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Risk-level assessment system on Bengawan Solo River basin flood prone areas using analytic hierarchy process and natural breaks: Study case: East Java

Risk-level assessment system on Bengawan Solo River basin fl...

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International Conference on Data and Software engineering (ICODSE)

作者： Haris Rahadianto Arna Fariza Jauari Akhmad Nur Hasim Department of Informatics and Computer Engineering Electronics Engineering Polytechnic Institute of Surabaya Surabaya Indonesia

Indonesia has the geographical conditions which are particularly vulnerable to disasters, especially floods and climate change. Throughout Indonesia, it is recorded that there are 5,590 main rivers and 600 rivers have the potential to cause flooding among others. One of it is Bengawan Solo River, which is the longest river in Java. The floods that hit the area have resulted in disruption of public health, disrupted economic activity, and damaged urban infrastructure. The phenomenon of floods and their negative impacts in the area of the Bengawan Solo river banks, indicating a condition of the area and the public about the lack of understanding of the characteristics of the hazards, behaviours that lead to degradation of natural resources, and lack of early warning that causes unpreparedness and inability in the face of danger. The purpose of this project is to be able to create an information system that can provide an assessment of the risk management in the Bengawan Solo's flood prone areas that passed in the province of East Java, by building a web-based information system that includes information on threats, vulnerabilities, and capacities, summarized in the disaster risks analysis that integrated with Geographic Information System to provide mapping areas that have high levels of risk in accordance. Based on the factors that are already said above and calculated by Analytical Hierarchy Process, the result of this project is a map with marked regions divided into three levels of risk like High, Medium, and Low using Natural Breaks to divide it. It also, by providing the risk-level for the regions, help the system to assess how much impact and damage that will be hit the risky area and give the recommendation to government and people how to increase the preparedness so it can reduce the damage from flood.

关键词： Rivers Floods Java Economics Risk management Software engineering

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Determination of Learning Media in Elementary School using Multi-Objective Optimization on the Basis of Ratio Analysis Method

Determination of Learning Media in Elementary School using M...

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International Electronics Symposium (IES)

作者： Netta Divana Vita Sembiring Irma Wulandari Desy Intan Permatasari Department of Informatics and Computer Engineering Electronic Engineering Polytechnic Institute of Surabaya Surabaya Indonesia

ISBN: (数字)9781728195308

ISBN: (纸本)9781728195643

In the learning process, learning media serves to improve the quality of the teaching and learning process. However, so far the determination of learning media in a class has not paid attention to several aspects, namely ease in getting media, characteristics of students to the type of media, learning time in the use of media, as well as funds needed to obtain media. This study aims to assist teachers in determining the optimal learning media based on student learning styles, as well as using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method in the optimization process. Determination of student learning styles is determined through filling questionnaires by students in the system that has been given a knowledge base and rules for determining learning styles. The MOORA method is used as a multi-objective system that optimizes several conflicting attributes simultaneously. The attributes needed in the optimization process in determining learning media are the ease of getting the media and student learning styles as the attributes to be maximized, as well as the time and funds required as the attributes to be minimized. The experimental result demonstrates that as much as 0.0859% for the assessment of each student experiencing a discrepancy because several factors can affect the acquisition of student learning outcomes, namely internal, external, and learning approaches. Besides, the assessment of the grade average shows a mismatch of 0.25%, because the system uses several criteria so that it does not only focus on the assessment criteria.

关键词： Media Education Optimization Knowledge based systems Visualization System analysis and design informatics

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Music recommendation using content and context information mining

Music recommendation using content and context information m...

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作者： Su, Ja-Hwung Yeh, Hsin-Ho Yu, Philip S. Tseng, Vincent S. Department of Computer Science and Information Engineering National Cheng Kung University Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science University of Illinois Chicago United States Department of Computer Science and Information Engineering Institute of Medical Informatics National Cheng Kung University Taiwan National Cheng Kung University Taiwan

Mobile devices such as smart phones are becoming popular, and realtime access to multimedia data in different environments is getting easier. With properly equipped communication services, users can easily obtain the widely distributed videos, music, and documents they want. Because of its usability and capacity requirements, music is more popular than other types of multimedia data. Documents and videos are difficult to view on mobile phones' small screens, and videos' large data size results in high overhead for retrieval. But advanced compression techniques for music reduce the required storage space significantly and make the circulation of music data easier. This means that users can capture their favorite music directly from the Web without going to music stores. Accordingly, helping users find music they like in a large archive has become an attractive but challenging issue over the past few years. © 2010 IEEE.

关键词： Digital storage

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Comparative Analysis of Brain Waves for EEG-Based Depression Detection in the Prefrontal Cortex Lobe using LSTM

Comparative Analysis of Brain Waves for EEG-Based Depression...

