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IEEE Latin American Robotics Symposium, LARS

作者： Gabriel Batistuta Urbano Lopes Sebastião Emidio Alves Filho B.Sc. in Computer Science Rio Grande do Norte State University Mossoró RN Brazil Graduate Program in Computer Science - PPgCC UERN/UFERSA Rio Grande do Norte State University (UERN) and Federal University of the Semi-Arid Region (UFERSA) Mossoró RN Brazil

Educational robotics awakens students’ interest and curiosity in the world of technology and innovation. By exploring concepts in programming, electronics, and mechanics, students are introduced to subject areas allowing students of all ages to develop science, technology, engineering, and math (STEM) skills. However, getting information on this topic has become difficult since, with the growth of internet content production, learning objects have become constantly dispersed. Thus, the present work has the general objective of presenting the strategy used to search and ingest data from learning objects in an automated way in RepositORE, a repository where these objects of Education and robotics can be stored and searched by users who need to acquire certain skills. For the objects of Educational Robotics to be found more quickly and accurately, the software uses data extraction techniques to search for data from the learning objects on the web. Robot Finder optimizes the search and recording of information from internet object data so that it can be accessed by RepositORE.

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Investigating the Impact of Data Augmentation for Fine-Grained Grocery Product Classification Based on Vision Transformer

Investigating the Impact of Data Augmentation for Fine-Grain...

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Artificial Intelligence Robotics, Signal and Image Processing (AIRoSIP), International Conference on

作者： Rissa Rahmania Yaya Heryadi Lukas Lukas Wayan Suparta Ilvico Sonata Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Cognitive Engineering Group (CEG) Faculty of Engineering Universitas Katolik Atma Jaya Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Yogyakarta Indonesia

ISBN: (数字)9798350327472

ISBN: (纸本)9798350327489

The existence of fine-grained image classification supporting smart retail provides effectiveness in recognizing products with high similarity. However, the generic classification method performs poorly in identifying products from a subordinate category. This paper aims to identify augmentation techniques to leverage the Vision Transformer (ViT) model to classify the fine-grained grocery product, which involves embedding patches and transformer encoders to extract the main features. First, we develop a fine-grained image dataset with ColorJitter, CutOut, and combining both augmentations. Secondly, we perform experiments and analysis of ViT size, embedded patch size and image size in the patch embedding process. Lastly, the ViT model are evaluated according to the image sizes 224, 384, and 512 in accuracy, loss, and confusion matrix. The highest accuracy was obtained at 0.9922. The ColorJitter and CutOut improved the confusion matrix in ViT-B/16 and ViT-L/16 with an image size of 384 and 512. The results show that both augmentations in the ViT model are able to distinguish fine-grained grocery products.

关键词： Surveys computer vision Accuracy Image recognition Transformers Feature extraction Data augmentation Artificial intelligence Image classification

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Electronic-photonic quantum systems on-chip

Electronic-photonic quantum systems on-chip

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Quantum 2.0, QUANTUM 2022

作者： Wang, Imbert Ramesh, Anirudh Kramnik, Danielius Fargas Cabanillas, Josep M. Stojanović, Vladimir Kumar, Prem Popović, Miloš A. Department of Electrical and Computer Engineering Photonics Center Boston University BostonMA02215 United States Graduate Program in Applied Physics Northwestern University EvanstonIL60208 United States Department of Electrical Engineering and Computer Science UC Berkeley BerkeleyCA94720 United States Center for Photonic Communication and Computing Dept. of Electrical and Computer Eng. Northwestern University EvanstonIL60208 United States

We present progress towards realizing electronic-photonic quantum systems on-chip;particularly, entangled photon-pair sources, placing them in the context of previous work, and outlining our vision for mass-producible... 详细信息

ISBN: (纸本)9781957171111

关键词： Quantum entanglement

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Beyond Visual Image: Automated Diagnosis of Pigmented Skin Lesions Combining Clinical Image Features with Patient Data

arXiv

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arXiv 2022年

作者： Esgario, José G.M. Krohling, Renato A. Federal University of Espírito Santo ES Vitória Brazil PPGI - Graduate Program in Computer Science LABCIN Production Engineering Department

Skin cancer is considered one of the most common type of cancer in several countries. Due to the difficulty and subjectivity in the clinical diagnosis of skin lesions, computer-Aided Diagnosis systems are being developed for assist experts to perform more reliable diagnosis. The clinical analysis and diagnosis of skin lesions relies not only on the visual information but also on the context information provided by the patient. This work addresses the problem of pigmented skin lesions detection from smartphones captured images. In addition to the features extracted from images, patient context information was collected to provide a more accurate diagnosis. The experiments showed that the combination of visual features with context information improved final results. Experimental results are very promising and comparable to experts. © 2022, CC BY.

