International journal of computer science and mobile computing最新文献

{"title":"Prediction of Hydrogen Storage Vessel Explosion with Blast Wall using Machine Learning","authors":"Hyunseok Min","doi":"10.47760/ijcsmc.2024.v13i07.002","DOIUrl":"https://doi.org/10.47760/ijcsmc.2024.v13i07.002","url":null,"abstract":"We present a prediction of hydrogen storage vessel explosion using machine learning. A neural network model is trained to learn the waveform of a hydrogen explosion with a blast wall and used to predict the waveform with arbitrary blast wall position. The initial training revealed one of the features, blast wall distance, greatly affects the blast waveform. To emphasize the effect of that feature, feature multiplication is used instead of normalization and this enabled the training to learn the waveform correctly. The trained model can predict the blast waveform with an arbitrarily located blast wall. The result can be used in structural analysis and this will help to construct the blast wall in the hydrogen refuelling station. This research uses the CFD (Computational Fluid Dynamics) simulation by Pukyong University, South Korea, as training data.","PeriodicalId":479201,"journal":{"name":"International journal of computer science and mobile computing","volume":"2 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PREDICTING UNDERNUTRITION RISK FACTORS USING MACHINE LEARNING TECHNIQUES IN NIGERIAN UNDER FIVE CHILDREN","authors":"Mohammed Ali Kawo, Muhammad Nuruddeen Idris, Kabiru Haruna, Firdausi Umar Kaita","doi":"10.47760/ijcsmc.2024.v13i07.006","DOIUrl":"https://doi.org/10.47760/ijcsmc.2024.v13i07.006","url":null,"abstract":"Childhood undernutrition remains a critical global health challenge with far-reaching consequences. This study developed and compare predictive models for three key indicators of under-five child undernutrition in Nigeria: stunting, wasting, and underweight. By leveraging various machine learning (ML) algorithms, we identified the most significant socio-demographic determinants of these nutritional outcomes. The study utilizes data from the Nigerian Multiple Indicator Cluster Survey (MICS6) 2021, a comprehensive nationwide survey. Four ML algorithms were employed to predict the risk factors for the under-5 child nutritional status: k-nearest neighbors (KNN), random forest (RF), decision tree (DT), and logistic regression (LR). These models were evaluated and compared based on their predictive performance. The study encompasses households across Nigeria, providing a broad representation of the country's diverse population. Preliminary analysis reveals significant regional disparities in the prevalence of stunting, wasting, and underweight among Nigerian children. Among the four ML algorithms tested, the KNN model demonstrated superior predictive capability across all evaluation metrics, including accuracy (89.65%, 95.00%, 80.04%), precision (91.02%, 87.79%, 93.53), recall (99.98%, 100%, 100%), and F1-score (94.44%, 98.83%, 88.60%). This outperformance was consistent for all three undernutrition indicators. The KNN model, identified as the most effective predictor, highlighted several key determinants of childhood undernutrition. These factors varied somewhat across the three outcomes but commonly included: household wealth index, geopolitical zone, source of drinking water, child age, birth size, mother's education level, and residential area (urban/rural) among others. This study demonstrates the efficacy of machine learning approaches, particularly the KNN algorithm, in predicting and understanding the determinants of children undernutrition in Nigeria. The findings provide valuable insights for targeted interventions and policy formulation. These results can inform evidence-based decision-making and resource allocation in Nigeria's efforts to improve child nutrition and achieve related Sustainable Development Goals.","PeriodicalId":479201,"journal":{"name":"International journal of computer science and mobile computing","volume":"13 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transformative Business Outcomes of AI-Driven Master Data Management (MDM) and Data Governance Programs","authors":"Bhuvaneshkarthick Krishnasamy","doi":"10.47760/ijcsmc.2024.v13i07.003","DOIUrl":"https://doi.org/10.47760/ijcsmc.2024.v13i07.003","url":null,"abstract":"Master Data management (MDM) has transitioned from a deferred task to a critical business imperative in the modern competitive landscape. Companies must swiftly identify and leverage their most valuable master data across the enterprise, at scale and in near real-time, to maintain a competitive edge. Master data serves as the foundational core that drives systems and business processes, powering the entire organization. Integrating AI into MDM accelerates value realization and goal attainment, enhances business outcomes, and maximizes return on investment (ROI). A meticulously implemented AI-driven MDM system, coupled with a Data Governance program, is essential for unlocking this potential. This paper highlights the pivotal role of AI-driven MDM and Data Governance programs in promoting operational excellence and sustainable growth through a comprehensive analysis of their strategic importance and diverse benefits and use