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2021 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2021

作者： Kaur, Navreet Gonzales, Manuel Alcaraz, Cristian Garcia Barnes, Laura E. Wells, Kristen J. Gong, Jiaqi Department of Engineering Systems and Environment University of Virginia VA22904 United States SDSU UC San Diego Joint Doctoral Program in Clinical Psychology San DiegoCA92120 United States Department of Psychology San Diego State University San DiegoCA92182 United States Department of Computer Science The University of Alabama TuscaloosaAL35487 United States

ISBN: (纸本)9781665403580

Long-term endocrine therapy (e.g. Tamoxifen, aromatase inhibitors) is crucial to prevent breast cancer recurrence, yet rates of adherence to these medications are low. To develop, evaluate, and sustain future interventions, individual-level modeling can be used to understand breast cancer survivors' behavioral mechanisms of medication-taking. This paper presents interdisciplinary research, wherein a model employing randomized neural networks was developed to predict breast cancer survivors' daily medication-taking behavior based on their survey data over three time periods (baseline, 4 months, 8 months). The neural network structure was guided by random utility theory developed in psychology and behavioral economics. Comparative analysis indicates that the proposed model outperforms existing computational models in terms of prediction accuracy under conditions of randomness. © 2021 IEEE

关键词： Diseases

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Estimating recombination rate distribution by optimal quantization

Estimating recombination rate distribution by optimal quanti...

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IEEE Conference on Bioinformatics

作者： M. Song S. Boissinot R.M. Haralick I.T. Phillips Department of Computer Science Queen's College Flushing NY USA Department of Biology Queen's College Flushing NY USA Doctoral Program in Computer Science Graduate CenterCity College and Graduate Center City University of New York New York NY USA

We obtain recombination rate distribution functions for all human chromosomes using an optimal quantization method. This nonparametric method allows us to control over-/under-fitting. The piece-wise constant recombination rate distribution functions are convenient to store and retrieve. Our experimental results showed more abrupt distribution functions than two recently published results. In the previous results, the over-/under-fitting issues were not addressed explicitly. Our estimation had greater log likelihood over a previous result using Parzen window. It suggests that the optimal quantization technique might be of great advantage for estimation of other genomic feature distributions.

关键词： Quantization Biological cells Distribution functions Humans computer science Educational institutions Bioinformatics Evolution (biology) Biology Genomics

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Development of mechanisms for MAC channel selection to improve the performance of IEEE 802.15.4 beacon-enabled network

Development of mechanisms for MAC channel selection to impro...

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IEEE International Conference on Broadband Network & Multimedia Technology (IC-BNMT)

作者： Chang Hsiang Ai-Wei Chen Chin-Jui Chang Bih-Yaw Shih Chen-Yuan Chen Department of Computer Science National Ping Tung University of Education Ping Tung Taiwan Department of Information Management Transworld University Yunlin Taiwan Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan

An improved mechanism called Scan First 3 Channels (SF3C) is developed to reduce the communicating frequency among devices and PAN Coordinator. The throughput and energy consumption are major performance indexes for it. Meanwhile, the beacon-enabled mode for broadcast transmissions in WPAN has higher flexibility than the non-beacon -enabled mode. In the research, a new analytic mode of the IEEE 802.15.4 beacon-enabled mode is developed to improve throughput. Furthermore, the MAC performance in the simple star topology is evaluated.

关键词： Binary phase shift keying Multiaccess communication Mobile communication Oils Microwave integrated circuits Zigbee Documentation

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Data Warehouse Design for Soil Nutrients with IoT Based Data Sources

Data Warehouse Design for Soil Nutrients with IoT Based Data...

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International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS)

作者： Abdul Rahman Ermatita Dedik Budianta Faculty of Engineering Sriwijaya University doctoral program student(lecture at AMIK MDP) Inderalaya Indonesia Faculty of Computer Science Sriwijaya University Inderalaya Indonesia Faculty of Agriculture Sriwijaya University Inderalaya Indonesia

ISBN: (纸本)9781728129310

Plant fertility is very dependent on the levels of nutrients present in the soil. Measurement of soil nutrients can be done through laboratory tests and can also be done using IoT technology. IoT equipment is supported by sensors that can be used to measure soil nutrients and the location of the soil is measured. Data from land measurements made through IoT technology can be stored and displayed in real-time through the cloud. This paper designs data sources derived from IoT -based nutrient measurement data to build data warehouse locations and soil nutrients. A data warehouse that is formed later can be done for analysis of the types of plants and fertilizers needed at a soil location.