关键词： computer aided diagnosis

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Design and Implementation of Business Intelligence Dashboard for Project Control at the Port Harbor-Company 12th

Design and Implementation of Business Intelligence Dashboard...

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12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020

作者： Lumban Gaol, Ford Syahir, Arsyan Matsuo, Tokuro Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Information System Bina Nusantara University Jakarta Indonesia Advanced Institute of Industry Technology Tokyo Japan

ISBN: (纸本)9789811533792

This study aims to assist resource management and the project controller at Port Harbor Company. Port Harbor Company is an IT Consulting. Problems that often occur in IT Consulting are related to the project cost, resource management and control of each project. Problems that occur at the Port Harbor Company are poor resource management, spending costs that exceed a predetermined budget and how to see the status of ongoing projects. Using Business Intelligence and the dashboard as a front end will help the project controller and resource management manage resources, manage project costs and monitor ongoing projects. In this study, the development and implementation of Business Intelligence and dashboards using the ASAP method are expected to be more structured and can solve the Port Harbor Company problem. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Project management

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Identification of Lampung Script Using K-Neighbor, Manhattan Distance and Population Matrix Algorithm 1

Identification of Lampung Script Using K-Neighbor, Manhattan...

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1st Virtual Conference on Engineering, science and Technology, ViCEST 2020

作者： Augusta, Gladys Ivana Hakim, Lukman Zainal, Anna Gustina Tannady, Hendy Computer Science Department Universitas Bunda Mulia14430 Indonesia Communication Department Lampung University 35141 Indonesia Graduate Program of Management Institut Teknologi Dan Bisnis Kalbis13210 Indonesia

Language is a communication tool that is used as interaction with others. The use of indigenous languages is decreasing and erasing over time. Lampung script is a script that becomes the identity of the province of Lampung. However, only a few native Lampung residents who know the Lampung script and the younger generation often write Lampung in Latin letters because it is considered easier. This study uses Optical Character Recognition to recognize Lampung characters in image images using a smartphone. This study uses the Pixel Population Matrix feature extraction to extract the characteristics of the characters. The distance calculation for each test character and database uses Manhattan Distance and is classified using K-Nearest Neighbor with the value of k is 3. The results of the character recognition process can be translated into Indonesian. Testing this application is done by taking image samples with several conditions. The script image tested is in the form of a screenshot image of printed writing with random fonts, a handwritten photo image, a screenshot image with a combination of several words and a photo image with a smaller size and random slope. The test results according to these conditions obtained an average percentage of success of 91.49%. © Published under licence by IOP Publishing Ltd.

关键词： Pixels

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Code-mixed sentiment analysis of Indonesian language and Javanese language using Lexicon based approach 2

Code-mixed sentiment analysis of Indonesian language and Jav...

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2nd Annual Conference of science and Technology, ANCOSET 2020

作者： Tho, C. Heryadi, Y. Lukas, L. Wibowo, A. Department of Computer Science Binus Graduate Program Bina Nusantara University Jakarta Indonesia Cognitive Engineering Research Group Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta Indonesia

Nowadays mixing one language with another language either in spoken or written communication has become a common practice for bilingual speakers in daily conversation as well as in social media. Lexicon based approach is one of the approaches in extracting the sentiment analysis. This study is aimed to compare two lexicon models which are SentiNetWord and VADER in extracting the polarity of the code-mixed sentences in Indonesian language and Javanese language. 3,963 tweets were gathered from two accounts that provide code-mixed tweets. Pre-processing such as removing duplicates, translating to English, filter special characters, transform lower case and filter stop words were conducted on the tweets. Positive and negative word score from lexicon model was then calculated using simple mathematic formula in order to classify the polarity. By comparing with the manual labelling, the result showed that SentiNetWord perform better than VADER in negative sentiments. However, both of the lexicon model did not perform well in neutral and positive sentiments. On overall performance, VADER showed better performance than SentiNetWord. This study showed that the reason for the misclassified was that most of Indonesian language and Javanese language consist of words that were considered as positive in both Lexicon model. © Published under licence by IOP Publishing Ltd.

