检索结果-内蒙古大学图书馆

Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Israeli, Abraham Naaman, Aviv Makhoul, Rawaa Maduel, Guy Ejmail, Amir Jubran, Julian Karain, Dana Lisnyansky, Dina Fine, Shai Bar, Kfir The Data Science Institute Reichman University Israel Department of Software and Information System Engineering Ben-Gurion University of the Negev Israel

ISBN: (纸本)9782493814104

We introduce DiaSet, a novel dataset of dialectical Arabic speech, manually transcribed and annotated for two specific downstream tasks: sentiment analysis and named entity recognition. The dataset encapsulates the Palestine dialect, predominantly spoken in Palestine, Israel, and Jordan. Our dataset incorporates authentic conversations between YouTube influencers and their respective guests. Furthermore, we have enriched the dataset with simulated conversations initiated by inviting participants from various locales within the said regions. The participants were encouraged to engage in dialogues with our interviewer. Overall, DiaSet consists of 644.8K tokens and 23.2K annotated instances. Uniform writing standards were upheld during the transcription process. Additionally, we established baseline models by leveraging some of the pre-existing Arabic BERT language models, showcasing the potential applications and efficiencies of our dataset. We make DiaSet publicly available for further research. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Sentiment analysis

来源：评论

学校读者我要写书评

暂无评论

Generalized interface automata with multicast synchronization

引用

Frontiers of Computer Science 2015年第1期9卷 1-14页

作者： Fei HE Xiaoyu SONG Ming GU Jiaguang SUN Tsinghua National Laboratory for Information Science and Technology (TNList) Tsinghua University Beijing 100084 China Key Laboratory for Information System Security Ministry of Education Beijing 100084 China School of Software Tsinghua University Beijing 100084 China Department of Electrical & Computer Engineering Portland State University Oregon 97207 USA

Interface automata are one of the prominent formalisms for specifying interface behaviors of componentbased systems. However, only one-to-one communication is allowed in the composition of interface automata. This paper presents multicast interface automata which generalize the classic interface automata and accommodate multicast communication mechanism. The multicast interface automata endorse both bottom-up and top-down design methodologies. Theoretical results on compatibility and refinement are established for incremental design and independent implementability.

关键词： interface automata multicast communication,component interaction verification

来源：评论

学校读者我要写书评

暂无评论

Handwritten Prescription Recognition Using VGG Based Architecture with Bi-LSTM

Handwritten Prescription Recognition Using VGG Based Archite...

引用

2024 International Research Conference on Smart Computing and systems engineering, SCSE 2024

作者： Kavinda, Isuru Fernando, Harinda Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe Sri Lanka

ISBN: (纸本)9798350375688

Illegible handwriting on medical prescriptions poses a significant challenge, often leading to the misinterpretation of drug names and dosages. This issue primarily stems from doctors' use of Latin abbreviations, driven by time constraints during patient consultations. The resultant discrepancies in prescription interpretation can potentially expose patients to incorrect medications and dosages, leading to adverse effects. In response to this concern, this study proposes a novel system integrating Convolution Neural Network (CNN) and Recurrent Neural Network (RNN) models. Promising findings are reported in this study, achieving a loss of 0.4874 and an accuracy of 0.83 in the latest trial. The final model offers a potential solution to the persistent problem of illegible prescriptions, enhancing patient safety in the healthcare domain. © 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

A comparative study for Arabic text classification algorithms based on stop words elimination 11

A comparative study for Arabic text classification algorithm...

引用

Proceedings of the 2011 International Conference on Intelligent Semantic Web-Services and Applications

作者： Al-Shargabi, Bassam Al-Romimah, Waseem Olayah, Fekry Software Engineering Department Faculty of Information Technology Al-Isra University Amman Jordan Computer Information System Department Faculty of Information Technology University of Science and Technology Sana'a Yemen Management Information System Department Faculty of Administrative Science Al-Isra University Amman Jordan

ISBN: (纸本)9781450304740

This paper compares three techniques for Arabic text classification;these techniques are Support Vector Machine (SVM) with Sequential Minimal Optimization (SMO), Naïve Bayesian (NB), and J48. The main objective of this paper is to measure the accuracy for each classifier and to determine which classifier is more accurate for Arabic text classification based on stop words elimination. The accuracy for classifier is measured by Percentage split method (holdout), and K-fold cross validation methods,. The results show that the SMO classifier achieves the highest accuracy and the lowest error rate, and shows that the time needed to build the SMO model is the smallest time. © 2010 ACM.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Implementation Learning Vector Quantization Using Neural Network for Classification of Ear, Nose and Throat Disease 1

Implementation Learning Vector Quantization Using Neural Net...

