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International Conference on computer, Control, Informatics and Its Applications (IC3INA)

作者： Irwin Santoso Soegiharto Abba Suganda Girsang Computer Science Department Binus Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Binus Graduate Program - Master of Computer Science Binus Nusantara University Jakarta Indonesia

ISBN: (数字)9798331542313

ISBN: (纸本)9798331542320

NoSQL database has gained popularity in Big Data and other various applications for its simplicity and flexibility. The non-relational nature of NoSQL database such as MongoDB proves to improve development lifecycles and resources efficiency. However, security challenges arise along with increasing usage of NoSQL database, and NoSQL database is no exception to injection attacks. Machine learning proved to be an efficient method, as much has been researched. However, in the future there may be an increasing complexity of features that may prove costly to the model’s performance. Therefore, this research aims to utilize principal component analysis as dimensionality reduction and deep neural network as the classification method, to improve the security of NoSQL database. The text query is converted to feature vectors then further processed to reduce the input dimension of the deep neural network using PCA. The features used are based on previous research and various sources, and some are added after analyzing the dataset.10-fold cross validation is also applied to ensure that the model does not overfit the data, attempting to reduce bias to the result. The 10-fold cross validation model accuracy result is in average 97.44% with a standard deviation of 1.7%, and the testing results are 97.5% in accuracy,95.65% in precision, 91.67% in recall, and 93.61% in F1 score. Thus, it can be concluded that the usage of PCA on injection feature vectors can reduce complexity of the model.

关键词： Technological innovation NoSQL databases Artificial neural networks Vectors Complexity theory Security Informatics Standards Principal component analysis Testing

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Comparison of K-Nearest Neighbor and Support Vector Regression for Predicting Oil Palm Yield 1

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International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, CITISIA 2022

作者： Pardamean, Bens Suparyanto, Teddy Sinaga, Gokma Sahat Tua Elwirehardja, Gregorius Natanael Firmansyah, Erick Ginting, Candra Mawandha, Hangger Gahara Putra, Dian Pratama Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program—Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Faculty of Agriculture Institute of Agriculture STIPER Yogyakarta55282 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

With the high demand for oil palm production, implementations of Machine Learning (ML) technologies to provide accurate predictions and recommendations to assist oil palm plantation management tasks have become beneficial, such as in predicting annual oil palm. However, different geographical and meteorological conditions may result in different scales of influence for each variable. In this research, K-Nearest Neighbors (KNN) and Support Vector Regression (SVR) were used in predicting oil palm yield based on data collected in Riau, Indonesia. Pearson’s correlation coefficient was also calculated in selecting the input features for the models, whereas normalization and standardization were used in scaling the data. By setting the minimum absolute correlation threshold to 0.1 and using standardization, both models managed to obtain more than 0.81 R2, with SVR obtaining the overall best performance with 0.8709 R2, 1.372 MAE, and 1.8025 RMSE without hyperparameter fine-tuning. It was also discovered that the oil palm yield in the previous year is the variable with the most influence in estimating oil palm yield in the current year, followed by the number of plants and soil types. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Machine learning

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A Systematic Literature Review of Deep Learning Application in Multiclass Anomaly Detection for Chest Medical Imaging 6

A Systematic Literature Review of Deep Learning Application ...

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6th International Conference on computer and Informatics Engineering, IC2IE 2023

作者： Philips Pardamean, Bens Elwirehardja, Gregorius Natanael Isnan, Mahmud Bina Nusantara University Binus Graduate Program - Master of Compuer Science Computer Science Department Jakarta Indonesia Bina Nusantara University Bioinformatics and Data Science Research Center Jakarta Indonesia

ISBN: (纸本)9798350345162

Medical imaging abnormality detection is challenging, but deep learning approaches have shown promise. This paper reviews the current state of the art in deep learning approaches for detecting abnormalities in chest medical imaging. To discover the trends, opportunities, and challenges associated with this field, 18 studies were selected from Google Scholar based on their titles, abstracts, and contents for extensive review to answer two research questions. The study found that the National Institutes of Health (NIH) Chest X-ray 14 dataset is the most used dataset for this task. Most research uses a single-modal approach, considering only image data as input, with X-ray being the more popular instrument. There are 8 out of 18 studies leverage the transfer learning approach, with ResN et50 being the most popular network. MobileNetV2 has demonstrated competitive results compared to more robust networks. Preprocessing techniques such as image enhancement and data augmentation are leveraged by 61.1 % of the reviewed studies and are shown to improve model performance. © 2023 IEEE.