关键词： agriculture cloud computing data handling data warehouses Internet of Things soil Data warehousing soil nutrients Internet of things data processing Cloud Computing Data sources agriculture Soil plant fertility

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Case Study of Service Oriented Enterprise Architecture Framework

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computer Technology and Application 2012年第3期3卷 240-249页

作者： Nassir Dino Awel Dico Dida Midekso Worku Alemu Software Engineering Track IT Doctoral Program Addis A baba University Addis A baba P. O. BOX 1176 Ethiopia Graduate Programme HiLCoE School of Computer Science ＆ Technology Addis Ababa P.O.BOX 33465 Ethiopia

Many organizations have now adopted Service Oriented Architecture （SOA） as an architectural style to help them with architecture, design and implementation of their core services and systems. Most of these organizations are challenged in integrating SOA style with their overall Enterprise Architecture work. This framework links an SOA style with the Enterprise Architecture （EA） methodologies to help organizations organize their SOA effort as a key part of their Enterprise Architecture. The case study demonstrates the implementation of architecture goal with organization vision in service oriented organizational structure using services that align Business with Technology. The framework is validated and has reserved the privileges of SOA and EA.

关键词： SOA （service oriented architecture） EA （enterprise architecture） service oriented enterprise （SOE） SOE strategicarchitecture SOE domain architecture SOE solution architecture SOE lifecycle service oriented enterprise architecture （SOEA）framework.

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Utilization of Linguistic Data for Learner Assessment on e-Learning: Instrument and Processing

Utilization of Linguistic Data for Learner Assessment on e-L...

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International Conference on Informatics and Computing (ICIC)

作者： Wenty Dwi Yuniarti Sri Hartati Sigit Priyanta Herman Dwi Surjono Doctoral Program of Computer Science Universitas Gadjah Mada Yogyakarta Indonesia Universitas Islam Negeri Walisongo Semarang Indonesia Department of Computer Science and Electronics Universitas Gadjah Mada Yogyakarta Indonesia Department of Informatics Engineering Education Faculty of Engineering Universitas Negeri Yogyakarta Yogyakarta Indonesia

ISBN: (纸本)9798350345728

The increasingly massive use of e-Learning illustrates the speed and need for innovation in learning. According to the National Higher Education Standards (SN-Dikti), constructive alignment is required between learning outcomes, processes, and assessments to properly implement learning in e-Learning. Assessment is an essential component of e-Learning. Unfortunately, the problem of assessment in e-Learning is still found. One of them is the limitations of e-Learning in accommodating and processing various assessment data, primarily linguistic. Even though the variety of assessment data, both numerical, linguistic, and a combination of the two, supports a comprehensive assessment. On the other hand, the accommodation of linguistic data raises problems regarding how to process of unifying linguistic data is carried out. Research related to linguistic data using computing with words has been carried out, but it still needs more precise results from the unification of the linguistic data. Therefore, this study proposes providing an assessment instrument to accommodate linguistic data in e-Learning, as well as showing how to process of unifying linguistic data is carried out using 2-Tuple Fuzzy Linguistic. This approach can avoid the loss of assessment information by presenting more informative and precise results in a 2-tuple (s, α) where $s$ indicates the ability level, and α shows a comparison of abilities with other learners and the potential of the learner to achieve higher abilities. This proposal has the potential to be applied in a learner assessment system for higher education e-Learning.

关键词： Technological innovation Electronic learning Instruments Education Linguistics Proposals Informatics

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A new estimation formula for minimum filter length of optimum FIR digital filters

A new estimation formula for minimum filter length of optimu...

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International Conference on Signal Processing Proceedings (ICSP)

作者： K. Ichige M. Iwaki R. Ishii Doctoral Program in Engineering University of Tsukuba Tsukuba Ibaraki Japan Japan Advanced Institute of Science and Technology Tatsunokuchi Ishikawa Japan Division of Electrical and Computer Engineering Yokohama National University Yokohama Japan

This paper presents an accurate estimation formula for the minimum filter length of optimum (the minimax criterion-based) FIR low-pass digital filters. The authors have proposed an accurate estimation formula for the particular case that the passband and stopband ripples are identical. Now we expand the formula for the general case. The accuracy of the proposed formula is evaluated in comparison with that of the conventional formulae. We also describe how to apply the proposed formula for the design of other types of filters.