引用

1st Lekantara Annual Conference on engineering and information Technology, LiTE 2021

作者： Samsir, Samsir Daulay, Nelly Khairani Harahap, Syaiful Zuhri Zalmi, Wahyuni Fithratul Sari, Afni Nia Nasution, Fitri Aini Watrianthos, Ronal Department of Informatics Engineering Universitas Al Washliyah Labuhanbatu Indonesia Department of Computer System Universitas Bina Insan Indonesia Department of Information System Universitas Labuhanbatu Indonesia Department of Information System Universitas Putra Indonesia Padang Indonesia Department of Software Engineer Universitas Dharmawangsa Medan Indonesia

This study aims to use data from 57 patients at Rantauprapat Hospital to train a Neural Network using a quantization learning vector method for the categorization of ear, nose, and throat disorders. The input factors were fever, tiredness, nausea, breathing pain, sore throat, hearing loss, allergies, chills and sweating, and thick and transparent mucus. The factors studied were ear canal infections, pharyngitis of the neck, throat, nose, and sinusitis. The findings revealed that ten neurons with an objective value of 0.01 in the learning rate range of 0.01 - 0.05 resulted in categorizing snoring, nose, and ear disorders, including the input layer. The MATLAB program is utilized in this approach, with an average accuracy of 67 per cent and a mean square error of 0.2. © Published under licence by IOP Publishing Ltd.

关键词： Mean square error

来源：评论

学校读者我要写书评

暂无评论

Creating granular learning object towards reusability of Learning Object in e-learning context

Creating granular learning object towards reusability of Lea...

引用

2011 International Conference on Electrical engineering and Informatics, ICEEI 2011

作者： Noor, Siti Fadzilah Mat Yusof, Norazah Hashim, Siti Zaiton Mohd School of Information Technology Faculty of Technology and Information Science National University of Malaysia Malaysia Software Engineering Department Faculty of Computer Science and Information System University Technology of Malaysia Malaysia

ISBN: (纸本)9781457707520

Learning Object (LO) is one of the main research topics in the e-learning community in the recent years, and most researchers pay attention to the issue of Learning Object Reusability. The most obvious motivation is the economic interest of reusing learning material instead of repeatedly authoring it. In this paper we present the process of creating granular learning object for enabling the reusing of LO in e-Learning context. Reusability requires the LO to be in a fine-grain form because raw media elements are often much easier to reuse then aggregate assemblies. In other words, as the LO size decreases (lower granularity), its potential for reuse increases. A prototype of learning objects repository that contain granular LO has been developed to show the process of granularizing LO. Each of existing LO will be extracted into granular element with the metadata and the system generated unique id for each LO based on its identifier (URL of LO) and save automatically the metadata contain in the LO. These metadata will be used for searching and retrieval process of the granule LO. © 2011 IEEE.

关键词： Metadata

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor Auto-Segmentation on Multimodal Imaging Modalities Using Deep Neural Network

引用

Computers, Materials & Continua 2022年第9期72卷 4509-4523页

作者： Elias Hossain Md.Shazzad Hossain Md.Selim Hossain Sabila Al Jannat Moontahina Huda Sameer Alsharif Osama S.Faragallah Mahmoud M.A.Eid Ahmed Nabih Zaki Rashed Department of Software Engineering Daffodil International UniversityDhaka 1207Bangladesh Department of Computing and Information System Daffodil International UniversityDhaka 1207Bangladesh Department of Computer Science&Engineering BRAC UniversityDhaka 1212Bangladesh Department of Information and Communication Engineering Bangladesh University of Professionals(BUP)Dhaka 1216Bangladesh Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Department of Electrical Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Electronics and Electrical Communications Engineering Department Faculty of Electronic EngineeringMenouf 32951Egypt

Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional MagneticResonance Image (MRI) and Computed Tomography (CT) scans utilizing3D U-Net Design and ResNet50, taken after by conventional classificationstrategies. In this inquire, the ResNet50 picked up accuracy with 98.96%, andthe 3D U-Net scored 97.99% among the different methods of deep *** is to be mentioned that traditional Convolutional Neural Network (CNN)gives 97.90% accuracy on top of the 3D MRI. In expansion, the imagefusion approach combines the multimodal images and makes a fused image toextricate more highlights from the medical images. Other than that, we haveidentified the loss function by utilizing several dice measurements approachand received Dice Result on top of a specific test case. The average mean scoreof dice coefficient and soft dice loss for three test cases was 0.0980. At thesame time, for two test cases, the sensitivity and specification were recordedto be 0.0211 and 0.5867 using patch level predictions. On the other hand,a software integration pipeline was integrated to deploy the concentratedmodel into the webserver for accessing it from the software system using theRepresentational state transfer (REST) API. Eventually, the suggested modelswere validated through the Area Under the Curve–Receiver CharacteristicOperator (AUC–ROC) curve and Confusion Matrix and compared with theexisting research articles to understand the underlying problem. ThroughComparative Analysis, we have extracted meaningful insights regarding braintumour segmentation and figured out potential gaps. Nevertheless, the proposed model can be adjustable in daily life and the healthcare domain to identify the infected regions and cancer of the brain through various imagingmodalities.

关键词： Brain cancer segmentation 3D U-Net ResNet50 Dice measurement ROC-AUC

来源：评论

学校读者我要写书评

暂无评论

Mobile and Simulation-based Approach to reduce the Dyslexia with children Learning Disabilities 10

Mobile and Simulation-based Approach to reduce the Dyslexia ...

