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Deep Learning-based Environmental Sound Classification Using Feature Fusion and Data Enhancement

Computers, Materials & Continua 2023年第1期74卷 1069-1091页

作者： Rashid Jahangir Muhammad Asif Nauman Roobaea Alroobaea Jasem Almotiri Muhammad Mohsin malik Sabah M.Alzahrani Department of Computer Science COMSATS University IslamabadVehari CampusPakistan Department of Computer Science University of Engineering and Technology LahorePakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21974Saudi Arabia

Environmental sound classification(ESC)involves the process of distinguishing an audio stream associated with numerous environmental *** common aspects such as the framework difference,overlapping of different sound events,and the presence of various sound sources during recording make the ESC task much more complicated and *** research is to propose a deep learning model to improve the recognition rate of environmental sounds and reduce the model training time under limited computation *** this research,the performance of transformer and convolutional neural networks(CNN)are *** audio features,chromagram,Mel-spectrogram,tonnetz,Mel-Frequency Cepstral Coefficients(MFCCs),delta MFCCs,delta-delta MFCCs and spectral contrast,are extracted fromtheUrbanSound8K,ESC-50,and ESC-10,***,this research also employed three data enhancement methods,namely,white noise,pitch tuning,and time stretch to reduce the risk of overfitting issue due to the limited audio *** evaluation of various experiments demonstrates that the best performance was achieved by the proposed transformer model using seven audio features on enhanced *** UrbanSound8K,ESC-50,and ESC-10,the highest attained accuracies are 0.98,0.94,and 0.97 *** experimental results reveal that the proposed technique can achieve the best performance for ESC problems.

关键词： Environmental sound classification convolutional neural network deep learning transformer data augmentation

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Proteome-wide screening for the analysis of protein targeting of Chlamydia pneumoniae in endoplasmic reticulum of host cells and their possible implication in lung cancer development

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BIOCELL 2022年第1期46卷 87-95页

作者： YANYAN LI SHAHANAVAJ KHAN ANIS AHMAD CHAUDHARY HASSAN AHMED RUDAYNI ABDUL malik ASHWAG SHAMI Department of Oncology Zhengzhou Central Hospital Affiliated to Zhengzhou UniversityZhengzhou450007China Department of Pharmaceutics College of PharmacyKing Saud UniversityRiyadh11451Saudi Arabia Department of Biosciences Shri Ram Group of College(SRGC)Muzaffarnagar251001India Department of Health Sciences Novel Global Community Educational FoundationSydneyAustralia Department of Biology College of ScienceImam Mohammad Ibn Saud Islamic University(IMSUI)Riyadh11623Saudi Arabia Department of Biology College of SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11617Saudi Arabia

Available reports have confirmed a link between bacterial infection and the progression of different types of cancers,including colon,lungs,and prostate *** we report the Chlamydia pneumonia proteins targeting in endoplasmic reticulum(ER)using in-silico approaches and their possible role in lung cancer *** predicted 48 proteins that target human ER,which may be associated with protein folding and protein-protein interactions during *** results showed *** proteins targeting human ER and their implications in lung cancer *** targeted proteins may be involved in competitive interactions between host and bacterial proteins,which may change the usual pathway functions and trigger the development of lung ***,*** unfolded protein accumulation in the human ER possibly induces ER stress,consequently activating the unfolded protein response(UPR),and providing a favorable microenvironment for cancer *** current study showed the *** protein targeting in ER of host cell and their implication in lung cancer *** results may help researchers better manage lung cancer and establish a molecular mechanism for *** lung cancer association.

关键词： Bacterial infection C.pneumoniae Proteomes ER Lung cancer

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Antibacterial mechanism with consequent cytotoxicity of different reinforcements in biodegradable magnesium and zinc alloys: A review

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Journal of Magnesium and Alloys 2023年第9期11卷 3038-3058页

作者： Chowdhury Ahmed Shahed Faiz Ahmad Ebru Günister Farhana Mohd Foudzi Saad Ali Khurshid malik Wan Sharuzi Wan Harun Department of Mechanical Engineering Universiti Teknologi PETRONAS(UTP)32610Seri IskandarPerakMalaysia Faculty of Engineering and Natural Sciences Department of Mechanical EngineeringIstanbul Health and Technology UniversityIstanbulTurkey Department of Mechanical and Manufacturing Engineering Faculty of Engineering and Built EnvironmentUniversiti Kebangsaan Malaysia43600 UKM BangiSelangorMalaysia Faculty of Mechanical&Automotive Engineering Technology Universiti Malaysia Pahang26600 PekanPahangMalaysia

