Probabilistic Entropy EMD Thresholding for Periodic Fault Signal Enhancement in Rotating Machine by Jian Dang, Rong Jia, Hua Wu, Xingqi Luo, Diyi Chen

“…However, for rotating machine with poor working environment, the components attributed to noise might have higher amplitudes, which restrict the efficiency of noise reduction in current EMD-based denoising methods. Therefore, a probabilistic entropy EMD thresholding algorithm for periodic fault signal enhancement in rotating machine is proposed in this paper. …”
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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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Dynamic programming for home appliance scheduling with renewable energy integration by Iqra Rafiq, Anzar Mahmood, Ubaid Ahmed, Imran Aziz, Zafar Ali Khan

“…This study proposes an energy cost minimization model, which is solved using a single Knapsack algorithm combined with dynamic programming (DP). The Knapsack problem is used to schedule appliances and ensure that users and producers receive the maximum benefits in terms of cost minimization and peak-to-average ratio (PAR) reduction. …”
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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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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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Unleashing the power of intelligence: revolutionizing malaria outbreak preparedness with an advanced warning system in Benin, West Africa by Gouvidé Jean Gbaguidi, Nikita Topanou, Walter Leal Filho, Komi Agboka, Guillaume K. Ketoh

“…Results Relative humidity and maximal temperature significantly influence malaria incidence in the northern region of Benin. SVM regression algorithm forecasts 80% prediction rate for malaria incidence. …”
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OR-FCOS: an enhanced fully convolutional one-stage approach for growth stage identification of Oudemansiella raphanipes by Runze Fang, Huamao Huang, Nuoyan Guo, Haichuan Wei, Shiyi Wang, Haiying Hu, Ming Liu

“…A neural architecture search (NAS)-enhanced FCOS decoder replaces both the traditional feature pyramid networks (FPN) and prediction head in FCOS, optimizing feature fusion and prediction. …”
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Machine Learning Prognostic Model for Post-Radical Resection Hepatocellular Carcinoma in Hepatitis B Patients by Zhu D, Tulahong A, Abuduhelili A, Liu C, Aierken A, Lin Y, Jiang T, Lin R, Shao Y, Aji T

“…A prognostic model was developed using a machine learning algorithm and evaluated for predictive performance using the concordance index (C-index), calibration curve, decision curve analysis (DCA), and receiver operating characteristic (ROC) curves.Results: Key predictors for constructing the best model included body mass index (BMI), albumin (ALB) levels, surgical resection method (SRM), and the American Joint Committee on Cancer (AJCC) stage. …”
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Development and evaluation of a triplex real-time PCR assay for enhanced plague diagnostics in Madagascar. by Beza Ramasindrazana, Zoé A Rahalison, Philippe Gauthier, Guillain Mikaty, Zaina I Bodoarison, Lanto A Maminirina, Soloandry Rahajandraibe, Mamy G Randriamanantsoa, Gilbert Kayoko, Jean-Claude Manuguerra, Anne-Sophie Le Guern, Andriamiliharison J Rasamindrakotroka, Minoarisoa Rajerison

“…<h4>Results</h4>Using bacteriology technique as the reference standard, the triplex qPCR demonstrated a sensitivity of 100% (89-100%) and a specificity of 82%. The positive predictive value (PPV) was 73% and the negative predictive value (NPV) was 100% (91-100%). …”
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Simultaneous and Proportional Control Based on an Enhanced Musculoskeletal Model by Lizhi Pan, Diyi Liu, Ruyi Wang, Jinhua Li

“…For offline experiment, another two MMs were established and taken as the control groups for validation of the proposed DC-NMF-MM, including the MM totally taking the NMF algorithm (T-NMF-MM) and that partly taking the NMF algorithm (P-NMF-MM) for predicting the wrist pronation/supination only. …”
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Precision Imaging for Early Detection of Esophageal Cancer by Po-Chun Yang, Chien-Wei Huang, Riya Karmakar, Arvind Mukundan, Tsung-Hsien Chen, Chu-Kuang Chou, Kai-Yao Yang, Hsiang-Chen Wang

“…We employed the Yolov5 model, a state-of-the-art object detection algorithm, to predict early ECA based on the provided images. …”
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