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When LoRa meets distributed machine learning to optimize the network connectivity for green and intelligent transportation system

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Green Energy and Intelligent Transportation 2024年第3期3卷 24-41页

作者： Malak Abid Ali Khan Hongbin Ma Arshad Farhad asad Mujeeb Imran Khan Mirani muhammad hamza National Key Lab of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Computer Science Namal UniversityPakistan Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Faculty of Information Technology Beijing University of TechnologyBeijing 100124China School of Mechanical Engineering Beijing Institute of TechnologyBeijing 100081China

LoRa technology contributes to green energy by enabling efficient,long-range communication for the Internet of Things(IoT).This paper addresses the challenges related to coverage range in outdoor monitoring systems utilizing LoRa,where the network performance is affected by the density of gateways(GWs)and end devices(EDs),as well as environmental *** mitigate interference,data throughput losses,and high-power consumption,the proposed spreading factor(SF)and hybrid(data rate|SF)models dynamically adjust the transmission *** orchestration of concurrent data modifications within the network server(NS)is crucial for uninterrupted communication between GWs and EDs,especially in monitoring electric vehicle(EV)stations to reduce traffic congestion and *** K-means and density-based spatial clustering of applications with noise(DBSCAN)algorithms optimizes ED allocation,averts data congestion,and improves the signal-tointerference noise ratio(SINR).These methods ensure seamless information reception by meticulously allocated EDs across various GW *** estimate the free-space losses(FSL),a log-distance path loss model(log-PL)is *** various bandwidths(BWs),bidirectional communications,and duty cycles(DCs)helps to prevent saturation,thus prolonging the operational lifespan of *** findings reveal a notable packet rejection rate(PRR)of 0%for the DBSCAN(hybrid model).In contrast,the K-means exhibits a PRR ranging from 5%(hybrid model)to 35.29%(SF model)for the ten GWs ***,the network saturation is reduced to 10.185%and 9.503%,respectively,highlighting an improvement in the average efficiency of slotted ALOHA(91.1%)and pure ALOHA(90.7%).These enhancements increase the lifespan of EDs to 15,465.27 days.

关键词： DBSCAN Green transportation Hybrid model Intelligent transportation K-means

An integrated land change modeler and distributed hydrological model approach for quantifying future urban runoff dynamics

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Science China Earth Sciences 2024年第10期67卷 3288-3301页

作者： asad Hussain muhammad Waseem muhammad Ajmal muhammad Atiq Ur Rehman Tariq muhammad Jiaqing XIAO Tao YANG Pengfei SHI Institute for Disaster Risk Management School of Geographical ScienceNanjing University of Information Science and TechnologyNanjing 210044China The National Key Laboratory of Water Disaster Prevention Hohai UniversityNanjing 210098China Yangtze Institute for Conservation and Development Hohai UniversityNanjing 210098China College of Hydrology and Water Resources Hohai UniversityNanjing 210098China Centre of Excellence in Water Resources Engineering University of Engineering and TechnologyLahore 54890Pakistan Department of Agricultural Engineering Faculty of CivilAgricultural and Mining EngineeringUniversity of Engineering and TechnologyPeshawar 25120Pakistan

Climate and land use changes have a significant impact on the runoff generation process in urban environments, and these effects could get worse in the future. The combined contributions of these changes have increased the risk of ***, there is a need for integrated modeling to better understand the runoff variability, especially in small urban catchments. To quantify and separate the effects of land-use changes and climate change on the hydrological response of urban catchments with a distributed hydrological model(Storm Water Management Model, SWMM), this study introduces a new integrated approach based on the Machine Learning based land use change modeler and climate change scenarios under *** on supervised classification and land use change model analysis, accumulated impervious area increase from 22%(in2023) to 33%(in 2060) was observed in the study area. Furthermore, integrating this projected increase in imperviousness with future climate change into SWMM by considering three different scenarios i.e., S1(Climate Change), S2(Combined Land Use and Climate Change), and S3(Land use Change) resulted that climate change could cause an increase in runoff from 13.2% to18.3% in peak runoff and the contribution of land use could range from 9.1% to 18.6%. Similarly, in response to the coupled effects of climate and land-use change, the runoff would likely change from 24.53% to 39.66%. Conclusively, the study showed that despite climate change, intensive urban development by the substitution of impervious surfaces could also have a severe impact on the microclimate and hydrology of small catchments. Lastly, this study could provide a way forward for the future planning and management of water resources in small catchments which could be extended to larger catchments.

