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| 1 | Video Analytics Framework for Human Action Recognition显示文摘Human action recognition(HAR)is an essential but challenging task for observing human movements.This problem encompasses the observations of variations in human movement and activity identification by machine learning algorithms.This article addresses the challenges in activity recognition by implementing and experimenting an intelligent segmentation,features reduction and selection framework.A novel approach has been introduced for the fusion of segmented frames and multi-level features of interests are extracted.An entropy-skewness based features reduction technique has been implemented and the reduced features are converted into a codebook by serial based fusion.A custom made genetic algorithm is implemented on the constructed features codebook in order to select the strong and wellknown features.The features are exploited by a multi-class SVM for action identification.Comprehensive experimental results are undertaken on four action datasets,namely,Weizmann,KTH,Muhavi,and WVU multi-view.We achieved the recognition rate of 96.80%,100%,100%,and 100%respectively.Analysis reveals that the proposed action recognition approach is efficient and well accurate as compare to existing approaches. | Muhammad Attique Khan Majed Alhaisoni Ammar Armghan Fayadh Alenezi Usman Tariq Yunyoung Nam Tallha Akram | 2021 | Computers, Materials & Continua2021，，9： | 0 |
| 2 | Multi Criteria Decision Making for Evaluation and Ranking of Cancer Information显示文摘Cancer is a disease that is rapidly expanding in prevalence all over the world.Cancer cells canmetastasize,or spread,across the body and impact several different cell types.Additionally,the incidence rates of several subtypes of cancer have been on the rise in India.The countermeasures for the cancer disease can be taken by determining the specific expansion rate of each type.To rank the various forms of cancer’s rate of progression,we used some of the available data.Numerous studies are available in the literature which show the growth rate of cancer by different techniques.The accuracy of the scheme in determining the highest growth rate may vary due to the variation in the dependent factors.Within the context of this research,the Fuzzy triangular technique for order preference by similarity to ideal solution(TOPSIS),is utilized to rank the various categorizations of cancer with the help of four groups of medical professionals acting in the capacity of decision-makers.The number of decision-makers may variate according to the required accuracy of results.The findings of the three-dimensional Fuzzy TOPSIS analysis categorize each variety of cancer according to the rate at which it spreads over time.Numerical results along with visual representation are presented to examine the efficiency of our proposed work. | Shahid Mahmood Muhammad Amin Mubashir Baig Mirza Salem Abu-Ghumsan Muhammad Akram Zahid Mahmood Janjua Arslan Shahid Usman Shahid | 2023 | Computers, Materials & Continua2023，，2： | 0 |
