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A Novel Hybrid Architecture for Superior IoT Threat Detection through Real IoT Environments

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Computers, Materials & Continua 2024年第11期81卷 2299-2316页

作者： Bassam mohammad Elzaghmouri Yosef Hasan Fayez Jbara Said Elaiwat Nisreen Innab Ahmed Abdelgader Fadol Osman Mohammed Awad Mohammed Ataelfadiel Farah H.Zawaideh Mouiad Fadeil Alawneh Asef Al-Khateeb Marwan Abu-Zanona Department of Computer Science Faculty of Computer Science and Information TechnologyJerash UniversityJerash26150Jordan Computer Engineering Department College of Engineering&Information Technology Buraydah CollegesBuraydah51418Saudi Arabia Faculty of Architecture and Design Al-Zaytoonah University of JordanAmman11733Jordan Department of Computer Science and Information Systems College of Applied SciencesAlMaarefa UniversityDiriyahRiyadh13713Saudi Arabia Applied College King Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Business Intelligence and Data Analysis Faculty of Financial Sciences and BusinessIrbid National UniversityIrbid21110Jordan Faculty of Information Technology Ajloun National UniversityAjlun26810Jordan Department of Management Information Systems College of Business AdministrationKing Faisal UniversityAl-Ahsa31982Saudi Arabia

As the Internet of Things(IoT)continues to expand,incorporating a vast array of devices into a digital ecosystem also increases the risk of cyber threats,necessitating robust defense *** paper presents an innovative hybrid deep learning architecture that excels at detecting IoT threats in real-world *** proposed model combines Convolutional Neural Networks(CNN),Bidirectional Long Short-Term Memory(BLSTM),Gated Recurrent Units(GRU),and Attention mechanisms into a cohesive *** integrated structure aims to enhance the detection and classification of complex cyber threats while accommodating the operational constraints of diverse IoT *** evaluated our model using the RT-IoT2022 dataset,which includes various devices,standard operations,and simulated *** research’s significance lies in the comprehensive evaluation metrics,including Cohen Kappa and Matthews Correlation Coefficient(MCC),which underscore the model’s reliability and predictive *** model surpassed traditional machine learning algorithms and the state-of-the-art,achieving over 99.6%precision,recall,F1-score,False Positive Rate(FPR),Detection Time,and accuracy,effectively identifying specific threats such as Message Queuing Telemetry Transport(MQTT)Publish,Denial of Service Synchronize network packet crafting tool(DOS SYN Hping),and Network Mapper Operating System Detection(NMAP OS DETECTION).The experimental analysis reveals a significant improvement over existing detection systems,significantly enhancing IoT security *** our experimental analysis,we have demonstrated a remarkable enhancement in comparison to existing detection systems,which significantly strength-ens the security standards of *** model effectively addresses the need for advanced,dependable,and adaptable security solutions,serving as a symbol of the power of deep learning in strengthening IoT ecosystems amidst the constantly evolving cyber threat *** achievemen

关键词： A hybrid deep learning model IoT threat detection real IoT environments cybersecurity attention mechanism

Fuzzy-Weighted Similarity Measures for Memory-Based Collaborative Recommender Systems

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Journal of Intelligent Learning Systems and Applications 2014年第1期6卷 1-10页

作者： mohammad Yahya H. Al-Shamri Nagi H. Al-Ashwal mohamad.alshamri@*** nlashwal@***

Memory-based collaborative recommender system (CRS) computes the similarity between users based on their declared ratings. However, not all ratings are of the same importance to the user. The set of ratings each user weights highly differs from user to user according to his mood and taste. This is usually reflected in the user’s rating scale. Accordingly, many efforts have been done to introduce weights to the similarity measures of CRSs. This paper proposes fuzzy weightings for the most common similarity measures for memory-based CRSs. Fuzzy weighting can be considered as a learning mechanism for capturing the preferences of users for ratings. Comparing with genetic algorithm learning, fuzzy weighting is fast, effective and does not require any more space. Moreover, fuzzy weightings based on the rating deviations from the user’s mean of ratings take into account the different rating scales of different users. The experimental results show that fuzzy weightings obviously improve the CRSs performance to a good extent.