关键词： Climate change Land-use modeling Runoff simulation Percent Imperviousness TerrSet

Modelling of debris-flow susceptibility and propagation: a case study from Northwest Himalaya

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Journal of Mountain Science 2024年第1期21卷 200-217页

作者： hamza DAUD Javed Iqbal TANOLI Sardar muhammad ASIF muhammad QASIM muhammad ALI Junaid KHAN Zahid Imran BHATTI Ishtiaq Ahmad Khan JADOON Badong National Observation and Research Station of Geohazards China University of GeosciencesWuhan 430074China Department of Earth Sciences COMSATS University IslamabadAbbottabad Campus 22010Pakistan Department of Earth Sciences Sultan Qaboos UniversityAl-KhoudMascat 123Oman Faculty of Engineering China University of Geosciences(Wuhan)Wuhan 430074China Department of Earth Sciences Abbottabad University of Science and TechnologyHavelian 22500Pakistan

The geological and geographical position of the Northwest Himalayas makes it a vulnerable area for mass movements particularly landslides and debris flows. Mass movements have had a substantial impact on the study area which is extending along Karakorum Highway(KKH) from Besham to Chilas. Intense seismicity, deep gorges, steep terrain and extreme climatic events trigger multiple mountain hazards along the KKH, among which debris flow is recognized as the most destructive geohazard. This study aims to prepare a field-based debris flow inventory map at a regional scale along a 200 km stretch from Besham to Chilas. A total of 117 debris flows were identified in the field, and subsequently, a point-based debris-flow inventory and catchment delineation were performed through Arc GIS analysis. Regional scale debris flow susceptibility and propagation maps were prepared using Weighted Overlay Method(WOM) and Flow-R technique sequentially. Predisposing factors include slope, slope aspect, elevation, Topographic Roughness Index(TRI), Topographic Wetness Index(TWI), stream buffer, distance to faults, lithology rainfall, curvature, and collapsed material layer. The dataset was randomly divided into training data(75%) and validation data(25%). Results were validated through the Receiver Operator Characteristics(ROC) curve. Results show that Area Under the Curve(AUC) using WOM model is 79.2%. Flow-R propagation of debris flow shows that the 13.15%, 22.94%, and 63.91% areas are very high, high, and low susceptible to debris flow respectively. The propagation predicated by Flow-R validates the naturally occurring debris flow propagation as observed in the field surveys. The output of this research will provide valuable input to the decision makers for the site selection, designing of the prevention system, and for the protection of current infrastructure.

关键词： North Pakistan Debris flow Flow-R Propagation Susceptibility mapping Debris-flow inventory Weighted Overlay Method

Deep Learning Based Efficient Crowd Counting System

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Computers, Materials & Continua 2024年第6期79卷 4001-4020页

作者： Waleed Khalid Al-Ghanem Emad Ul Haq Qazi muhammad hamza Faheem Syed Shah Amanullah Quadri Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh12372Saudi Arabia Centre of Excellence in Cybercrime and Digital Forensics Naif Arab University for Security SciencesRiyadh14812Saudi Arabia Center of Excellence for Information Assurance(COEIA) King Saud UniversityRiyadh12372Saudi Arabia

Estimation of crowd count is becoming crucial nowadays,as it can help in security surveillance,crowd monitoring,and management for different *** is challenging to determine the approximate crowd size from an image of the crowd’s *** in this research study,we proposed a multi-headed convolutional neural network architecture-based model for crowd counting,where we divided our proposed model into two main components:(i)the convolutional neural network,which extracts the feature across the whole image that is given to it as an input,and(ii)the multi-headed layers,which make it easier to evaluate density maps to estimate the number of people in the input image and determine their number in the *** employed the available public benchmark crowd-counting datasets UCF CC 50 and ShanghaiTech parts A and B for model training and testing to validate the model’s *** analyze the results,we used two metrics Mean Absolute Error(MAE)and Mean Square Error(MSE),and compared the results of the proposed systems with the state-of-art models of crowd *** results show the superiority of the proposed system.

