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2023 International Conference on informatics, Multimedia, Cyber and Information Systems, ICIMCIS 2023

作者： Riyanto, Eko Amalia, Rifka Dwi Stmik Himsya Informatics Engineering Semarang Indonesia Universitas Pembangunan Nasional Veteran Jakarta Information Systems Faculty of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350307306

The COVID-19 pandemic (Coronavirus) is likely to be one of the most serious global problems in the last year. Countries do not have similar experiences with the spread of the virus and its impact from various fields. Estimating the number of COVID-19 cases in the past can help in decision-making about action and plan for virus prevention. The study aims to provide accurate predictive model in predicting confirmed cases of COVID-19 in Semarang city. In predicting the number of people exposed to Covid-19 positive need to be accurate and accurate methods, in some previous studies the two methods most recommended are neural network and LSTM (Long Short Term Memory) which have high levels of accuracy. Based on research that has been carried out that the results of accurate prediction comparison between RNN and LSTM obtain the smallest MSE result is the method. © 2023 IEEE.

关键词： Forecasting

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Creating Robust and Secure Decentralized Autonomous Organizations (DAOs) for the Metaverse Using Blockchain Technology 6th

Creating Robust and Secure Decentralized Autonomous Organiza...

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6th International Conference on Recent Innovations in Computing, ICRIC 2023

作者： Goyal, S.B. Rajawat, Anand Singh Shaari, Rosnizah Bt Verma, Chaman Singh, Pradeep Kumar City University Petaling Jaya Malaysia School of Computer Sciences and Engineering Sandip University Nashik India City University Petaling Jaya46100 Malaysia Department of Media and Educational Informatics Faculty of Informatics Eötvös Loránd University Budapest1053 Hungary Department of Computer Science and Engineering Central University of Jammu Jammu India

ISBN: (纸本)9789819778614

This paper presents an all-encompassing exploration on the conception and implementation of sturdy and impregnable decentralized autonomous organizations (DAOs) custom-made for the Metaverse, capitalizing on the capabilities of blockchain technology. The Metaverse, an incorporation of virtual shared space, is evolving at a rapid pace, necessitating governance structures that are decentralized, transparent, efficient, and impervious to points of failure. DAOs, governed by smart contracts and consensus mechanisms, offer a promising resolution to this exigency. To commence by scrutinizing the distinctive prerequisites of the Metaverse milieu, encompassing scalability, interoperability, and user involvement. Subsequently, we delve into the framework of DAOs, accentuating blockchain’s essential role in ensuring security, transparency, and decentralized governance. Our approach involves a stratified method to DAO design, amalgamating blockchain’s immutable ledger, smart contract functionality, and advanced cryptographic techniques to safeguard against potential hazards and susceptibilities that are specific to the Metaverse. To propose innovative mechanisms for decentralized decision-making, asset management, and dispute resolution within DAOs, ensuring consonance with the dynamic and engrossing essence of the Metaverse. Moreover, to tackle the obstacles of incorporating DAOs with existing Metaverse platforms, with a focus on interoperability between distinct blockchain protocols and virtual domains. Our proposed model encompasses a collection of exemplary practices for DAO deployment in the Metaverse, ensuring adaptability and resilience. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Smart contract

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Data Driven Methods to Predict Vertical Profiles of the Rails: A Case Study 10

Data Driven Methods to Predict Vertical Profiles of the Rail...

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10th International Conference on ICT for Smart Society, ICISS 2023

作者： Nugraha, Ade Chandra Supangkat, Suhono Harso Nugraha, Igb Baskara Handoko, Yunendar Aryo Purwadinata, Awan Hermawan Saputro, Dimas Wisnu Bandung State of Polytechnic School of Electrical Engineering and Informatics Bandung Institute of Technology Department of Computer Engineering and Informatics Bandung Indonesia School of Electrical Engineering and Informatics Bandung Institute of Technology Smart City and Community Innovation Center Bandung Indonesia Bandung Institute of Technology Faculty of Mechanical and Aerospace Engineering Bandung Indonesia PT Kereta Api Indonesia Managing Director of Infrastructure Bandung Indonesia Bandung State of Polytechnic Department of Computer Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350339543

