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Prediction of traffic congestion based on time series dataset number of vehicles using neural network algorithm

AIP Conference Proceedings 2024年第1期2982卷

作者： Prasetyo Wibowo Yunanto Rahmat Gernowo Oky Dwi Nurhayati Doctoral Program of Information System Diponegoro University Jl. Imam Bardjo SH No.5 Semarang Indonesia Information Systems and Technology Universitas Negeri Jakarta Jl. Rawamangun Muka Jakarta Indonesia Department of Physics Diponegoro University Jl. Prof. H. Soedarto Semarang Indonesia Computer Engineering Department Diponegoro University Jl. Prof. H. Soedarto Semarang Indonesia

The increasing number of vehicles that was not accompanied by an adequate road infrastructure readiness causes traffic jams. Traffic jams often occur repeatedly every day, especially at certain times, such as when people are going to and from work. The same traffic jams can also occur at the beginning or the end of the week; this usually repeats every week. As a result, if the congestion dataset is known, the repeating traffic congestion for daily and weekly congestion can be anticipated. In this study, traffic congestion predictions are modeled using the Neural Network Algorithm based on traffic congestion data collected within 24 hours for one to two weeks. The parameters used in optimizing Neural Network performance are learning rate, momentum, and epochs (training cycles). Based on these experiments, the Neural Network Algorithm successfully modeled traffic density patterns which are recurring congestion patterns, with quite good results.

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A Study on Phase Shift Keying on 2-Sphere

A Study on Phase Shift Keying on 2-Sphere

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International Symposium on Computing and Networking Workshops (CANDARW)

作者： Sho Kakuwa Masahiro Fujii Graduate Program in Information Electrical and Electronics Systems Engineering Utsunomiya University Utsunomiya JAPAN

In this paper, we propose new modulation schemes to achieve high transmit energy efficiency. Although one of them has a cube shape on a 2-sphere and is equivalent to the conventional QPSK, the others whose symbol constellations are its twisted and crushed shapes can outperform QPSK. In comparison with QPSK, the proposed signal designs can reduce the required E b /N 0 by more than 0.25 dB at 10 -7 of the BER because it is possible to extend the minimum distance.

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The Evaluation of the Local Beer Industry during the COVID-19 Pandemic and Its Relationship with Open Innovation

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第3期8卷

作者： Ong, Ardvin Kester S. Pequeña, Arianne R. Prasetyo, Yogi Tri Chuenyindee, Thanatorn Buaphiban, Thapanat Persada, Satria Fadil Nadlifatin, Reny School of Industrial Engineering and Engineering Management Mapua University 658 Muralla St. Intramuros Manila 1102 Philippines School of Graduate Studies Mapúa University 658 Muralla St. Intramuros Manila 1002 Philippines Department of Industrial Engineering and Management Yuan Ze University 135 Yuan-Tung Road Chung-Li 32003 Taiwan Department of Industrial Engineering and Aviation Management Navaminda Kasatriyadhiraj Royal Air Force Academy Bangkok 10220 Thailand BINUS Business School Undergraduate Program Entrepreneurship Department Bina Nusantara University Jakarta 11480 Indonesia Department of Information Systems Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya 60111 Indonesia

The beer industry is one of the businesses affected during the COVID-19 pandemic. Despite the exponential growth of the beer industry throughout the years, this aspect of the beverage industry has gained limited attention and has been underexplored. This study aimed to provide a better and up-to-date understanding of Philippine-beer consumers to speed up its recovery. An online survey with 853 volunteer respondents was conducted to investigate Filipinos’ local beer consumption considering frequency, intake, expenses, and preference. A descriptive analysis of the consumers’ self-perceived evaluation of the changes in drinking showed a slight decrease in frequency, intake, and expenses and a minor change in preference. Somers’ d and the chi-squared test results indicated significant relationships between each demographic information (age, sex, and income) and frequency, intake, and expenses. In addition, a conjoint analysis with an orthogonal design indicated that price was the most important attribute (58.025%), followed by primary taste (12.452%), alcohol content (9.706%), mouthfeel (6.445%), aftertaste (6.355%), aroma (5.189%), and, lastly, color (1.827%). The findings of this study could be used as a baseline for improved product offerings, customized advertisements, and market segmentation. Moreover, the results of this study could be applied and extended by breweries to promote and create strategies. Lastly, this study could be extended and utilized by other beverage industries worldwide. © 2022 by the authors.

关键词： beer conjoint analysis consumer preference COVID-19 pandemic expenditure

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Predicting online item-choice behavior: A shape-restricted regression approach

arXiv

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arXiv 2020年

作者： Nishimura, Naoki Sukegawa, Noriyoshi Takano, Yuichi Iwanaga, Jiro Graduate School of Systems and Information Engineering University of Tsukuba Ibaraki305-8577 Japan Recruit Lifestyle Co. Ltd. Tokyo100-6640 Japan Department of Information and Computer Technology Tokyo University of Science Tokyo125-8585 Faculty of Engineering Information and Systems University of Tsukuba Ibaraki305-8577 Doctoral Program in Policy and Planning Sciences University of Tsukuba Ibaraki305-8577 Erdos Inc. Kanagawa222-0033

