Halftone image compression based on probabilistic run length encoding by H. K. Al-Bahadily, V. Yu. Tsviatkou, V. K. Kanapelka

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The Emergence of AI-Driven Virtual Hospitals: Redefining Patient Care Beyond Physical Boundaries by Ifrah Hameed, Hafiz Muhammad Haseeb Khaliq

“…It also reduces the rate of readmissions as well. Predictive analysis has been proven to lower hospital readmissions by 32% which is beneficial for cost savings for healthcare systems 4. …”
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Procedimiento de corte en cuerpos sólidos poliédricos // Section procedure in solid polyhedral bodies. by A. Miguel Iznaga Benítez, I. Pérez Mallea

“…<br />This algorithm can be use in the software creation that will help to the educational process</p><p><br />Key words: section, separation of solids, algorithm, geometric modeling, graphic, CAD. teaching.…”
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Trabecular bone score in rheumatic disease by M. V. Kozyreva, O. A. Nikitinskaya, N. V. Toroptsova

“…The data obtained indicate that TBS predicts fractures better in RD, especially in patients receiving glucocorticoids, than BMD or the FRAX algorithm. …”
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“Can computed tomographic angiography” solve the puzzle of complexities in the pediatric complex congenital heart disease’s by Javaid Iqbal, Sheikh Riaz Rasool, Tariq Ahmad Gojwari, Naseer Ahmad Choh, Moonisah Rafiq

“…The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and diagnostic accuracy for diagnosing CHD were 95.83%, 100%, 100%, 99.35%, and 99.44% for CTA and 76.96%, 99.78%, 98.24%, 96.51%, and 96.69% for TTE respectively. …”
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From understanding to justifying: Computational reliabilism for AI-based forensic evidence evaluation by Juan M. Durán, David van der Vloed, Arnout Ruifrok, Rolf J.F. Ypma

“…However, it is generally not possible to fully understand how and why these algorithms reach their conclusions. Whether and how we should include such ‘black box’ algorithms in this crucial part of the criminal law system is an open question that has not only scientific but also ethical, legal, and philosophical angles. …”
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Gesture recognition based on flexible solar cells and ultrathin hydrogel film by Rucheng WU, Wenbo DING, Xiaomin XU, Linqi SONG, Weitao XU

“…Daily life involves various gestures, and combining these with smart wearable devices is crucial for improving quality of life.One effective solution to the challenges of gesture recognition and device energy consumption isutilizing the photoelectric conversion characteristics of solar energy-related devices.The data of five commonly used gestures were collected in the research of the combination of flexible solar cells and gesture recognition.Z-Score, low-pass filter, sliding window techniques for signal processing were applied, and successfully achieved 100% predicted accuracy using random forest, support vector machine and neural network algorithms even with small samples which showed that this method had significant advantages in the application of gesture recognition.…”
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Towards Machine Learning Interpretability for Tabular Data with Mixed Data Types by Prativa Pokhrel, Alina Lazar

“…Gradient Boosting (GB) algorithms have been proposed for a variety of automated predictions and classification tasks with applications in many domains. …”
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Komparasi Algoritma Klasifikasi Dengan Menggunakan Anaconda untuk Memprediksi Ramai Penonton Film di Bioskop by Rano Agustino

“…By using CART classification, NBC (Naive Bayes Classifier) algorithm, SVM (Support Vector Machine), LR (Logis Text Regression) and LDA (Linear Discriminant Analysis) which will be compared which accuracy is the best for predicting the absence or absence of the audience. …”
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Optimizing demand charge of data center base on PE method by Yan HUANG, Peng WANG, Gao-hui XIE

“…Demand charge and energy charge are the two main components of data center electricity cost,previous re-searches have not take demand charge into consideration.PEDC algorithm was proposed by modeling time slot,work-load,service quality constraint and response time constraint.With PEDC algorithm peak power was decreased by partial execution on the condition of service quality constrai and response time constraint.PE method was executed in the heavy loaded time slots to reduce peak power so as to ize demand charge.Energy charge and total charge were also optimized.By comparing with four algorithms and with accurately predicted,PEDC algorithm can reduce elec-tricity cost by 5.9%~12.7% and improve cluster utilization 1.32 times.…”
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Using A One-Class SVM To Optimize Transit Detection by Jakob Roche

“…As machine learning algorithms become increasingly accessible, a growing number of organizations and researchers are using these technologies to automate the process of exoplanet detection. …”
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Spatial Information of Somatosensory Stimuli in the Brain: Multivariate Pattern Analysis of Functional Magnetic Resonance Imaging Data by In-Seon Lee, Won-mo Jung, Hi-Joon Park, Younbyoung Chae

