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SSRN 2024年

作者： Tahyudin, Imam Rozaq, Hasri Akbar Awal Nambo, Hidetaka Department of Information System Faculty of Computer Science Amikom Purwokerto University Jl. Letjendpol Soemarto Banyumas Purwanegara 53127 Indonesia Graduate School of Informatics Faculty of Computer Science Gazi Üniversitesi Ankara Yenimahalle Turkey Graduate School of NST Division of Electrical Engineering and Computer Science Kanazawa University Kakumamachi Ishikawa Kanazawa920-1192 Japan

Plants are living things that have many secrets in them. One that is very interesting is how plants can communicate with the surrounding environment through the activities of the plants themselves. Then, from this communication activity, plants produce electricity, which we can use to study further the behavior of these plants, commonly known as bioelectric potential. This study has aim to analyze the ability of bioelectric potential of plant to response a room temperature in different condition. This research is analyzed using a deep learning algorithm, namely Long-Short Term Memory (LSTM). The data was recording using a modified amplifier and the output is signal data. The signal obtained is an analog signal which is then converted into a digital signal. The data that has been obtained is then transformed first before being analyzed using the Wavelet Transform method. The algorithm will be evaluated between the baseline and hyperparameter tuning models. The result showed that hyperparameter tuning has the smallest RMSE. Therefore, it is better than baseline model. © 2024, The Authors. All rights reserved.

关键词： Wavelet transforms

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Analysis of the Impact of an Execution Algorithm with an Order Book Imbalance Strategy on the Financial Market Using an Agent-based Simulation

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Transactions of the Japanese Society for Artificial Intelligence 2024年第4期39卷

作者： Endo, Shuto Mizuta, Takanobu Yagi, Isao Information and Computer Sciences Graduate School of Engineering Kogakuin University Japan SPARX Asset Management Co. Ltd Japan Department of Information Science Faculty of Informatics Kogakuin University Japan

One measure of financial markets is order book imbalance (OBI), defined as the number of buy orders minus the number of sell orders in the order book around the best quote. Thus, OBI is an indicator of an imbalance in supply and demand, which can potentially impact the price as price movements in the financial market. There is known to be a positive correlation between OBI and returns, and some investors attempt to exploit this characteristic to improve their investment performance. In financial markets, an investor sometimes want to place a large order. When the investor places the large order at one time, some other investors find out someone wants to trade large amount and trade ahead of time, or the market price gets rough and losses are incurred. Therefore, execution algorithms are used, by which a machine automatically divides orders into smaller lots to avoid distorting the market price. Execution algorithms could be expected to achieve improved performance when OBI is taken into account, but no such findings have been reported so far. One reason for the lack of research findings is that it is virtually impossible to measure the impact of OBI alone on the performance of execution algorithms, since there are many external factors that can affect financial markets. Multi-agent simulation is one way to solve problems that are difficult to analyse using empirical research and conventional methods. In a multi-agent simulation, individual actors in the world are regarded as agents and the behavioural rules and interactions of these agents constitute a model. In this context, a financial market constructed using multi-agent simulation is called an artificial market. In this study, we modelled an execution algorithm considering OBI, investigated how the model is affected by the market under several market patterns using artificial markets, and analysed the mechanism. The results showed that in stable markets, the performance of the execution algorithm with the OBI st

关键词： Financial markets

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On using Euler's Factorization Algorithm to Factor RSA Modulus 4

On using Euler's Factorization Algorithm to Factor RSA Modul...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Budiman, M.A. Zarlis, M. Sitompul, O.S. Mawengkang, H. Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

The RSA public key cryptosystem was among the first algorithms to implement the Diffie-Hellman key exchange protocol. At the core of RSA's security is the problem of factoring its modulus, a very large integer, into its prime factors. In this study, we show a step-by-step tutorial on how to factor the RSA modulus using Euler's factorization algorithm, an algorithm that belongs to the class of exact algorithms. The Euler's factorization algorithm is implemented in Python programming language. In this experiment, we also record the relation between the length of the RSA moduli and its factorization time. As a result, this study shows that the Euler's factorization algorithm can be used to factor small modulus of RSA, the correlation between the factoring time and the size of RSA modulus is directly proportional, and better selection of some Euler's parameters may lead to lower factoring time. © Published under licence by IOP Publishing Ltd.

