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arXiv 2022年

作者： da Silva, Alysson Ribeiro Computer Science Graduate Program Federal University of Minas Gerais Belo Horizonte Brazil

Natural disasters can cause substantial negative socio-economic impacts around the world, due to mortality, relocation, rates, and reconstruction decisions. Robotics has been successfully applied to identify and rescue victims during the occurrence of a natural hazard. However, little effort has been taken to deploy solutions where an autonomous robot can save the life of a citizen by itself relocating it, without the need to wait for a rescue team composed of humans. Reinforcement learning approaches can be used to deploy such a solution, however, one of the most famous algorithms to deploy it, the Q-learning, suffers from biased results generated when performing its learning routines. In this research a solution for citizen relocation based on Partially Observable Markov Decision Processes is adopted, where the capability of the Double Q-learning in relocating citizens during a natural hazard is evaluated under a proposed hazard simulation engine based on a grid world. The performance of the solution was measured as a success rate of a citizen relocation procedure, where the results show that the technique portrays a performance above 100% for easy scenarios and near 50% for hard ones. © 2022, CC BY-NC-ND.

关键词： Hazards

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Handcrafted Feature Selection Techniques for Pattern Recognition: A Survey

arXiv

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arXiv 2022年

作者： da Silva, Alysson Ribeiro Silveira, Camila Guedes Computer Science Graduate Program Federal University of Minas Gerais Belo Horizonte Brazil

The accuracy of a classifier, when performing Pattern recognition, is mostly tied to the quality and representativeness of the input feature vector. Feature Selection is a process that allows for representing information properly and may increase the accuracy of a classifier. This process is responsible for finding the best possible features, thus allowing us to identify to which class a pattern belongs. Feature selection methods can be categorized as Filters, Wrappers, and Embed. This paper presents a survey on some Filters and Wrapper methods for handcrafted feature selection. Some discussions, with regard to the data structure, processing time, and ability to well represent a feature vector, are also provided in order to explicitly show how appropriate some methods are in order to perform feature selection. Therefore, the presented feature selection methods can be accurate and efficient if applied considering their positives and negatives, finding which one fits best the problem's domain may be the hardest task. © 2022, CC BY-NC-ND.

关键词： Feature Selection

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Aspect-based Sentiment Analysis using Long Short-term Memory Model for Leveraging Restaurant Service Management

Aspect-based Sentiment Analysis using Long Short-term Memory...

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computer science, Information Technology and Engineering (ICCoSITE), International Conference on

作者： Yaya Heryadi Bambang Dwi Wijanarko Dina Fitria Murad Cuk Tho Kiyota Hashimoto Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta Indonesia Computer Science Department BINUS Online Learning Jakarta Indonesia Information Systems Department BINUS Online Learning Jakarta Indonesia Interdisciplinary Graduate School or Earth System Science and Andaman Natural Disaster Management Prince of Songkla University Phuket Thailand

In general, the hospitality industry has been acknowledged as a major sector that gives a high contribution to economic development in many countries including Indonesia. For that reason, many initiatives have been implemented to help the growth of the hospitality industry in many countries including Indonesia to rebound from the harsh impact of the Covid-19 Pandemic. One such initiative is improving restaurant services as the main sector of the hospitality industry. This paper presents empirical results of sentiment analysis as a means to assess the quality of restaurant services as the first step to improving service quality. In particular, this study explores the aspect-based sentiment analysis method to identify some aspects of restaurant service which need improvement by learning the polarity of customers toward the restaurant services without having to meet the customers directly. By using the aspect-based sentiment analysis method, the customer sentiments comprising opinions, sentiments, evaluations, attitudes, and emotions from restaurant service can be analyzed using customers’ online reviews as input. The main experiment findings showed that the Long Short-term Memory model can achieve high performance in predicting aspect polarization in restaurant service reviews. Other findings suggest that Sigmoid as an activation function achieved 0.97 average training accuracy and 0.69 average testing accuracy giving a better performance to the model in comparison to ReLU, Tanh, and ELU activation functions.

关键词： Industries Training Economics Sentiment analysis Pandemics Computational modeling Predictive models

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AI in EEG-Based BCI for the Diagnosis of Mild Cognitive Impairment: A Mini Review

AI in EEG-Based BCI for the Diagnosis of Mild Cognitive Impa...

