检索结果-内蒙古大学图书馆

26th International Computer Science and Engineering Conference, ICSEC 2022

作者： Sagulkoo, Pakorn Suratanee, Apichat Plaimas, Kitiporn Chiang Mai University Center of Biomedical Informatics Department of Family Medicine Faculty of Medicine Chiang Mai50200 Thailand King Mongkut's University of Technology North Bangkok Department of Mathematics Faculty of Applied Science Bangkok10800 Thailand Faculty of Science Chulalongkorn University Advance Virtual and Intelligent Computing Center Department of Mathematics and Computer Science Bangkok10330 Thailand

ISBN: (纸本)9781665491983

Bioinformatics and systems biology play a vital role in the computational prediction of disease-associated genes using multi-omics data. The network-based approach is one of the most potent tools in disease-associated gene prediction. The two commonly used methods are neighborhood-based and network diffusion techniques. However, there is still a lack of studies comparing the performance of these methods, especially in terms of functional pathway discovery. Thus, this study demonstrated the performance comparison of these two techniques in both numerical accuracies based on the area under the receiver operating characteristic curve (AUROC) and biological meaning efficiency based on functional pathway enrichment. In this study, we analyzed data of severe COVID-19 immune-related genes using heterogeneous data. The prediction results of the COVID-19 immune-related genes in the human protein-protein interaction (PPI) network showed that the network diffusion had better performance in both AUROC and pathway enrichment even though it provided a longer computational time than the neighborhood method. © 2022 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

RALB-HC: A resource-aware load balancer for heterogeneous cluster

RALB-HC: A resource-aware load balancer for heterogeneous cl...

引用

作者： Ahmed, Usman Aleem, Muhammad Noman Khalid, Yasir Arshad Islam, Muhammad Azhar Iqbal, Muhammad Department of Computing Mathematics and Physics Faculty of Engineering and Science Western Norway University of Applied Sciences Bergen Norway Islamabad Pakistan Department of Computer Science Capital University of Science and Technology Islamabad Pakistan SWJTU-Leeds Joint School Southwest Jiaotong University Chengdu China

In the heterogeneous computing environment, programmers map the applications either on CPUs or GPUs. However, this default mapping process does not produce improved results, particularly on the heterogeneous clusters. If one resource of the cluster is more compute capable, then most of the scheduling schemes favor that powerful device. In this scenario, the scheduling schemes overload the powerful resources while making all other compute resources remain under utilized. This load imbalance problem results in higher energy consumption and increased execution time. In this research, a novel Resource-Aware Load Balancer for the Heterogeneous Cluster (RALB-HC) is proposed that distributes workload based on resources computing capabilities and applications computing needs. The RALB-HC uses supervised machine learning approach to classify applications using the static code-features. The RALB-HC framework comprises of two phases: (1) job mapping based on the availability of the resources and (2) the resource-aware load balancing to achieve the higher resource utilization ratio. The experimental results on a large set of real-world and synthetic workloads show that the RALB-HC reduces execution time by 31.61%, increased resource utilization ratio by 67.8% and improved throughout 147.35% as compared to baseline scheduling schemes. © 2019 John Wiley & Sons, Ltd.