关键词： Collaborative Recommender Systems Pearson Correlation Coefficient Cosine Similarity Measure Mean Difference Weights Similarity Measure Fuzzy Weighting

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海栖热袍菌极端耐热木聚糖酶B的提纯

中国农业大学学报 2001年第6期6卷 32-37页

作者：江正强李里特林清 mohammad Mainul Ahsan 中国农业大学食品学院日本食品综合研究所酵素利用研究室

克隆并在大肠杆菌中表达的海栖热袍菌的 xyn B基因 ,其表达产物木聚糖酶 B的 C 末端带有 6×His标签 ,研究了这种基因重组酶的提纯方法。通过对粗酶提取液的热变性处理 ,Ni NTA亲和柱层析和离子柱层析 ,最终得到了电泳纯的木聚糖酶 B,... 详细信息

克隆并在大肠杆菌中表达的海栖热袍菌的 xyn B基因 ,其表达产物木聚糖酶 B的 C 末端带有 6×His标签 ,研究了这种基因重组酶的提纯方法。通过对粗酶提取液的热变性处理 ,Ni NTA亲和柱层析和离子柱层析 ,最终得到了电泳纯的木聚糖酶 B,提纯倍数 4 4.4 ,得率 11。SDS PAGE法测定木聚糖酶 B的相对分子质量为 4 2 ku,与理论推算值 4 2

关键词：海栖热袍菌耐热木聚糖酶B 热处理离子交换柱层析提纯

Demographic, Clinical and Biochemical Characteristics of Drug Naive Type 2 Diabetes Patients of Bangladesh

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Open Journal of Endocrine and Metabolic Diseases 2021年第8期11卷 145-154页

作者： Shahjada Selim Masud-Un Nabi mohammad Saifuddin mohammad Abdul Hannan Muhammed Abu Bakar Samir Kumar Talukder A. B. M. Kamrul Hasan mohammad Nurul Amin Md. Azizul Hoque Md. Shahinur Rahman Ahmed Salam Mir Faria Afsana Department of Endocrinology Bangabandhu Sheikh Mujib Medical University Dhaka Bangladesh Department of Endocrinology Rajshahi Medical College Rajshahi Bangladesh Diabetes & Endocrinology Dhaka Medical College Dhaka Bangladesh Department of Endocrinology North East Medical College & Hospital Sylhet Bangladesh Department of Endocrinology Chattogram Maa O Shishu Hospital Chattogram Bangladesh Department of Endocrinology Rangpur Medical College Rangpur Bangladesh Department of Endocrinology Mymensingh Medical College Mymensingh Bangladesh Department of Endocrinology Mugda Medical College Dhaka Bangladesh Endocrinology Shaheed Ziaur Rahman Medical College Bogura Bangladesh Department of Diabetes and Endocrinology Pabna Diabetic Association Hospital Pabna Bangladesh Department of Endocrinology Bangladesh Institute of Health Sciences Dhaka Bangladesh Department of Endocrinology BIRDEM Dhaka Bangladesh

Background: Although the frequencies of getting drug naive type 2 diabetes patients among all the diabetic patients are very low, nowadays it claims more attention in the treatment procedures of drug naive diabetic patients. But in Bangladesh, we have very few research-oriented data regarding the demographic, clinical and biochemical characteristics of drug naive type 2 diabetes patients. The aim of this study was to determine the demographic clinical and biochemical characteristics of drug naive type 2 diabetes patients of Bangladesh. Methods: This was an open label observational real-life study which was conducted in the chambers of the investigators in several places of Bangladesh as outdoor setting during the period from August 2020 to December 2020. In total, 250 patients with drug naive type 2 diabetes mellitus were enrolled as the study population. Proper written consents were taken from all the participants before starting data collection. A pre-designed questionnaire was used in patient data collection. All data were processed, analyzed and disseminated by MS Office and SPSS version as per need. Result: Two hundred and fifty (250) participants were selected as study population. The male-female ratio of the participants was 1.4:1. The highest number of participants was from 51 - 60 years’ age group (31.20%). The highest number of participants (41%) was with overweight (BMI: 25 - 30 kg/m2). Majority (65%) of the patients of this study suffered from diabetes for ≤5 years. The mean (±SD) SBP of the participants was 137.25 ± 17.50 mmHg and the mean (±SD) DBP of the participants was 85.16 ± 13.39 mmHg. We found the mean (±SD) fasting blood sugar (mg/dl), post prandial blood sugar (mg/dl), total cholesterol (mg/dl), triglycerides (mg/dl), HDL-Cholesterol (mg/dl), LDL-cholesterol (mg/dl), VLDL-cholesterol (mg/dl), uric acid (mg/dl), creatinine (mg/dl), urea (mg/dl), total bilirubin (mg/dl), direct biliru

