检索结果-南通市图书馆

A Novel Energy and Communication Aware Scheduling on Green Cloud Computing

Computers, Materials & Continua 2023年第12期77卷 2791-2811页

作者： Laila Almutairi shabnam mohamed aslam Department of Computer Engineering Computer Science and Information Technology CollegeMajmaah UniversityAl Majmaah11952Saudi Arabia Department of Information Technology Computer Science and Information Technology CollegeMajmaah UniversityAl Majmaah11952Saudi Arabia

The rapid growth of service-oriented and cloud computing has created large-scale data centres worldwide.Modern data centres’operating costs mostly come from back-end cloud infrastructure and energy consumption.In cloud computing,extensive communication resources are required.Moreover,cloud applications require more bandwidth to transfer large amounts of data to satisfy end-user requirements.It is also essential that no communication source can cause congestion or bag loss owing to unnecessary switching buffers.This paper proposes a novel Energy and Communication(EC)aware scheduling(EC-scheduler)algorithm for green cloud computing,which optimizes data centre energy consumption and traffic load.The primary goal of the proposed EC-scheduler is to assign user applications to cloud data centre resources with minimal utilization of data centres.We first introduce a Multi-Objective Leader Salp Swarm(MLSS)algorithm for task sorting,which ensures traffic load balancing,and then an Emotional Artificial Neural Network(EANN)for efficient resource allocation.EC-scheduler schedules cloud user requirements to the cloud server by optimizing both energy and communication delay,which supports the lower emission of carbon dioxide by the cloud server system,enabling a green,unalloyed environment.We tested the proposed plan and existing cloud scheduling methods using the GreenCloud simulator to analyze the efficiency of optimizing data centre energy and other scheduler metrics.The EC-scheduler parameters Power Usage Effectiveness(PUE),Data Centre Energy Productivity(DCEP),Throughput,Average Execution Time(AET),Energy Consumption,and Makespan showed up to 26.738%,37.59%,50%,4.34%,34.2%,and 33.54%higher efficiency,respectively,than existing state of the art schedulers concerning number of user applications and number of user requests.

关键词： EC-scheduler green cloud energy efficiency task scheduling task sorting resource allocation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Semi/Fully-Automated Segmentation of Gastric-Polyp Using Aquila-Optimization-Algorithm Enhanced Images

引用

Computers, Materials & Continua 2022年第2期70卷 4087-4105页

作者： Venkatesan Rajinikanth shabnam mohamed aslam Seifedine Kadry Orawit Thinnukool Department of Electronics and Instrumentation Engineering St.Joseph’s College of Engineering Chennai600119India Department of Information Technology College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Faculty of Applied Computing and Technology Noroff University CollegeKristiansand4608Norway Research Group of Embedded Systems and Mobile Application in Health Science College of ArtsMedia and TechnologyChiang Mai UniversityChiang Mai50200Thailand

The incident rate of the Gastrointestinal-Disease(GD)in humans is gradually rising due to a variety of reasons and the Endoscopic/Colonoscopic-Image(EI/CI)supported evaluation of the GD is an approved practice.Extraction and evaluation of the suspicious section of the EI/CI is essential to diagnose the disease and its severity.The proposed research aims to implement a joint thresholding and segmentation framework to extract the Gastric-Polyp(GP)with better accuracy.The proposed GP detection system consist;(i)Enhancement of GP region using Aquila-Optimization-Algorithm supported tri-level thresholding with entropy(Fuzzy/Shannon/Kapur)and between-class-variance(Otsu)technique,(ii)Automated(Watershed/Markov-Random-Field)and semi-automated(Chan-Vese/Level-Set/Active-Contour)segmentation of GPfragment,and(iii)Performance evaluation and validation of the proposed scheme.The experimental investigation was performed using four benchmark EI dataset(CVC-ClinicDB,ETIS-Larib,EndoCV2020 and Kvasir).The similarity measures,such as Jaccard,Dice,accuracy,precision,sensitivity and specificity are computed to confirm the clinical significance of the proposed work.The outcome of this research confirms that the fuzzyentropy thresholding combined with Chan-Vese helps to achieve a better similarity measures compared to the alternative schemes considered in this research.

