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An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl Roshanpanah Mahdi Abbasi Hani Attar ayman.amer Mohammad R.Khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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Heating-Cooling Monitoring and Power Consumption Forecasting Using LSTM for Energy-Efficient Smart Management of Buildings: A Computational Intelligence Solution for Smart Homes

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Tsinghua Science and Technology 2024年第1期29卷 143-157页

作者： Omid Akbarzadeh Sahand Hamzehei Hani Attar ayman.amer Nazanin Fasihihour Mohammad R.Khosravi Ahmed A.Solyman Department of Electronics and Telecommunications Politecnico di TorinoTurin 10129Italy Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 262799China Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNisantası UniversityIstanbul 25370The Republic of Turkiye

Energy management in smart homes is one of the most critical problems for the Quality of Life(QoL)and preserving energy *** of the relevant issues in this subject is environmental contamination,which threatens the world's *** computing-enabled Artificial Intelligence(Al)algorithms can provide impactful solutions to this *** research proposes using one of the Recurrent Neural Network(RNN)algorithms known as Long Short-Term Memory(LSTM)to comprehend how it is feasible to perform the cloud/fog/edge-enabled prediction of the building's *** parameters of power electricity,power heating,power cooling,and total power in an office/home in cold-climate cities are considered as our features in the *** on the collected data,we evaluate the LSTM approach for forecasting parameters for the next year to predict energy consumption and online monitoring of the model's performance under various *** implementing the Al predictive algorithm,several existing tools are *** results have been generated through simulations,and we find them promisingforfutureapplications.

关键词： design-builder Besos smart cities smart building neural network Long Short-Term Memory(LSTM)

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High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

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Tsinghua Science and Technology 2024年第4期29卷 1118-1137页

作者： Azam Fazel-Najafabadi Mahdi Abbasi Hani H.Attar ayman.amer Amir Taherkordi Azad Shokrollahi Mohammad R.Khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster

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Robust Malicious Executable Detection Using Host-Based Machine Learning Classifier

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Computers, Materials & Continua 2024年第4期79卷 1419-1439页

作者： Khaled Soliman Mohamed Sobh ayman M.Bahaa-Eldin Department of Computer and Systems Engineering Ain Shams UniversityCairo11517Egypt Department of Computer Engineering Technology ElSewedy University of TechnologyCairo44629Egypt

The continuous development of cyberattacks is threatening digital transformation endeavors worldwide and leadsto wide losses for various organizations. These dangers have proven that signature-based approaches are insufficientto prevent emerging and polymorphic attacks. Therefore, this paper is proposing a Robust Malicious ExecutableDetection (RMED) using Host-based Machine Learning Classifier to discover malicious Portable Executable (PE)files in hosts using Windows operating systems through collecting PE headers and applying machine learningmechanisms to detect unknown infected files. The authors have collected a novel reliable dataset containing 116,031benign files and 179,071 malware samples from diverse sources to ensure the efficiency of RMED *** most effective PE headers that can highly differentiate between benign and malware files were selected totrain the model on 15 PE features to speed up the classification process and achieve real-time detection formalicious executables. The evaluation results showed that RMED succeeded in shrinking the classification timeto 91 milliseconds for each file while reaching an accuracy of 98.42% with a false positive rate equal to 1.58. Inconclusion, this paper contributes to the field of cybersecurity by presenting a comprehensive framework thatleverages Artificial Intelligence (AI) methods to proactively detect and prevent cyber-attacks.

关键词： Portable executable malware intrusion detection cybersecurity zero-day threats Host IntrusionDetection System(HIDS) machine learning Anomaly-based Intrusion Detection System(AIDS) deep learning

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Optimal Coordination of Transportable Power Sources and Repair Crews for Service Restoration of Distribution Networks Considering Uncertainty of Traffic Congestion

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Journal of Modern Power Systems and Clean Energy 2024年第1期12卷 189-201页

作者： Zhao Shi Yan Xu Dunjian Xie Shiwei Xie amer M.Y.M.Ghias Nanyang Technological University Singapore the School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108China

This paper proposes a new method for service restoration of distribution network with the support of transportable power sources(TPSs)and repair crews(RCs).Firstly,a coupling model of distribution networks and vehicle routing of TPSs and RCs is proposed,where the TPSs serve as emergency power supply sources,and the RCs are used to repair the faulted *** the uncertainty of traffic congestion,the probability distribution of the travel time spent on each road is derived based on the Nesterov user equilibrium model,and a two-stage stochastic program is formulated to determine the optimal routings of TPSs and *** efficiently solve the proposed stochastic mixed-integer linear program(MILP),a two-phase scenario reduction method is then developed to scale down the problem size,and an adaptive progressive hedging algorithm is used for an efficient *** effectiveness of the proposed methods and algorithms has been illustrated in a modified IEEE 33-bus system.