关键词： Demographic Biochemical Clinical Characteristics Drug Naive Type 2 Diabetes Bangladesh

Simulation of Low TDS and Biological Units of Fajr Industrial Wastewater Treatment Plant Using Artificial Neural Network and Principal Component Analysis Hybrid Method

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Journal of Water Resource and Protection 2012年第6期4卷 370-376页

作者： Naser Mehrdadi Hamed Hasanlou mohammad Taghi Jafarzadeh Hamidreza Hasanlou Hamid Abdolabadi Department of Environmental Engineering Faculty of Environment University of Tehran Tehran Iran Department of Environmental Preservation National Petrochemical Company Tehran Iran Department of Environmental Science Faculty of Science Zanjan University Zanjan Iran

Being familiar with characteristics of industrial town effluents from various wastewater treatment units, which have high qualitative and quantitative variations and more uncertainties compared to urban wastewaters, plays very effective role in governing them. With regard to environmental issues, proper operation of wastewater treatment plants is of par- ticular importance that in the case of inappropriate utilization, they will cause serious problems. Processes that exist in environmental systems mostly have two major characteristics: they are dependent on many variables;and there are complex relationships between its components which make them very difficult to analyze. In order to achieve a better and efficient control over the operation of an industrial wastewater treatment plant (WWTP), powerful mathematical tool can be used that is based on recorded data from some basic parameters of wastewater during a period of treatment plant operation. In this study, the treatment plant was divided into two main subsystems including: Low TDS (Total Dissolved Solids) treatment unit and Biological unit (extended aeration). The multilayer perceptron feed forward neural network with a hidden layer and stop training method was used to predict quality parameters of the industrial effluent. Data of this study are related to the Fajr Industrial Wastewater Treatment Plant, located in Mahshahr—Iran that qualita- tive and quantitative characteristics of its units were used for training, calibration and validation of the neural model. Also, Principal Component Analysis (PCA) technique was applied to improve performance of generated models of neural networks. The results of L-TDS unit showed good accuracy of the models in estimating qualitative profile of wastewater but results of biological unit did not have sufficient accuracy to being used. This model facilitates evaluating the performance of each treatment plant units through comparing the results of prediction model with the stand

关键词： Fajr Industrial Wastewater Treatment Plant Simulation Artificial Neural Network PCA Low TDS Biological Unit

SARS-CoV-2 involvement in central nervous system tissue damage

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Neural Regeneration Research 2022年第6期17卷 1228-1239页

作者： Muhammad Ali Haidar Zaynab Shakkour mohammad Amine Reslan Nadine Al-Haj Perla Chamoun Karl Habashy Hasan Kaafarani Shima Shahjouei Sarah HFarran Abdullah Shaito Esber SSaba Bassam Badran Mirna Sabra Firas Kobeissy Maya Bizri Department of Biochemistry and Molecular Genetics Faculty of MedicineAmerican University of BeirutBeirutLebanon Faculty of Health Sciences University of BalamandBeirutLebanon Faculty of Medicine University of BalamandKouraLebanon Faculty of Science Lebanese UniversityBaabdaLebanon Program for Neurotrauma Neuroproteomics&Biomarkers ResearchDepartments of Emergency MedicineUniversity of FloridaGainesvilleFLUSA Department of Pathology and Laboratory Medicine American University of Beirut Medical CenterBeirutLebanon Biomedical Research Center Qatar UniversityDohaQatar Department of Experimental Pathology Immunology and MicrobiologyFaculty of MedicineAmerican University of BeirutBeirutLebanon Laboratory of Cancer Biology and Molecular Immunology Faculty of Sciences ILebanese UniversityHadathBeirutLebanon Faculty of Medicine Lebanese UniversityNeuroscience Research Center(NRC)BeirutLebanon Neuroscience Institute Neurology DepartmentGeisinger Health SystemPAUSA Department of Psychiatry American University of BeirutBeirutLebanon

As the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)continues to spread globally,it became evident that the SARS-CoV-2 virus infects multiple organs including the *** clinical studies revealed that patients with COVID-19 infection experience an array of neurological signs ranging in severity from headaches to life-threatening *** the exact mechanism by which the SARS-CoV-2 virus directly impacts the brain is not fully understood,several theories have been suggested including direct and indirect pathways induced by the *** possible theory is the invasion of SARS-CoV-2 to the brain occurs either through the bloodstream or via the nerve endings which is considered to be the direct *** findings are based on studies reporting the presence of viral material in the cerebrospinal fluid and brain ***,the indirect mechanisms,including blood-clotting abnormalities and prolonged activation of the immune system,can result in further tissue and organ damages seen during the course of the *** overview attempts to give a thorough insight into SARS-CoV-2 coronavirus neurological infection and highlights the possible mechanisms leading to the neurological manifestations observed in infected patients.