关键词： Endoscopic/colonoscopic-image gastric polyp aquila-optimizationalgorithm fuzzy entropy chan-vese segmentation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Two-Tier Clustering with Routing Protocol for IoT Assisted WSN

引用

Computers, Materials & Continua 2022年第5期71卷 3375-3392页

作者： AArokiaraj Jovith Mahantesh Mathapati M.Sundarrajan N.Gnanasankaran Seifedine Kadry Maytham N.Meqdad shabnam mohamed aslam Department of Networking and Communications College of Engineering and Technology SRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science and Engineering Rajarajeswari College of EngineeringBengaluru560074India Department of Computer Science and Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science Thiagarajar CollegeMadurai625019India Department of Applied Data Science Noroff University CollegeKristiansandNorway Al-Mustaqbal University College HillahIraq Department of Information Technology College of Computing and Information SciencesMajmaah UniversityAl Majmaah11952Saudi Arabia

In recent times,Internet of Things(IoT)has become a hot research topic and it aims at interlinking several sensor-enabled devices mainly for data gathering and tracking applications.Wireless Sensor Network(WSN)is an important component in IoT paradigm since its inception and has become the most preferred platform to deploy several smart city application areas like home automation,smart buildings,intelligent transportation,disaster management,and other such IoT-based applications.Clustering methods are widely-employed energy efficient techniques with a primary purpose i.e.,to balance the energy among sensor nodes.Clustering and routing processes are considered as Non-Polynomial(NP)hard problems whereas bio-inspired techniques have been employed for a known time to resolve such problems.The current research paper designs an Energy Efficient Two-Tier Clustering with Multi-hop Routing Protocol(EETTC-MRP)for IoT networks.The presented EETTC-MRP technique operates on different stages namely,tentative Cluster Head(CH)selection,final CH selection,and routing.In first stage of the proposed EETTC-MRP technique,a type II fuzzy logic-based tentative CH(T2FL-TCH)selection is used.Subsequently,Quantum Group Teaching Optimization Algorithm-based Final CH selection(QGTOA-FCH)technique is deployed to derive an optimum group of CHs in the network.Besides,Political Optimizer based Multihop Routing(PO-MHR)technique is also employed to derive an optimal selection of routes between CHs in the network.In order to validate the efficacy of EETTC-MRP method,a series of experiments was conducted and the outcomes were examined under distinct measures.The experimental analysis infers that the proposed EETTC-MRP technique is superior to other methods under different measures.

关键词： Wireless networks internet of things energy efficiency clustering multi-hop routing metaheuristics

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

ActivityNET:Neural networks to predict public transport trip purposes from individual smart card data and POIs

引用

Geo-Spatial Information Science 2021年第4期24卷 711-721页

作者： Nilufer Sari aslam mohamed R.Ibrahim Tao Cheng Huanfa Chen Yang Zhang SpaceTimeLab Department of CivilEnvironmental and Geomatic EngineeringUniversity College London(UCL)LondonUK Centre for Advanced Spatial Analysis(CASA) University College LondonLondonUK

Predicting trip purpose from comprehensive and continuous smart card data is beneficial for transport and city planners in investigating travel behaviors and urban mobility.Here,we propose a framework,ActivityNET,using Machine Learning(ML)algorithms to predict passengers’trip purpose from Smart Card(SC)data and Points-of-Interest(POIs)data.The feasibility of the framework is demonstrated in two phases.Phase I focuses on extracting activities from individuals’daily travel patterns from smart card data and combining them with POIs using the proposed“activity-POIs consolidation algorithm”.Phase II feeds the extracted features into an Artificial Neural Network(ANN)with multiple scenarios and predicts trip purpose under primary activities(home and work)and secondary activities(entertainment,eating,shopping,child drop-offs/pick-ups and part-time work)with high accuracy.As a case study,the proposed ActivityNET framework is applied in Greater London and illustrates a robust competence to predict trip purpose.The promising outcomes demonstrate that the cost-effective framework offers high predictive accuracy and valuable insights into transport planning.

