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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mahmud Isnan Gregorius Natanael Elwirehardja Kuncahyo Setyo Nugroho Imelda Liana Ritonga Roby Pahala Januario Gultom Elida Afni Lubis Bens Pardamean Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Undergraduate of Nursing Program Universitas Imelda Medan Indonesia Medan Indonesia Undergraduate Pharmacy Program Universitas Imelda Medan Indonesia Medan Indonesia Clinical Pathology Unit Rumah Sakit Imelda Pekerja Indonesia Medan Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

The need for an early screening and computer-Aided Diagnosis (CAD) system based on Artificial Intelligence (AI) for the field of radiology is essential to realize considering the large impact of lung diseases globally. However, developing AI requires a lot of data, which is a challenge because data in the health sector tends to be limited in quantity and has disparities between diagnostic categories (data imbalance). To overcome this issue, DINO ViT models was trained with the publicly available COVID-19 Radiography Database in our previous study. The model was subsequently implemented into a web application, with this study focusing on the development of a prototype for the application. The study found this application can be useful for medical personnel and doctors in carrying out early screening and CAD. Meanwhile, it also highlighted the general unfamiliarity with AI applications among medical staff, emphasizing the need for increased education and training on AI's role in healthcare.

关键词： Training Solid modeling Design automation Pulmonary diseases Prototypes Radiology Predictive models computer aided diagnosis Artificial intelligence Medical diagnostic imaging

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Application of LDPE Film–Loaded Nutmeg Essential Oil Pickering Emulsion to Extend Tilapia Fillets’ Shelf Life

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Food and Bioprocess Technology 2024年第10期17卷 3031-3045页

作者： Yudhistira, Bara Chang, Chao-Kai Punthi, Fuangfah Cheng, Kuan-Chen Husnayain, Naila Hsieh, Chang-Wei Department of Food Science and Biotechnology National Chung Hsing University Taichung City402 Taiwan Department of Food Science and Technology Sebelas Maret University Surakarta City Central Java57126 Indonesia Institute of Biotechnology National Taiwan University Taipei10617 Taiwan Graduate Institute of Food Science Technology National Taiwan University Taipei10617 Taiwan Department of Optometry Asia University Taichung City413305 Taiwan Department of Medical Research China Medical University Hospital Taichung City404333 Taiwan International Master Program of Agriculture National Chung Hsing University Taichung City402 Taiwan

The food industry is still dependent on plastics for packaging materials, primarily due to their effectiveness in safeguarding products from external factors, such as moisture, light, and gas. However, traditional plastic packaging lacks the ability to actively preserve the quality and extend the shelf life of food. To address this challenge, various methods are currently being developed through surface modifications and the incorporation of active compounds. In most cases, studies on the modification of active film using low-pressure plasma (LPP) use different parameters, including time, pressure, and power, without a systematic optimization process. Therefore, this study aims to determine the optimum parameters for the combination of LPP treatment and Pickering emulsion (PE) of nutmeg essential oil (NEO) using Taguchi’s orthogonal assay design (OAD) to produce LDPE-active film. The results showed that the optimum conditions were 15 W LPP power, 30 s LPP duration time, and 1.5% PE-NEO concentration. These results showed a 50% improvement in power and time efficiency. LDPE film–loaded PE-NEO was then applied to tilapia fillets in cold storage. The results showed that the TBARS and TBVN values of the samples after the treatment were lower than those of the control by 12.11% and 16.74%, respectively. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Cold storage

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COCOMO II Analysis of Developing Multi-Account Partner Software for Crypto Exchange

COCOMO II Analysis of Developing Multi-Account Partner Softw...

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Advanced Applied Informatics Winter (IIAI-AAI-Winter), International Congress on

作者： Oscar Adam Darmawan Ford Lumban Gaol Haryono Soeparno Yulyani Arifin Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara University Jakarta Indonesia

The technique of calculating the work required for software development is known as software development estimation. The objective cost estimating technique for organizing and carrying out Multi Account Partner (MAP) software projects, COCOMO II, was employed in this study. The MAP software is a software architecture designed to support brokerage cryptocurrency exchanges using the order book and liquidity of established crypto exchanges. This research uses data sets from MAP project development at Indonesia Crypto Exchange Platform. It aims to create a software cost estimation model for MAP software using COCOMO II so that the resulting estimation model can be used as input or reference for estimates of subsequent MAP software development. The result estimated that MAP software finished in about four to five months, with a price range for software development of $7,441 to $8,780. Further research is needed with datasets from other crypto exchanges tested to increase cost estimation accuracy using COCOMO II.

