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7th International Conference on information technology, InCIT 2023

作者： Deemee, Chanatip Ngampis, Kirati Noraset, Thanapon Thaipisutikul, Tipajin Sun, Min-Te Kitchat, Kotcharat Mahidol University Faculty of Information and Communication Technology Thailand National Central University Department of Computer Science and Information Engineering Taiwan

ISBN: (纸本)9798350358698

Stock market forecasting is important for financial decision-making and risk management. Among the various time series models, the Autoregressive (p) Integrated (d) Moving Average (q) (ARIMA) model has been widely adopted for its simplicity and effectiveness in capturing temporal patterns. However, selecting appropriate ARIMA orders remains a crucial and challenging task, impacting the accuracy of predictions. This paper presents a comprehensive statistical comparison of ARIMA order performance in the context of stock market forecasting. We examine the impact of different ARIMA model orders. Our study utilizes historic New York Stock Exchange (NYSE) stock price data. Our findings shed light on the complex interplay between ARIMA parameters and predictive accuracy, offering valuable insights for robust financial forecasting. © 2023 IEEE.

关键词： Financial markets

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A Data-Driven Reconstruction Technique based on Newton's Method for Emission Tomography

A Data-Driven Reconstruction Technique based on Newton's Met...

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2021 IEEE Nuclear science Symposium and Medical Imaging Conference, NSS/MIC 2021

作者： Koutsantonis, Loizos Carneiro, Tiago Kieffer, Emmanuel Pinel, Frederic Bouvry, Pascal University of Luxembourg Faculty of Science Technology and Medicine Department of Computer Science Luxembourg

ISBN: (纸本)9781665421133

In this work, we present the Deep Newton Reconstruction Network (DNR-Net), a hybrid data-driven reconstruction technique for emission tomography inspired by Newton's method, a well-known iterative optimization algorithm. The DNR-Net employs prior information about the tomographic problem provided by the projection operator while utilizing deep learning approaches to a) imitate Newton's method by approximating the Newton descent direction and b) provide data-driven regularisation. We demonstrate that DNR-Net is capable of providing high-quality image reconstructions using data from SPECT phantom simulations by applying it to reconstruct images from noisy sinograms, each one containing 24 projections. The Structural Similarity Index (SSIM) and the Contrast-to-Noise ratio (CNR) were used to quantify the image quality. We also compare our results to those obtained by the OSEM method. According to the quantitative results, the DNR-Net produces reconstructions comparable to the ones produced by OSEM while featuring higher contrast and less noise. © 2021 IEEE.

关键词： Image reconstruction

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Automatic Speech Emotion Recognition: a systematic Literature Review

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International Journal of Speech technology 2024年第1期27卷 267-285页

作者： Mustafa, Haidy H. Darwish, Nagy R. Hefny, Hesham A. Computer Science Department Faculty of Graduate Studies for Statistical Research Cairo University Giza12613 Egypt Information Systems and Technology Department Faculty of Graduate Studies for Statistical Research Cairo University Giza12613 Egypt

Automatic Speech Emotion Recognition (ASER) has recently garnered attention across various fields including artificial intelligence, pattern recognition, and human–computer interaction. However, ASER encounters numerous challenges such as a shortage of diverse datasets, appropriate feature selection, and suitable intelligent recognition techniques. To address these challenges, a systematic literature review (SLR) was conducted following established guidelines. A total of 60 primary research papers spanning from 2011 to 2023 were reviewed to investigate, interpret, and analyze the related literature by addressing five key research questions. Despite being an emerging area with applications in real-life scenarios, ASER still grapples with limitations in existing techniques. This SLR provides a comprehensive overview of existing techniques, datasets, and feature extraction tools in the ASER domain, shedding light on the weaknesses of current research studies. Additionally, it outlines a list of limitations for consideration in future work. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Speech recognition

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Application of Classification and Regression Tree and Spectral Clustering to Breast Cancer Prediction: Optimizing the Precision-Recall Trade-Off 3

Application of Classification and Regression Tree and Spectr...