关键词： Trip purpose prediction smart card data POIs neural networks machine learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Estimation of Standard Splenic Volume in Saudi Arabian Adult Population: Using 3D Reconstruction of Abdominal CT Scan Images

引用

Open Journal of Internal Medicine 2014年第1期4卷 7-12页

作者： Mohammad aslam Siddiqui Ali Hassan A. Ali mohamed Abdelmohsen Bedewi Omar O. Serhan Anatomy & Radiology Departments Salman bin Abdulaziz University Al-Kharj KSA Anatomy & Radiology Departments Salman bin Abdulaziz University Al-Kharj KSA Faculty of Medicine Al Azhar University Cairo Egypt King Khalid Hospital Al-Kharj KSA

Purpose: Spleen is enlarged in a variety of clinical conditions including infectious, infiltrative, immunologic and malignant states. Evaluation of splenic size is important in every physical examination of the abdomen by a physician. Determination of its size by palpation can be extremely inaccurate because spleen is never palpable till it is enlarged 2 to 3 times its own size. The accurate diagnosis of splenic enlargement is a matter of considerable importance as it is a useful guide for arriving at a diagnosis of the disease. It is therefore of utmost importance to resort to a mechanism that will give us an accurate estimation of the size of spleen. Aim of this work was to determine the normal range of spleen dimensions in average adult Saudi Arabian population and compare it with the published data. Methods: CT scans of 34 adult patients (male and female) aged between 20 - 70 years, having no splenic disorders, were collected from department of radio-diagnosis King Khalid Hospital Al-Kharj, KSA. Splenic volume was measured by two methods—by volumetric software and the prolate ellipsoid formula. Results: The average splenic volume of all subjects was 161.42 ± 54.91 cm3 with a range of 106 - 319 cm3. The average splenic volume of males was 196.95 ± 48.70 cm3 and that of female was 196.95 ± 26.97 cm3. Conclusions: These results provide normative data for evaluating patients with splenic enlargement.

关键词： Spleen 3D Reconstruction Computerized Tomography

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Evaluation of Age Related Changes in Cervical Spine in Saudi Arabian Adult Population: Using CT Scan Images

引用

Forensic Medicine and Anatomy Research 2014年第2期2卷 28-36页

作者： Ali Hassan A. Ali Mohammad aslam Siddiqui mohamed Abdelmohsen Bedewi Omar O. Serhan Anatomy & Radiology Departments Salman Bin Abdulaziz University Al-Kharj KSA King Khalid Hospital Al-Kharj KSA

Purpose: Cervical spine is considered to be the most moving part of vertebral column. It is located in a very important part of the body i.e. neck having some very important structures related to it. Any age related changes occurring in such a part of vertebral column may lead to many disorders and disabilities. Complete familiarity of this entire region anatomically as well as radiologically is therefore of utmost importance for the diagnosis and management of such disorders. Aim of this work is to evaluate the frequency of age related degeneration in cervical spine in Saudi adult asymptomatic subjects using CT scan images. Methods: In this study, 105 cases of symptomless adults ranging between 18 - 90 years of age were included. The cases were classified into 3 groups;adult group (18 - 35 years old), middle age group (36 - 55 years old) and old age group (56 - 90 years old). Their CT scans were performed in the department of radiology, King Khalid Hospital, Al Kharj and studied for any age related changes. Results: The first age group category included 35 cases;20 had normal and 15 degenerative changes. The second category included 35 cases;3 had normal and 32 degenerative changes. The third category included 35 cases. Single had normal and 34 degenerative changes. Conclusion: Asymptomatic degenerative changes are common in the cervical spine after 30 years of age in Saudi adult asymptomatic subjects.

关键词： Cervical Spine Age Changes Spondylosis CT

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：