关键词： Service restoration distribution network traffic uncertainty transportable power source repair crew stochastic program

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A Proposed Feature Selection Particle Swarm Optimization Adaptation for Intelligent Logistics--A Supply Chain Backlog Elimination Framework

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Computers, Materials & Continua 2024年第6期79卷 4081-4105页

作者： Yasser Hachaichi ayman E.Khedr Amira M.Idrees College of Computing and Information Technology at Khulais Department of Information SystemsUniversity of JeddahJeddah21959Saudi Arabia Faculty of Computers and Information Technology Future University in EgyptCairo11835Egypt

The diversity of data sources resulted in seeking effective manipulation and *** challenge that arises from the increasing dimensionality has a negative effect on the computation performance,efficiency,and stability of *** of the most successful optimization algorithms is Particle Swarm Optimization(PSO)which has proved its effectiveness in exploring the highest influencing features in the search space based on its fast convergence and the ability to utilize a small set of parameters in the search *** research proposes an effective enhancement of PSO that tackles the challenge of randomness search which directly enhances PSO *** the other hand,this research proposes a generic intelligent framework for early prediction of orders delay and eliminate orders backlogs which could be considered as an efficient potential solution for raising the supply chain *** proposed adapted algorithm has been applied to a supply chain dataset which minimized the features set from twenty-one features to ten significant *** confirm the proposed algorithm results,the updated data has been examined by eight of the well-known classification algorithms which reached a minimum accuracy percentage equal to 94.3%for random forest and a maximum of 99.0 for Naïve ***,the proposed algorithm adaptation has been compared with other proposed adaptations of PSO from the literature over different *** proposed PSO adaptation reached a higher accuracy compared with the literature ranging from 97.8 to 99.36 which also proved the advancement of the current research.

关键词： Optimization particle swarm optimization algorithm feature selection logistics supply chain management backlogs

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Cardiac arrest, stony heart, and cardiopulmonary resuscitation: An updated revisit

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World Journal of Cardiology 2024年第3期16卷 126-136页

作者： ayman El-Menyar Bianca M Wahlen Department of Trauma and Vascular Surgery Clinical ResearchHamad Medical CorporationDoha 3050Qatar Department of Clinical Medicine Weill Cornell Medical CollegeDoha 24144Qatar Department of Anesthesiology Hamad Medical CorporationDoha 3050Qatar

The post-resuscitation period is recognized as the main predictor of cardiopul-monary resuscitation(CPR)*** first description of post-resuscitation syndrome and stony heart was published over 50 years *** manifestations may include but are not limited to,persistent precipitating pathology,systemic ischemia/reperfusion response,post-cardiac arrest brain injury,and finally,post-cardiac arrest myocardial dysfunction(PAMD)after successful *** do some patients initially survive successful resuscitation,and others do not?Also,why does the myocardium response vary after resuscitation?These ques-tions have kept scientists busy for several decades since the first successful resuscitation was *** modifying the conventional modalities of resu-scitation together with new promising agents,rescuers will be able to salvage the jeopardized post-resuscitation myocardium and prevent its progression to a dismal,stony *** awareness and staff education are crucial for shortening the resuscitation time and improving short-and long-term *** of these components before and early after the restoration of circulation will enhance the resuscitation *** review extensively addresses the underlying pathophysiology,management,and outcomes of post-resuscitation *** pattern,management,and outcome of PAMD and post-cardiac arrest shock are different based on many factors,including in-hospital cardiac arrest vs out-of-hospital cardiac arrest(OHCA),witnessed vs unwitnessed cardiac arrest,the underlying cause of arrest,the duration,and protocol used for *** restoring spontaneous circulation is a vital sign,it should not be the end of the game or lone primary outcome;it calls for better understanding and aggressive multi-disciplinary interventions and *** development of stony heart post-CPR and OHCA remain the main challenges in emergency and critical care medicine.