cases.","PeriodicalId":479201,"journal":{"name":"International journal of computer science and mobile computing","volume":"5 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Sediment Accumulation in the Operation on Hydro Plant: A Case Study of the Nam Sana Hydropower Plant Lao PDR","authors":"Nitsakhone Keochomsi, Kanchit Ngamsanroaj, A. Promwungkwa","doi":"10.47760/ijcsmc.2024.v13i07.005","DOIUrl":"https://doi.org/10.47760/ijcsmc.2024.v13i07.005","url":null,"abstract":"The annual electricity production in Laos amounts to $1.98 billion, representing 12.8% of the country's GDP, with hydropower accounting for 80% of the total production. However, the run-of-river hydroelectric power facility has been facing issues with sediment accumulation in its reservoir. This accumulation leads to system inefficiency and corrosion of turbine components. This paper examines the impact of sediment accumulation on electricity productivity, turbine efficiency, and sediment management within the reservoir. The Nam Sana Hydropower Plant (NSN HPP) in Lao PDR serves as the case study, with data collected from 2015 to 2023. The average annual sedimentation volume is 6,459 cubic meters, which is 28.3% of the total reservoir volume, and has been removed using heavy machinery. The proposed method in the study compares monthly production before and after sediment removal, showing a 12.1% increase in production over a 30-day period. As a long-term solution to mitigate sediment accumulation, the construction of a sediment trap is suggested. This trap, with a volume of 4,000 cubic meters, can be installed by NSN HPP before the reservoir, capturing 62% of the average annual sediment accumulation.","PeriodicalId":479201,"journal":{"name":"International journal of computer science and mobile computing","volume":"12 37","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MRBM Reordering for Efficient Secret Message Cryptography","authors":"S. M. Al-Saleh, Hind Alhusban, Shatha Ghazal, Reem S. Khaldi, Saad Musa Ali Khalifah, Amal Abdelfattah Rabah Alsedawi","doi":"10.47760/ijcsmc.2024.v13i07.001","DOIUrl":"https://doi.org/10.47760/ijcsmc.2024.v13i07.001","url":null,"abstract":"An efficient method of secret message cryptography will be introduced; this method will be efficiently used to encrypt-decrypt short and long messages. The introduced method will use a simplified encryption and decryption functions, these functions will use a simple message bits reordering to get the encrypted and decrypted messages, the reordering operations will be applied based on the contents of the generated secret indices key. A private key will be used to generate the required indices key, this key will have a long key capable to provide a huge key space to protect hacking attacks, the produced decrypted message will be sensitive to the selected values of the private key components. The private key components will be used to run a simple chaotic logistic map model to generate a chaotic key, which will be sorted to form the indices key. The introduced method will be tested using various messages; the obtained results will be analyzed to prove that this method will satisfy the speed and quality requirements of good crypto system. The obtained speed results will be compared with other existing methods speeds to show how the proposed method will speed up the process of message cryptography by decreasing the encryption-decryption time.","PeriodicalId":479201,"journal":{"name":"International journal of computer science and mobile computing","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Uniform Cubic Spline Interpolation with Some Additional Techniques for Functions with Strong Gradients","authors":"Gehan Waleed Ibraheem","doi":"10.47760/ijcsmc.2024.v13i07.004","DOIUrl":"https://doi.org/10.47760/ijcsmc.2024.v13i07.004","url":null,"abstract":"Spline interpolation is commonly applied in many applications because several desirable interpolation properties are evident and related to the smoothness and accuracy. It may distort somewhat because of the Gibbs phenomenon though it is less noticeable if there is a gap or if the change from one slope to another is steep. Moreover, the issues of data consistency are needed in some applications, but these peculiarities are not checked automatically by interpolation. Thus, it becomes imperative to apply a few more additional technologies to facilitate the uniformity. Orden and repetitiveness of C^2 are not ensured simultaneously, and thus, the last interpolation is not a spline in actuality. The analysis of the given problem is carried out in the context of developing a sufficient condition for generating a homogeneous cubic spline based on the cubic Hermite interpolator and the identification of two construction methods based on nonlinear formulas. As such, these methods are aimed at reducing the regions where accuracy of order is not maximum or where interpolation is less than C^2 order. We compare the order of accuracy and the intrapolar pattern of the extended and the original method and perform many numbers experiment to check with theory.","PeriodicalId":479201,"journal":{"name":"International journal of computer science and mobile computing","volume":"5 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141795732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}