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3D Image Generation from X-ray Projections Using Generative Adversarial Networks 23

3D Image Generation from X-ray Projections Using Generative ...

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23rd IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2023

作者： AlShurbaji, Mohammad Dhou, Salam Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9798350393118

The human brain can effortlessly imagine a 3D image from only 2D images with a little expertise and imagination, but for machines, this is not a trivial task. Because of this, reconstructing 3D images from 2D ones is a hot topic and has many applications. In this paper, we propose a Generative Adversarial Network (GAN)-based approach that generates CT-like images using pairs of orthogonal X-ray projections taken from different angles. In this work, a variety of orthogonal pairs from different angles, ranging from 0 &90 to 60 &150, were considered as input to the 3D image generation model. The effectiveness of the proposed method was assessed by measuring the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR), which resulted in values of 0.641 and 29.21, respectively. Furthermore, the model's ability to capture the respiratory motion in the input projections and reflect it in the generated images was also assessed. This work demonstrated the feasibility of generating CT-like images from X-ray projections captured from different orthogonal angles taking into consideration the respiratory motion exhibited in these projections. © 2023 IEEE.

关键词： Generative adversarial networks

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Vegetation Coverage and Urban Amenity Mapping Using computer Vision and Machine Learning

Vegetation Coverage and Urban Amenity Mapping Using Computer...

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3rd International Conference on Image Processing and Vision Engineering, IMPROVE 2023

作者： Karkut, Nicholas Kiriluk, Alexey Zhang, Zihao Zhu, Zhigang Computer Science Department The City College of New York - CUNY New YorkNY10031 United States Graduate Landscape Architecture Program The City College of New York - CUNY New YorkNY10031 United States PhD Program in Computer Science The Graduate Center - CUNY New YorkNY10016 United States

ISBN: (纸本)9789897586422

This paper proposes a computer vision-based workflow that analyses Google 360-degree street views to understand the quality of urban spaces regarding vegetation coverage and accessibility of urban amenities such as benches. Image segmentation methods were utilized to produce an annotated image with the amount of vegetation, sky and street coloration. Two deep learning models were used -- Monodepth2 for depth detection and YoloV5 for object detection -- to create a 360-degree diagram of vegetation and benches at a given location. The automated workflow allows non-expert users like planners, designers, and communities to analyze and evaluate urban environments with Google Street Views. The workflow consists of three components: (1) user interface for location selection;(2) vegetation analysis, bench detection and depth estimation;and (3) visualization of vegetation coverage and amenities. The analysis and visualization could inform better urban design outcomes. © 2023 by SCITEPRESS – science and Technology Publications, Lda.

关键词： Vegetation mapping

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Towards a Healthy AI Tradition: Lessons from Biology and Biomedical science

arXiv

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arXiv 2024年

作者： Kasif, Simon Department of Biomedical Engineering Bioinformatics Graduate Program Department of Computer Science Boston University United States Department of Computer Science Tel Aviv University

AI is a magnificent field that directly and profoundly touches on numerous disciplines ranging from philosophy, computer science, engineering, mathematics, decision and data science and economics, to cognitive science, neuroscience and more. The number of applications and impact of AI is second to none and the potential of AI to broadly impact future science developments is particularly thrilling. While attempts to understand knowledge, reasoning, cognition and learning go back centuries, AI remains a relatively new field. In part due to the fact it has so many wide-ranging overlaps with other disparate fields it appears to have trouble developing a robust identity and culture. Here we suggest that contrasting the fast-moving AI culture to biological and biomedical sciences is both insightful and useful way to inaugurate a healthy tradition needed to envision and manage our ascent to AGI and beyond (independent of the AI Platforms used). After all, the human brain is a biological organ produced by evolution and human intelligence is a remarkable bi-product of nature and nurture and their complex interaction. In this perspective, we focus on traditions and culture, namely the commonly observed practices of evaluating, recognizing applauding, critiquing, debating and managing all progress including useful advances and discovery of challenging limitations. We are not discussing specific scientific exchanges between AI and Biology that include interdisciplinary cross fertilization of scientific methods, technology, ideas and applications that have been amply demonstrated and will continue to be transformative in the future. In a previous perspective, we suggested that biomedical laboratories or centers can usefully embrace logistic traditions in AI labs that will allow them to be highly collaborative, improve the reproducibility of research, reduce risk aversion and produce faster mentorship pathways for PhDs and fellows. This perspective focuses on the benefits of AI a

关键词： Biological organs

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Feasibility Analysis Study on Constructing a Grid Intrusion Detection System Using Semi-supervised Learning Models 2nd

Feasibility Analysis Study on Constructing a Grid Intrusion ...