关键词： Factorization

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Web Attack Detection Using the Input Validation Method:DPDA Theory

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computers, Materials & Continua 2021年第9期68卷 3167-3184页

作者： Osamah Ibrahim Khalaf Munsif Sokiyna Youseef Alotaibi Abdulmajeed Alsufyani Saleh Alghamdi Al-Nahrain University Al-Nahrain Nano Renewable Energy Research CenterBaghdadIraq Department of Management Information Systems Faculty of Science&Information TechnologyCyprus International UniversityNicosiaCyprus Department of Computer Science College of Computers and Information SystemsUmm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information Technology Taif UniversityTaif21944Saudi Arabia

A major issue while building web applications is proper input validation and *** can quickly exploit errors and vulnerabilities that lead to malicious behavior in web application validation *** are rapidly improving their capabilities and technologies and now focus on exploiting vulnerabilities in web applications and compromising ***-site scripting(XSS)and SQL injection attack(SQLIA)are attacks in which a hacker sends malicious inputs(cheat codes)to confuse a web application,to access or disable the application’s back-end without user *** this paper,we explore the problem of detecting and removing bugs from both client-side and server-side code.A new idea that allows assault detection and prevention using the input validation mechanism is *** addition,the project supports web security tests by providing easy-to-use and accurate models of vulnerability prediction and methods for *** these attributes imply a program statement that is vulnerable in an SQLIA,this can be evaluated and checked for a set of static code ***,we provide a script whitelisting interception layer built into the browser’s JavaScript engine,where the SQLIA is eventually detected and the XSS attack resolved using the method of input validation and script whitelisting under pushdown *** framework was tested under a scenario of an SQL attack and *** is demonstrated to offer an extensive improvement over the current *** framework’s main ability lies in the decrease of bogus *** has been demonstrated utilizing new methodologies,nevertheless giving unique access to sites dependent on the peculiarity score related to web *** proposed input validation framework is shown to identify all anomalies and delivers better execution in contrast with the current program.

关键词： Static dynamic detection prevention input validation deterministic push down automata

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Performance Upper Bound of the Grover-Mixer Quantum Alternating Operator Ansatz

arXiv

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arXiv 2024年

作者： Xie, Ningyi Xu, Jiahua Chen, Tiejin Saito, Yoshiyuki Asai, Nobuyoshi Cai, Dongsheng Graduate School of Science and Technology University of Tsukuba Japan School of Computing and Augmented Intelligence Arizona State University United States Graduate School of Computer Science and Engineering University of Aizu Japan School of Computer Science and Engineering University of Aizu University of Aizu Japan Faculty of Engineering Information and Systems University of Tsukuba Japan

The Quantum Alternating Operator Ansatz (QAOA) represents a branch of quantum algorithms designed for solving combinatorial optimization problems. A specific variant, the Grover-Mixer Quantum Alternating Operator Ansatz (GM-QAOA), ensures uniform amplitude across states that share equivalent objective values. This property makes the algorithm independent of the problem structure, focusing instead on the distribution of objective values within the problem. In this work, we prove the probability upper bound for measuring a computational basis state from a GM-QAOA circuit with a given depth, which is a critical factor in QAOA cost. From this, we derive the upper bounds for the probability of sampling an optimal solution and for the approximation ratio of maximum optimization problems, based on the objective value distribution. Using numerical analysis, we link the distribution to the problem size and build the regression models that relate the problem size, QAOA depth, and performance upper bound. Our results suggest that the GM-QAOA provides a quadratic enhancement in sampling probability and requires circuit depth that scales exponentially with problem size to maintain consistent performance. © 2024, CC BY.

关键词： Mixers (machinery)

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Physician Scheduling using Constraint Satisfaction programming

Physician Scheduling using Constraint Satisfaction Programmi...

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Electronics, Communications, and Computations (JAC-ECC), International Japan-Africa Conference on

作者： Hend A. Bakr Ahmed M. Salama Ahmed Fares Ahmed B. Zaky Biomedical Engineering Program Faculty of Engineering Cairo University Giza Egypt Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University Banha Egypt Computer science and information technology Programs Egypt-Japan University of Science and Technology (E-JUST) Alexandria Egypt On leave from Computer Systems Engineering Program Faculty of Engineering at Shoubra Benha University

Physician scheduling is a critical task that impacts the quality of patient care, staff satisfaction, and operational efficiency in healthcare institutions. The traditional approach to physician scheduling is manual and time-consuming, which can result in errors, staff burnout, and suboptimal schedules. To address these challenges, researchers have turned to optimization techniques like CSP, which has shown promise in solving physician scheduling problems. This paper reviews the existing literature on CSP for physician scheduling and highlights the benefits and limitations of this approach. CSP's benefits include generating schedules quickly and efficiently, incorporating complex constraints and preferences, and handling changes and disruptions in real time. However, CSP also has some limitations, such as the need for a formalized model and the fact that it may not always generate the most intuitive schedules. Overall, the findings suggest that CSP is a promising approach to physician scheduling that can produce high-quality schedules while minimizing staff burnout and improving operational efficiency.