| 3 | The charge state distribution of B, C, Si, Ni, Cu and Au ions on 5 MV pelletron accelerator显示文摘Stripper gas and terminal potential play a key role for the charge state distribution in a tandem pelletron accelerator. The knowledge of this distribution is important for experiments performed on tandem accelerators. The charge state distribution of B, C, Si, Ni, Cu and Au beams is measured by using Ar as stripper gas, and terminal potential is varied from 0.3 to 3.0 MV on 5UDH-2 tandem pelletron accelerator installed at the National Centre for Physics, Islamabad. The individual charge state is measured after the switching magnet at 15° in high-energy portion. It is observed that the higher charge states are stable in the range of lower and middle atomic masses of periodic table, whereas higher atomic mass(Au) shows beam current instability in higher charge states. For carbon,the charge distribution at 1.7 MV terminal potential by varying stripper gas pressure is also studied, which resulted in decreased overall transmission with good current value for higher charge states. | Ali Awais Javaid Hussain Muhammad Usman Waheed Akram Kashif Shahzad Turab Ali Ishaq Ahmad Malik Maaza | 2017 | Nuclear Science and Techniques2017，28，5： | 0 |
| 4 | Facile synthesis of ironenickelecobalt ternary oxide(FNCO)mesoporous nanowires as electrode material for supercapacitor application显示文摘Transition Metal Oxides have drawn significant attention due to their reversible chemical redox reaction and long-life stability.Inexorable agglomeration and shrinkage/expansion of transition metal oxides in the nanosize regime have a noticeable effect on their electrochemical properties.Here in this work,mesoporous nanowires(NWs)with a typical composition of iron-nickel-cobalt ternary oxide(FNCO)are synthesized using a simple,facile and cost-effective hydrothermal process followed by furnace annealing.These NWs are then extensively investigated as an electrode material for supercapacitor application.To compare the electrochemical properties,nanowires of nickel-cobalt oxide(NCO),iron-cobalt oxide(FCO)and cobalt oxide(CO)were also produced by following the same protocol.The FNCO NWs are found to overcome the shortcomings in the electrochemical energy storage devices by exhibiting higher values of specific capacitance(2197 Fg^(-1))and energy density(109 Whkg^(-1))at 1 Ag^(-1) current rate.Moreover,the FNCO NWs also showed a cyclic charge/discharge stability of 96%even up to 20,000 cycles.Furthermore,a FNCO//graphene asymmetric device,fabricated with FNCO NWs and graphene as positive and negative electrodes,respectively,which exhibit high energy density(47 Whkg^(-1)),power density(375 Wkg^(-1))and excellent capacitance retention(86%)after 15,000 cycles. | Muhammad Usman Muhammad Tayyab Ahsan Sofia Javed Zeeshan Ali Yiqiang Zhan Irfan Ahmed Sajid Butt Mohammad Islam Asif Mahmood M.Aftab Akram | 2022 | Journal of Materiomics2022，8，1： | 0 |
| 5 | Smart Devices Based Multisensory Approach for Complex Human Activity Recognition显示文摘Sensors based Human Activity Recognition(HAR)have numerous applications in eHeath,sports,fitness assessments,ambient assisted living(AAL),human-computer interaction and many more.The human physical activity can be monitored by using wearable sensors or external devices.The usage of external devices has disadvantages in terms of cost,hardware installation,storage,computational time and lighting conditions dependencies.Therefore,most of the researchers used smart devices like smart phones,smart bands and watches which contain various sensors like accelerometer,gyroscope,GPS etc.,and adequate processing capabilities.For the task of recognition,human activities can be broadly categorized as basic and complex human activities.Recognition of complex activities have received very less attention of researchers due to difficulty of problem by using either smart phones or smart watches.Other reasons include lack of sensor-based labeled dataset having several complex human daily life activities.Some of the researchers have worked