RETRACTED: Bone Age Assessment Based on Deep Convolutional Features and Fast Extreme Learning Machine Algorithm by Longjun Guo, Juan Wang, Jiaqi Teng, Yukun Chen

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Rancang Bangun Purwarupa Pemilah Sampah Pintar Berbasis Deep Learning by Kahlil Muchtar, Nyak Twoman Anshari, Chairuman Chairuman, Khalid Alhabibie, Khairul Munadi

“… Pengolahan sampah di Indonesia masih menjadi pekerjaan rumah yang besar dan belum terselesaikan. Menurut penelitian aktual Sustainable Waste Indonesia (SWI) mengungkapkan bahwa 24% sampah di Indonesia masih tidak dikelola dengan baik. …”
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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…Efficient resource allocation and workload distribution are vital to ensuring continuous and reliable service in growing IoT ecosystems with increasing data volumes and changing application demands. This study proposes a novel optimisation approach utilising deep learning to tackle these challenges. …”
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Key experimental technologies and their development directions for the exploration and production of deep coalbed methane by Xia YAN, Fengyin XU, Xianyue XIONG, Feng WANG, Chunhu LI, Jiyuan ZHANG, Borui XU, Qianhui CHENG, Xiong HU, Xueguang ZHU, Wei LIANG, Pu YUAN, Yanqing FENG, Zhenji WEI

“…ProspectsThis study posits seven development directions for deep CBM production and in-situ coal conversion experiments: (1) Clear, direct observation techniques for micropores (< 2 nm) in deep coal seams with ultra-low porosity and permeability, full-scale pore size splicing technology for multiscale pore structure characterized by abundant micropores, a few mesopores, and many macropores, and assessment techniques for pore-fracture connectivity. (2) Isothermal adsorption test technologies for raw coals considering the effects of deep coal seam wettability, fracturing fluid invasion, and high total dissolved solids (TDS) under high-temperature, high-pressure in-situ conditions; (3) Sealed coring devices and in-situ pressure-retaining coring technologies featuring high pressure retaining success rates, heat preservation rates, and traceable gas volume. (4) Nanoscience-based assessment technologies for gas and water occurrence in micropores in deep coal seams under high-temperature and high-pressure multi-field coupling, and experimental technologies for desorption, diffusion, and seepage across nano-micro-millimeter scales. (5) Techniques for developing and testing multifunctional mechanical experiment equipment applicable to in-situ conditions of deep coal seams featuring high stress, low modulus of elasticity, and high Poisson's ratio. (6) Experimental techniques for the purpose of enhancing CBM recovery of deep coal seams, including reservoir stimulation (microwaves, laser, and electric heating), stimulation for permeability enhancement (electromagnetic pulses, pulsed ultrasonic waves, and controlled shockwaves), displacement via CO2 injection, and mechanical pulsation with supercritical CO2. (7) Experimental techniques for in-situ coal conversion and utilization, including pyrolysis, underground coal gasification (UCG), geothermal utilization, and CO2 geological storage. …”
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Studi Awal Deteksi COVID-19 Menggunakan Citra CT Berbasis Deep Learning by Windra Swastika

“…Pada bulan Desember 2019, virus COVID-19 menyebar ke banyak negara, termasuk di Indonesia yang kemudian menjadi pandemi dan menimbulkan masalah serius karena masih belum adanya vaksin untuk mencegah penularan. Uji spesimen saluran nafas atas dan saluran nafas bawah saat ini merupakan salah satu metode yang efektif untuk mengetahui apakah seseorang terinfeksi COVID-19 atau tidak. …”
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Research on comprehensive characterization of deep coal full aperture structure and burial depth effect by Qi Li, Xiaoxia Zhang, Zhengzong Wang, Lei Qiao, Shitan Shao

“…Abstract With the increasing depletion of shallow mineral resources, deep mining has become important; however, basic research on deep resource development remains insufficient, and basic laws are unclear. …”
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A low functional redundancy-based network slimming method for accelerating deep neural networks by Zheng Fang, Bo Yin

“…Deep neural networks (DNNs) have been widely criticized for their large parameters and computation demands, hindering deployment to edge and embedded devices. …”
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Analysis of pressure-maintaining coring process in deep coal seams and gas content determination methods by Jian WU, Songhang ZHANG, Tengfei JIA, Weiwei CHAO, Wenchun PENG, Shilong LI

“…Gas content is an important parameter for calculating coalbed methane (CBM) reserves and guiding their exploration and development. For deep coal seams, the prolonged coring duration and inaccuracies in lost gas volume calculations result in reduced accuracy in gas content measurement using conventional wireline coring methods. …”
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Data Augmentation For Sorani Kurdish News Headline Classification Using Back-Translation And Deep Learning Model by Soran Badawi

