Hubungan Personal Hygiene Dengan Kejadian Enterobiasis Pada Anak Usia 6-12 Tahun Di Panti Asuhan Kota Padang by Elen Pebriyani, Adrial Adrial, Eka Nofita

“…Pengambilan sampel dengan teknik proportional random sampling. Personal hygiene dinilai dengan menggunakan kuesioner dan kejadian enterobiasis dinilai dengan pemeriksaan anal swab. …”
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Comparison of Febuxostat and Allopurinol in the Treatment of Patients with Chronic Kidney Disease Stage 3∼5 with Hyperuricemia by Zhimin Liao, Lei Xu, Bo Wan, Liping Wang, Chengzhi Zhao, Gang Wu, Rui Xie

“…A total of 100 patients with stage 3 to 5 CKD with hyperuricemia in our hospital from July 2018 to December 2019 were selected and divided into the control group (n = 50) and the experimental group (n = 50) according to the random number expression method, the control group on the basis of conventional treatment with allopurinol treatment, the experimental group based on conventional treatment using the febuxostat be treatment. …”
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Specialty-specific Evaluation of Virtual care Outcomes: A retrospective QUality and safety analysis (S-EVOQUe). by Shawn Mondoux, Frank Battaglia, Anastasia Gayowsky, Natasha Clayton, Cailin Langmann, Paul Miller, Alim Pardhan, Julie Mathews, Alex Drossos, Keerat Grewal

“…Overall, 9,340,519 visits were compared between populations using a 1:1 match on a 20% random sample of the available eligible visits. Over 70% of patients included were seen by a General Practitioner. …”
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Prediction of Dissolved Oxygen Concentration in Sewage Treatment Process Based on Data Recognition Algorithm by Lili Ma, Jiangping Liu

“…On the one hand, it avoids the excessive random or blind selection of the initial weight threshold of the neural network in the initial stage; on the other hand, in the optimization process of the weight threshold, two types of search mechanisms, FWA and COA, are used to give full play to their respective strengths and to continuously conduct information exchange and mutual cooperation between groups and individuals. …”
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Financing the future: insights into sustainable energy investments through scientific mapping and meta-analysis by Mustafa Raza Rabbani, Madiha Kiran, Zakir Hossen Shaikh

“…The study highlights the most frequently cited articles, notable authors, key institutions, affiliations, and journals in sustainable energy finance. A random effects model meta-analysis was also conducted to assess the overall effect size of each research stream. …”
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Investigations on Driver Unique Identification from Smartphone’s GPS Data Alone by Arijit Chowdhury, Tapas Chakravarty, Avik Ghose, Tanushree Banerjee, P. Balamuralidhar

“…Further, it is shown that certain behavioral attributes like high driving skill impact identification accuracy. We observe that Random Forest classifier offers the best results. …”
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What is a recognized mechanism for transforming big data analytics into firm performance? A meta-analysis from cultural view by Zongyuan Liu, Harcharanjit Singh Mahinder Singh, Fatema Al Shibli

“…Furthermore, we examine potential methodological moderators in the BDA-FP relationship. Using the random-effect model, meta-analytic structural equation modeling, subgroup analysis, and meta-regression, we analyzed 34 studies with 42 independent samples conducted between 2019 and 2024. …”
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Assessing urban resilience and sustainability in the face of natural hazards with emphasis on reducing vulnerability in cities (Case study: Semnan city) by mozaffar mohamadkhani, zeynab karke abadi, abbas arghan

“…Using Cochranchr('39')s formula, a sample of 384 people was selected from them by random sampling method. To assess the validity (validity), using face validity, the opinions of related people were examined and its reliability was assessed using Cronbachchr('39')s test in the SPSS software environment equal to / 863. …”
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Enhancing Heart Attack Prediction with Machine Learning: A Study at Jordan University Hospital by Mohammad Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh, Yara Alkayed, Yasmin Al Trabsheh, Bahaaldeen Alshraideh

“…Various artificial intelligence techniques, namely, random forest, SVM, decision tree, naive Bayes, and K-nearest neighbours (KNN) were explored with particle swarm optimization (PSO) for feature selection. …”
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Enhanced Isolation of Streptomyces from Different Soil Habitats in Calamba City, Laguna, Philippines using a Modified Integrated Approach by Jhon Wilson A. Antido, Fresthel Monica M. Climacosa

