PENGARUH BIAYA OPERASIONAL, BIAYA PRODUKSI DAN PENJUALAN TERHADAP LABA BERSIH by Ainur Rozi, Syaiful Bahri

“…Non probability sampling technique with purposive sampling method with total data 57. Multiple regression analysis is a research data analysis technique. …”
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Characteristic genes and immune infiltration analysis of gastric cancer based on bioinformatics analysis and machine learning by Chengwei Xia, Yini Liu, Xin Qing

“…The limma package was utilized to normalize these data, thus identifying differentially expressed genes (DEGs). …”
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APPLICATION OF THINK TALK WRITE MODEL TO IMPROVE JUNIOR HIGH SCHOOL STUDENTS’ MATHEMATICAL ACHIEVEMENT by Novita Jenianis Soselisa, Magy Gaspersz, Darma Andreas Ngilawajan

“…Research data is analyzed by using qualitative and quantitative data analysis. …”
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An improved method of studying user-system interaction by combining transaction log analysis and protocol analysis by Jillian R. Griffiths, R.J. Hartley, Jonathan P. Willson

“…The approach is set in context by a discussion of transaction logging and protocol analysis and examples of the search logging in operation are presented…”
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The Influence of Digital Talent Development and Green Innovation and The Use of Green Innovation As Mediation To Measure Data Centre Performance by Rifa Herdian, Mohammad Syamsul Maarif, Anggraini Sukmawati, Irman Hermandi

“…Respondents are Data Center Managers, Digital Talent Development Experts, Data Center Operational and Technical Teams, and Experts and Consultants in the Field of Green Technology and Data Centers. …”
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Meeting Global Health Needs via Infectious Disease Forecasting: Development of a Reliable Data-Driven Framework by Ravikiran Keshavamurthy, Karl T Pazdernik, Colby Ham, Samuel Dixon, Samantha Erwin, Lauren E Charles

“…ConclusionsAs the need for real-time, operational ID forecasting capabilities increases, this standardized and automated platform for data collection, analysis, and reporting is a major step forward in enabling evidence-based public health decisions and policies for the prevention and mitigation of future ID outbreaks.…”
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BANKING LOANS AND HOUSEHOLD DEPOSITS IN THE REPUBLIC OF BULGARIA UNDER ECONOMIC CRISIS: DYNAMICS AND STRUCTURAL TRANSFORMATIONS by Zhelyo Vatev

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Novel feature extraction method for signal analysis based on independent component analysis and wavelet transform. by Mariusz Topolski, Jędrzej Kozal

“…Feature extraction is an important part of data processing that provides a basis for more complicated tasks such as classification or clustering. …”
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Raya: A Bio-Inspired AUV for Inspection and Intervention of Underwater Structures by Pedro Pereira, Renato Silva, Joao V. Amorim Marques, Raul Campilho, Anibal Matos, Andry Maykol Pinto

“…This work presents a bio-inspired Autonomous Underwater Vehicle (AUV) concept called Raya that enables high manoeuvrability required for close-range inspection and intervention tasks, while fostering endurance for long-range operations by enabling efficient navigation. The AUV has an estimated terminal velocity of 0.82 m/s in an optimal environment, and a capacity to acquire visual data and sonar measurements in all directions. …”
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Improving of the Generation Accuracy Forecasting of Photovoltaic Plants Based on <i>k</i>-Means and <i>k</i>-Nearest Neighbors Algorithms by P. V. Matrenin, A. I. Khalyasmaa, V. V. Gamaley, S. A. Eroshenko, N. A. Papkova, D. A. Sekatski, Y. V. Potachits

“…Then, for each cluster, its own machine learning model was trained for generation forecasting and the k-nearest neighbours algorithm was built to attribute the current conditions at the model operation stage to one of the formed clusters. The study was conducted on hourly meteorological data for the period from 1985 to 2021. …”
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Predictive Assessment of Forest Fire Risk in the Hindu Kush Himalaya (HKH) Region Using HIWAT Data Integration by Sunil Thapa, Tek Maraseni, Hari Krishna Dhonju, Kiran Shakya, Bikram Shakya, Armando Apan, Bikram Banerjee