关键词： Sentiment analysis

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Solving Combinatorial Optimization Problems on Fujitsu Digital Annealer

arXiv

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arXiv 2023年

作者： Kao, Yu-Ting Liao, Jia-Le Hsu, Hsiu-Chuan Graduate Institute of Applied Physics National Chengchi University B.S. Program in Electrophysics National Chengchi University Department of Money and Banking National Chengchi University Taipei City Taiwan B.S. Program in Electrophysics National Chengchi University Department of Computer Science National Chengchi University Taipei City Taiwan Graduate Institute of Applied Physics National Chengchi University Department of Computer Science National Chengchi University Taipei City Taiwan

Combinatorial optimization problems are ubiquitous in various disciplines and applications. Many heuristic algorithms have been devoted to solve these types of problems. In order to increase the efficiency for finding the optimal solutions, an application–specific hardware, called digital annealer (DA) has been developed for solving combinatorial optimization problems using quadratic unconstrained binary optimization (QUBO) formulations. In this study, we formulated the number partitioning problem and the graph partitioning problem into QUBO forms and solved such problems with the DA developed by Fujitsu Ltd. The QUBO formulation of the number partitioning problem was fully connected. The DA found the overall runtime for the optimal solution to be less than 30 seconds for 6500 binary variables. For the graph partitioning problem, we adopted modularity as the metric for determining the quality of the partitions. For Zachary’s Karate Club graph, the modularity obtained was 0.445, a 6% increase against D–wave Quantum Annealer and Simulated Annealing. Moreover, to explore the DA’s potential applications to real–world problems, we used the search for communities or virtual microgrids in a power distribution network as an example. The problem was formulated into graph partitioning. It is shown that the DA effectively identified community structures in the IEEE 33–bus and IEEE 118–bus network. © 2023, CC BY.

关键词： Simulated annealing

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Demonstration of a Polarization-Agnostic Geometric Phase in Nonlocal Metasurfaces

arXiv

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arXiv 2023年

作者： Overvig, Adam Kasahara, Yoshiaki Xu, Gengyu Alù, Andrea Photonics Initiative Advanced Science Research Center Graduate Center of the City University of New York United States Department of Electrical and Computer Engineering The University of Texas Austin United States Physics Program Graduate Center City University of New York United States

Symmetry-driven phenomena arising in nonlocal metasurfaces supporting quasi-bound states in the continuum (q-BICs) have been opening new avenues to tailor enhanced light-matter interactions via perturbative design principles. Geometric phase concepts—observed in many physical systems—are particularly useful in nonlocal metasurfaces, as they enable to locally pattern the q-BIC scattering rate and phase across the metasurface aperture without affecting the delocalized nature of the q-BIC resonance. However, this control typically comes with stringent limitations in terms of efficiency and/or of polarization operation. Here, we unveil a new form of geometric phase control, accumulated along a continuous contour of geometric perturbations that parametrically encircle a singularity associated with a bound state. This response is obtained regardless of the chosen polarization state, which can be rationally specified by a judicious choice of the perturbation geometry. Our findings extend geometric phase concepts to arbitrary polarizations, including linear and elliptical states, with near-unity scattering efficiency. This polarization-agnostic geometric phase offers new opportunities for wavefront manipulation, multifunctional operation and light emission, with applications in augmented reality, secure communications, wireless systems, imaging, lasing, nonlinear and quantum optics. © 2023, CC BY.

关键词： Polarization

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A Cascade Deep Neural Network Approach for Oil Spills Classification and Detection

A Cascade Deep Neural Network Approach for Oil Spills Classi...

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International Conference on Electric Power and Energy Conversion Systems (EPECS)

作者： Mohammad Rashwan Mohammed Alhadi Mohammad A. Jaradat Mohammad I. Daoud Mechatronics Graduate Program American University of Sharjah Sharjah United Arab Emirates Mechanical Engineering Department American University of Sharjah Sharjah United Arab Emirates Computer Science and Engineering Department American University of Sharjah Sharjah United Arab Emirates

ISBN: (数字)9798331516963

ISBN: (纸本)9798331516970

Oil spills represent a growing environmental challenge that poses a significant threat to living organisms. Moreover, the treatment of oil spills, especially in severe cases, has serious economic repercussions and requires substantial labor and time. Therefore, the effective detection of oil spills has become an important research problem. Traditional methods for detecting oil spills, such as manual patrolling and dynamic sensors, are often limited in accuracy and coverage. As a result, the automation of oil spills detection has emerged as a critical global imperative in scientific research. The aim of this paper is to employ deep learning technology to achieve effective detection of oil spills based on aerial images. Our approach is composed of two phases. In the first phase, a Deep Convolutional Neural Network (DCNN), namely ResNet50, is trained on a large dataset containing images showing oil spills at a seaport. The trained DCNN is used to classify the input image as "Oil Spill" or "No Oil Spill". In the second phase, the images classified as "Oil Spill" are analyzed using a deep learning detection model, namely You-Only-Look-Once (YOLOv4), to localize the oil spills. The results indicate the capability of the proposed method to achieve effective oil spill detection. In particular, the classification accuracy obtained by the ResNet50 model is equal to 98%. Moreover, the YOLOv4 model was able to obtain effective localization of the oil spills with mean-average precision of 62%.

关键词： Deep learning Accuracy Oils Manuals Seaports Organisms Sensors Power systems Convolutional neural networks Residual neural networks

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