关键词： autoantibodies CNS infection coagulopathy COVID-19 encephalitis neuroinflammation renin-angiotensin system viral encephalopathy

Signal Transduction Pathways Mediated by Secreted and Non-Secreted Forms of Intact Insulin-Like Growth Factor Binding Protein-3 (IGFBP-3) and Its 1-97 N-Terminal Fragment in PC-3 Human Prostate Cancer Cells

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Journal of Cancer Therapy 2013年第8期4卷 1290-1297页

作者： Hanief mohammad Shahjee Benjamin Kefas Nisan Bhattacharyya Mohamed K. Radwan Department of Biochemistry and Biophysics University of Rochester Medical Center Rochester USA Diabetes Branch NIDDK National Institutes of Health Bethesda USA Division of Neuro-Oncology Neurology Department University of Virginia Health System Charlottesville USA

Our previous results indicated that both the secreted and the intracellular form of full length and 1-97 N-terminal fragment of IGFBP-3 induce apoptosis in PC-3 human prostate cancer cells in an IGF-dependent and independent manner. This study was undertaken to delineate possible down-stream signaling pathways that are involved in this process. Intact IGFBP-3 and its N-terminal 1-97 fragments with or without a signal propeptide were fused to YFP and expressed in PC-3 human prostate cancer cells. In some cases, the putative IGF-binding site was presented in full length IGFBP-3 and its N-terminal fragment was also mutated. Extent of apoptosis was quantified using FACS. Up-regulation of total Stat-1 and activation of phospho-Stat-1 were shown by western blot. TGF-β signal was measured by luciferase reporter assay. Results from inhibitor studies indicated that both the Caspase 8 and caspase 9 pathways are involved in IGFBP-3 (non-secreted form) which induced apoptosis in PC-3 cells. Exogenous addition of IGFBP-3 to PC-3 cells increased Stat-1 protein expression/tyrosine phosphorylation. Interestingly, results also showed that knockdown of Stat-1 by siRNA potentiated the IGFBP-3 induced apoptosis in PC-3 cells. In addition, both full-length IGFBP-3 and its 1-97 Nterminal fragments inhibited TGF-β signaling in these cells. This is the first report that compares the signal transduction pathways involved in apoptotic pathways mediated by IGFBP-3 in PC-3 human prostate cancer cells. Non-secreted form of full length IGFBP-3 and its N-terminal fragments induced apoptosis in PC-3 cells via activation of caspase 8 and caspase 9. Although, only non-secreted form of IGFBP-3 is involved in inducing apoptosis in PC-3 cells via caspase 8 and caspase 9 activation pathways but both secreted and non-secreted forms of IGFBP-3 are involved in modulating Stat-1 and TGF-β pathways to induce apoptotic actions in PC-3 cells. Non-secreted intact IGFBP-3 and its N-terminal fragments induced apo

关键词： N-Terminal Fragment Apoptosis Caspases Human Prostate Cancer Cells

LBP–Bilateral Based Feature Fusion for Breast Cancer Diagnosis

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Computers, Materials & Continua 2022年第11期73卷 4103-4121页

作者： Yassir Edrees Almalki Maida Khalid Sharifa Khalid Alduraibi Qudsia Yousaf Maryam Zaffar Shoayea Mohessen Almutiri Muhammad Irfan mohammad Abd Alkhalik Basha Alaa Khalid Alduraibi Abdulrahman Manaa Alamri Khalaf Alshamrani Hassan A.Alshamrani Division of Radiology Department of MedicineMedical CollegeNajran UniversityNajran 61441Saudi Arabia Department of Computer Science and Information Technology Ibadat International UniversityIslamabad44000Pakistan Department of Radiology College of MedicineQassim UniversityBuraidah 52571Saudi Arabia Department of Radiology King Fahad Specialist HospitalBuraydah 52571Saudi Arabia Electrical Engineering Department College of EngineeringNajran UniversityNajran 61441Saudi Arabia Radiology Department Human Medicine CollegeZagazig UniversityZagazig 44631Egypt Department of Surgery College of MedicineNajran UniversityNajran 61441Saudi Arabia Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran 61441Saudi Arabia