关键词： Crowd counting EfficientNet multi-head attention convolutional neural network transfer learning

Retroperitoneal bronchogenic cyst:A case report and review of literature

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World Journal of Clinical Cases 2024年第15期12卷 2586-2596页

作者： Abdul Malik Qais Ahmad Naseer muhammad asad Iqbal Shi-Ya Han Sheng-Chun Dang Department of General Surgery The Affiliated Hospital of Jiangsu UniversityZhenjiang 212001Jiangsu ProvinceChina Department of Preventive Medicine and Public Health Laboratory Science School of MedicineJiangsu UniversityZhenjiang 212013Jiangsu ProvinceChina Department of Laboratory Medicine School of MedicineJiangsu UniversityZhenjiang 212013Jiangsu ProvinceChina Department of Clinical Pharmacy Shenyang Pharmaceutical UniversityShenyang 110000Liaoning ProvinceChina Department of Surgery Siyang HospitalSuqian 223700Jiangsu ProvinceChina

BACKGROUND Bronchogenic cysts are rare developmental anomalies that belong to the category of congenital enterogenous *** arise from lung buds and are present at *** embryonic foregut is their ***,they are located within the chest cavity,particularly in the cavum mediastinale of the thoracic cavity or lodged in the pulmonary parenchyma,and are considered a type of lung bud *** SUMMARY A 49-year-old male patient was admitted to the hospital due to the detection of a retroperitoneal mass during a physical *** weeks before admission,the patient underwent a physical examination and routine laboratory tests,which revealed a space-occupying mass in the retroperitoneal *** patient did not report any symptoms(such as abdominal pain,flatulence,nausea,vomiting,high fever,or chills).The computed tomography(CT)revealed a retroperitoneal spaceoccupying lesion with minimal enhancement and a CT value of approximately 36 Hounsfield *** lesion was not delineated from the boundary of the pancreatic body and was closely related to the retroperitoneum *** Following a series of tests,an abdominal mass was identified,prompting the implementation of a laparoscopic retroperitoneal mass excision *** the investigation,an 8 cm×7 cm cystic round-shaped mass with a distinct demarcation was identified in the upper posterior region of the ***,full resection of the mass was *** pathological examination reveled a cystic mass characterized by a smooth inner *** cystic mass was found to contain a white,viscous liquid within its capsule.

关键词： Bronchogenic cyst Retroperitoneal space Excision Laparoscopic surgery Case report

Predicting short-term thromboembolic risk following Roux-en-Y gastric bypass using supervised machine learning

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World Journal of Gastrointestinal Surgery 2024年第4期16卷 1097-1108页

作者： Hassam Ali Faisal Inayat Vishali Moond Ahtshamullah Chaudhry Arslan Afzal Zauraiz Anjum hamza Tahir muhammad Sajeel Anwar Dushyant Singh Dahiya muhammad Sohaib Afzal Gul Nawaz Amir H Sohail muhammad Aziz Department of Gastroenterology East Carolina University Brody School of MedicineGreenvilleNC 27834United States Department of Internal Medicine Allama Iqbal Medical CollegeLahorePunjab 54550Pakistan Department of Internal Medicine Saint Peter's University Hospital and Robert Wood Johnson Medical SchoolNew BrunswickNJ 08901United States Department of Internal Medicine St.Dominic's HospitalJacksonMS 39216United States Department of Internal Medicine Rochester General HospitalRochesterNY 14621United States Department of Internal Medicine Jefferson Einstein HospitalPhiladelphiaPA 19141United States Department of Internal Medicine UHS Wilson Medical CenterJohnsonNY 13790United States Division of Gastroenterology Hepatology and MotilityThe University of Kansas School of MedicineKansasKS 66160United States Department of Internal Medicine Louisiana State University HealthShreveportLA 71103United States Department of Surgery University of New Mexico School of MedicineAlbuquerqueNM 87106United States Department of Gastroenterology and Hepatology The University of ToledoToledoOH 43606United States