关键词： Digital filters Finite impulse response filter Low pass filters Design optimization Algorithm design and analysis Iterative algorithms Passband Cutoff frequency Minimax techniques Iterative methods

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FINE-TUNING TRANSFER LEARNING MODEL IN WOVEN FABRIC PATTERN CLASSIFICATION

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International Journal of Innovative Computing, Information and Control 2022年第6期18卷 1885-1894页

作者： Noprisson, Handrie Ermatita, Ermatita Abdiansah, Abdiansah Ayumi, Vina Purba, Mariana Setiawan, Hadiguna Program of Doctoral Program in Engineering Universitas Sriwijaya Jalan Raya Prabumulih-Inderalaya Palembang30128 Indonesia Faculty of Computer Science Universitas Sriwijaya Jalan Raya Prabumulih-Inderalaya Palembang30128 Indonesia Department of Research and Development Stikhafi Academy Jalan Timur Indah Raya Bengkulu38225 Indonesia

It is important to figure out the patterns of woven fabrics before producing woven fabric with a machine. Recognition of woven fabric pattern usually with the help of the human eye can understand the fabric pattern. However, this manual checking takes a lot of time, money, and work, which will raise the cost of making woven fabrics. This study uses the VGG16, VGG19, MobileNet, and Inception-V3 methods to classify woven fabric patterns. It also wants to see how fine-tuning method can help algorithms be more accurate at classifying images. The research was divided into four phases, including image acquisition, image preprocessing, image classification and evaluation. A total of 978 pictures of motifs included in the research dataset. There are 351 images for the cotton class, 76 images for linen, 195 images for silk, and 356 images for wool. As the result, the highest testing accuracy was in the Inception-V3 experiment (with fine-tuning) of 72.51%, and the lowest was in the VGG19 experiment (with fine-tuning) of 52.92%. © 2022 ICIC International.

关键词： Weaving

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Integrating Noise Classification and Speech Enhancement Model for Hearing Aids 21

Integrating Noise Classification and Speech Enhancement Mode...

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21st International System-on-Chip Design Conference, ISOCC 2024

作者： Hung, Ying-Hsiu Chang, Yen-Ching Lai, Shin-Chi Juang, Wen-Ho Sheu, Ming-Hwa Lee, Jeng-Dao National Yunlin University of Science and Technology Dept. Electronics Engineering Douliu Taiwan National Formosa University Doctoral Degree Program in Smart Industry Technology Research and Development Huwei Taiwan National Formosa University Dept. Automation Engineering Smart Machinery and Intelligent Manufacturing Research Center Huwei Taiwan National Formosa University Dept. Computer Science and Information Engineering Huwei Taiwan National Formosa University Dept. Automation Engineering Huwei Taiwan

ISBN: (纸本)9798350377088

As the global population ages, the number of elderly people needing hearing aids is increasing. This paper proposed an architecture designed to enhance speech based on noise conditions. After noise types are identified by a Convolutional Neural Network (CNN) noise classification model, these noise conditions are combined with the noisy speech and input into a conditional Generative Adversarial Network (cGAN) for speech enhancement. The CNN noise classification model achieves an average recognition accuracy of nearly 92%, with a Kappa value as high as 0.88. The cGAN speech enhancement achieves lower error values in the Mel-Cepstral Distortion (MCD) measure. Although some parts of the human voice may be filtered out, the results demonstrate the potential development of the proposed algorithm. © 2024 IEEE.

关键词： Generative adversarial networks

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Expert System Research for Prostate Cancer : A Literature Review

Expert System Research for Prostate Cancer : A Literature Re...

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Networking, Electrical Engineering, computer science, and Technology (IConNECT), International Conference on

作者： Rusliyawati Rusliyawati Sutyarso Sutyarso Agus Wantoro Doctoral Program of Mathematics and Natural Science Faculty University of Lampung Bandar Lampung Indonesia Faculty of Engineering and Computer Science Universitas Teknokrat Indonesia Bandar Lampung Indonesia Faculty of Mathematics and Natural Sciences University of Lampung Bandar Lampung Indonesia

In the field of computer science, expert systems have attracted many computer scientists. In recent years, expert systems have been widely used in the medical field, particularly for diagnosing and treating various diseases, especially prostate cancer. Reality has shown that expert systems hold great promise for accurate diagnosis and treatment of prostate cancer. This research summarizes several studies related to the application of artificial intelligence in the field of prostate cancer through bibliometric analysis and explores potential future research. Articles and reviews on the application of expert systems in prostate cancer from 2015 to 2022 were selected from the PubMed, Embase, and Web of science databases. Microsoft Excel 2019 and GraphPad Prism 8 were used for target variable analysis. A total of 37 articles were selected for this research. Research on artificial intelligence in prostate cancer has grown exponentially in recent years, particularly in Indonesia. Image data usage is more predominant (62%) than numerical data types in prostate cancer research. Artificial intelligence research in prostate cancer, especially in the field of treatment cases, and the use of Deep Neural Network (DNN), Human Neural Network (HNN), Fully Convolutional Network (FCN), QT Environment for C++, Artificial Neural Network (ANN) algorithms, are highly feasible for further research.

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