“…A total of 25 soil samples were collected from a depth of 0–20 cm using systematic random soil sampling. All soil samples were air-dried, crushed, pretreated with calcium carbonate, and incubated on a rotary shaker. …”
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Clinical Effect of Hufu Copper Scraping on Shoulder-Hand Syndrome after Stroke by Lianyi He, Xinyu Chen, Yuejuan Zhang

“…A total of 60 patients with shoulder-hand syndrome after stroke admitted to the First Affiliated Hospital of Hunan University of Traditional Chinese Medicine were enrolled between January 2020 and June 2021. According to the random number table method, they were divided into the control group (n = 30) and the intervention group (n = 30). …”
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A comparative assessment of machine learning models and algorithms for osteosarcoma cancer detection and classification by Amoakoh Gyasi-Agyei

“…The empirical model based on the extra trees algorithm and fitted to class-balanced dataset via random oversampling and multicollinearity removed via principal component analysis proved to be the best, as it detected and classified osteosarcoma cancer in 10 ms with 97.8% area under the receiver operating characteristics curve and acceptably low false alarm and misdetection. …”
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Bright and stable anti-counterfeiting devices with independent stochastic processes covering multiple length scales by Junfang Zhang, Adam Creamer, Kai Xie, Jiaqing Tang, Luke Salter, Jonathan P. Wojciechowski, Molly M. Stevens

“…By embedding SPNs in photoresists, we generate PUFs consisting of nanoscale (distribution of SPNs within microspots), microscale (fractal edges on microspots), and macroscale (random microspot array) designs. With the assistance of a deep-learning model, the resulting PUFs show both near-ideal performance and accessibility for general end users, offering a strategy for next-generation security devices.…”
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Research on the impacts and mechanisms of digital strategy on corporate innovation investment by Dong Yang, Huayu Shen

“…The robustness of these findings is confirmed through additional tests, such as two-stage instrumental variable regression, a panel random effects model, and substitution of the dependent variable. …”
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Factors Associated with Risky Sexual Behavior in Adolescents in Indonesia Rural Areas by Setiawati Nina, Susmarini Dian, Kartikasari Aprilia, Anggraeni Mekar Dwi, Latifah Lutfatul, Rahmawati Eni

“…A probability sampling technique with proportional stratified random sampling was used and obtained 452 respondents. …”
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Vaccination Coverage and Associated Factors among Children Aged 12–23 Months in Debre Markos Town, Amhara Regional State, Ethiopia by Tenaw Gualu, Abebe Dilie

“…Study populations were selected using systematic random sampling technique. Structured interviewer administered questionnaires were used to collect data. …”
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Use of Machine Learning Models for Prediction of Organic Carbon and Nitrogen in Soil from Hyperspectral Imagery in Laboratory by Manuela Ortega Monsalve, Mario Cerón-Muñoz, Luis Galeano-Vasco, Marisol Medina-Sierra

“…Transformations were applied to spectral and chemical data and the models used were Random Forest (RF) and Support Vector Machine (SVM). …”
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ENVIRONMENTAL AND SOCIAL INFORMATION DISCLOSURE QUALITY AND FINANCIAL PERFORMANCE OF LISTED MANUFACTURING COMPANIES IN NIGERIA by Saka Tunde Abdulsalam

“…The study employs Ex-Post Facto research design and data collected from annual reports of forty-seven LMCNs were analyzed using panel regression analysis based on random effect model. While quality of ESID of companies were measured based on GRI sustainability quality principle such as Balance, Clarity, Timeliness, Relevance, Reliability and Comparability, financial performance (FP) was measured by OCF of the studied companies. …”
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Predicting and Investigating the Permeability Coefficient of Soil with Aided Single Machine Learning Algorithm by Van Quan Tran

“…To acquire this purpose, five single ML algorithms including K-nearest neighbors (KNN), support vector machine (SVM), light gradient boosting machine (LightGBM), random forest (RF), and gradient boosting (GB) are used to build ML models for predicting the permeability coefficient of soils. …”
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Prediction of inhibitory peptides against E.coli with desired MIC value by Nisha Bajiya, Nishant Kumar, Gajendra P. S. Raghava

“…Feature selection techniques, particularly mRMR, were utilized to refine our model inputs. Our Random Forest regressor built using default parameters achieved a correlation coefficient (R) of 0.78, R2 of 0.59, and RMSE of 0.53 on the validation set. …”
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