BACKGROUND Roux-en-Y gastric bypass(RYGB)is a widely recognized bariatric procedure that is particularly beneficial for patients with class III *** aids in significant weight loss and improves obesity-related medical *** its effectiveness,postoperative care still has *** evidence shows that venous thromboembolism(VTE)is a leading cause of 30-d morbidity and mortality after ***,a clear unmet need exists for a tailored risk assessment tool for VTE in RYGB *** To develop and internally validate a scoring system determining the individualized risk of 30-d VTE in patients undergoing *** Using the 2016–2021 Metabolic and Bariatric Surgery Accreditation Quality Improvement Program,data from 6526 patients(body mass index≥40 kg/m^(2))who underwent RYGB were analyzed.A backward elimination multivariate analysis identified predictors of VTE characterized by pulmonary embolism and/or deep venous thrombosis within 30 d of *** resultant risk scores were derived from the coefficients of statistically significant *** performance of the model was evaluated using receiver operating curves through 5-fold *** Of the 26 initial variables,six predictors were *** included a history of chronic obstructive pulmonary disease with a regression coefficient(Coef)of 2.54(P7%(Coef 1.19,P<0.001),venous stasis history(Coef 1.43,P<0.001),and preoperative anticoagulation use(Coef 1.24,P<0.001).These variables were weighted according to their regression coefficients in an algorithm that was generated for the model predicting 30-d VTE risk *** risk model's area under the curve(AUC)was 0.79[95%confidence interval(CI):0.63-0.81],showing good discriminatory power,achieving a sensitivity of 0.60 and a specificity of *** training,the same model performed satisfactorily

关键词： Roux-en-Y gastric bypass Venous thromboembolism Machine learning Bariatric surgery Predictive modeling

Design and Synthesis of NiO@Co_(3)O_(4)@ZSM-5 Heterogeneous Multitask Hollow Structures for Tandem Catalysis

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Chemical Research in Chinese Universities 2024年第3期40卷 529-535页

作者： muhammad Waqas Interdisciplinary Research Center for Refining and Advanced Chemicals King Fahd University of Petroleum&MineralsDhahran 31261Saudi Arabia

Precipitation and impregnation procedures unevenly distribute metals on zeolite,limiting chemical transformation in Lewis-acid,Brönsted-acid and metal-catalyzed tandem ***,heterogeneous multitask transition metals oxides@zeolites are promising catalysts for sustainable processes;nevertheless,synthesis is fascinating and ***,the construction of purposely designed multitask materials segregated in selective shells reveals the remarkable spatial organization of metals-zeolite,resulting in them being suitable for a wide range of tandem *** synthesis of multi-site catalysts begins with a universal wet chemistry approach that yields nickel oxide(NiO)***,the NiO crystals are stabilized using cationic dodecyltrimethylammonium bromide,followed by achieving cross-linking carbon growth by emulsion polymerization of glucose in hydrothermal treatment to yield uniformed NiO@carbon spheres(NiO@CSs).Next,sequential adsorption of cobalt cations and colloidal ZSM-5(1%in H_(2)O,mass fraction),followed by calcination in air,yielded NiO@cobalt oxide@zeolite denoted as NiO@Co_(3)O_(4)@ZEO hollow *** hollowing mechanism and materials segregation within shells are revealed by scanning and transmission electron microscopy,thermogravimetric analysis,and X-ray *** finding advances the rational synthesis of heterogenous core-shell hollow structures for various gas phase catalytic tandem reactions to yield valuable chemicals.