关键词： abnormality detection attention mechanisms chest x-ray CT images deep learning transfer learning

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Purchase intention of Amazon sustainable brands: a hybrid approach of structural equation modeling and Rasch model

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SN Business and Economics 2023年第12期3卷 1-29页

作者： Santos, Luiz Diego Vidal Holanda, Francisco Sandro Rodrigues de Santana Oliveira, Catuxe Varjão Pedrotti, Alceu de Menezes, Pedro Vinícius Bertulino Villwock, Ana Paula Schervinski Graduate Program in Intellectual Property Science Universidade Federal de Sergipe-UFS Sergipe São Cristóvão Brazil Agronomy Engineering Department Universidade Federal de Sergipe-UFS Sergipe São Cristóvão Brazil Computer Science Department Instituto Federal de Sergipe-UFS Sergipe Lagarto Brazil

This article conducts a comprehensive examination of brand-based equity closely linked to environmental sustainability in the Amazon Rainforest. The research is primarily dedicated to identifying the factors that influence consumers’ willingness to purchase products from sustainable brands within six categories: cosmetics, tourism, clothing, accessories, and food. The central aim of this study is to investigate how brand equity constructs, rooted in environmental sustainability within the Amazon Rainforest, impact consumer loyalty and purchase intention. To accomplish this objective, a mixed-methodology approach was employed, combining structural equation modeling with item response theory. This study involved 535 potential consumers, and data from eight selected brands served as the basis for the analysis. Within the framework of Purchase Intention (PI), the following variables were regarded as formative constructs: Strategic Brand Positioning (SBP), Perceived Brand Quality (PBQ), Retail Innovation (RI), and Brand Authenticity (BA). The results obtained from the structural equation models underscore the statistical significance and substantial impact of all pathways. Notably, SBP emerged as the most significant contributor to the effect on PI, as hypothesized. Brand equity and environmental sustainability were found to indirectly affect behavioral PI. Consumers exhibited a high level of latent trait (θ), with items consistently reflecting elevated values, confirming their acceptance of products, except brand differentiation. Overall, the findings highlight the effectiveness of branding strategies rooted in environmental sustainability in enhancing the brand equity of small forest companies. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Amazon Rainforest Brands Entrepreneurship Microenterprises Sustainability performance Sustainable development

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Implementation of Lightweight PRNG on PLC for Industrial Control Systems 3

Implementation of Lightweight PRNG on PLC for Industrial Con...

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3rd International Conference on Intelligent Cybernetics Technology and Applications, ICICyTA 2023

作者： Sama, Andi Gaol, Ford Lumban Harso Supangkat, Suhono Ranti, Benny Binus Graduate Program Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Institute of Technology Bandung Faculty of Digital Communication and Hotel & Tourism Bandung Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9798350394559

The Information Technology/Operational Technology convergence towards Industry 4.0 opens the opportunity to leverage recent advancements in Information Technology for Operational Technology, such as Cloud, Internet of Things, and Artificial Intelligence. Meanwhile, cyber-attacks are increasing for Operational Technology. The security aspect in Operational Technology systems has traditionally been a low priority, in contrast with speed. This introduces challenges as Industrial Control Systems such as programmable Logic Controller in Operational Technology have been traditionally optimized for speed rather than security due to limited computing power. As computations need to be as efficient as possible, security in Operational Technology has yet to be managed as robustly as in Information Technology. Operational Technology communication protocols for securing data transfer, for example, have no or just a few security capabilities, even for basic authentication and encryption. Common security algorithms rely on random numbers. However, Random Number Generator is not usually part of standard functions in programmable Logic Controllers, the core control component in Industrial Control Systems. In Industrial Control Systems, the Random Number Generator is mostly implemented as a software-based Pseudo Random Number Generator. This paper shows how to apply a Pseudo Random Number Generator in a Siemens Compact PLC S7-1200 using a modified lightweight XORshift algorithm. The XORshift algorithm can generate better randomness than the system's clock-based implementation in the Siemens Library of Generic Functions. © 2023 IEEE.

