Implementasi Algoritma BFCC dan kNN pada Embedded System untuk Deteksi Dini Bronchitis by Septiyo Budi Perkasa, Barlian Henryranu Prasetio, Eko Setiawan, Edita Rosana Widasari, Dahnial Syauqy

“…The proposed system applied the Bark Frequency Cepstral Coefficients (BFCC) and K-Nearest Neighbor (kNN) algorithms. BFCC is an algorithm that is used to extract cough sound features and produce cepstral coefficient values. …”
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Image depth estimation assisted by multi-view projection by Liman Liu, Jinshan Tian, Guansheng Luo, Siyuan Xu, Chen Zhang, Huaifei Hu, Wenbing Tao

“…Abstract In recent years, deep learning has significantly advanced the development of image depth estimation algorithms. The depth estimation network with single-view input can only extract features from a single 2D image, often neglecting the information contained in neighboring views, resulting in learned features that lack real geometrical information in the 3D world and stricter constraints on the 3D structure, leading to limitations in the performance of image depth estimation. …”
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Anomaly Detection in High Mobility MDT Traces Through Self-Supervised Learning by J. M. Sanchez-Martin, C. Gijon, M. Toril, S. Luna-Ramirez, V. Wille

“…Performance analysis includes the comparison of six well-known SL algorithms and 3 different sets of input features aiming to improve model accuracy, generalizability, and explainability, respectively. …”
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Efficacy of drugs most commonly prescribed at functional gastrointestinal diseases (functional dyspepsia syndrome and irritable bowel syndrome) observational study results by V. T. Ivashkin, Ye. A. Poluektova, D. V. Reykhart, O. S. Shifrin, A. G. Beniashvili, O. S. Lyashenko, A. V. Belostotsky

“…The analysis of primary documentation and results symptom assessment of 383 patients with verified diagnosis of functional gastrointestinal disease by «7×7» questionnaire was carried out. Treatment algorithms, their conformity to establish diagnosis and efficacy were analyzed as well. …”
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Identification and validation of immune and diagnostic biomarkers for interstitial cystitis/painful bladder syndrome by integrating bioinformatics and machine-learning by Tao Zhou, Can Zhu, Wei Zhang, Qiongfang Wu, Mingqiang Deng, Zhiwei Jiang, Longfei Peng, Hao Geng, Zhouting Tuo, Zhouting Tuo, Ci Zou

“…Hub genes in IC/BPS patients were identified through the application of three distinct machine-learning algorithms. Additionally, the inflammatory status and immune landscape of IC/BPS patients were evaluated using the ssGSEA algorithm. …”
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Generation of Variations on Theme Music Based on Impressions of Story Scenes Considering Human's Feeling of Music and Stories by Kenkichi Ishizuka, Takehisa Onisawa

“…The present system varies melodies, tempos, tones, tonalities, and accompaniments of given theme music based on impressions of story scenes. Genetic algorithms (GAs) using modular neural network (MNN) models as fitness functions are applied to music generation in order to reflect user's feeling of music and stories. …”
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PLL Based Energy Efficient PV System with Fuzzy Logic Based Power Tracker for Smart Grid Applications by G. Rohini, V. Jamuna

“…The performance of the system is compared with the existing maximum power point tracking algorithms. The authors have endeavored to accomplish maximum power and improved reliability for the same insolation of the PV system. …”
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Development of Intermediate Cooling Technology and Its Control for Two-Stand Plate Rolling by Fei Zhang, Wei Yu, Tao Liu

“…Based on a simplified dynamic model, a cooling control scheme with combined feedforward, feedback, and adaptive algorithms is put forward. The new controlled rolling process and the highly efficient control system improve the controlled rolling efficiency by an average of 17.66%. …”
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A SIC and ML approach for MIMO non-orthogonal multiple access signal detection by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…Additionally, the suggested algorithms are compared with traditional ML, SIC, Zero Forcing (ZF), and Minimum Mean Square Error (MMSE) approaches, and rigorous estimations are made of metrics like Bit Error Rate (BER) and Power Spectral Density (PSD). …”
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Range-Free Localization Scheme in Wireless Sensor Networks Based on Bilateration by Chi-Chang Chen, Chi-Yu Chang, Yan-Nong Li

“…The proposed scheme uses only two anchor nodes and uses bilateration to estimate the coordinates of unknown nodes. Many localization algorithms for WSNs require the installation of extra components, such as a GPS, ultrasonic transceiver, and unidirectional antenna, to sensors. …”
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A Novel Multiband Miniature Planar Inverted F Antenna Design for Bluetooth and WLAN Applications by J. M. Jeevani W. Jayasinghe, Disala Uduwawala

“…A novel compact planar inverted F antenna (PIFA) optimized using genetic algorithms for 2.4 GHz (Bluetooth) and 5 GHz (UNII-1, UNII-2, UNII-2 extended, and UNII-3) bands is presented. …”
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Taylor Expansion of Surface Potential in MOSFET: Application to Pao-Sah Integral by Hugues Murray, Patrick Martin, Serge Bardy

“…The solution is presented analytically wherever possible, and the integration is made from simple numerical methods (Simpson, Romberg) or adaptative algorithms and can be implemented in simple C-program or in usual mathematical software. …”
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Improving the Accuracy for Analyzing Heart Diseases Prediction Based on the Ensemble Method by Xiao-Yan Gao, Abdelmegeid Amin Ali, Hassan Shaban Hassan, Eman M. Anwar

“…The comparison between machine learning algorithms and ensemble learning methods is applied to selected features. …”
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Output Feedback Model Predictive Control for NCSs with Input Quantization by Hongchun Qu, Yu Li, Wei Liu

“…The presented method involves an offline designed state observer using linear matrix inequality (LMI) and online robust output feedback MPC algorithms which optimize one free control move followed by the output feedback using the estimated state. …”
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Compressed sensing for electrocardiogram acquisition in wireless body sensor network: A comparative analysis by Junxin Chen, Jiazhu Xing, Leo Yu Zhang, Lin Qi

“…The performances of involved important factors, such as wavelet basis, overcomplete dictionaries, and the reconstruction algorithms, are comparatively illustrated, with the purpose to give data reference for practical applications. …”
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Application of semi-supervised Mean Teacher to rock image segmentation by Jiashan Li, Yuxue Wang

“…Then, we introduce self-attention mechanism into the semi-supervised Mean Teacher algorithm to further enhance its performance in rock image segmentation. …”
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Real-Time Football Match Prediction Platform by An Zhongqi

“…Future work will focus on enhancing model algorithms and incorporating more complex data sources, such as social media sentiment analysis, to further improve prediction accuracy.…”
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Supporting Efficient Family Joins for Big Data Tables via Multiple Freedom Family Index by Qiang Zhu, Chao Zhu

“…Detailed definitions, practical applications, and processing strategies and algorithms for family joins are provided. Experimental results demonstrate that the index-based join method is quite promising in efficiently processing family joins.…”
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Accurate Identification of Cancerlectins through Hybrid Machine Learning Technology by Jieru Zhang, Ying Ju, Huijuan Lu, Ping Xuan, Quan Zou

“…We improved the prediction accuracy of the original feature extraction methods and classification algorithms by more than 10% on average. Our work provides a basis for the computational identification of cancerlectins and reveals the power of hybrid machine learning techniques in computational proteomics.…”
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The Complexity of the Minimum Sensor Cover Problem with Unit-Disk Sensing Regions over a Connected Monitored Region by Ren-Song Ko

“…Furthermore, we propose an efficient algorithm for reducing MUDC to MSC which has many well-known algorithms for approximated solutions. …”
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