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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Pratama, Ilham Fitrah Eka Mantoro, Teddy Wijayanti, Rika Persadha, Pratama Dahlian Postgraduate Program of Medical Intelligence National Intelligence College Bogor Indonesia Sampoerna University Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

Cybersecurity threats affect all sectors of the economy, especially the chemical industry. The chemical industry is a critical infrastructure vulnerable to cyberattacks. In addition to financial and reputational losses, they can also cause serious accidents (such as loss of control of hazardous materials) with serious consequences for workers, society, and the environment. Industrial control panel systems are typically embedded in a variety of physical devices. The safety of control systems is crucial for ensuring the secure functioning of industrial chemical processes. Nevertheless, the susceptibility of control systems to cyber-attacks has intensified due to the extensive deployment of actuators, sensor measurements, and wireless communications. These attacks have the potential to propagate swiftly and result in severe industrial accidents. This study was conducted as part of a systematic literature review. The purpose of this study is to analyze cybersecurity threats to the chemical industry. Research shows that although cyber attacks are highly vulnerable to the chemical industry, they can be detected through neural network-based integration (NN) without having to know the process model when large quantities of historical data are available and easy to apply. It has been shown that it can be done. It is hoped that the policy recommendations obtained from this research will provide more effective guidelines for protecting the chemical industry from the risks of cyber threats. © 2023 IEEE.

关键词： Chemical industry

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A Machine Learning-Based Approach to Calibrate Low-Cost Particulate Matter Sensors 12

A Machine Learning-Based Approach to Calibrate Low-Cost Part...

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12th Brazilian Symposium on Computing Systems Engineering, SBESC 2022

作者： Pastorio, Andre F. Spanhol, Fabio A. Martins, Leila D. De Camargo, Edson T. Graduate Program in Computer Science Cascavel Brazil Toledo Brazil Londrina Brazil

ISBN: (数字)9781665474252

ISBN: (纸本)9781665474252

Low-cost particulate matter (LC-PM) sensors have been studied around the world as a viable alternative to expensive reference stations for monitoring air quality. However, LC-PM sensors require periodic calibration, since their data are often inaccurate and subject to uncertainty. Sensors calibration can be performed through machine learning methods where the sensor is placed in a real environment subject to the local environmental conditions of the place and its measurement compared to a reference equipment. This work evaluates different machine learning methods in five different models of LC-PM sensors, aiming to select the most appropriate sensor and a calibration method to be used in a low-cost air quality station in the context of smart cities. © 2022 IEEE.

关键词： Calibration

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The Utilization of Fuzzy Logic and Bollinger Bands to Enhance Trading Decision-Making During the Bitcoin Halving Phase 9th

The Utilization of Fuzzy Logic and Bollinger Bands to Enhanc...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Darmawan, Oscar Adam Heryadi, Yaya Lukas Wulandhari, Lili Ayu Sonata, Ilvico Computer Science Department Binus Graduate Program Bina Nusantara University Jakarta11480 Indonesia Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

The volatile behavior of Bitcoin's price, especially during its halving periods, poses considerable obstacles for forecasting and decision-making in cryptocurrency trading. This paper presents a novel method that combines application fuzzy logic with Bollinger Bands to improve trading decision-making in times of high market volatility. This study conducted an experiment utilizing three fuzzy logic controllers and Bollinger Bands (BB) to determine the strength of buy, hold, and sell signals. This dataset includes the initial and final prices that are used to calculate the BB. The raw and computed values serve as the precise input parameters for the Fuzzy Inference System (FIS). The membership functions were categorized into four levels: very low, low, high, and very high, based on the input default settings utilized by traders. Rulesets were created using fuzzy logic to produce signals that indicate the level of strength of a trading advice. This study evaluate the effectiveness of this hybrid method in comparison to the traditional utilization of the Bollinger Band only indicator and Moving Average Convergence Divergence (MACD) indicator, which is widely favored by traders to identify possible market fluctuations. This methodology involves creating a trading simulation that is based on past Bitcoin halving events. The objective is to assess the efficacy of these strategies in managing heightened volatility. The application of fuzzy logic with the Bollinger Bands model yielded a success rate of 92.47% while analyzing 93 daily data points from the previous Bitcoin halving event on May 11, 2020. © 2024 The Authors.