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Realtime Vehicle Counting Method Using Haar Cascade Classifier Model

Realtime Vehicle Counting Method Using Haar Cascade Classifi...

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2021 International Conference on Advanced Mechatronics, Intelligent Manufacture and Industrial Automation, ICAMIMIA 2021

作者： Mimboro, Prasetyo Heryadi, Yaya Lukas Suparta, Wayan Wibowo, Antoni Bina Nusantara University Computer Science Faculty of Computer Science Jakarta Indonesia Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta Indonesia Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9781665499699

The proliferation of digital camera technology has provided many digital images for object detection and counting in public places. This paper presents an experiment on the realtime vehicle counting method to be implemented in a single board computer. The proposed design's objective is to detect and count vehicles entering and exiting at entrances using haar cascade classifier algorithms and other automatic open and close door systems controlled by a single board computer (SBC). The proposed system was tested using raspberry pi 4 model B with a 4GB RAM platform. The empiric results using 3-minute video as input with a total of 113 passing vehicles the proposed method achieve of 91.2 % of average accuracy. © 2021 IEEE.

关键词： computer vision

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Introduction to the HICSS-55 Collaboration for Data science Minitrack

Proceedings of the Annual Hawaii International Conference on...

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Proceedings of the Annual Hawaii International Conference on System sciences 2022年 2022-January卷 314-315页

作者： Zhou, Lina Paul, Souren Schwade, Florian Business Information Systems and Operations Management The University of North Carolina at Charlotte CharlotteNC28223 United States Graduate School of Computer & Information Sciences Nova Southeastern University 3301 College Avenue Fort LauderdaleFL33314 United States University of Koblenz-Landau Faculty of Computer Science Institute for IS Research Universitaetsstrasse 1 KoblenzD-56070 Germany

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Classification of Alzheimer’s Disease using Random Oversampling and Albumentations on Convolutional Neural Network

Classification of Alzheimer’s Disease using Random Oversamp...

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International Conference on Informatics and Computing (ICIC)

作者： Calvin Kamardi I Kadek Perry Bagus Laksana Maria Susan Anggreainy Nora Fitriawati Michiko Amaya Yonatan Tesalonika Abigail Eikwine Mangkang Vianny Pengesa Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia

Alzheimer’s Disease (AD) is a brain disorder that causes dementia and affects the memory, cognitive, and behavioral function. Early detection for AD can help to reduce the symptoms and slow down AD progression. Deep learning, particularly Convolutional Neural Network (CNN), a component of artificial intelligence, has demonstrated efficacy in resolving image-related issues and has gained widespread use in the analysis of medical images. CNN works well on large datasets, however, in imbalanced datasets, it can perform poorly by misclassifying minority classes. In this study, the random over-sampling technique is used to address the imbalance in the dataset, while Albumentations is used for image augmentation to prevent overfitting. The results demonstrate that the combination of these techniques leads to improved classification performance compared to traditional approaches. The proposed method has the potential to improve the accuracy of AD diagnosis and contribute to the development of effective treatments for this debilitating condition.

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Society with Trust: A Scientometrics Review of Zero-Knowledge Proof Advanced Applications in Preserving Digital Privacy for Society 5.0 1

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

作者： Dominic, Nicholas Pratama, Naufal Rizqi Cornelius, Kenny Senewe, Shavellin Herliman Pardamean, Bens Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Department of Computer Science Universitas Multimedia Nusantara Tangerang15111 Indonesia Psychology Department Faculty of Humanities Bina Nusantara University Jakarta11480 Indonesia BINUS Graduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (数字)9783031290787

ISBN: (纸本)9783031290770

Society 5.0 focuses on human productivity in the midst of advanced technological services. While the concept has human trust at its core, technology development is now leading to zero-trust architecture. In this scientometrics review, 107 selected papers were analyzed to obtain the nature of the Zero-knowledge Proof (ZKP) theory and its advanced applications to favor digital privacy in greater society. With the common literature review strategy, it was found that the most citations in this field appeared in 2018, with IEEE, Springer, and Elsevier as the top three publishers. By affiliations, China and United States are both leading countries where the researcher comes from. And as the positive trend emerged, the ZKP mechanism will keep being leveraged as one of the cryptographic toolsets in the cloud services, Internet of Things (IoT), smart contracts, healthcare, electronic systems, and many other industrial needs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Smart contract

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