关键词： Cardiac arrest Out-of-hospital cardiac arrest In-hospital cardiac arrest Post-resuscitation Myocardial dysfunction Cardiopulmonary resuscitation Stony heart

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Complementary and alternative medicine on cognitive defects and neuroinflammation after sepsis

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Journal of Traditional Chinese Medicine 2024年第2期44卷 408-416页

作者： LI Zhenxuan WANG Xuerui Luis Ulloa ayman Youssef BAI Yunjing XU Xiaolong LIU Qingquan Department of Infectious Diseases Beijing Hospital of Traditional Chinese MedicineCapital Medical UniversityBeijing 100010China Beijing Key Laboratory of Basic Research with Traditional Chinese Medicine on Infectious Diseases Beijing 100010China Infection immunity laboratory Beijing Institute of Traditional Chinese MedicineBeijing 100010China Clinical College of Traditional Chinese Medicine Capital Medical UniversityBeijing 100069China Center for Perioperative Organ Protection Department of AnesthesiologyDuke University Medical CenterDurhamNorth Carolina 27710USA

Sepsis-associated encephalopathy(SAE)is a common manifestation of sepsis,ranging from mild confusion and delirium to severe cognitive impairment and deep *** is associated with higher mortality and long-term outcomes,particularly substantial declines in cognitive *** mechanisms of SAE probably include neuroinflammation that is mediated by systemic inflammation and ischemic lesions in the brain,a disrupted blood–brain barrier,oxidative stress,neurotransmitter dysfunction,and severe microglial *** evidence suggests that complementary and alternative medicine,especially Traditional Chinese Medicine(TCM),is favorable in alleviating cognitive decline after ***,we summarized the studies of traditional herbal remedies,TCM formulas and acupuncture therapy in animal models of neurological dysfunctions after sepsis in recent decades and reviewed their potential mechanisms.

关键词： sepsis-associated encephalopathy cognitive dysfunction complementary therapies neuroinflammatory diseases medicine Chinese traditional review

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Efficient ECG classification based on Chi-square distance for arrhythmia detection

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Journal of Electronic Science and Technology 2024年第2期22卷 1-15页

作者： Dhiah Al-Shammary Mustafa Noaman Kadhim Ahmed M.Mahdi ayman Ibaida Khandakar Ahmedb College of Computer Science and Information Technology University of Al-QadisiyahAl Diwaniyah58001Iraq Intelligent Technology Innovation Lab Victoria UniversityMelbourne3011Australia

This study introduces a new classifier tailored to address the limitations inherent in conventional classifiers such as K-nearest neighbor(KNN),random forest(RF),decision tree(DT),and support vector machine(SVM)for arrhythmia *** proposed classifier leverages the Chi-square distance as a primary metric,providing a specialized and original approach for precise arrhythmia *** optimize feature selection and refine the classifier’s performance,particle swarm optimization(PSO)is integrated with the Chi-square distance as a fitness *** synergistic integration enhances the classifier’s capabilities,resulting in a substantial improvement in accuracy for arrhythmia *** results demonstrate the efficacy of the proposed method,achieving a noteworthy accuracy rate of 98% with PSO,higher than 89% achieved without any previous *** classifier outperforms machine learning(ML)and deep learning(DL)techniques,underscoring its reliability and superiority in the realm of arrhythmia *** promising results render it an effective method to support both academic and medical communities,offering an advanced and precise solution for arrhythmia detection in electrocardiogram(ECG)data.

关键词： Arrhythmia classification Chi-square distance Electrocardiogram(ECG)signal Particle swarm optimization(PSO)

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Unique presentation of neonatal liver failure:A case report

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World Journal of Clinical Pediatrics 2024年第2期13卷 221-226页

作者： Eman Al Atrash amer Azaz Samar Said Mohammad Miqdady Department of Pediatrics Division of Pediatric GastroenterologySheikh Khalifa Medical CityAbu Dhabi 971United Arab Emirates Department of Pathology Mayo ClinicRochesterMN 55905United States

BACKGROUND Acute fulminant liver failure rarely occurs in the neonatal *** etiologies include viral infection(15%),metabolic/genetic disease(10%),hematologic disorders(15%),and ischemic injury(5%).Gestational alloimmune liver disease usually manifests as severe neonatal liver failure,with extensive hepatic and extrahepatic iron overload,sparing the reticuloendothelial *** liver failure is a rare cause of liver failure where a patient presents with liver failure in the neonatal period with no hepatocytes in liver *** SUMMARY A 5-week-old male presented with *** examination revealed an alert but deeply icteric *** data demonstrated direct hyperbilirubinemia,a severely deranged coagulation profile,normal transaminase,and normal *** resonance imaging of the abdomen was suggestive of perinatal *** biopsy showed histiocytic infiltration with an absence of *** hemosiderin deposition was identified in a buccal mucosa *** Neonatal liver failure in the absence of hepatocellular regeneration potentially reflects an acquired or inborn defect in the regulation of hepatic regeneration.

关键词： Liver Hyperbilirubinemia Le foie vide Neonatal hemochromatosis Case report

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