关键词： Scheduling

来源：评论

学校读者我要写书评

暂无评论

DeepCNN:Spectro-temporal feature representation for speech emotion recognition

引用

CAAI Transactions on Intelligence technology 2023年第2期8卷 401-417页

作者： Nasir Saleem Jiechao Gao Rizwana Irfan Ahmad Almadhor Hafiz Tayyab Rauf Yudong Zhang Seifedine Kadry Department of Electrical Engineering Faculty of Engineering and TechnologyGomal UniversityD.I.KhanPakistan Department of Computer Science University of VirginiaCharlottesvilleVirginiaUSA Department of Information Technology College of Computing and Information Technology at KhulaisUniversity of JeddahJeddahSaudi Arabia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySkaka AljoufSaudi Arabia Centre for Smart Systems AI and CybersecurityStaffordshire UniversityStoke‐on‐TrentUK School of Computing and Mathematical Sciences University of LeicesterLeicesterUK Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) Ajman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Speech emotion recognition(SER)is an important research problem in human-computer interaction *** representation and extraction of features are significant challenges in SER *** the promising results of recent studies,they generally do not leverage progressive fusion techniques for effective feature representation and increasing receptive *** mitigate this problem,this article proposes DeepCNN,which is a fusion of spectral and temporal features of emotional speech by parallelising convolutional neural networks(CNNs)and a convolution layer-based *** parallel CNNs are applied to extract the spectral features(2D-CNN)and temporal features(1D-CNN)representations.A 2D-convolution layer-based transformer module extracts spectro-temporal features and concatenates them with features from parallel *** learnt low-level concatenated features are then applied to a deep framework of convolutional blocks,which retrieves high-level feature representation and subsequently categorises the emotional states using an attention gated recurrent unit and classification *** fusion technique results in a deeper hierarchical feature representation at a lower computational cost while simultaneously expanding the filter depth and reducing the feature *** Berlin Database of Emotional Speech(EMO-BD)and Interactive Emotional Dyadic Motion Capture(IEMOCAP)datasets are used in experiments to recognise distinct speech *** efficient spectral and temporal feature representation,the proposed SER model achieves 94.2%accuracy for different emotions on the EMO-BD and 81.1%accuracy on the IEMOCAP dataset *** proposed SER system,DeepCNN,outperforms the baseline SER systems in terms of emotion recognition accuracy on the EMO-BD and IEMOCAP datasets.

关键词： decision making deep learning

来源：评论

学校读者我要写书评

暂无评论

Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

引用

Computers, Materials & Continua 2023年第2期74卷 3263-3278页

作者： Sagheer Abbas Syed Ali Raza MAKhan Muhammad Adnan Khan Atta-ur-Rahman Kiran Sultan Amir Mosavi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science GC University LahorePakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Pattern Recognition and Machine Learning LabGachon UniversitySeongnam13120Korea Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah31261Saudi Arabia John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

File labeling techniques have a long history in analyzing the anthological trends in computational *** situation becomes worse in the case of files downloaded into systems from the ***,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user ***,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic ***,one major drawback of current topic modeling approaches is better *** rely on specific language types and domain similarity of the *** this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the *** results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.

关键词： Automated file labeling file organization machine learning topic modeling

来源：评论

学校读者我要写书评

暂无评论

Comparison of Robust Estimators for Detecting Outliers in Multivariate Datasets 28

Comparison of Robust Estimators for Detecting Outliers in Mu...

引用

28th Simposium Kebangsaan Sains Matematik, SKSM 2021

作者： Mutalib, Sharifah Sakinah Syed Abd Satari, Siti Zanariah Yusoff, Wan Nur Syahidah Wan Centre for Mathematical Sciences College of Computing Applied Universiti Malaysia Pahang Lebuhraya Tun Razak Sciences Pahang Kuantan Gambang26300 Malaysia Faculty of Computer Media and Technology Management University College TATI Jalan Panchur Telok Kalong Terengganu Kemaman24000 Malaysia

Detecting outliers for multivariate data is difficult and does not work by visual inspection. Mahalanobis distance (MD) has been a classical method to detect outliers in multivariate data. However, classical mean and covariance matrix in MD suffer from masking and swamping effects. Masking effects happened when outliers are not identified and swamping effects happened when inliers are identified as outliers. Hence, robust estimators have been proposed to overcome these problems. In this study, the performance of a new robust estimator named Test on Covariance (TOC) is tested and compared with other robust estimators which are Fast Minimum Covariance Determinant (FMCD), Minimum Vector Variance (MVV), Covariance Matrix Equality (CME) and Index Set Equality (ISE). These five robust estimators' performance is being tested on five real multivariate datasets. Brain and weight, Hawkins-Bradu Kass, Stackloss, Bushfire and Milk datasets were used as these five real datasets are well-known in most outlier detection studies. Results show that TOC has proven to be able in detecting outliers, does not have a masking effect and has the same performance as other robust estimators in all datasets. © Published under licence by IOP Publishing Ltd.