“…For binary classification (discriminating between two stimulated body parts, i.e., the arm or leg), the SVC algorithm successfully predicted the stimulated body parts for both acupuncture (mean accuracy, 0.63; q<0.001) and touch stimulation (mean accuracy, 0.60; q<0.01). …”
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Analysis of Coordinated Operation of the Clean Energy System Based on the Multiobjective Optimization Model by Xunyang Wang, Zhicheng Ma, Chen Liang, Shien He, Yongqiang Wang

“…According to the model, in the example in this paper, the maximum value of photovoltaic power prediction is 1290 MW, and the minimum value is 210 MW; the maximum value of wind power prediction is 780 MW, and the minimum value is 28 MW; the minimum cost of power purchase and maintenance is 56,950.395; the maximum generating capacity is 5.045 GW; the minimum output fluctuation is 0.120 GW.…”
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Personalised Prostate Cancer Diagnosis: Evaluating Biomarker-based Approaches to Reduce Unnecessary Magnetic Resonance Imaging and Biopsy Procedures by Timo F.W. Soeterik, Xiaobo Wu, Roderick C.N. Van den Bergh, Claudia Kesch, Fabio Zattoni, Ugo Falagario, Alberto Martini, Marcin Miszczyk, Vittorio Fasulo, Martina Maggi, Veeru Kasivisvanathan, Pawel Rajwa, Giancarlo Marra, Giorgio Gandaglia, Peter K.F. Chiu

“…PSMA PET has emerging potential to improve csPCa prediction in combination with MRI and may further reduce unnecessary biopsies. …”
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EFFICACY OF CARDIOVERTER-DEFIBRILLATORS IN PREVENTION OF SUDDEN DEATH AND OVERALL MORTALITY DECREASE IN PATIENTS WITH THE SYNDROME OF DILATION CARDIOMYOPATHY: DIFFERENTIAL APPROA... by O. V. Blagova, A. V. Nedostup, E. V. Zaklyazminskaya

“…Main predictors of the shocks were genetic origin of DCMP (isolated or with myocarditis, 25/75%, comparing with 20/33% in patients with no shocks, p&lt;0,01, HR 1,58, OR 10,93, sensitivity 94,1%, negative predictive value 99,2%), and sustained (HR 18,0, sensitivity 98,1%) and non-sustained ventricular tachycardia (HR 1,43, sensitivity and negative predictive value 100%), decrease of QRS voltage and absence of the signs of LV hypertrophy on ECG (negative predictive value 92,8% and 95,6%).Conclusion. …”
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Artificial Neural Network Modeling of NixMnxOx based Thermistor for Predicative Synthesis and Characterization by T.D. Dongale, K.G. Kharade, N.B. Mullani, G.M. Naik, R.K. Kamat

“…Transition metal oxides especially the NixMnxOx are widely used for thermistor synthesis in spite of the main difficulty of predicting the final sensor characteristics before the actual synthesis. …”
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Interpretable Machine Learning for Thermospheric Mass Density Modeling Using GRACE/GRACE‐FO Satellite Data by Qian Pan, Chao Xiong, ShunZu Gao, Zhou Chen, Artem Smirnov, Chunyu Xu, Yuyang Huang

“…A critical aspect of our work is minimizing the number of input parameters while maintaining high prediction accuracy. And the interpretability analysis of the input parameters using the Shapley additive explanation algorithm has been applied, revealing that the altitude, solar activity index P10.7 and solar zenith angle are the three most influential parameters affecting TMD variations at GRACE satellite. …”
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Artificial Intelligence Empowers Solid-State Batteries for Material Screening and Performance Evaluation by Sheng Wang, Jincheng Liu, Xiaopan Song, Huajian Xu, Yang Gu, Junyu Fan, Bin Sun, Linwei Yu

“…The achievements of various ML algorithms in predicting different performances of the battery management system are discussed. …”
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Machine learning based on pangenome-wide association studies reveals the impact of host source on the zoonotic potential of closely related bacterial pathogens by Cheng Han, Shiying Lu, Pan Hu, Jiang Chang, Deying Zou, Feng Li, Yansong Li, Qiang Lu, Honglin Ren

“…Integrating these genes into an ML model based on the support vector machine (SVM) algorithm allows us to predict the zoonotic potential of various Brucella strains with high accuracy. …”
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Modelling soil prokaryotic traits across environments with the trait sequence database ampliconTraits and the R package MicEnvMod by Jonathan Donhauser, Anna Doménech-Pascual, Xingguo Han, Karen Jordaan, Jean-Baptiste Ramond, Aline Frossard, Anna M. Romaní, Anders Priemé

“…We created the trait sequence database ampliconTraits, constructed by cross-mapping species from a phenotypic trait database to the SILVA sequence database and formatted to enable seamless classification of environmental sequences using the SINAPS algorithm. The R package MicEnvMod enables modelling of trait – environment relationships, combining the strengths of different model types and integrating an approach to evaluate the models' predictive performance in a single framework. …”
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