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

作者： Tsai, Chia-Wei Lin, Jason Yang, Chun-Wei Loo, Fu-Nie Department of Computer Science and Information Engineering National Taichung University of Science and Technology No.129 Sec.3 Sanmin Rd North District Taichung404 Taiwan Department of Computer Science and Engineering National Chung Hsing University No. 145 Xingda Rd. South District Taichung40227 Taiwan Master Program for Digital Health Innovation China Medical University No. 100 Sec. 1 Jingmao Rd. Beitun Dist. Taichung406040 Taiwan

ISBN: (纸本)9789819777853

In recent years, due to the proliferation of information and communication technology, as well as AI technology, industrial control systems, which were once in a closed network environment, have also integrated related technologies and gradually connected to external networks. Although this can enhance the efficiency of industrial production, it greatly increases the information security threats to industrial control systems. Among them, the information security issues of critical infrastructures are a key issue. If these critical infrastructures are attacked by cyber hackers, it could pose threats that jeopardize the safety of the general population. In light of this, this study focuses on the critical infrastructure of the power grid, proposing a semi-supervised intrusion detection system (IDS) technology by using the one-class classification. It analyzes data from the electricity distribution system to assess whether the system has been attacked. This research employs a power grid dataset to train the proposed model and execute the experiments. The experimental results demonstrate the feasibility of the proposed method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Network intrusion

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A Review on Collaborative Filtering Using Geographical Information 8

A Review on Collaborative Filtering Using Geographical Infor...

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8th International Conference on Information Technology and Digital Applications, ICITDA 2023

作者： Pohan, Husni Iskandar Sutoto Heryadi, Yaya Prabowo, Harjanto Bina Nusantara University Binus Graduate Program Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Indonesian Hospital Accreditation Commision Jakarta Indonesia Jakarta12960 Indonesia Binus Business School Doctor of Research in Management Management Department Jakarta11480 Indonesia

ISBN: (纸本)9798350344691

Since the corona pandemic, many internet users have maximized their interactions with the internet to minimize face-to-face meetings. As a result, many collaborative filtering algorithms, which are part of recommender systems, have been optimized so that users can obtain the best results. Collaborative filtering is an approach to providing recommendations that relies on the interactions and preferences of past users. Essentially, recommendations are generated by considering how users with similar preferences and behaviors have interacted. There are two primary forms of collaborative filtering: user-user and item-item. User-user collaborative filtering suggests recommendations based on users who share similar preferences with the current user. On the other hand, item-item collaborative filtering suggests recommendations based on items that are frequently selected together by other users. Both types of collaborative filtering rely on user interaction and preference data to deliver effective results. The latest trend related to collaborative filtering involves the use of geographic information. This paper aims to map the research developments related to collaborative filtering with geographic information in recent years, including the algorithms used, implementation issues, and challenges faced. Our hope is that this research can provide an overview of where this technology is heading. © 2023 IEEE.

关键词： Recommender systems

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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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AI-Based Feature Extraction and Cosine Similarity for Automation of Student Learning Assessment 24

AI-Based Feature Extraction and Cosine Similarity for Automa...

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24th International Arab Conference on Information Technology, ACIT 2023

作者： Wijanarko, Bambang Dwi Bachtiar Hassan, Rosilah Binti Murad, Dina Fitria Ihsan, Ridho Bramulya Heryadi, Yaya Kuncoro, Engkos Achmad Julianti, Eka Binus Online Learning Bina Nusantara University Computer Science Department Jakarta Indonesia Graduate School Universitas Terbuka Master of English Education Jakarta Indonesia Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Selangor Bangi43600 Malaysia Binus Online Learning Bina Nusantara University Information Systems Department Jakarta Indonesia Binus Online Learning Bina Nusantara University Manajemen Department Jakarta Indonesia Binus Graduate Program-Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia Binus Business School Undergraduate Program Bina Nusantara University Management Department Jakarta Indonesia Universitas Terbuka Information System Department Jakarta Indonesia

ISBN: (纸本)9798350384307

This research is ongoing research into the student learning process which aims to develop artificial intelligence-based technology to calculate essay exam scores automatically, based on the textual proximity of students' answers to the answer key. This research uses an approach based on natural language processing (NLP) and text analysis. Feature extraction was carried out using the BERT model and similarity comparison using the Cosine distance method. Model evaluation was carried out using sensitivity and specificity tests. The model evaluation results show a sensitivity of 98.21%, which means this assessment model is able to detect positive cases well. © 2023 IEEE.

关键词： artificial intelligence BERT essay exam score natural language processing transformer

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