Since reporting cases of breast cancer are on the rise all over the *** in regions such as Pakistan,Saudi Arabia,and the United *** methods for the early detection and diagnosis of breast cancer are *** usual diagnosis procedures followed by physicians has been updated with modern diagnostic approaches that include computer-aided support for better *** learning based practices has increased the accuracy and efficiency of medical diagnosis,which has helped save lives of many *** is much research in the field of medical imaging diagnostics that can be applied to the variety of data such as magnetic resonance images(MRIs),mammograms,X-rays,ultrasounds,and histopathological images,but magnetic resonance(MR)and mammogram imaging have proved to present the promising *** proposed paper has presented the results of classification algorithms over Breast Cancer(BC)mammograms from a novel dataset taken from hospitals in the Qassim health cluster of Saudi *** paper has developed a novel approach called the novel spectral extraction algorithm(NSEA)that uses feature extraction and fusion by using local binary pattern(LBP)and bilateral algorithms,as well as a support vector machine(SVM)as a *** NSEA with the SVM classifier demonstrated a promising accuracy of 94%and an elapsed time of 0.68 milliseconds,which were significantly better results than those of comparative experiments from classifiers named Naïve Bayes,logistic regression,K-Nearest Neighbor(KNN),Gaussian Discriminant Analysis(GDA),AdaBoost and Extreme Learning Machine(ELM).ELM produced the comparative accuracy of 94%however has a lower elapsed time of 1.35 as compared to *** has produced a fairly well accuracy of 82%,KNN has a low accuracy of 66%.However Logistic Regression,GDA and Naïve Bayes have produced the lowest accuracies of 47%,43%and 42%.

关键词： Artificial intelligence machine learning breast cancer mammograms supervised learning classification feature fusion

Assessing preventive health behaviors from COVID-19:a cross sectional study with health belief model in Golestan Province,Northern of Iran

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Infectious Diseases of Poverty 2020年第6期9卷 91-99页

作者： Hossein Shahnazi Maryam Ahmadi-Livani Bagher Pahlavanzadeh Abdolhalim Rajabi mohammad Shoaib Hamrah Abdurrahman Charkazi Department of Health Education and Promotion School of HealthIsfahan University of Medical SciencesIsfahanIran Faculty of Health Golestan University of Medical SciencesGorganIran Department of Biostatistics School of Allied Medical SciencesShahid Beheshti University of Medical SciencesTehranIran Faculty of Health Environmental Health Research CenterGolestan University of Medical SciencesGorganIran Center for Rural Health School of Health SciencesUniversity of TasmaniaHobartAustralia Faculty of Health Environmental Health Research CenterLate Falsefi University ComplexKM 5of Gorgan-Sari RoadGolestanIran

Background: Coronavirus disease 2019(COVID-19)is a new viral disease that has caused a pandemic in the *** to the lack of vaccines and definitive treatment,preventive behaviors are the only way to overcome the ***,the present study aimed to determine the preventive behaviors from the disease based on constructs of the health belief ***:: In the present cross-sectional study during March 11–16,2020,750 individuals in Golestan Province of Iran were included in the study using the convenience sampling and they completed the questionnaires through *** scores were calculated using the confirmatory factor *** effects of different factors were separately investigated using the univariate analyses,including students sample t-test,ANOVA,and simple linear ***,the effective factors were examined by the multiple regression analysis at a significant level of 0.05 and through Mplus 7 and SPSS ***: The participants’mean age was 33.9±9.45 years;and 57.1%of them had associate and bachelor's *** regression indicated that the mean score of preventive behavior from COVID-19 was higher in females than males,and greater in urban dwellers than rural ***,one unit increase in the standard deviation of factor scores of self-efficacy and perceived benefits increased the scores of preventive behavior from COVID-19 by 0.22 and 0.17 units *** the contrary,one unit increase in the standard deviation of factor score of perceived barriers and fatalistic beliefs decreased the scores of the preventive behavior from COVID-19 by 0.36 and 0.19 units ***: Results: of the present study indicated that female gender,perceived barriers,perceived self-efficacy,fatalistic beliefs,perceived interests,and living in city had the greatest preventive behaviors from COVID-19 *** interventions were necessary among males and villagers.

关键词： COVID-19 Health belief model Fatalism Preventive behavior Iran