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International Winter Workshop on Brain-computer Interface (BCI)

作者： Vasilii Zaitsev Chun-Shu Wei EECS International Graduate Program National Yang Ming Chiao Tung University Hsinchu Taiwan Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

ISBN: (数字)9798331521929

ISBN: (纸本)9798331521936

Mild Cognitive Impairment (MCI) is a condition that often precedes dementia, making early diagnosis critical for delaying cognitive decline. Electroencephalography (EEG) has emerged as a non-invasive, cost-effective tool for monitoring brain activity and detecting MCI. This paper overviews recent advancements in machine learning (ML) and deep learning (DL) models for EEG-based MCI diagnosis. Traditional ML approaches, such as support vector machines (SVM) and K-nearest neighbors (KNN), have been widely used but rely on manually extracted features and face challenges with the complex nature of EEG signals. In contrast, DL models like convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and transformers have shown promise in automatically learning features and capturing temporal and spatial information from EEG data. Despite these advancements, issues such as small dataset sizes and variability in EEG recordings remain barriers to clinical application. This paper discusses these challenges and highlights potential future directions for improving the diagnosis of MCI.

关键词： Deep learning Support vector machines Reviews Nearest neighbor methods Brain modeling Feature extraction Transformers Electroencephalography Recording Dementia

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Single Image Perspective Grid System on Floor Surface for 2D to 3D Transformation

Single Image Perspective Grid System on Floor Surface for 2D...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Darma Rusjdi Edi Abdurachman Yaya Heryadi Gede Putra Kusuma Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665453905

Our study discusses the application of the perspective grid concept as the basis for the process of transforming the 2D coordinates of the image into 3D coordinates in real space for estimating the location of objects in a single image scene. In several other studies in the field of robotics, AR use methods and media in the form of a chessboard box as a reference for camera calibration and location estimation. However, it does not show accurate results for the size of objects in the room. We saw the potential areas of Alberti's perspective grid, which is often used as a reference in making sketches for the arts and various engineering fields so that they are visually precise with reality. Our study uses 6 reference points in a room arrangement with a floor grid pattern as a reference for the formation of a perspective grid. Based on the triangle comparison approach to determine the x-ordinate, the average error is 0.2193. And through 3 interpolation approaches to get the most accurate results with the Lagrange and Newton methods on the 6th order with the average difference between the actual and predicted points of 1.5 cm from the y-direction distance of the camera from 2 meters to 6.80 meters.

关键词： Meters Interpolation Three-dimensional displays Robot kinematics Robot vision systems Estimation Media

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Impact of CLAHE-based image enhancement for diabetic retinopathy classification through deep learning 7

Impact of CLAHE-based image enhancement for diabetic retinop...

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7th International Conference on computer science and Computational Intelligence, CSCI 2022

作者： Hayati, Mira Muchtar, Kahlil Roslidar Maulina, Novi Syamsuddin, Irfan Elwirehardja, Gregorius Natanael Pardamean, Bens Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Universitas Syiah Kuala Banda Aceh23111 Indonesia Faculty of Medicine Universitas Syiah Kuala Banda Aceh23111 Indonesia Department of Computer and Networking Engineering Politeknik Negeri Ujung Pandang Makassar90245 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Diabetic retinopathy (DR) is a type of diabetes mellitus that attacks the retina of the eye. DR will cause patients to experience blindness slowly. Generally, DR can be detected by using a special instrument called an ophthalmoscope to view the inside of the eyeball. However, in conditions where there is a very small difference between the normal image and the DR image, computer-based assistance is needed for maximizing image reading value. In this research, a method of image quality improvement will be carried out which will then be integrated with a classification algorithm based on deep learning. The results of image improvement using Contrast Limited Adaptive Histogram Equalization (CLAHE) shows that the average accuracy of the method on several models is very competitive, 91% for the VGG16 model, 95% for InceptionV3, and 97% for EfficientNet compared to the results original image which only has an accuracy of 87% for VGG16 model, 90% for InceptionV3 model, and 95% for EfficientNet. However, in ResNet34 better accuracy is obtained in the original image with an accuracy of 95% while in the CLAHE image the accuracy value is only 84%. The results of this comprehensive evaluation and recommendation of famous backbone networks can be useful in the computer-Aided diagnosis of diabetic retinopathy. © 2022 Elsevier B.V.. All rights reserved.

关键词： Image enhancement

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Hyperbolic Polariton Lenses For Sub-Diffractive Imaging

Hyperbolic Polariton Lenses For Sub-Diffractive Imaging

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CLEO: Fundamental science, CLEO:FS 2024 - Part of Conference on Lasers and Electro-Optics, CLEO 2024

作者： Renzi, Enrico Maria Yves, Simon Strickland, Diana Erland, Sveinung Bachmat, Eitan Alù, Andrea Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program The Graduate Center City University of New York NY10026 United States Department of Maritime Studies Western Norway University of Applied Sciences Haugesund5528 Norway Department of Computer Science Ben-Gurion University of the Negev Beer Sheva84105 Israel

We introduce the design of lenses for hyperbolic surface phonon polaritons operated in the mid-infrared range. Based on Minkowski space considerations, these lenses offer unbounded numerical aperture and can largely o... 详细信息

ISBN: (纸本)9781957171395

关键词： Polariton

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High-Resolution Hydrogen Molecule Detection Utilizing a Nanocandle-Based Optical Sensor 16

High-Resolution Hydrogen Molecule Detection Utilizing a Nano...