Predicting the value of railroad track geometry is needed to reduce the cost and time of rail condition measurements that have been carried out periodically every three months by railroad operators in Indonesia (PT Kereta Api Indonesia/PT KAI). Four track geometry parameters - vertical profile, horizontal alignment, twist, and gauge - are the reference measurements that will be mapped with alternative measurement results using accelerometers installed on regular trains (in-service trains). In this paper, eight prediction algorithms from the machine learning model are applied to map the vertical profile with 73 kilometers of measurement data in the Jakarta to Padalarang railroad segment, precisely on the Jatinegara-Cikampek measuring trip conducted from April 2019 to June 2022. The evaluation performance of the prediction results has been measured with the GadientBoosting Regressor algorithm is the best algorithm with MSE = 0.791, R2 = 0.507 and feature importance on the Train speed and Az attributes. The research can be continued to detect the correlation of three other track geometry parameters referring to the dataset of rail geometry condition measurement results through accelerometers on regular trains (in-service trains). © 2023 IEEE.

关键词： Forecasting

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The Correlation Between Architecture Smells, Package Stability and Reusability: A Case Study 4

The Correlation Between Architecture Smells, Package Stabili...

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4th IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2024

作者： Benidris, Mrwan Elfallah, Ehab A. Omar Cheema, Marwa Aslam Alsma, Mohammed Salah Addin Kadiki, Tareq Ziad Elbarsha, Abdelfattah University of Benghazi Faculty of Information Technology Dep. of Computer Science Libya Libyan International Medical University Faculty of Information Technology Dept. of Software Engineering Libya University of Benghazi Faculty of Public Health Health Informatics Department Libya

ISBN: (纸本)9798350372632

the design decisions made in the architecture of a software system are essential to its maintainability, and thus its quality is of great importance. Architecture smells (ASs) can be used to identify any quality issues within the system. To further explore the relationships between ASs, stability, and reusability, Spearman correlation coefficients will be calculated. This paper seeks to examine the connection between architecture smells, software stability, and reusability. To do this, we utilized a dataset created by other researchers and conducted an empirical study of the associations between five types of architecture smells and software stability and reusability. This research is necessary as there is a lack of in-depth research on architecture smells and their relationship to software stability and reusability. We found a relationship between the presence of Feature Concentration in package and the stability and reusability of the package. Also, package's stability is affected by both Cyclic Dependency and Unstable Dependency. A slight positive correlation has been found between God Class and stability, as well as a very weak negative correlation between Unstable Dependency and reusability. Finally, we found a slight negative correlation between package stability and reusability. © 2024 IEEE.

关键词： Reusability

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An automated speech analysis system for the detection of cognitive decline in elderly

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International Journal of Speech Technology 2023年第2期26卷 337-353页

作者： Loizou, Christos P. Pantzaris, Marios Faculty of Engineering & Technology Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology 30 Arch. Kyprianos Str. Office 420 Limassol3036 Cyprus Cyprus Institute of Neurology and Genetics P. O. Box 23462 Nicosia1683 Cyprus

The goal of this study is to develop and test an automated integrated speech analysis system for detecting mild cognitive impairment (MCI) and dementia in spontaneous free speech. During the years 2010–2016, speech recordings (N = 2800) were obtained from 200 Greek Cypriots over the age of 65. These were divided into three groups (G1, G2, and G3) based on the results of their Mini-mental state examination (MMSE): G1:95 normal (NOR) individuals with an MMSE greater than 26;G2:65 MCI subjects with 20 ≤ MMSE ≤ 26;G3:40 dementia subjects with 0 ≤ MMSE © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Neurodegenerative diseases

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The Effect of Preprocessing on Skin Lesion Segmentation 8

The Effect of Preprocessing on Skin Lesion Segmentation

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8th International Conference on Information Technology, InCIT 2024