关键词： Multifunctional Core-shell hollow spheres Gas-phase reaction Valuable chemical

Enhancing PDF Malware Detection through Logistic Model Trees

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Computers, Materials & Continua 2024年第3期78卷 3645-3663页

作者： muhammad Binsawad Department of Information Systems King Abdulaziz UniversityP.O.Box 80217Jeddah21589Saudi Arabia

Malware is an ever-present and dynamic threat to networks and computer systems in cybersecurity,and because of its complexity and evasiveness,it is challenging to identify using traditional signature-based detection *** study article discusses the growing danger to cybersecurity that malware hidden in PDF files poses,highlighting the shortcomings of conventional detection techniques and the difficulties presented by adversarial *** article presents a new method that improves PDF virus detection by using document analysis and a Logistic Model *** a dataset from the Canadian Institute for Cybersecurity,a comparative analysis is carried out with well-known machine learning models,such as Credal Decision Tree,Naïve Bayes,Average One Dependency Estimator,Locally Weighted Learning,and Stochastic Gradient *** traditional structural and JavaScript-centric PDF analysis,the research makes a substantial contribution to the area by boosting precision and resilience in malware *** use of Logistic Model Tree,a thorough feature selection approach,and increased focus on PDF file attributes all contribute to the efficiency of PDF virus *** paper emphasizes Logistic Model Tree’s critical role in tackling increasing cybersecurity threats and proposes a viable answer to practical issues in the *** results reveal that the Logistic Model Tree is superior,with improved accuracy of 97.46%when compared to benchmark models,demonstrating its usefulness in addressing the ever-changing threat landscape.

关键词： Malware detection PDF files logistic model tree feature selection cybersecurity

Progress in electrocatalytic nitrate reduction for green energy:Catalyst engineering,mechanisms,and techno-economic feasibility

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Journal of Energy Chemistry 2024年第8期95卷 380-406,I0009页

作者： Hafiz muhammad Adeel Sharif Hafiz muhammad Farooq Khan Sadeeq Ullah Yuwei Wang muhammad Ahmad Bo Yang Changping Li muhammad Bilal Asif Research Center for Eco-Environmental Engineering Dongguan University of TechnologyDongguan 523808GuangdongChina College of Chemistry and Engineering Shenzhen UniversityShenzhen 518060GuangdongChina FMH College of Medicine and Dentistry LahorePakistan School of Environment and Civil Engineering Research Center for Eco-Environment EngineeringDongguan University of TechnologyDongguan 523106GuangdongChina Advanced Membranes and Porous Materials Center(AMPMC) Physical Sciences and Engineering(PSE)King Abdullah University of Science and Technology(KAUST)Thuwal 23955Saudi Arabia

Ammonia(NH_(3))is an irreplaceable chemical that has been widely demanded to keep the sustainable development of modern ***,its industrial production consumes a huge amount of energy and releases extraordinary greenhouse gases(GHGs),leading to various environmental *** the green production of ammonia is a great challenge,which has been extensively pursued in the last *** this review,the most promising strategy,electrochemical nitrate reduction reaction(e-NO_(3)RR),is comprehensively investigated to give a complete understanding of its development and mechanism and provide guidance for future ***,owing to the complex reactions and limited selectivity,a comprehensive understanding of the mechanisms is crucial to further development and ***,NO_(3)^(-)RR is a promising strategy for simultaneous water treatment and NH_(3)production.A detailed overview of the recent progress in NO_(3)^(-)RR for NH_(3)production with nontransition and transition metal based electrocatalysts is *** addition,critical advanced techniques,future challenges,and prospects are discussed to guide future research on transition metal-based catalysts for commercial NH_(3)synthesis by NO_(3)^(-)reduction.

关键词： Nitrate reduction Electrolysis Pollution to solution Transition metal catalysts Ammonia synthesis Green energy