on the smart phone’s inertial sensors to perform human activity recognition,whereas a few of them used both pocket and wrist positions.In this research,we have proposed a novel framework which is capable to recognize both basic and complex human activities using builtin-sensors of smart phone and smart watch.We have considered 25 physical activities,including 20 complex ones,using smart device’s built-in sensors.To the best of our knowledge,the existing literature consider only up to 15 activities of daily life. | Muhammad Atif Hanif Tallha Akram Aamir Shahzad Muhammad Attique Khan Usman Tariq Jung-In Choi Yunyoung Nam Zanib Zulfiqar | 2022 | Computers, Materials & Continua2022，，2： | 0 |
| 6 | HybridHR-Net:Action Recognition in Video Sequences Using Optimal Deep Learning Fusion Assisted Framework显示文摘The combination of spatiotemporal videos and essential features can improve the performance of human action recognition(HAR);however,the individual type of features usually degrades the performance due to similar actions and complex backgrounds.The deep convolutional neural network has improved performance in recent years for several computer vision applications due to its spatial information.This article proposes a new framework called for video surveillance human action recognition dubbed HybridHR-Net.On a few selected datasets,deep transfer learning is used to pre-trained the EfficientNet-b0 deep learning model.Bayesian optimization is employed for the tuning of hyperparameters of the fine-tuned deep model.Instead of fully connected layer features,we considered the average pooling layer features and performed two feature selection techniques-an improved artificial bee colony and an entropy-based approach.Using a serial nature technique,the features that were selected are combined into a single vector,and then the results are categorized by machine learning classifiers.Five publically accessible datasets have been utilized for the experimental approach and obtained notable accuracy of 97%,98.7%,100%,99.7%,and 96.8%,respectively.Additionally,a comparison of the proposed framework with contemporarymethods is done to demonstrate the increase in accuracy. | Muhammad Naeem Akbar Seemab Khan Muhammad Umar Farooq Majed Alhaisoni Usman Tariq Muhammad Usman Akram | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 7 | A Double-Branch Xception Architecture for Acute Hemorrhage Detection and Subtype Classification显示文摘This study presents a deep learning model for efficient intracranial hemorrhage(ICH)detection and subtype classification on non-contrast head computed tomography(CT)images.ICH refers to bleeding in the skull,leading to the most critical life-threatening health condition requiring rapid and accurate diagnosis.It is classified as intra-axial hemorrhage(intraventricular,intraparenchymal)and extra-axial hemorrhage(subdural,epidural,subarachnoid)based on the bleeding location inside the skull.Many computer-aided diagnoses(CAD)-based schemes have been proposed for ICH detection and classification at both slice and scan levels.However,these approaches performonly binary classification and suffer from a large number of parameters,which increase storage costs.Further,the accuracy of brain hemorrhage detection in existing models is significantly low for medically critical applications.To overcome these problems,a fast and efficient system for the automatic detection of ICH is needed.We designed a double-branch model based on xception architecture that extracts spatial and instant features,concatenates them,and creates the 3D