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16th Pacific Rim Conference on Lasers and Electro-Optics, CLEO-PR 2024

作者： Park, Nu-Ri Kim, Min-Joong Lee, Jongsu Seo, Minah Ryu, Yong-Sang Kim, Myung-Ki KU-KIST Graduate School of Converging Science and Technology Korea University Seoul02841 Korea Republic of Korea Institute of Science and Technology Sensor System Research Center Seoul02792 Korea Republic of Northwestern University Department of Electrical Engineering and Computer Science EvanstonIL60208 United States School of Biomedical Engineering Korea University Seoul02481 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02481 Korea Republic of

Our research introduces a novel method for safe hydrogen detection. We've developed an advanced nano-candle sensor, combining Pd with nano-candles, enabling accurate detection of low-concentration hydrogen ( ©... 详细信息

ISBN: (纸本)9798350372076

关键词： Nanoclay

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News Classification Based On News Headline Using SVC Classifier

News Classification Based On News Headline Using SVC Classif...

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International Conference on Telecommunication Systems, Services, and Applications (TSSA)

作者： Goldius Leonard Fukriandy Sisnadi Nicholas Vigo Wardhana Muhammad Abdul Aziz Al-Ghofari Abba Suganda Girsang Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

News gives new insight and information from all over the world. News has many categories, such as politic, economy, science, and other common news categories. Every news will have their own category based on its content. The classification of news is usually done manually by inputting the category during the news posting. Some of the categories may be inputted incorrectly. The news classifier can be the solution for problem, but the news classifications out there are usually based on the news content. The classifier will receive the word vector inputs that are taken from the news content and try to classify it into one of certain categories. Unfortunately, news contents can be longer and harder to be processed rather than processing the news headline. The news headline is shorter and packs a decent information for the classifier to find out what category it is. Besides the news headline usage, the classifier also needs to be chosen correctly. In this paper, the SVC model will be tested using the news headline data to classify the news and compare with several other models, such as Linear Regression, Multinomial Naive Bayes, Decision Tree, and Random Forest. The common variables to be compared are the accuracy, recall, and precision to evaluate the SVC model.

关键词： Training Linear regression Static VAr compensators Data models Telecommunications Decision trees Random forests

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Fuzzy Decision Support Model on Virtual Plant Computational Model of Water Spinach (Ipomoea aquatica. Forssk) in Farming Business

Fuzzy Decision Support Model on Virtual Plant Computational ...

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International Conference on Information Technology, Information Systems and Electrical Engineering (ICITISEE)

作者： Ditdit Nugeraha Utama Ika Diah Agustia Rachmawati Heraldo Yusron Purwantono Computer Science Department Binus Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

Using soil as a planting medium (conventional system) raises several problems, such as the need for large agricultural land, but the available land is limited. This problem is triggered by an increase in demand for nutrients needed by the body to support daily activities, one of which can be met by consuming green vegetables, such as Water Spinach. To solve this problem, a hydroponic wick system or a wick system can use that is simple and easy to care for. Water Spinach (Ipomoea aquatica. Forssk) vegetables are easy to grow and care for. Nutrients contained in 100 grams of Water Spinach, energy: 29 kcal, protein: 3 grams, Fat: 0.3 grams, carbohydrates: 5.4 grams, calcium: 73 mg, phosphorus: 50 mg, iron: 3 mg, vitamin A: 6300IU,vitamin B1: 0.07 mg, vitamin C: 32 mg. In addition, a combination of disciplines such as mathematics, computer science, plant science, biology, and statistics can be used. This combination of knowledge is known as Plant Computational Modeling (PCM), which uses the Growth Grammar Interactive Modeling Platform (GroIMP) with the Functional Structural Plant Modeling (FSPM) method. The virtual plant model was successfully built, the results were divided into two parts, such as single plant and multi-plant. Plant computational modeling and DSM can help deal with agricultural problems. By using a plant dataset, the GroIMP-FSPM platform, and fuzzy logic, the model could help researchers in making a better decision based on BEP evaluation. The minimum numbers of plants cultivated were 650 plants in one harvest period in order to gain a desirable profit. We recommend to cultivate even more plants in one harvest period to gain even higher profits.

关键词： Proteins Phase change materials Computational modeling Plants (biology) Soil Phosphorus Mathematical models

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