关键词： Internet of things

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A Diagnosis on the Teaching of Software Design in a Sample of Undergraduate Courses in computer science in Brazil

A Diagnosis on the Teaching of Software Design in a Sample o...

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Frontiers in Education (FIE) Conference

作者： Vitor De Souza Castro Sandro Ronaldo Bezerra Oliveira Graduate Program in Computer Science (PPGCC) Federal University of Pará (UFPA) Federal University of the South and Southeast of Para (UNIFESSPA) Belém Pará Brazil Graduate Program in Computer Science (PPGCC) Federal University of Pará (UFPA) Belém Pará Brazil

The training of a professional in the area of computing involves understanding the process of building software. In the computer science course curricular guidelines, this training is a requirement for graduating from the course. For the construction of the Pedagogical Project of the Course (PPC), the In-stitutions observe reference documents for the development of the project according to the local/regional specificity. Dealing with computing courses, the National Curricular Guidelines (DCN) for Computing courses, the training references of the Brazil-ian Computing Society (SBC) and the Guide to the Software Engineering Body of Knowledge (SWEBOK), are key elements to support the construction of the PPC. In computer science courses, software engineering is presented as a central element in technological training for students. Software engineering defines stages for the construction of quality software, which begins with the requirements conception, analysis, design and ends with the construction of the solution. The scope of this article will deal with the software design area, which is responsible for defining an implementable structure for a software product, which meets the specified requirements, that is, makes the communication interface between the requirements and the construction of the software. In the specialized literature, the area of Software Design (SD) is presented as important and emerging topics in the training of Computing professionals. Emerging topics for teaching Software Engineering aligned with teaching Software Design were identified, such as: UX Design Practices, Current Interface Prototyping Tools and Design Patterns. One of the challenges for the area of Software Engineering is the high heterogeneity of solutions, leading to hybrid systems, with multi-paradigms, and this heterogeneity reflects on how the professional designs the solution, what is directly associated with training in Software Design. The justification for the development of

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An Extended Euclidean Algorithm Implementation over Ciphertext Space 2nd

An Extended Euclidean Algorithm Implementation over Ciphert...

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2nd International Conference on Security and Information Technologies with AI, Internet Computing and Big-data Applications, SITAIBA 2023

作者： Chi, Po-Wen Lin, Yuan-Pang Wang, Ming-Hung Chuang, Yun-Hsin Department of Computer Science and Information Engineering National Taiwan Normal University Taiwan Taipei Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Taiwan Chiayi Taiwan Engineering Management Graduate Program College of Engineering National Cheng Kung University Taiwan Tainan Taiwan

ISBN: (纸本)9789819777853

Fully homomorphic encryption (FHE) is a useful cryptographic primitive. It makes a third-party manipulate data in the ciphertext space and therefore is a key technology for privacy-preserving outsourcing services. Theoretically, FHE can evaluate any circuits. However, the implementation is not trivial. The reason it lacks lots of basic operations like conditional check and branch control. In this paper, we focus on extended Euclidean algorithm operation over FHE. We introduce the problems we encounter and show how we solve these issues. We implement our design and evaluate its performance on a real computer. Finally, we propose some research directions for our future work. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Ciphertext

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CRISPR/Cas genome editing in soybean: challenges and new insights to overcome existing bottlenecks

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Journal of Advanced Research 2024年 73卷 53-72页