关键词： Covariance matrix

来源：评论

学校读者我要写书评

暂无评论

A Stochastic Flight Problem Simulation to Minimize Cost of Refuelling

引用

Computers, Materials & Continua 2021年第10期69卷 849-871页

作者： Said Ali Hassan Khalid Alnowibet Miral H.Khodeir Prachi Agrawal Adel F.Alrasheedi Ali Wagdy Mohamed Department of Operations Research and Decision Support Faculty of Computers and Artificial IntelligenceCairo UniversityGiza12613Egypt Department of Statistics and Operations Research College of ScienceKing Saud UniversityRiyadh11451Kingdom of Saudi Arabia Department of Mathematics and Scientific Computing National Institute of Technology HamirpurHimachal Pradesh177005India Department of Operations Research Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt

Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses for airline activities.A nonlinear mixed binary mathematical programming model for the airline fuel task is presented to minimize the total cost of refueling in an entire flight route *** model is enhanced to include possible discounts in fuel prices,which are performed by adding dummy variables and some restrictive constraints,or by fitting a suitable distribution function that relates prices to purchased *** obtained fuel plan explains exactly the amounts of fuel in gallons to be purchased from each airport considering tankering strategy while minimizing the pertinent cost of the whole flight *** relation between the amount of extra burnt fuel taken through tinkering strategy and the total flight time is also considered.A case study is introduced for a certain flight rotation in domestic US air transport *** mathematical model including stepped discounted fuel prices is *** problem has a stochastic nature as the total flight time is a random variable,the stochastic nature of the problem is realistic and more appropriate than the deterministic *** stochastic style of the problem is simulated by introducing a suitable probability distribution for the flight time duration and generating enough number of runs to mimic the probabilistic real *** similar real application problems are modelled as nonlinear mixed binary ones that are difficult to handle by exact ***,metaheuristic approaches are widely used in treating such different optimization *** this paper,a gaining sharing knowledge-based procedure is used to handle the mathematical *** algorithm basically based on the process of gaining and sharing knowledge throughout the human *** generated simulation runs of

关键词： Stochastic flight problem cost of refuelling ferrying strategy tankering discounted prices simulation procedure nonlinear mixed binary model metaheuristic algorithm gaining-sharing knowledge-based algorithm

来源：评论

学校读者我要写书评

暂无评论

Is spiking logic the route to memristor-based computers?

Is spiking logic the route to memristor-based computers?

引用

2013 IEEE 20th International Conference on Electronics, Circuits, and Systems, ICECS 2013

作者： Gale, Ella De Lacy Costello, Ben Adamatzky, Andrew Unconventional Computing Centre Bristol Robotics Laboratory University of the West of England Bristol BS16 1QY United Kingdom Unconventional Computing Centre Faculty of Applied Sciences University of the West of England Bristol BS16 1QY United Kingdom Unconventional Computing Centre Computer Science and Creative Technology University of the West of England Bristol BS16 1QY United Kingdom

ISBN: (纸本)9781479924523

Memristors have been suggested as a novel route to neuromorphic computing based on the similarity between neurons (synapses and ion pumps) and memristors. The D.C. action of the memristor is a current spike, which we think will be fruitful for building memristor computers. In this paper, we introduce 4 different logical assignations to implement sequential logic in the memristor and introduce the physical rules, summation, 'bounce-back', directionality and 'diminishing returns', elucidated from our investigations. We then demonstrate how memristor sequential logic works by instantiating a NOT gate, an AND gate and a Full Adder with a single memristor. The Full Adder makes use of the memristor's memory to add three binary values together and outputs the value, the carry digit and even the order they were input in. © 2013 IEEE.

关键词： Memristors

来源：评论

学校读者我要写书评

暂无评论

Fake Twitter Followers Detection using Machine Learning Approach 2

Fake Twitter Followers Detection using Machine Learning Appr...

引用

2nd International Conference on Business Analytics for technology and Security, ICBATS 2023

作者： Zeshan Shabbir, Muhammad Naseer, Iftikhar Akhter, Shamim Abubakar, Muhammad Issa, Ghassan F. Hassaan Mehmood, Muhammad Comsats University Faculty of Information and Technology Islamabad Pakistan The Superior University Faculty of Computer Science & Information Technology Lahore Pakistan Minhaj University School of Library & Information Sciences Lahore Pakistan Fast School of Computing National University of Computer and Emerging Sciences Lahore Pakistan Skyline University College School of Information Technology University City Sharjah Sharjah1797 United Arab Emirates NCBA&E School of Computer Science Lahore Pakistan Applied Science Private Universit Applied Science Research Center Amman11937 Jordan