关键词： Costs

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Benefits and Threats of Telemedical Application in Psychiatric Services 1

Benefits and Threats of Telemedical Application in Psychiatr...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Martaningga, Farra Mantoro, Teddy Andoko, Djoko Postgraduate Program of Medical Intelligence National Intelligence College Bogor Indonesia Sampoerna University Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

Health development is one part of national development. Telemedical is an innovation in engineering and computing application technology healthcare in the era of society 5.0 is needed as a supporting tool. The purpose of this paper is to explain the benefits and threats of using telemedicine in the field of psychiatry in the care system. This study uses a qualitative descriptive method, data collection by literature study, which is a method that explains a phenomenon regarding the benefits and threats of telemedicine in psychiatric services. Telepsychiatry is a health service carried out by mental medicine specialists using information and communication technology to diagnose, treat and estimate the patient's health condition in accordance with their ability and authority as evidenced by the validity of the Registration Certificate (STR) and Practice Permit (SIP) while maintaining service quality and patient safety. Telepsychiatry is carried out by mental medicine specialists with other doctors, or mental medicine specialists with patients in a Health Service Facility (Fasyankes), or between Fasyankes. As a result of the dialogue, Telepsychiatry has demonstrated significant cost-effectiveness and efficiency as a viable option to conventional psychiatric services, increasing accessibility for patients seeking providers. Innovative advances in the field of mental healthcare technology solutions have the potential to provide substantial benefits to recipients and stakeholders. Threats to telemedicine, including telepsychiatry, include misuse of patients' personal data by employees or hacking by cybercriminals for purposes that jeopardise the security of patients and the country. Special attention should be paid to the problem of misuse and hacking of patient data in telemedicine by individuals and hackers. © 2023 IEEE.

关键词： Telemedicine

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The Role of Biosafety and Biosecurity in Biotechnology to Prevent Bioterrorism Threats 1

The Role of Biosafety and Biosecurity in Biotechnology to Pr...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Subariyah, Riski Mantoro, Teddy Ratmono, Barito Mulyo Postgraduate Program of Medical Intelligence National Intelligence College Bogor Indonesia Sampoerna University Department of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

'Society 5.0' is characterized as a high degree of integration of cyberspace and physical space capable of promoting economic growth and addressing social problems in a modern information society based on cutting-edge technology advancements for data processing and knowledge creation. Recent developments in the field of biotechnology have been demonstrated by gene editing techniques, especially CRISPR-Cas9, such as basic research, applied biotechnology, and biomedical research Most biotechnology is essentially 'dual use' because its development can result in both profitable and nefarious goals, all depending on the perspective and motivation of the perpetrator. The purpose of this research is a better understanding of biosecurity, biosecurity, and bioterrorism threats, so as to provide a foundation for policymakers, researchers, and health professionals to improve global health security so as to realize effective biodefense systems. The research was conducted by library research, namely data collection with literature studies. By implementing biosafety and biosecurity laboratory measures in accordance with established guidelines and guidelines can help protect people, animals, the environment, and national security. Medical intelligence is vital to monitoring and assessing the threat of bioterrorism through the process of data collection, which is then analyzed, and data dissemination. The medical intelligence community can help protect public safety and prevent bioterrorism by understanding and implementing strong biosafety and biosecurity practices in laboratories. Bioterrorism attacks that can occur at any time must be anticipated by medical intelligence by conducting research and assessment of bioterrorism threats, analyzing information so that it can be passed on to the government to take appropriate policies to be able to detect and monitor the spread of infectious diseases quickly, and developing strategies to prevent the spread of disease. Combining health s

关键词： Bioterrorism

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Integration of Government Regulations to Anticipate Terrorist Threats in the Misuse of Chemicals as Chemical Weapons 1

Integration of Government Regulations to Anticipate Terroris...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Wulandari, Retno Mantoro, Teddy Pasma, Satriani Aga Suliantoro, Dwi Sani National Intelligence College Postgraduate Program of Medical Intelligence Bogor Indonesia Sampoerna University Dept of Computer Science Jakarta Indonesia