spatial context(common feature vectors)fed to a decision tree classifier for final predictions.The data employed for the experimentation was gathered during the 2019 Radiologist Society of North America(RSNA)brain hemorrhage detection challenge.Our model outperformed benchmark models and achieved better accuracy in intraventricular(99.49%),subarachnoid(99.49%),intraparenchymal(99.10%),and subdural(98.09%)categories,thereby justifying the performance of the proposed double-branch xception architecture for ICH detection and classification. | Muhammad Naeem Akram Muhammad Usman Yaseen Muhammad Waqar Muhammad Imran Aftab Hussain | 2023 | Computers, Materials & Continua2023，76，9： | 0 |
| 8 | Triple Key Security Algorithm Against Single Key Attack on Multiple Rounds显示文摘In cipher algorithms,the encryption and decryption are based on the same key.There are some limitations in cipher algorithms,for example in polyalphabetic substitution cipher the key size must be equal to plaintext otherwise it will be repeated and if the key is known then encryption becomes useless.This paper aims to improve the said limitations by designing of Triple key security algorithm(TKS)in which the key is modified on polyalphabetic substitution cipher to maintain the size of the key and plaintext.Each plaintext character is substituted by an alternative message.The mode of substitution is transformed cyclically which depends on the current position of the modified communication.Three keys are used in the encryption and decryption process on 8 or 16 rounds with the Exclusively-OR(XOR)of the 1st key.This study also identifies a single-key attack on multiple rounds block cipher in mobile communications and applied the proposed technique to prevent the attack.By utilization of the TKS algorithm,the decryption is illustrated,and security is analyzed in detail with mathematical examples. | Muhammad Akram Muhammad Waseem Iqbal Syed Ashraf Ali Muhammad Usman Ashraf Khalid Alsubhi Hani Moaiteq Aljahdali | 2022 | Computers, Materials & Continua2022，，9： | 0 |
| 9 | Brain Tumor Detection and Classification Using PSO and Convolutional Neural Network显示文摘Tumor detection has been an active research topic in recent years due to the high mortality rate.Computer vision(CV)and image processing techniques have recently become popular for detecting tumors inMRI images.The automated detection process is simpler and takes less time than manual processing.In addition,the difference in the expanding shape of brain tumor tissues complicates and complicates tumor detection for clinicians.We proposed a newframework for tumor detection aswell as tumor classification into relevant categories in this paper.For tumor segmentation,the proposed framework employs the Particle Swarm Optimization(PSO)algorithm,and for classification,the convolutional neural network(CNN)algorithm.Popular preprocessing techniques such as noise removal,image sharpening,and skull stripping are used at the start of the segmentation process.Then,PSO-based segmentation is applied.In the classification step,two pre-trained CNN models,alexnet and inception-V3,are used and trained using transfer learning.Using a serial approach,features are extracted from both trained models and fused features for final classification.For classification,a variety of machine learning classifiers are used.Average dice values on datasets BRATS-2018 and BRATS-2017 are 98.11 percent and 98.25 percent,respectively,whereas average jaccard values are 96.30 percent and 96.57%(Segmentation Results).The results were extended on the same datasets for classification and achieved 99.0%accuracy,sensitivity of 0.99,specificity of 0.99,and precision of 0.99.Finally,the proposed method is compared to state-of-the-art existingmethods and outperforms them. | Muhammad Ali Jamal Hussain Shah Muhammad Attique Khan Majed Alhaisoni Usman Tariq Tallha Akram Ye Jin Kim Byoungchol Chang | 2022 | Computers, Materials & Continua2022，，12： | 0 |