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Conference on New Media Studies (CoNMedia)

作者： Monica Pratiwi Department of Computer Engineering Faculty of Engineering and Informatics Universitas Multimedia Nusantara Tangerang Indonesia

Global anxiety and depression have become 25% more prevalent, with teenagers and women being the most affected. Approximately 280 million people suffer from depression. Doctors and psychologists are able to diagnose depressive disorders through counselling sessions and ask relevant questions to the subject, despite being vulnerable to mistakes due to the examiner's lack of experience. Therefore, automated depression detection development is necessary to validate doctor and psychiatrist assessment. Electroencephalography (EEG) is considered to be a popular option for the detection and investigation of various mental disorders. In this study, a comparison and analysis of each existing brain wave is carried out, namely Alpha (8-12Hz), Beta (13-30Hz), Theta (4–8 Hz), Delta (0.5-4 Hz) and Gamma (30-50Hz). From each wave, an accuracy testing is carried out for three groups of features: linear features, nonlinear features, and a combination of linear and nonlinear features. The given results demonstrate that the combination of linear and nonlinear data consistently yields the highest accuracy outcomes across all waves. Also, the combination of theta waves and linear nonlinear features contributed the highest accuracy (84%) using LSTM as the classifier.

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Performance Analysis of RouteSegmentation Algorithm in Identifying Perimeter Area Around Travel Route 16

Performance Analysis of RouteSegmentation Algorithm in Ident...

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16th International Conference on Information Technology and Electrical engineering, ICITEE 2024

作者： Bachmid, Muhammad Avied Anshari Haq, Muhammad Yasir Mumtaz, Muhammad Rafly Pinandito, Aryo Universitas Brawijaya Faculty of Computer Science Media Game and Mobile Laboratory Department of Informatics Engineering Malang Indonesia Universitas Brawijaya Faculty of Computer Science Malang Indonesia Universitas Brawijaya Faculty of Computer Science Media Game and Mobile Laboratory Department of Information System Malang Indonesia

ISBN: (纸本)9798350375817

Prior study has developed the RouteSegmentation algorithm to identify the perimeter area surrounding a route. In this study, a comparative experiment was carried out to investigate the performance of the RouteSegmentation algorithm implementation in contrast to the RouteBoxer algorithm. Both algorithms play a crucial role in geographical information systems (GIS), particularly in enhancing navigational tools by identifying points of interest along specified routes. Through systematic experimentation using various perimeter distance values and types of route, the trade-offs between processing efficiency and the granularity of the area identified by these algorithms were evaluated. The results demonstrate that RouteSegmentation maintained relatively consistent performance across different perimeter distance values and statistically significantly faster processing time than RouteBoxer. Furthermore, while the RouteBoxer algorithm benefits from larger perimeter distance values by reducing processing time, it compromises the coverage results of the algorithm and potentially undermines its usefulness in practical scenarios. This study not only provides insights into the optimal use of perimeter distance values for each algorithm but also guides users in selecting the appropriate algorithm based on their specific application needs, balancing detailed geographical analysis and runtime efficiency. © 2024 IEEE.

关键词： Transportation routes

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Uncertainty Management with Fuzzy and Rough Sets 1

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丛书名： Studies in Fuzziness and Soft Computing

1000年

作者： Rafael Bello Rafael Falcon José Luis Verdegay

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An Advanced Hierarchical algorithm for protein complex prediction

An Advanced Hierarchical algorithm for protein complex predi...

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IEEE EMBS International Conference on Information Technology Applications in Biomedicine (ITAB)

作者： Charalampos Moschopoulos Konstantinos Theofilatos Dimitris Fotakis Spiridon Likothanasis Sophia Kossida Department of Computer Engineering & Informatics Bioinformatics & Medical Informatics Team of Biomedical Research Foundation University of Patras Greece Department of Computer Engineering & Informatics University of Patras Greece School of Electrical and Computer Engineering National and Technical University of Athens Greece Bioinformatics & Medical Informatics Team of Biomedical Research Foundation Academy of Athens Greece

High throughput experimental methods which detect protein-protein interactions have generated large datasets offering a first estimation and representation of an organism's protein interaction network. However, there is still lack of information concerning protein complexes, although many automated methods have been applied to this problem. In this paper, a new hierarchical clustering algorithm, called Advanced Hierarchical Clustering (AHC) algorithm, is proposed which detects protein complexes with high predictive ratio. The main advantage of our algorithm is the accuracy of prediction of the protein complexes from the initial protein interaction graphs. We present experimental results using 7 experimental datasets and compare them with those derived from other existing algorithms (such as Mcode, HCS, RNSC and SideS), to demonstrate the efficiency of the AHC regarding successful prediction ratio of protein complexes and accuracy.