ISBN: (纸本)9798350360554

Armed conflicts occur in various parts of the world and result in many casualties and material losses. Weapons of mass destruction are one of the most feared weapons, along with the emergence of chemical, nuclear, radiological, biological, and explosive weapons. The use of weapons of mass destruction is prohibited, but their production is still uncontrolled making it possible for various parties such as terrorists, to easily use available chemical weapons raw materials such as triacetone triperoxide (TATP) bombs and the like. In addition, chemical weapons whose distribution in liquid or gas form is not regulated by the Chemical Weapons Convention (CWC) can cause long-term damage, such as the risk of permanent burns or long-term illness and even infect victims after they expire. Of course, these cases represent a threat to national security due to the irresponsible availability of chemicals to the public or what are called man-made disasters. Therefore, similar incidents need to be avoided to minimize the damage they cause. Society 5.0 can leverage information and communication technology to strengthen early detection systems and prompt responses to terrorist threats involving the misuse of chemicals as chemical weapons. This research was conducted through a systematic literature review in the form identifying, assessing, and interpreting all findings on a research topic to answer research question. The aim of this research is to analyze strategies for preventing chemicals used as chemical weapons through controlling Law Number 9 of 2008. The results of the research show that the rules regarding the control and supervision of chemicals used as chemical weapons are still being enforcedand ineffective. Indonesia in general is still vulnerable to the circulation of chemicals. Therefore, it is necessary to optimize the role of all relevant stakeholders in forming and controlling the Indonesian chemical industry against the threat of dual use. © 2023 IEEE.

关键词： National security

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The Students' Performance of Digital Sustainable Development Education in Gaining Competitive Advantage in ASEAN's Business Competition in the Post-Pandemic Era 23

The Students' Performance of Digital Sustainable Development...

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6th International Conference on Software Engineering and Information Management, ICSIM 2023

作者： Pane, Murty Magda Siregar, Christian Character Building Development Center School of Computer Science Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Character Building Development Center Mass Communication Program Communication Department Faculty of Digital Communication and Hotel and Tourism Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450398237

This study is a preliminary one aims to find out the performance of the attitudes and behaviors of Binus University students towards sustainable development to gain the competitive advantages in ASEAN business competition in the post-pandemic era. It was taken using the convenience sampling technique to 225 students from varied semester and departments. It used the quantitative method (corrected item total correlations for both variables are 0.433 and 0.419 (>0.3), α for both are 0.750 and 0.773 (> 0.5)) with Likert scale to measure the performance of agree and disagree for managing and interpreting the data. The respondents are 250 students from varied semesters and departments. The performance of the most chosen variable of attitudes are: scale 4 is chosen by 44.44% and scale 5 is chosen by 35.56% of respondents. Whilst the performance of the most chosen variable of behaviors is: scale 4 is chosen by 39.56% and scale 5 is chosen by 27.56% of respondents. These results indicated that the sustainable development awareness of Bina Nusantara students tends to the level of moderate to high. © 2023 ACM.

关键词： Students

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YOLOS-MCI: Automating Microservices Coupling Index Calculation using Vision Transformers 9th

YOLOS-MCI: Automating Microservices Coupling Index Calculati...

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9th International Conference on computer science and Computational Intelligence, ICCSCI 2024

作者： Gintoro Heryadi, Yaya Lukas Wulandhari, Lili Ayu Sonata, Ilvico Computer Science Department BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

Microservice Architectures (MSA) provide flexibility and scalability in software development. However, accurately measuring the level of interdependence among Microservices continues to be a difficult task. Precisely evaluating this connection is essential for efficient MSA design, maintenance, and future development. Conventional techniques for assessing Microservice coupling are frequently done by hand, require a significant amount of time, and are susceptible to mistakes. This impedes the capacity to make well-informed judgments regarding the integration and adjustment of services. This study introduces a new method for automating the computation of the Microservice Coupling Index (MCI) by utilizing the You Only Look at One Sequence (YOLOS) object identification technique in combination with Vision Transformer (ViTs) technology. YOLOS is utilized for identifying constituents within Unified Modeling Language (UML) Component Diagrams, facilitating precise classification and effective assessment of coupling. The model exhibits varying performance over multiple Intersection over Union (IoU) thresholds and object sizes, with an average precision (AP) of 0.406 over IoU values ranging from 0.50 to 0.95. The maximum precision is achieved at an IoU of 0.50, with an AP of 0.709. The model demonstrates good performance in identifying smaller components, especially when evaluated at a 0.75 IoU threshold. However, it faces challenges in detecting small items, suggesting potential areas for improvement in future iterations. Initial results indicate that this automation greatly decreases the need for manual, labor-intensive tasks and enhances the precision of measuring coupling in MSA, hence facilitating effective decision-making in service integration and modification. Automating the computation of the coupling index has the potential to significantly influence the design and management of durable and readily controllable microservice architectures. © 2024 The Authors.