| 10 | JUNO sensitivity on proton decay p→νK^(+)searches显示文摘The Jiangmen Underground Neutrino Observatory(JUNO)is a large liquid scintillator detector designed to explore many topics in fundamental physics.In this study,the potential of searching for proton decay in the p→νK^(+)mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification.Moreover,the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals.Based on these advantages,the detection efficiency for the proton decay via p→νK^(+)is 36.9%±4.9%with a background level of 0.2±0.05(syst)±0.2(stat)events after 10 years of data collection.The estimated sensitivity based on 200 kton-years of exposure is 9.6×1033 years,which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies. | Angel Abusleme Thomas Adam Shakeel Ahmad Rizwan Ahmed Sebastiano Aiello Muhammad Akram 安丰鹏 安琪 Giuseppe Andronico Nikolay Anfimov Vito Antonelli Tatiana Antoshkina Burin Asavapibhop João Pedro Athayde Marcondes de André Didier Auguste Nikita Balashov Wander Baldini Andrea Barresi Davide Basilico Eric Baussan Marco Bellato Antonio Bergnoli Thilo Birkenfeld Sylvie Blin David Blum Simon Blyth Anastasia Bolshakova Mathieu Bongrand Clément Bordereau Dominique Breton Augusto Brigatti Riccardo Brugnera Riccardo Bruno Antonio Budano Mario Buscemi Jose Busto Ilya Butorov Anatael Cabrera Barbara Caccianiga 蔡浩 蔡啸 蔡严克 蔡志岩 Riccardo Callegari Antonio Cammi Agustin Campeny 曹传亚 曹国富 曹俊 Rossella Caruso Cédric Cerna 常劲帆 Yun Chang 陈平平 Po-An Chen 陈少敏 陈旭荣 Yi-Wen Chen 陈义学 陈羽 陈长 程捷 程雅苹 Alexey Chetverikov Davide Chiesa Pietro Chimenti Artem Chukanov Gérard Claverie Catia Clementi Barbara Clerbaux Selma Conforti Di Lorenzo Daniele Corti Flavio Dal Corso Olivia Dalager Christophe De La Taille 邓智 邓子艳 Wilfried Depnering Marco Diaz Xuefeng Ding 丁雅韵 Bayu Dirgantara Sergey Dmitrievsky Tadeas Dohnal Dmitry Dolzhikov Georgy Donchenko 董建蒙 Evgeny Doroshkevich Marcos Dracos Frédéric Druillole 杜然 杜书先 Stefano Dusini Martin Dvorak Timo Enqvist Heike Enzmann Andrea Fabbri Ulrike Fahrendholz 范东华 樊磊 方建 方文兴 Marco Fargetta Dmitry Fedoseev Li-Cheng Feng 冯启春 Richard Ford Amélie Fournier 甘浩男 Feng Gao Alberto Garfagnini Arsenii Gavrikov Marco Giammarchi Agnese Giaz Nunzio Giudice Maxim Gonchar 龚光华 宫辉 Yuri Gornushkin Alexandre Göttel Marco Grassi Christian Grewing Vasily Gromov 顾旻皓 谷肖飞 古宇 关梦云 Nunzio Guardone Maria Gul 郭聪 郭竞渊 郭万磊 郭新恒 郭宇航 Paul Hackspacher Caren Hagner 韩然 Yang Han Muhammad Sohaib Hassan 何苗 何伟 Tobias Heinz Patrick Hellmuth 衡月昆 Rafael Herrera 贺远强 侯少静 Yee Hsiung Bei-Zhen Hu 胡航 胡健润 胡俊 胡守扬 胡涛 胡宇翔 胡焯钧 黄春豪 黄桂鸿 黄翰雄 黄文昊 黄鑫 黄性涛 黄永波 惠加琪 霍雷 霍文驹 Cédric Huss Safeer Hussain Ara Ioannisian Roberto Isocrate Beatrice Jelmini Kuo-Lun Jen Ignacio Jeria 季筱璐 吉星曌 贾慧慧 贾俊基 蹇司玉 蒋荻 蒋炜 江晓山 金如意 荆小平 Cécile Jollet Jari Joutsenvaara Sirichok Jungthawan Leonidas Kalousis Philipp Kampmann 康丽 Rebin Karaparambil Narine Kazarian Amina Khatun Khanchai Khosonthongkee Denis Korablev Konstantin Kouzakov Alexey Krasnoperov Andre Kruth Nikolay Kutovskiy Pasi Kuusiniemi Tobias Lachenmaier Cecilia Landini Sébastien Leblanc Victor Lebrin Frederic Lefevre 雷瑞庭 Rupert Leitner Jason Leung 李德民 李飞 李福乐 李高嵩 李海涛 李慧玲 李佳褀 李梦朝 李民 李楠 李楠 李清江 李茹慧 黎山峰 李涛 李卫东 李卫国 李笑梅 李小男 李兴隆 李仪 李依宸 李玉峰 李兆涵 李志兵 李紫源 梁浩 梁昊 廖佳军 