Benefits achieved by the biodegradable magnesium(Mg) and zinc(Zn) implants could be suppressed due to the invasion of infectious microbial, common bacteria, and fungi. Postoperative medications and the antibacterial properties of pure Mg and Zn are insufficient against biofilm and antibiotic-resistant bacteria, bringing osteomyelitis, necrosis, and even death. This study evaluates the antibacterial performance of biodegradable Mg and Zn alloys of different reinforcements, including silver(Ag), copper(Cu), lithium(Li), and gallium(Ga). Copper ions(Cu^(2+)) can eradicate biofilms and antibiotic-resistant bacteria by extracting electrons from the cellular structure. Silver ion(Ag^(+)) kills bacteria by creating bonds with the thiol group. Gallium ion(Ga^(3+)) inhibits ferric ion(Fe^(3+)) absorption, leading to nutrient deficiency and bacterial death. Nanoparticles and reactive oxygen species(ROS) can penetrate bacteria cell walls directly, develop bonds with receptors, and damage nucleotides. Antibacterial action depends on the alkali nature of metal ions and their degradation rate, which often causes cytotoxicity in living cells. Therefore, this review emphasizes the insight into degradation rate, antibacterial mechanism, and their consequent cytotoxicity and observes the correlation between antibacterial performance and oxidation number of metal ions.

关键词： Biodegradable materials Biomedical implants Antibacterial mechanism Cytotoxicity Reactive oxygen species

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Active Queue Management Exploiting the Rate Information in TCP-IP Networks

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IEEE/CAA Journal of Automatica Sinica 2018年第1期5卷 223-231页

作者： Abderrahmane Boudi malik Loudini Laboratoire de la Communication dans les Systemes Informatiques Ecole nationale Superieure d'Informatique ESI Algiers 16309 Algeria IEEE

In this paper, we propose a new mechanism called explicit rate notification(ERN) to be used in end-to-end communications. The ERN scheme encodes in the header of transmission control protocol(TCP) packets information about the sending rate and the round trip time(RTT) of the flows. This new available information to the intermediate nodes(routers) is used to improve fairness, increase utilization, decrease the number of drops, and minimize queueing delays. Thus, it induces a better management of the queue. A comparison of our scheme with preexistent schemes, like the explicit congestion notification scheme, shows the effectiveness of the proposed mechanism.

关键词： Active queue management congestion control fairness transmission control protocol(TCP)

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Automated Brain Hemorrhage Classification and Volume Analysis

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Computers, Materials & Continua 2023年第4期75卷 2283-2299页

作者： Maryam Wardah Muhammad Mateen Tauqeer Safdar malik Mohammad Eid Alzahrani Adil Fahad Abdulmohsen Almalawi Rizwan Ali Naqvi Department of Computer Science Air University Multan CampusMultan60000Pakistan Department of Information Technology Bahauddin Zakariya UniversityMultan60800Pakistan Department of Engineering and Computer Science College of Computer Science and Information TechnologyAl Baha UniversityAl BahaSaudi Arabia School of Computer Science&Information Technology King Abdulaziz UniversityJeddahSaudi Arabia Department of Intelligent Mechatronics Engineering Sejong UniversitySeoul05006Korea

Brain hemorrhage is a serious and life-threatening condition. It cancause permanent and lifelong disability even when it is not fatal. The wordhemorrhage denotes leakage of blood within the brain and this leakage ofblood from capillaries causes stroke and adequate supply of oxygen to thebrain is hindered. Modern imaging methods such as computed tomography(CT) and magnetic resonance imaging (MRI) are employed to get an idearegarding the extent of the damage. An early diagnosis and treatment can savelives and limit the adverse effects of a brain hemorrhage. In this case, a deepneural network (DNN) is an effective choice for the early identification andclassification of brain hemorrhage for the timely recovery and treatment of anaffected person. In this paper, the proposed research work is divided into twonovel approaches, where, one for the classification and the other for volumecalculation of brain hemorrhage. Two different datasets are used for twodifferent techniques classification and volume. A novel algorithm is proposedto calculate the volume of hemorrhage using CT scan images. In the firstapproach, the ‘RSNA’ dataset is used to classify the brain hemorrhage typesusing transfer learning and achieved an accuracy of 93.77%. Furthermore,in the second approach, a novel algorithm has been proposed to calculate thevolume of brain hemorrhage and achieved tremendous results as 1035.91mm3and 9.25 cm3, using the PhysioNet CT scan tomography dataset.