关键词： Electronics packaging Electronic mail Artificial neural networks Prediction algorithms Proteins Genomics Bioinformatics

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An Empirical Study of Unanswered Python-Related Questions on Stack Overflow

An Empirical Study of Unanswered Python-Related Questions on...

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Information Technology Research and Innovation (ICITRI), International Conference on

作者： Yusuf Sulistyo Nugroho Salsabil Aisyah Abdul Halim Syful Islam Yogiek Indra Kurniawan Tati Erlina Informatics Engineering Faculty of Communication and Informatics Universitas Muhammadiyah Surakarta Surakarta Indonesia Computer Science and Engineering Faculty of Engineering BSMRSTU Gopalganj Bangladesh Informatics Engineering Faculty of Engineering Universitas Jenderal Soedirman Purwokerto Indonesia Computer Engineering Faculty of Information Technology Universitas Andalas Padang Indonesia

ISBN: (数字)9798350376210

ISBN: (纸本)9798350376227

As a high-level programming language, Python supports user-friendly coding and system integration. It is not only used for data analytics but is also applied in software development. Although it has several benefits, users have various issues while running Python code. When programmers face issues, they often use Stack Overflow (SO) to get assistance for their problems. However, many Pythonrelated questions on SO are not responded to and remain unanswered. Thus, in this paper, we analyzed these unanswered questions to identify potential weaknesses of user and discussion characteristics. We applied a mixed-methods approach, including quantitative and qualitative analysis of user reputation, question types, and discussion topics. Our analysis shows that unanswered questions are mostly from low-reputation users ($\mathbf{7 2. 5 2 \%}$), followed by mid-reputation users $(\mathbf{1 7. 9 3 \%}$), and high-reputation users $\mathbf{(9. 5 5 \%)}$. The distribution of the unanswered question types shows that low-reputation users ask more “how” type of question ($\mathbf{3 8. 9 0 \%}$) followed by mid and high-reputation users. In contrast, the “what” and “why” questions are mostly posted by high-reputation users, followed by mid and low-reputation users. Our word-cloud analysis suggests a correlation between user reputation and the question topics. We acknowledge that there are limitations in our study, include potential misclassifications due to the time of posting and biases in manual labeling, which may affect the accuracy of our findings. This study provides insights into unanswered questions posted by the community, open up potential areas for future work such as improving support mechanisms and community engagement.

关键词： Technological innovation Information sharing System integration Manuals Encoding Labeling Information technology Faces Python Software development management

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Experimental study of neuromorphic node based on a multiwaveband emitting two-section quantum dot laser

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Photonics Research 2021年第4期9卷 I0007-I0015页

作者： George Sarantoglou Menelaos Skontranis Adonis Bogris Charis Mesaritakis Department of Information and Communication Systems Engineering University of the AegeanPalama 2Karlovassi 83200 SamosGreece Department of Informatics and Computer Engineering University of West AtticaAghiou Spiridonos12243 EgaleoAthensGreece

In this work,we present experimental results concerning excitability in a multiband emitting quantum-dot-based photonic *** experimental investigation revealed that the same two-section quantum dot laser can be tuned through a simple bias adjustment to operate either as a leaky integrate and fire or as a resonate and fire ***,by exploiting the inherent multiband emission of quantum-dot devices revealed by the existence of multiple lasing thresholds,a significant enhancement in the neurocomputational capabilities,such as spiking duration and firing rate,is *** firing rate increased by an order of magnitude that leads to an enhancement in processing speed and,more importantly,neural spike duration was suppressed to the picosecond scale,which corresponds to a significant temporal resolution *** new regimes of operation,when combined with thermal insensitivity,silicon cointegration capability,and the fact that these multiband mechanisms are also present in miniaturized quantum-dot devices,render these neuromorphic nodes a proliferating platform for large-scale photonic spiking neural networks.

关键词： laser quantum section

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Guaranteed Coverage Prediction Intervals with Gaussian Process Regression

arXiv

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arXiv 2023年

作者： Papadopoulos, Harris The Department of Electrical Engineering Computer Engineering and Informatics Frederick University Nicosia1036 Cyprus

Gaussian Process Regression (GPR) is a popular regression method, which unlike most Machine Learning techniques, provides estimates of uncertainty for its predictions. These uncertainty estimates however, are based on the assumption that the model is well-specified, an assumption that is violated in most practical applications, since the required knowledge is rarely available. As a result, the produced uncertainty estimates can become very misleading;for example the prediction intervals (PIs) produced for the 95% confidence level may cover much less than 95% of the true labels. To address this issue, this paper introduces an extension of GPR based on a Machine Learning framework called, Conformal Prediction (CP). This extension guarantees the production of PIs with the required coverage even when the model is completely misspecified. The proposed approach combines the advantages of GPR with the valid coverage guarantee of CP, while the performed experimental results demonstrate its superiority over existing methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Prediction models

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