Daniel Liebau Ayut Limphirat Sukit Limpijumnong Guey-Lin Lin 林盛鑫 林韬 凌家杰 Ivano Lippi 刘芳 刘海东 刘宏邦 刘红娟 刘洪涛 刘绘 刘江来 刘金昌 刘敏 刘倩 刘钦 Runxuan Liu 刘双雨 刘树彬 刘术林 刘小伟 刘熙文 刘言 刘云哲 Alexey Lokhov Paolo Lombardi Claudio Lombardo Kai Loo 陆川 路浩奇 陆景彬 吕军光 路书祥 卢晓旭 Bayarto Lubsandorzhiev Sultim Lubsandorzhiev Livia Ludhova Arslan Lukanov 罗凤蛟 罗光 罗朋威 罗舒 罗武鸣 Vladimir Lyashuk 马帮争 马秋梅 马斯 马骁妍 马续波 Jihane Maalmi Yury Malyshkin Roberto Carlos Mandujano Fabio Mantovani Francesco Manzali 冒鑫 冒亚军 Stefano M.Mari Filippo Marini Sadia Marium Cristina Martellini Gisele Martin-Chassard Agnese Martini Matthias Mayer Davit Mayilyan Ints Mednieks 孟月 Anselmo Meregaglia Emanuela Meroni David Meyhöfer Mauro Mezzetto Jonathan Miller Lino Miramonti Paolo Montini Michele Montuschi Axel Müller Massimiliano Nastasi Dmitry V.Naumov Elena Naumova Diana Navas-Nicolas Igor Nemchenok Minh Thuan Nguyen Thi 宁飞鹏 宁哲 Hiroshi Nunokawa Lothar Oberauer Juan Pedro Ochoa-Ricoux Alexander Olshevskiy Domizia Orestano Fausto Ortica Rainer Othegraven Alessandro Paoloni Sergio Parmeggiano 裴亚田 Nicomede Pelliccia 彭安国 彭海平 Frédéric Perrot Pierre-Alexandre Petitjean Fabrizio Petrucci Oliver Pilarczyk Luis Felipe Piñeres Rico Artyom Popov Pascal Poussot Wathan Pratumwan Ezio Previtali 齐法制 祁鸣 钱森 钱小辉 钱圳 乔浩 秦中华 丘寿康 Muhammad Usman Rajput Gioacchino Ranucci Neill Raper Alessandra Re Henning Rebber Abdel Rebii 任斌 任杰 Barbara Ricci Mariam Rifai Markus Robens Mathieu Roche Narongkiat Rodphai Aldo Romani Bedřich Roskovec Christian Roth 阮向东 阮锡超 Saroj Rujirawat Arseniy Rybnikov Andrey Sadovsky Paolo Saggese Simone Sanfilippo Anut Sangka Nuanwan Sanguansak Utane Sawangwit Julia Sawatzki Fatma Sawy Michaela Schever Cédric Schwab Konstantin Schweizer Alexandr Selyunin Andrea Serafini Giulio Settanta Mariangela Settimo 邵壮 Vladislav Sharov Arina Shaydurova 石京燕 史娅楠 Vitaly Shutov Andrey Sidorenkov FedorŠimkovic Chiara Sirignano Jaruchit Siripak Monica Sisti Maciej Slupecki Mikhail Smirnov Oleg Smirnov Thiago Sogo-Bezerra Sergey Sokolov Julanan Songwadhana Boonrucksar Soonthornthum Albert Sotnikov OndřejŠrámek Warintorn Sreethawong Achim Stahl Luca Stanco Konstantin Stankevich DušanŠtefánik Hans Steiger Jochen Steinmann Tobias Sterr Matthias Raphael Stock Virginia Strati Alexander Studenikin 孙世峰 孙希磊 孙勇杰 孙永昭 Narumon Suwonjandee Michal Szelezniak 唐健 唐强 唐泉 唐晓 Alexander Tietzsch Igor Tkachev Tomas Tmej Marco Danilo Claudio Torri Konstantin Treskov Andrea Triossi Giancarlo Troni Wladyslaw Trzaska Cristina Tuve Nikita Ushakov Johannes van den Boom Stefan van Waasen Guillaume Vanroyen Vadim Vedin Giuseppe Verde Maxim Vialkov Benoit Viaud Cornelius Moritz Vollbrecht Cristina Volpe Vit Vorobel Dmitriy Voronin Lucia Votano Pablo Walker 王彩申 Chung-Hsiang Wang 王恩 王国利 王坚 王俊 王坤宇 汪璐 王美芬 王孟 王萌 王瑞光 王思广 王维 王为 王文帅 王玺 王湘粤 王仰夫 王耀光 王义 王忆 王贻芳 王元清 王玉漫 王喆 王铮 王志民 王综轶 Muhammad Waqas Apimook Watcharangkool 韦良红 魏微 韦雯露 魏亚东 温凯乐 温良剑 Christopher Wiebusch Steven Chan-Fai Wong Bjoern Wonsak 吴帝儒 吴群 吴智 Michael Wurm Jacques Wurtz Christian Wysotzki 习宇飞 夏冬梅 Xiang Xiao 谢小川 谢宇广 谢章权 邢志忠 续本达 徐程 徐东莲 徐繁荣 许杭锟 徐吉磊 徐晶 徐美杭 徐音Yu Xu 闫保军 Taylor Yan 闫文奇 严雄波 Yupeng Yan 杨安波 杨长根 杨成峰 杨欢 杨洁 杨雷 杨晓宇 杨翊凡 Yifan Yang 姚海峰 Zafar Yasin 叶佳璇 叶梅 叶子平 Ugur Yegin Frédéric Yermia 易培淮 尹娜 尹翔伟 尤郑昀 俞伯祥 余炽业 喻纯旭 余泓钊 于淼 于向辉 于泽源 于泽众 袁成卓 袁影 袁振雄 岳保彪 Noman Zafar Andre Zambanini Vitalii Zavadskyi 曾珊 曾婷轩 曾裕达 占亮 张爱强 张飞洋 张国庆 张海琼 张宏浩 张家梁 张家文 张杰 张金 张景波 张金楠 张鹏 张清民 张石其 张澍 张涛 张晓梅 张鑫 张玄同 张学尧 张岩 张银鸿 张易于 张永鹏 张宇 张圆圆 张玉美 张振宇 张志坚 赵凤仪 赵洁 赵荣 赵书俊 赵天池 郑冬琴 郑华 郑阳恒 钟伟荣 周静 周莉 周楠 周顺 周彤 周详 朱江 朱康甫 朱科军 朱志航 庄博 庄红林 宗亮 邹佳恒 JUNO Collaboration | 2023 | Chinese Physics C2023，47，11： | 0 |
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