作者： Nugroho, Arief Kelik Afiahayati Wibowo, Moh Edi Soebono, Hardyanto Universitas Gadjah Mada Faculty of Mathematics and Natural Science Department of Computer Science and Electronics Yogyakarta Indonesia Universitas Jenderal Soedirman Faculty of Engineering Department of Informatics Engineering Purwokerto Indonesia Public Health and Nursing Universitas Gadjah Mada Faculty of Medicine Department of Dermatology and Venereology Yogyakarta Indonesia

ISBN: (纸本)9798350366303

Image preprocessing is a crucial step in enhancing the quality of skin lesion images before segmentation, with the primary objective of removing noise and artifacts that could interfere with the segmentation process and reduce accuracy. This process involves various techniques designed to address artifacts such as hair, black frames, skin lines, and vignettes, which may arise due to variables in image acquisition, such as lighting conditions and skin characteristics. Several preprocessing techniques used include artifact removal using Gaussian filter, bottom hat filter, and median filter, as well as hair removal methods like DullRazor and short line detector. Image augmentation techniques, such as rotation and transformation, are also employed to ensure that key features in the image are well preserved and accurately reflected in the data, helping to prevent overfitting during the classification stage. Additionally, contrast enhancement through methods like Contrast-Limited Adaptive Histogram Equalization (CLAHE) and gamma correction is used to improve lesion visibility and enhance the accuracy of lesion boundary detection. Findings from various studies indicate that appropriate preprocessing can significantly improve image quality, leading to more accurate segmentation. Descriptive statistical testing can be employed to analyze the extent to which these preprocessing steps affect segmentation outcomes, focusing on accuracy improvements and the reduction of segmentation errors caused by artifacts and noise in the images. Thus, effective preprocessing not only enhances image quality but also provides a stronger foundation for more accurate segmentation and classification in skin lesion diagnosis. © 2024 IEEE.

关键词： Median filters

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Recognition of Colon Neoplasm using Contrast-Aware Capsule Network 9

Recognition of Colon Neoplasm using Contrast-Aware Capsule N...

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9th IEEE International Conference on Adaptive Science and Technology, ICAST 2024

作者： Yeboah, Mavis Serwaa Kwabena Mensah, Patrick Adekoya, Adebayo Felix Abra Ayidzoe, Mighty University of Energy and Natural Resources Department of Computer Science and Informatics Sunyani Ghana Sunyani Technical University Department of Computer Science Sunyani Ghana Catholic University of Ghana Faculty of Computing Engineering and Mathematical Sciences Sunyani Ghana

ISBN: (纸本)9798350385403

Colon neoplasms are the second leading cause of mortality worldwide, and despite advances in endoscopy, even experienced endoscopists miss 22-28% of cases. Intelligent systems can bridge this gap, but current approaches face significant challenges. For instance, Convolutional Neural Networks (CNNs) excel in image recognition but require large datasets, which are often scarce in healthcare. On the other hand, Capsule Networks, suitable for smaller datasets, struggle with complex images. To address these limitations, we propose a novel contrast-aware Capsule Network for colon neoplasm recognition. By incorporating a novel contrast-aware feature transformation algorithm, our proposed model enhances extracted features and focuses on processing relevant features, achieving remarkable recognition accuracies of 96.70%, 93.68%, and 99.99% on PolyGen, ETIS-Larib, and CVC-ClinicDB datasets, respectively. Our approach outperforms state-of-the-art Capsule Network algorithms and offers a promising solution to support endoscopists in accurate colon neoplasm detection, reducing the burden of image analysis and improving patient outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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Blockchain-based Internet of Musical Things

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Blockchain(Research and Applications) 2022年第3期3卷 60-69页

作者： Luca Turchet Chan Nam Ngo Department of Information Engineering and Computer Science University of TrentoTrento38122Italy Faculty of Mathematics Informaticsand Mechanics of the University of WarsawWarsaw00-927Poland

