bayes has the advantage of minimal parameters, its accuracy is susceptible to too many features. AdaBoost is used to overcome sensitivity to an excessive number of features and optimize its ability to handle complex datasets. This research aims to analyze the classification results of the Naïve Bayes method with the help of the AdaBoost method. This data comes from Community Health Centers I, II, and III Mengwi District, Bali Province patient medical records. The classification process uses the Naïve Bayes method and Naïve Bayes with AdaBoost, which is then evaluated using a confusion matrix. Two scenarios were used in testing: Naïve Bayes and AdaBoost-based Naïve Bayes. The algorithm is implemented on the dataset and tested directly using cross-validation. The evaluation results show that the Naïve Bayes method experienced an increase in accuracy of 5.92% at 5-fold and 5.93% at 10-fold on a dataset with 890 data. The addition of the AdaBoost method to diabetes classification has been proven to improve the accuracy performance of the Naïve Bayes method
Modern and comprehensive soil studies in grape agrocenoses in Azerbaijan
Get PDFThe article presents some results of a comparative analysis of the agrochemical, microbiological, and environmental properties of grape plants and soil types common in regions located on the slopes of the Lesser Caucasus. The objectives of this study were to assess the current state and quality of soils used for vineyards in some villages of the Ganja-Kazakh economic region, taking into account the long-term use of fertilizers and chemicals to protect plantations from various diseases for the resulting wine materials. Growing and exporting grapes is of great importance for the development of the economy of the Republic of Azerbaijan. Since it is a break-even plant, expanding the area under grapes to attract wetlands to agriculture has been an important issue for soil scientists in recent years. During the period of rapid development of viticulture in the republic, ensuring rapid harvesting and longevity of vineyards is one of the important scientific and practical tasks
Water quality assessment of groundwater resources in rural areas of Karachi, Pakistan
Get PDFThe quality of drinking water directly controls many diseases and affects the growth of the human body. The provision of quality water is a major concern around the world, especially for developing countries that have poor environmental rules, insufficient water supply, and poor drainage systems. Considering these issues, this research was undertaken to assess drinking water quality in the rural areas surrounding Karachi, Pakistan. Samples were collected in the monitoring of the Pakistan Council of Research in Water Resources (PCRWR) and tested for physicochemical and bacteriological parameters (PCB) using geographical information system (GIS). Further, the results were compared with World Health Organization (WHO) standards for human consumption. An analysis of 35 drinking water samples revealed that 14% exceeded the permissible ranges for physical parameters. Moreover, 60% of the samples were deemed unsafe for consumption as the levels of inorganic substances surpassed permissible ranges outlined by WHO. All water samples contained coliform bacteria, making them unsafe, and 46% were contaminated with E. coli, highlighting the urgent need for improved sanitation and water treatment infrastructure in the area
Electronic health records with decision support systems for sharper diagnoses: bibliometric analysis
Get PDFClinical decision support systems (CDSS) and electronic health records (EHRs) are computer systems designed to assist decision-makers in making optimal and streamlined judgments on disease diagnosis, treatment, patient care, and health institution management. This study conducted descriptive and bibliometric evaluations of CDSS integrated with EHRs studies published in journals included in the Scopus database from 2007 to 2024. During the initial phase, the publications were distributed based on their publication year, nation, institution, journal, and citation numbers, as part of a descriptive analysis. During the second stage, the articles were subjected to bibliometric analysis, which involved doing common keyword analyses. The research yielded 409 papers about CDSS and EHRs. The United States has been identified as the country with the highest number of studies on this issue. The journal with the highest number of citations observed was Studies in Health Technology and Informatics. Furthermore, the text showcases visual representations of co-citations and cooperation between authors from different institutions and countries. This study aims to present a systematic framework for examining CDSS with EHRs to improve diagnosis and offer a comprehensive viewpoint to researchers and specialists in the field
A novel solar PV integrated fuzzy-logic controlled UAPQC device for power quality enhancement
Get PDFA novel solar photovoltaics (PV) connected unified active power quality conditioner (UAPQC) device is extensively adopted for enhancing the voltage and current quality of the distribution system. In a three-phase distribution system, the proposed UAPQC mitigates both load-side and source-side allied power quality (PQ) issues. Furthermore, as part of the distributed generation (DG) system, active electricity from solar PV is injected into the grid or source when solar PV is available. In this regard, the proposed UAPQC has been operated by using a workable control method, in both PQ improvement mode and DG incorporation mode. The direct current-link (DC-link) control of the shunt voltage source inverter (VSI) utilizes the proportional-integral controller, which is not suited for the regulation of DC-link voltage at the desired level because of improper selection of gain values. In this work, an intelligent fuzzy-logic DC-link control of UAPQC evidences the intelligent knowledge base for better regulation of power-quality issues. The suggested fuzzy-logic controlled UAPQC device's performance for both PQ improvement and integration of DG is validated using the MATLAB/Simulink computing tool, and simulation findings are given with an appealing comparison analysis