“…With the increase in the volume of news articles and headlines being generated, it is becoming more difficult for individuals to keep up with the latest developments and find relevant news articles in the Kurdish language. …”
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Analisis Perbandingan Algoritma Machine Learning dan Deep Learning untuk Klasifikasi Citra Sistem Isyarat Bahasa Indonesia (SIBI) by Mohammad Farid Naufal, Selvia Ferdiana Kusuma

“…Pada penelitian sebelumnya belum ada yang melakukan perbandingan algoritma klasifikasi machine learning dan deep learning untuk pengenalan SIBI. …”
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Main controlling factors of production and reasonable fracturing scale optimization of deep coalbed methane wells in Shenfu block, Ordos Basin by Lichun SUN, Jia LIU, Na LI, Xinze LI, Heng WEN

“…The factors affecting post-fracturing production capacity of deep CBM wells, ranked by correlation, are as follows: gas content > fracturing sand amount > construction flow rate > fracturing fluid volume > structural depth > thickness. …”
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Storage and permeation space development characteristics and water production capacity evaluation of deep coal reservoirs in Linxing-Shenfu area of Ordos Basin by Jinwei WANG, Hao XU, Yinan LIU, Bing ZHANG, Yanyong XU, Ding LIU, Peng ZONG, Yajuan WANG, Xuejing SONG

“…As coal rank increases, the total pore volume first decreases and then increases. The original water content of deep coal samples declines sharply, while the water storage capacity first decreases and then increases, with bright coal showing a greater advantage in water storage capacity. …”
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Combined characterization of pore structurein deep medium-rank coal using mercury intrusion and liquid nitrogen adsorption methods and its pore fractal characteristics by Qi LI, Yong WU, Lei QIAO

“…The pore development in the main coal seams of typical deep mining areas was relatively similar. The pore volume distribution was dominated by macropores, with micropores and transition pores contributing roughly equally, and mesopores having a relatively small distribution. …”
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Characteristics, controlling factors of development and exploration areas of deep coal-rock reservoirs in rift basins: a case study of the second member of Cretaceous Nantun Format... by Geng GAO, Yingyi XIE, Beibei HOU, Wenjuan MA, Hui XU, Yujie WANG, Yingdong HUO, Jingyuan ZHANG, Shichao LIU, Wei ZHAO, Yuan LIANG

“…The predicted resource volume exceeds one trillion cubic meters, making it a favorable breakthrough area for deep coal-rock gas exploration in the Huhehu Sag. …”
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ANTi-JAM solutions for smart roads: Ant-inspired traffic flow rules under CAVs environment by Marco Guerrieri, Nicola Pugno

“…The macroscopic traffic flow variables of interest were estimated using the deep learning method and the YOLO detection algorithm. …”
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Synthetic CT generation from CBCT and MRI using StarGAN in the Pelvic Region by Paritt Wongtrakool, Chanon Puttanawarut, Pimolpun Changkaew, Supakiet Piasanthia, Pareena Earwong, Nauljun Stansook, Suphalak Khachonkham

“…Abstract Rationale and objectives This study evaluated StarGAN, a deep learning model designed to generate synthetic computed tomography (sCT) images from magnetic resonance imaging (MRI) and cone-beam computed tomography (CBCT) data using a single model. …”
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Association between the subclinical level of problematic internet use and habenula volume: a look at mediation effect of neuroticism by Toshiya Murai, Hironobu Fujiwara, Qi Dai, Halwa Zakia, Yusuke Kyuragi, Naoya Oishi, Yuzuki Ishikawa, Lichang Yao, Morio Aki

“…The significant trait was then treated as a mediator between Hb volume and IAT correlation in mediation analysis with a bootstrap value of 5000.Results Relative Hb volume was negatively correlated with IAT scores (partial rho=−0.142, p=0.009). …”
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A Postharvest Fruit Rot Caused by Alternaria sp. on Imported Plum Tomatoes in South Florida by Zelalem Mersha, Shouan Zhang, Jerry A. Bartz

“…Florida’s deep-water ports are ideal for importing many fruits and vegetables, including tomatoes, by ship from the Caribbean as well as Central and South American production areas. …”
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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

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Evaluation method and application for in-situ stress in No. 8+9 coal seam, southern Shenfu block, northeastern margin of Ordos Basin by Jiawei WU, Wei TANG, Yanhe ZHU, Cunwu WANG, Yongjing TIAN, Jingyu ZI, Jianghao YANG, Xian SHI

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