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3rd IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer Engineering, MI-STA 2023

作者： Agaal, Asma Essgaer, Mansour Alshareef, Almahdi Alkhadafe, Hasan Benyahmed, Yahyia Sebha University Faculty of Sciences Department of Computer Science Sebha Libya Sebha University Faculty of Information Technology Department of Artificial Intelligence Sebha Libya Sebha University Faculty of Information Technology Department of Information Systems Sebha Libya University of Fezzan College of Education Traghen Department of Computer Science Murzuq Libya

ISBN: (纸本)9798350319897

The Receiver Operator Characteristic (ROC) test is often used to evaluate classification performance. However, it calls for special consideration when applied to the class-imbalanced data. The Precision-Recall Curve (PRC) is dependent on the class imbalance ratio. It summarizes the trade-off between the true positive rate and the positive predictive value for a predictive model using different probability thresholds. In this work, PRC is used to enhance the precision and recall of the Classification And Regression Tree (CART) algorithm to diagnose breast cancer;this enhanced the CART recall's capacity to predict wrongly classified samples by 10%, from 89% to 99%, when compared to the standard CART algorithm. On the other hand, when evaluating the performance of the improved CART on unseen data, it achieved a recall of 95%. Thus, the recall of the CART decreased by 4% from 99% to 95%. This drawback can be attributed to the small size of the training data, which has been labeled using one of the clustering methods, spectral clustering, which achieved the best Silhouette in separating data into two clustering with a score of 0.43. © 2023 IEEE.

关键词： Diseases

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Analysis and verification of dynamic stock trading systems

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information technology Journal 2008年第3期7卷 466-473页

作者： Du, Yuyue Zheng, Hong Yu, Shuxia College of Information Science and Engineering Shandong University of Science and Technology Qingdao 266510 China Department of Computer Science and Engineering East China University of Science and Technology Shanghai 200237 China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100080 China

A dynamic stock trading system with a distributed shared memory is analyzed formally based on its temporal Petri net model. The functional correctness of the system is formally verified and some important properties of the system are investigated, such as liveness, fairness, safeness and temporal properties. Finally, conclusions are found. © 2008 Asian Network for Scientific information.

关键词： Petri nets

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Making semantic annotation on patient data of depression 18

Making semantic annotation on patient data of depression

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2nd International Conference on Medical and Health Informatics, ICMHI 2018

作者： Du, Yanan Lin, Shaofu Huang, Zhisheng Faculty of Information Technology Beijing University of Technology Beijing100124 China Department of Computer Science Vrije University Amsterdam Amsterdam Netherlands

ISBN: (纸本)9781450363891

Patient data, more exactly, electronic medical records (EMR), usually contain a lot of free texts. Those unstructured medical data cannot be easily understood by computers. In addition, EMR data have a strong privacy, which hinders the sharing and use of medical data and makes it impossible to conduct more in-depth medical research. This paper presents a method of the realization of semantic EMR by making semantic annotations on free texts in medical records. We will show how to use Natural Language Processing (NLP) tools to create semantic annotation with wellknown biomedical terminologies/ontologies such as the Unified Medical Language system (UMLS). Moreover, we will describe how to make the semantic annotations on a set of virtual patient data for depression, which are generated by using the Advanced Patient Data Generator (APDG), a knowledge-based patient data generator. In short, our goal is to use semantic technology to improve the sharing and utilization of medical data and the interoperability among systems. © 2018 Association for Computing Machinery.

关键词： Data integration

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Current practices of software cost estimation technique in Malaysia context

Current practices of software cost estimation technique in M...

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International Conference on Informatics Engineering and information science, ICIEIS 2011

作者： Mansor, Zulkefli Mohd Kasirun, Zarinah Yahya, Saadiah Hj Arshad, Noor Habibah Faculty of Information Technology Industry Universiti Selangor Jalan Timur Tambahan Bestari Jaya Selangor 45600 Malaysia Department of Software Engineering Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur 50603 Malaysia Computer Technology and Networking Studies Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam Selangor 40450 Malaysia System Science Studies Faculty of Computer and Mathematical Sciences Universiti Teknologi MARA Shah Alam Selangor 40450 Malaysia

ISBN: (纸本)9783642253263

Software cost estimation process is frequently debated by software development community for decades. In order to estimate the cost, numerous methods can be used such as an expert judgment, algorithmic model or parametric, top-down approach, price-to-win, bottom-up and many more. Questionnaire and literature survey were carried out in this study. The result from the survey shows that the expert judgment method, which is based on experience and past estimation histories, is commonly use to estimate cost in software development project while the result from the literature shows that COCOMO II provides accurate result because many variables are being considered including the reuse of parameter besides the expert judgment. As a conclusion, expert judgment and algorithmic model are widely used as methods in software cost estimation process and the process was done manually. The integration of these two methods helps in producing accurate result for cost estimation process. © 2011 Springer-Verlag.