ISBN: (纸本)9798350335644

Fake user accounts on social media are a serious threat. Artificial intelligence can play an important role in getting rid of fake user accounts. Twitter has a problem with fake accounts that are run by automated bots. These bots are used for bad things like spamming, sabotaging trends, and getting more followers. In this research, publicly available information about Twitter users, such as their activity patterns, profile information, and tweets, to figure out how real each one is. Twitter's API and other ways of getting information will be used to get user data. The proposed model consists of a machine learning technique, and it detects whether the user accounts are real or fake. Various algorithms such as logistic regression, long short-term memory, K-mean, and random forest are applied to evaluate the proposed model. The experimental results show that the random forest algorithm has obtained the highest accuracy 0.7557, a precision of 0.7277, and F1 of 0.7943 among all other algorithms. © 2023 IEEE.

关键词： Logistic regression

来源：评论

学校读者我要写书评

暂无评论

Navigating the Newscape: Long Short-Term Memory Models for Misinformation Detection 11

Navigating the Newscape: Long Short-Term Memory Models for M...

引用

11th IEEE International Conference on Software Defined Systems, SDS 2024

作者： Tahat, Dina Alfaisal, Raghad Tahat, Khalaf Salloum, Said Al Ain University Applied Sociology Department United Arab Emirates Universiti Pendidikan Faculty of Computing and Meta-Technology Tanjung Malim Malaysia United Arab Emirates University Yarmouk University Media & Creative Industries Jordan University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798331518325

In an era where digital misinformation poses a severe challenge to societal trust, identifying fake news is imperative. This study employs a Long Short-Term Memory (LSTM) neural network to discern misinformation within a dataset of approximately 79,000 labeled news texts. Our LSTM model benefits from its aptitude for processing sequential data, crucial for understanding textual context. We evaluate our model's proficiency through accuracy, precision, recall, and F1 score, key metrics reflecting its classification capability. The model exhibits robust performance with a test accuracy of 94.09%, precision of 91.57%, recall of 95.45%, and an F1 score of 93.47%. These results underscore the potential of LSTM networks in automating fake news detection, which could significantly support the integrity of information consumption in the digital realm. © 2024 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Achieving compelling student comprehension of complex information structures for both on-site and on-line courses

Achieving compelling student comprehension of complex inform...

引用

2008 ASEE Annual Conference and Exposition

作者： Uhlig, Ronald Farahani, Alireza Viswanathan, Shekar Evans, Howard Sotelo, Mark National University Department of Computer Science and Information Systems School of Engineering and Technology National University Wireless Communications for the Master ot Science in Wireless Communications Program International Telecommunications Academy School of Engineering and Technology Department of Applied Engineering Lead Faculty for Engineering Management and Homeland Security and Safety Engineering Academic Computing for National University

Teaching engineering and technology subjects involves conveying understanding of abstract information structures and processes such as complex telecommunications protocols, complex mathematical concepts, and data structures. These are multidimensional and can be difficult to grasp quickly. Supported by a Hewlett-Packard (HP) technology for Teaching grant, the School of Engineering and technology at National University has embarked on a project to enable students to grasp these complex concepts more quickly and easily, using continuous dialog among students and instructors as the structures are first introduced and then examined from multiple perspectives through real-time interaction among students, small groups, and instructors. HP Wireless Tablet PCs are used to discuss and experiment with diagrams and processes in realtime. This allows combining lectures and problem-solving sessions into a single class session. Our hypothesis is that: 1) an in-depth learning of theory is accomplished, and 2) student engagement is enhanced. Presentation of theory by the instructor is integrated with application while the theory is still in the student's short-term memory. Students no longer have to wait for a separate session such as a recitation session to apply the concepts. This approach often takes less time. In addition to accelerating the learning process, expert instructors find this approach more rewarding as students grasp new concepts more quickly. Analysis of data captured from both students and instructors are presented to support our hypotheses, and our results are compared with similar research carried out by other universities. In addition, the level of interaction enabled by the use of HP Tablets in on-line classes is discussed. The best teaching tools available in existing on-line teaching platforms are compared with the additional tools available in on-site courses when every student has a wireless Tablet PC and specific recommendations are made to on-line teachi

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

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

请选择保存的检索档案：

请选择收藏分类：

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

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

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：