关键词： Deep learning computed tomography magnetic resonance imaging brain hemorrhage classification volume analysis

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Reinforcing Artificial Neural Networks through Traditional Machine Learning Algorithms for Robust Classification of Cancer

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Computers, Materials & Continua 2023年第5期75卷 4293-4315页

作者： Muhammad Hammad Waseem malik Sajjad Ahmed Nadeem Ishtiaq Rasool Khan Seong-O-Shim Wajid Aziz Usman Habib Department of Computer Sciences and Information Technology University of Azad Jammu and KashmirMuzaffarabad13100Pakistan Department of Computer Science and AI College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of Computer and Network Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah23890Saudi Arabia Department of AI&DS School of ComputingNational University of Computer and Emerging SciencesIslamabad44000Pakistan

Machine Learning(ML)-based prediction and classification systems employ data and learning algorithms to forecast target ***,improving predictive accuracy is a crucial step for informed *** the healthcare domain,data are available in the form of genetic profiles and clinical characteristics to build prediction models for complex tasks like cancer detection or *** ML algorithms,Artificial Neural Networks(ANNs)are considered the most suitable framework for many classification *** network weights and the activation functions are the two crucial elements in the learning process of an *** weights affect the prediction ability and the convergence efficiency of the *** traditional settings,ANNs assign random weights to the *** research aims to develop a learning system for reliable cancer prediction by initializing more realistic weights computed using a supervised setting instead of random *** proposed learning system uses hybrid and traditional machine learning techniques such as Support Vector Machine(SVM),Linear Discriminant Analysis(LDA),Random Forest(RF),k-Nearest Neighbour(kNN),and ANN to achieve better accuracy in colon and breast cancer *** system computes the confusion matrix-based metrics for traditional and proposed *** proposed framework attains the highest accuracy of 89.24 percent using the colon cancer dataset and 72.20 percent using the breast cancer dataset,which outperforms the other *** results show that the proposed learning system has higher predictive accuracies than conventional classifiers for each dataset,overcoming previous research ***,the proposed framework is of use to predict and classify cancer patients ***,this will facilitate the effective management of cancer patients.

关键词： ANN decision support systems gene-expression data hybrid classification machine learning predictive analytics

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Plasmon resonance-enhanced graphene nanofilmbased dual-band infrared silicon photodetector

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Photonics Research 2023年第10期11卷 1657-1666页

作者： XINYU LIU SHAOXIONG WU XIAOXUE CAO FENG TIAN SRIKRISHNA CHANAKYA BODEPUDI MUHAMMAD malik CHAO GAO LI PENG HUAN HU YANG XU School of Micro-Nano Electronics ZJU-Hangzhou Global Scientific and Technological Innovation CenterState Key Laboratory of Silicon and Advanced Semiconductor MaterialsZhejiang UniversityHangzhou 310027China ZJU-UIUC Institute International CampusZhejiang UniversityHaining 314400China Department of Polymer Science and Engineering MOE Key Laboratory of Macromolecular Synthesis and FunctionalizationKey Laboratory of Adsorption and Separation Materials&Technologies of Zhejiang ProvinceZhejiang UniversityHangzhou 310027China

Graphene-based photodetectors have attracted much attention due to their unique properties,such as high-speed and wide-band detection ***,they suffer from very low external quantum efficiency in the infrared(IR)region and lack spectral ***,we construct a plasmon-enhanced macro-assembled graphene nanofilm(nMAG)based dual-band infrared silicon *** Au plasmonic nanostructures improve the absorption of long-wavelength photons with energy levels below the Schottky barrier(between metal and Si)and enhance the interface transport of *** with the strong photo-thermionic emission(PTI)effect of nMAG,the n MAG–Au–Si heterojunctions show strong dual-band detection capability with responsivities of52.9 mA/W at 1342 nm and 10.72 mA/W at 1850 nm,outperforming IR detectors without plasmonic nanostructures by 58–4562 *** synergy between plasmon–exciton resonance enhancement and the PTI effect opens a new avenue for invisible light detection.