引用

10th IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2022

作者： Muthumal, S.A.D.M. Neranga, K.T. Harshanath, S.M.B. Sandeepa, V.D.R.P. Lihinikaduwa, D.N.R. Rajapaksha, U.U.S.K. Sri Lanka Institute of Information Technology Department of Information System Engineering Malabe Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe Sri Lanka Sri Lanka Institute of Information Technology Department Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (数字)9781665401562

ISBN: (纸本)9781665401562

Learning disabilties are frequently overlooked while treating various limitations. The primary causes for such a dropout might be a lack of awareness of the risks and access to adequate medical care. Because Learning Disabilities are neurological illnesses, their etiology is unknown. Learning Disabilities do not have a therapy or a cure. Dyslexia, Dysgraphia and Dyscalculia are the most common types of Learning Dis-abilities among school children. There are numerous approaches for diagnosing and treating this ailment available today. The optimal method is to make use of a mobile application. Existing applications either do not adequately handle the problem or have minor limitations in terms of meeting genuine expectations. We can mitigate this dysfunction by utilizing mobile and simulation-based technologies. Furthermore, earlier research has not given contact and curiosity among children a significant emphasis and children have not interacted with robots. Therefore, this paper, introduces interactive and collaborative mobile appli-cation called 'Helply' with a robotic based simulation that may foster learning and help children improve and encour-age Color identification skills, Reading skills and Short-term memory skills the learning process while reducing their other dyslexic disorders. Also, NAO Robot is used to taking inputs as voice clip using voice recognition technology and images using image processing technology which embedded in NAO robot. We constructed three models for three distinct disorders and obtained accurate findings. CNN model for colour disorder had a training accuracy of 93%, FFNN model for short-term memory disorder had a training accuracy of 98%, and CNN model for reading disorder had a training accuracy of 94%. © 2022 IEEE.

关键词： Diagnosis

来源：评论

学校读者我要写书评

暂无评论

The simulation of open one-side uncertain probability for fusion model of data uncertainty and data relation uncertainty 3

The simulation of open one-side uncertain probability for fu...

引用

3rd IEEE International Conference on Big Data Analysis, ICBDA 2018

作者： Ye, Ruiqi Liao, Mingxue Cui, Tianyu Lv, Pin Science and Technology on Integrated Information System Laboratory Institute of Software CAS South No.4 street Zhongguancun Beijing China Department of Software Engineering School of Software Shandong University Jinan Shandong China

ISBN: (纸本)9781538647936

Uncertain big data has become increasingly important in our life, since uncertainties exist in data generation/acquisition, physical measurements and data staling. Thus, in this paper, we aim to create a unified mathematical model between data uncertainties and data relation uncertainties, which are both important aspects of uncertain big data. We first proposed the fusion model of data uncertainty and data relation uncertainty, which consists of data uncertainty model and data relation uncertainty model. Then we defined two fundamental forms for data uncertainty model and two fundamental forms for fusion model, which are open uncertainty, closed uncertainty and one-side uncertainty, coupling uncertainty respectively. After that we picked a part of the fusion model called open one-side uncertainty to discuss. We studied the open one-side uncertainty under both continuous distribution assumption and discrete distribution assumption, and obtained the expressions for reverse probability respectively. Last but not least, we simulated our model and acquired the averaged values of relative error and absolute error under two kinds of distribution assumption, which are around 0.5% and 0.1% respectively. Finally, we concluded that our model is correct and feasible while the simulation program is efficient as well. © 2018 IEEE.

关键词： Big data

来源：评论

学校读者我要写书评

暂无评论

K-Banhatti Sombor Invariants of Certain Computer Networks

引用

Computers, Materials & Continua 2022年第10期73卷 15-31页

作者： Khalid Hamid Muhammad Waseem Iqbal Abaid Ur Rehman Virk Muhammad Usman Ashraf Ahmed Mohammed Alghamdi Adel A.Bahaddad Khalid Ali Almarhabi Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Mathematics University of SialkotSialkot51013Pakistan Department of Computer Science GC Women UniversitySialkot53310Pakistan Department of Software Engineering College of Computer Science and EngineeringUniversity of Jeddah21493Saudi Arabia Department of Information System Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computing in Al-QunfudahUmm Al-Qura UniversityMakkah24381Saudi Arabia

Any number that can be uniquely determined by a graph is called a graph *** the last twenty years’countless mathematical graph invariants have been characterized and utilized for correlation ***,no reliable examination has been embraced to decide,how much these invariants are related with a network graph or molecular *** this paper,it will discuss three different variants of bridge networks with good potential of prediction in the field of computer science,mathematics,chemistry,pharmacy,informatics and biology in context with physical and chemical structures and networks,because k-banhatti sombor invariants are freshly presented and have numerous prediction qualities for different variants of bridge graphs or *** study solved the topology of a bridge graph/networks of three different types with two invariants KBanhatti Sombor Indices and its reduced *** deduced results can be used for the modeling of computer networks like Local area network(LAN),Metropolitan area network(MAN),and Wide area network(WAN),backbone of internet and other networks/structures of computers,power generation,bio-informatics and chemical compounds synthesis.

关键词： Bridge networks invariants k-banhatti sombor indices maple network graph molecular graph

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：