关键词： Software design

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Using CNN and Transformer Model for Unimodal Speech Emotion Recognition on MELD and IEMOCAP

Using CNN and Transformer Model for Unimodal Speech Emotion ...

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Advancement in Data science, E-learning and Information Systems (ICADEIS), International Conference on

作者： Clarence Aurelio Andry Chowanda 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

ISBN: (数字)9798331513320

ISBN: (纸本)9798331513337

Emotion Recognition is one field that is taking the world by storm in this current age. Multimodal emotion recognition has shown promising results however, previous studies shows that recognition using speech is a field has not performed that greatly. Previous research used popular methods such as CNN, RNN, and other machine learning methods has been used to achieved good results with the help of other modality, where if speech were to be used alone the results won't be as good. A factor that contributes to the result of the speech modality not performing as well is the fact of the dataset and the way it was processed. Therefore, this research looks into what makes speech one of the lowest performing modalities by preprocessing the dataset using a different method than previous researches as well as using a CNN model paired with a Transformer model. Results achieved from this research showed an improvement when using IEMOCAP by 8.09% and MELD by 1.06%. A comparison results of using the pre-processed data with previous studies model was also done to compare the results. In conclusion, this research has explored a different preprocessing method and deep learning model that has achieved results better than previous works with the same dataset.

关键词： Deep learning Hands Emotion recognition Storms Speech recognition Transformers Data models Mel frequency cepstral coefficient Speech processing Information systems

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Optimal Synergic Deep Learning for COVID-19 Classification Using Chest X-Ray Images

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computers, Materials & Continua 2023年第6期75卷 5255-5270页

作者： JoséEscorcia-Gutierrez Margarita Gamarra Roosvel Soto-Diaz Safa Alsafari Ayman Yafoz Romany F.Mansour Departament of Computational Science and Electronic Universidad de la CostaCUCBarranquilla080002Colombia Biomedical Engineering Program Universidad Simón BolívarBarranquilla080002Colombia Department of Computer Science and AI Faculty of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddahSaudi Arabia Department of Mathematics Faculty of ScienceNew Valley UniversityEl-Kharga72511Egypt

A chest radiology scan can significantly aid the early diagnosis and management of COVID-19 since the virus attacks the *** X-ray(CXR)gained much interest after the COVID-19 outbreak thanks to its rapid imaging time,widespread availability,low cost,and *** radiological investigations,computer-aided diagnostic tools are implemented to reduce intra-and inter-observer *** lately industrialized Artificial Intelligence(AI)algorithms and radiological techniques to diagnose and classify disease is *** current study develops an automatic identification and classification model for CXR pictures using Gaussian Fil-tering based Optimized Synergic Deep Learning using Remora Optimization Algorithm(GF-OSDL-ROA).This method is inclusive of preprocessing and classification based on *** data is preprocessed using Gaussian filtering(GF)to remove any extraneous noise from the image’s ***,the OSDL model is applied to classify the CXRs under different severity levels based on CXR *** learning rate of OSDL is optimized with the help of ROA for COVID-19 diagnosis showing the novelty of the *** model,applied in this study,was validated using the COVID-19 *** experiments were conducted upon the proposed OSDL model,which achieved a classification accuracy of 99.83%,while the current Convolutional Neural Network achieved less classification accuracy,i.e.,98.14%.

关键词： Artificial intelligence chest X-ray COVID-19 optimized synergic deep learning preprocessing public health

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