关键词： resonance band dual

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Windows 10’s Browser Forensic Analysis for Tracing P2P Networks’Anonymous Attacks

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Computers, Materials & Continua 2022年第7期72卷 1251-1273页

作者： Saima Kauser Tauqeer Safdar malik Mohd Hilmi Hasan Emelia Akashah P.Akhir Syed Muhammad Husnain Kazmi Air University Department of Computer ScienceMultan60000Pakistan Centre for Research in Data Science Department of Computer and Information SciencesUniversiti Teknologi PETRONASSeri IskandarPerak32610Malaysia IAR Systems MästaStockholmStation Gatan 2319542Sweden

A web browser is the most basic tool for accessing the internet from any of the machines/***,data breaches have been reported frequently from users who are concerned about their personal information,as well as threats from criminal *** loss of data and information to an innocent user comes under the jurisdiction of *** kinds of cyber-attacks are far more dangerous when it comes to the many types of devices employed in an internet of things(IoT)*** surveillance of IoT devices and forensic tools are required to overcome the issues pertaining to secure data and *** to peer(P2P)applications have been utilized for criminal operations on the ***,it is a challenge for a forensic investigator to perform forensic analysis of the evolving hardware and software platforms for *** identity concealment and privacy protection,the Onion Router(Tor)and Chrome with the Invisible Internet Project(I2P)as the foundation browser are often *** is required to determine whether Tor is truly anonymous and private as they *** people,on the other hand,utilize the Tor browser for evil *** and techniques are available for the collection of artifacts,identifying problem areas,further processing and analysis of data on the computer and *** research tried to explore a few tools for the tracing of I2P activities over computer on windows 10 that reflects IoT *** to the results of this research,it leaves an excessive amount of important digital evidence on the operating system that can be exploited to attack the information of *** research is based on windows operating system and does not support other operating systems.

关键词： Cyber-security peer-to-peer invisible internet project(I2P) forensic analysis the onion router(Tor)

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Modelling of electronegative collisional warm plasma for plasma-surface interaction process

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Plasma Science and Technology 2021年第4期23卷 48-54页

作者： Rajat DHAWAN Hitendra K malik Plasma Science and Technology Laboratory Department of PhysicsIndian Institute of Technology DelhiNew Delhi—110016India

An electronegative collisional plasma having warm and massive positive ions,non-extensive distributed electrons and Boltzmann distributed negative ions is modelled for the plasma-surface interaction process that is used for the surface *** the sheath formation is evaluated through the Bohm’s criterion,which is found to be modified,and the variation of the sheath thickness and profiles of the density of plasma species and the net space charge density in the sheath region in addition to the electric *** effect of ion temperature,nonextensivity and collisional parameter is examined in greater detail considering the collisional cross-section to obey power-law dependency on the positive ion *** positive ions are found to enter in the sheath region at lower velocities in the collisional plasma compared to the case of collision-less plasma;this velocity sees minuscule reduction with increasing *** increasing ion temperature and collisional parameter lead to the formation of sheath with smaller thickness.

关键词： electronegative sheath ion temperature non-extensivity sheath thickness power-law dependency collisions

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Technologies Behind the Smart Grid and Internet of Things: A System Survey

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Computers, Materials & Continua 2023年第6期75卷 5049-5072页

作者： Kuldeep Sharma Arun malik Isha Batra A.S.M.Sanwar Hosen Md Abdul Latif Sarker Dong Seog Han Department of Computer Science and Engineering Lovely Professional UniversityPunjabIndia Department of Artificial Intelligence and Big Data Woosong UniversityDaejeon34606Korea Center for ICT&Automotive Convergence Kyungpook National UniversityDaegu41566Korea School of Electronics Engineering Kyungpook National UniversityDaegu41566Korea

Electric smart grids enable a bidirectional flow of electricity and information among power system *** proper monitoring and con-trolling of power quality,reliability,scalability and flexibility,there is a need for an environmentally friendly system that is transparent,sustainable,cost-saving,energy-efficient,agile and *** paper provides an overview of the emerging technologies behind smart grids and the internet of *** dependent variables are identified by analyzing the electricity consumption patterns for optimal utilization and planning preventive maintenance of their legacy assets like power distribution transformers with real-time parameters to ensure an uninterrupted and reliable power *** addition,the paper sorts out challenges in the traditional or legacy electricity grid,power generation,transmission,distribution,and revenue management challenges such as reduc-ing aggregate technical and commercial loss by reforming the existing manual or semi-automatic techniques to fully smart or automatic *** article represents a concise review of research works in creating components of the smart grid like smart metering infrastructure for postpaid as well as in prepaid mode,internal structure comparison of advanced metering methods in present scenarios,and communication systems.

关键词： Electricity consumption bidirectional advanced meter infrastructure energy internet of things smart grid smart meter

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