Blockchain technology is impacting several industries,including the creative industries and those operating in the Internet of Things(IoT).Lately,researchers'attention has been devoted to the application of blockchain in the recorded music ***,thus far,no research has investigated the use of such technology in the Internet of Musical Things(IoMusT).The IoMusT is a new area emerging in industry and academy as an extension of the IoT to the musical *** IoMusT itself,as the IoT,is a distributed network of musical things,which are objects augmented with information and communication technologies serving a musical *** IoMusT vision requires,above all,IoT features such as decentralization,seamless authentication,transparency,data integrity and privacy,and self-maintenance,as well as the musical domain features such as efficient handling of copyrights and speed of royalties *** features can be brought by *** this paper,we investigate the integration of blockchain technology with the IoMusT,and we name such synthesis“Blockchain-based IoMusT”.We present a vision for this new paradigm in terms of the novel opportunities that are enabled,and we propose a set of application scenarios enabled by technological ***,we outline the open research directions in this promising area.

关键词： Internet of Musical Things Blockchain Music industry Privacy Security Internet of Things

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Evaluation of the security of password-protected encrypted RAR3 and RAR5 archives

Evaluation of the security of password-protected encrypted R...

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2022 International Conference on Networks, Communications and Information Technology, NCIT 2022

作者： Krupalija, Ehlimana Mrdović, Saša Cogo, Emir Prazina, Irfan Bećirović, Šeila Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (纸本)9783800760190

Roshal Archive (RAR) format is one of the most widely used data archive formats, enabling users to reduce the size of data and protect it with the desired password before the data is transferred to its intended recipients over the network. This work focuses on the security of encrypted RAR archives and various different approaches for their decryption. Two different datasets composed of randomly generated and real-world user passwords were used for deploying brute force and dictionary attacks on password-protected RAR archives. Two available and widely used tools, John the Ripper and Hashcat, were used for cracking passwords of encrypted RAR3 and RAR5 archives. Experimental results indicate that both brute force and dictionary attacks were unsuccessful for RAR archives protected with randomly generated passwords, even of very small length. Real-world user passwords were successfully cracked only partially by brute force attacks, whereas dictionary attacks were very successful. The success rate for RAR5 archives was only slightly lower than for RAR3 archives and processing times were similar, indicating that this new version of the RAR format does not significantly improve data security. Instead, the security of RAR archives can be increased by using longer passwords more similar to randomly generated data, which are not present in commonly used dictionaries, as indicated by the experimental results. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Cryptography

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Heart and Lung Sound Monitoring System Based Embedded System 7

Heart and Lung Sound Monitoring System Based Embedded System

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7th International Conference on Sustainable Information engineering and Technology, SIET 2022

作者： Endrawan, Nadi Rahmat Prasetio, Barlian Henryranu Maulana, Rizal Department of Informatics Engineering Brawijaya University Indonesia Faculty of Computer Science University of Brawijaya Indonesia

ISBN: (纸本)9781450397117

Every year, Indonesians still suffer from heart and lung diseases. To anticipate many lethal effects caused by these diseases, an early diagnosis solution is needed. This research discusses the implementation of a heart and lung auscultation monitoring system that aims to facilitate doctors in diagnosing patients. The system has three main components: sampler, signal conditioner, and interface. The sampler samples the signal with a period of 250 μs which is also the deadline of task completion in the system. The signal conditioner will filter the signal according to the doctor's wishes with a choice of two modes (heart and lung). Then the interface can display heart rate (HR) or respiration rate (RR) parameters according to the selected mode and other features such as sound output and signal visualization. The test results show that the system completes the task faster than the deadline with an average of each sampler, signal conditioner, and interface: 21.6 μs, 185.13 μs, and 122.62 μs. There is an increase in the signal-To-noise ratio value of both filters after filtering with a value of 35.05 for the heart and 23.64 for the lungs. Finally, the performance of the Smoothed Z score algorithm in predicting HR and RR gives an accuracy of 94% and 82%. © 2022 ACM.

关键词： FIR filters

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