关键词： Project management

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An Image-Based Virtual Reality Prototype system

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Journal of computer science & technology 1998年第5期13卷 475-480页

作者：蔡勇王平安吴恩华刘学慧李洪举孙庆杰 Computer Science Laboratory Institute of Software Chinese Academy of Sciences Beijing P.R. China Department of Computer Science Chinese University of Hong Kong P.R. China Faculty of Science and Technology University of Macau Macau

The most important goal of virtual reality is to create a virtual world by computers where users are allowed to view the environment and control the virtual objects interactively. naditionally virtual reality systems use 3D computer graphics to model and render a virtual environment in real time. However, this approach usually requires laborious modeling and expensive special-purpose rendering hardware. Image-based rendering is a new approach in composing a virtual environment in which a set of panoramic images is used to compose the virtual environment and walking in the space is accomplished by 'hopping' to different panoramic points. This paper introduces an experimeatal image-based VR system. The techniques utilized in the system, in particular the authoring and interactive control tools of the system, are described in detail.

关键词： Virtual reality image-based rendering panoramic image

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iGrade: an automated short answer grading system 6

iGrade: an automated short answer grading system

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6th International Conference on Natural Language Processing and information Retrieval, NLPIR 2022

作者： Alhamed, Dina Hamed Alajmi, Aljawharah Mohammad Alqahtani, Tayma Abdulrahman Alali, Yasminah Hani Alnassar, Maryam Riyadh Alabbad, Dina Abdullah Department of Computer Engineering College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia Department of Computer Information Systems College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia

ISBN: (纸本)9781450397629

During the COVID-19 pandemic, most countries rely on E-Learning to apply social distance policy which affects the exams evaluation process. This project aimed to assist instructors in grading the short answer questions for CCSIT courses. By implanting a website application that the instructors could use to upload the students' answers and the ĝiGrade"software model will grade it. Moreover, the system will reduce the workload on the facilities members by saving time and effort as well as guarantee an objective grading for students. The model used in this project is a state-of-the-art BERT Neural Network model along with layers of BiLSTM that was trained using a dataset that has been collected from previous midterm and final exams of the CIS 211 course. The dataset consists of three categories which are (0, 0.5, 1) with around 1,128 instances. The "iGrade"test obtained an accuracy score of 85,4%, demonstrating BERT's superiority and independence from features during short answer grading as a default method in NLP. CCS CONCEPTS •Computing methodologies •Artificial intelligence •Natural language processing © 2022 ACM.

关键词： Grading

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AutoNotes: A Touch-Free Blink-Based Interactive Model for Generation of Notes from Lecture Videos

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Journal of The Institution of Engineers (India): Series B 2021年第6期102卷 1157-1166页

作者： Kar, Pragma Banerjee, Soumya Chakraborty, Sandip Chattopadhyay, Matangini Department of Information Technology Jadavpur University Salt Lake City Kolkata India Department of Computer Science & Engineering Indian Institute of Technology Kharagpur India School of Education Technology Jadavpur University Kolkata India

The recent explosion of interest in online courses can directly be attributed to the current pandemic which has collated to the adoption of Massive Open Online Courses. While the enforced social distancing protocol inevitably demands the involvement of technology in raising awareness, it further requires the imposition of preventive restrictions on touch-based systems. Visual gestures like simple blinks can account for a significant subset of possible actions in mobile application domains. The proposed model introduces a novel approach that facilitates the automated generation of relevant lecture notes and web-linked keywords from videos through a blink-controlled interface. Functions like auto-video pausing and auto-closing of the application based on eye attribute tracking have been integrated into the system for handling context switching. The experimental results reveal 84.17 usability score, an average of 89.55% of different types of blink detection accuracy, 91.56% of text generation accuracy and 70.41% of keyword detection accuracy along with low false positives and false negatives under different lighting conditions. © 2021, The Institution of Engineers (India).

关键词： E-learning

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