作者： Freitas-Alves, Nayara Sabrina Moreira-Pinto, Clidia E. Távora, Fabiano T.P.K. Paes-de-Melo, Bruno Arraes, Fabricio B.M. Lourenço-Tessutti, Isabela T. Moura, Stéfanie M. Oliveira, Antonio C. Morgante, Carolina V. Qi, Yiping Fatima Grossi-de-Sa, Maria Embrapa Genetic Resources and Biotechnology DF Brasília Brazil Bioprocess Engineering and Biotechnology Graduate Program Federal University of Paraná (UFPR) PR Curitiba Brazil National Institute of Science and Technology INCT PlantStress Biotech EMBRAPA DF Brasília Brazil Federal University of Pelotas (UFPEL) RS Pelotas Brazil Embrapa Semi-Arid PE Petrolina Brazil Department of Plant Science and Landscape Architecture University of Maryland College Park MD United States Catholic University of Brasília Graduate Program in Genomic Sciences and Biotechnology DF Brasília Brazil Catholic University Dom Bosco Graduate Program in Biotechnology MS Campo Grande Brazil

Background: Soybean is a worldwide-cultivated crop due to its applications in the food, feed, and biodiesel industries. Genome editing in soybean began with ZFN and TALEN technologies;however, CRISPR/Cas has emerged and shortly became the preferable approach for soybean genome manipulation since it is more precise, easy to handle, and cost-effective. Recent reports have focused on the conventional Cas9 nuclease, Cas9 nickase (nCas9) derived base editors, and Cas12a (formally Cpf1) as the most commonly used genome editors in soybean. Nonetheless, several challenges in the complex plant genetic engineering pipeline need to be overcome to effectively edit the genome of an elite soybean cultivar. These challenges include (1) optimizing CRISPR cassette design (i.e., gRNA and Cas promoters, gRNA design and testing, number of gRNAs, and binary vector), (2) improving transformation frequency, (3) increasing the editing efficiency ratio of targeted plant cells, and (4) improving soybean crop production. Aim of review: This review provides an overview of soybean genome editing using CRISPR/Cas technology, discusses current challenges, and highlights theoretical (insights) and practical suggestions to overcome the existing bottlenecks. Key scientific concepts of review: The CRISPR/Cas system was discovered as part of the bacterial innate immune system. It has been used as a biotechnological tool for genome editing and efficiently applied in soybean to unveil gene function, improve agronomic traits such as yield and nutritional grain quality, and enhance biotic and abiotic stress tolerance. To date, the efficiency of gRNAs has been validated using protoplasts and hairy root assays, while stable plant transformation relies on Agrobacterium-mediated and particle bombardment methods. Nevertheless, most steps of the CRISPR/Cas workflow require optimizations to achieve a more effective genome editing in soybean plants. © 2024

关键词： Base editors Cas12a CRISPR/Cas9 Crops Genetic transformation Glycine max

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

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IEEE Transactions on Services Computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, Social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized Social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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Mobile Application for Children to Learn BISINDO Sign Language 6

Mobile Application for Children to Learn BISINDO Sign Langua...

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6th International Conference on Inventive Computation Technologies, ICICT 2023

作者： Andreas, Raynaldo Maria, Sarah Satyadhana, Alexander Khrisna Warnars, Harco Leslie Hendric Spits Ramadhan, Arief Muyeba, Maybin K. Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Indonesia Computer Science Bina Nusantara University Jakarta11480 Indonesia Telkom University Bandung40257 Indonesia MIST Consulting ManchesterM410SA United Kingdom

ISBN: (纸本)9798350398496

Sign language is the most commonly used communication medium for people who are deaf and mute. By using body movements, they can convey meaning through visual cues, not vocal cues. This type of language is learned almost exclusively by people who are deaf or dumb and those who interact with them on a daily basis. Most people do not learn it because sign language is not part of basic education, and the lack of need to use it, especially from a young age. Most of the spoken languages in the world usually have sign language variants according to the language of their respective countries. In this study, a mobile application is developed for children to learn Indonesian sign language where the process model is designed using use case diagrams, and the database design is modeled with class diagrams. As for the implementation, the Android Studio software is used for the application, and the MySQLdatabase is for database storage. © 2023 IEEE.

关键词： Mobile computing

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