“…This research presents a novel, scalable, and operational framework tailored for data-scarce and topographically complex regions. …”
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Pengaruh Customer Engagement terhadap Online Purchase Intention dengan Customer Operant Resources Sebagai Variabel Intervening pada Layanan Platinum Mahasiswa di Vidio.com by Lela Septatiana Ratnawati, Sanaji Sanaji

“…The analysis results show that Customer Engagement has a significant effect on Customer Operant Resources, indicating that customer engagement positively influences operant resources. …”
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A Comparison of Two Operation Methods Revealed the Risk Factors and the Necessity of LN-prRLN Dissection in Papillary Thyroid Carcinoma: A Retrospective Cohort Study in FUSCC by Yunjun Wang, Dezhi Wang, Lili Chen, Kai Guo, Tuanqi Sun

“…A total of 1487 consecutive patients with PTC who underwent total thyroidectomy or right lobectomy plus isthmic resection with central LN dissection (CLND) were divided into two groups: patients with LN-prRLN dissection (group A) and patients without LN-prRLN dissection (group B). Clinicopathologic data were reviewed of the patients who were operated on by the same thyroid surgery team in the Department of Head Neck Surgery, Fudan University Shanghai Cancer Center (FUSCC) between August 2011 and May 2019. …”
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Relationship Between Fulfillment Of Pre-Operative Fluid Needs And The Incidence Of Nausea And Vomiting In Patients Post General Anesthesia At Dr Saiful Anwar Hospital, East Java Pr... by Shaumi Miftahul Rasyida, Achmad Dafir Firdaus, Sismala Harningtyas

“…This research instrument uses the RINVR observation sheet and fluid calculations based on the fresh holiday formula. Data analysis using the Fisher Test with SPSS IBM Version 23. …”
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Mapping Lithology with Hybrid Attention Mechanism–Long Short-Term Memory: A Hybrid Neural Network Approach Using Remote Sensing and Geophysical Data by Michael Appiah-Twum, Wenbo Xu, Emmanuel Daanoba Sunkari

“…To address these limitations, a hybrid-attention-integrated long short-term memory (LSTM) network is employed to diagnose, interpret, and identify lithological feature representations in a remote sensing-based geological analysis using multisource data fusion. The experimental design integrates varied datasets including Sentinel-2A, Landsat-9, ASTER, ALOS PALSAR DEM, and Bouguer anomaly gravity data. …”
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Comparing the effects of intercostal and subcostal flank incision on post-operative pain and incisional hernia or bulge in patients undergoing open kidney surgery: A randomized cli... by Alireza Abdi, Behzad Imani, Seyed Habibollah Mousavibahar, Salman Khazaei, Shima Bahrami Jalal

“…Data analysis was done using SPSS-23. RESULTS: In the subcostal group, a higher incidence of AWA was observed when compared to the intercostal group at 6 months post-operation, and this difference was statistically significant (P = 0.039). …”
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Big data meets big wind: A scientometric review of machine learning approaches in offshore wind energy by Prangon Das, Maisha Mashiata, Gregorio Iglesias

“…The research methodology employs a circular framework, integrating data acquisition and statistical analysis to provide a comprehensive scientometric insight into the state of the art. …”
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Integration of Satellite, Models and Ground Sensors for City-scale Air Quality Monitoring through the Open Data Cube by A. Moazzam, D. Oxoli, J. R. Cedeno Jimenez, M. A. Brovelli

“…Traditional ground-based monitoring stations provide accurate data but lack the spatial coverage necessary for comprehensive city-wide analysis. …”
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Anomaly detection of industrial state quantity time-Series data based on correlation and long short-term memory by Mingxin Tang, Wei Chen, Wen Yang

“…Anomaly detection of multi-dimensional time-series data is a key research area, and the analysis of control, switching, and other state signals (i.e., industrial state quantity time series) is of particular importance to the operational sciences. …”
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Integrating Learning-Driven Model Behavior and Data Representation for Enhanced Remaining Useful Life Prediction in Rotating Machinery by Tarek Berghout, Eric Bechhoefer, Faycal Djeffal, Wei Hong Lim

“…The increasing complexity of modern mechanical systems, especially rotating machinery, demands effective condition monitoring techniques, particularly deep learning, to predict potential failures in a timely manner and enable preventative maintenance strategies. Health monitoring data analysis, a widely used approach, faces challenges due to data randomness and interpretation difficulties, highlighting the importance of robust data quality analysis for reliable monitoring. …”
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