This paper examines the relationship between user pageview (PV) histories and their item-choice behavior on an e-commerce website. We focus on PV sequences, which represent time series of the number of PVs for each user-item pair. We propose a shape-restricted optimization model that accurately estimates item-choice probabilities for all possible PV sequences. This model imposes monotonicity constraints on item-choice probabilities by exploiting partial orders for PV sequences, according to the recency and frequency of a user's previous PVs. To improve the computational efficiency of our optimization model, we devise efficient algorithms for eliminating all redundant constraints according to the transitivity of the partial orders. Experimental results using real-world clickstream data demonstrate that our method achieves higher prediction performance than that of a state-of-the-art optimization model and common machine learning methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Graph theory

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Classification of the Structural Integrity by the General Vibration Method

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Procedia Computer Science 2019年 157卷 382-387页

作者： Fergyanto E. Gunawan Benfano Soewito Nico Surantha Tuga Mauritsius Nobumasa Sekishita Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Information Systems Information Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Department of Mechanical Engineering Toyohashi University of Technology Toyohashi Aichi 441-8580 Japan

Traditionally, for the purpose of classifying the integrity of an engineering structure, one may use the information of the natural frequencies or mode shapes or some other measures derived from the two. In this research, we propose a classification method on the basis of the general vibration model. The general vibration model is essentially a set of differential equations describing the dynamics of the structure under consideration. For the purpose of damage detection, a deviation of the general vibration model from the dynamic equilibrium point marks the occurrence of the damage. To demonstrate the effectiveness of the method, we study two simplest dynamical systems consisting of one- and two-concentrated masses subjected to a prescribed dynamic load. The structural damages are introduced artificially by reducing the stiffness of spring in the structures. We find that the general vibration model is more sensitive to damages than the traditional methods.

关键词： General Vibration Model Structural Integrity Structural Health Monitoring Power Spectral Density Damage Index

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A Study of the Sensitivity of the Fuel Consumption to Driving Strategy by Micro Simulation

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Procedia Computer Science 2019年 157卷 375-381页

Global warming due to excessive emission greenhouse gases is a significant issue faced by humanity, and collectively, cars and trucks contribute about 20% to the entire global-warming gases. For a reason, recently, many attempts have been endured to reduce the emission and to increase fuel efficiency, including vehicle platooning, better driving strategy, and increasing engine efficiency. This study intends to provide a more detail assessment regarding the effects of the driving strategy to fuel consumption. For the purpose, the vehicle dynamics are quantified by employing the car-following model based on the optimal velocity model. The fuel consumption is estimated from the regression model of Ahn 18 . The result suggests that the braking distance strongly affects fuel consumption.

关键词： Optimal Velocity Model Micro Simulation Car-Following Model Fuel Efficiency

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A Study on Transmission Efficiency of Systematic Spinal Codes

A Study on Transmission Efficiency of Systematic Spinal Code...

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International Symposium on Computing and Networking Workshops (CANDARW)

作者： Yota Katagishi Masahiro Fujii Department of Information Systems Science Utsunomiya University Utsunomiya Tochigi JAPAN Graduate Program in Information Electrical and Electronics Systems Engineering Utsunomiya University Utsunomiya Tochigi JAPAN

A spinal code is one of promising rate-less code by combining forward error collection with automatic repeat-request. In the decoding of the spinal code, a collision of codewords may degrade the transmission efficiency. The systematic coded spinal code can improve the transmission efficiency because of the avoidance of the collision of the codewords. In this paper, we compare the systematic spinal code with the conventional convolutional codes used in current communication systems and evaluate the transmission efficiency of the systematic spinal code. As a result, we show that the systematic spinal code has poor error correction capability although it can efficiently use the communication channel in the high SNR.

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information Security Risk Management Model for Peruvian SMEs

Information Security Risk Management Model for Peruvian SMEs

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2018 IEEE Sciences and Humanities International Research Conference, SHIRCON 2018

作者： Garcia-Porras, Chris Huamani-Pastor, Sarita Armas-Aguirre, Jimmy Universidad Peruana de Ciencias Aplicadas Information Systems Engineering Program Lima Peru

ISBN: (纸本)9781538683743

In this paper, we propose a risk management model of information security for Peruvian SMEs, taking as reference the OCTAVE-S methodology and the ISO / IEC 27005 standard. The model consists of the 3 phases of OCTAVE-S (Construction of the threats profile, Identification of infrastructure vulnerabilities, and Strategies and security plans). This model contains the contemplated lists of ISO / IEC 27005, it also contains the calculation and the risk treatment of this standard. Likewise, the model adopts a quantitative approach that allows calculating the residual risk, for example, the most critical asset identified obtained 216 of risk value and the residual risk obtained was 109 of risk value, this is obtained on the basis of the effectiveness of the controls that are part of the proposed model, for example, formalize procedures and policies and their occasional review. This model provides guidelines for information security risks for companies. It was implemented in the sales process of a Peruvian SME of the ceramic sector, proving to be easy to use and it was possible to identify the necessary controls to reduce the risk, whose implementation reduces the risk by 53%. © 2018 IEEE.

关键词： Security of data

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Accelerating Real-Time Imaging for Radiotherapy: Leveraging Multi-GPU Training with PyTorch

Accelerating Real-Time Imaging for Radiotherapy: Leveraging ...

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International Conference on Machine Learning and Applications (ICMLA)

作者： Ruth Obe Brandt Kaufmann Kaelen Baird Sam Kadel Yasmin Soltani Mostafa Cham Matthias K. Gobbert Carlos A. Barajas Zhuoran Jiang Vijay R. Sharma Lei Ren Stephen W. Peterson Jerimy C. PoIf Dept. of Computer Science and of Software Engineering U. of Houston-Clear Lake USA Dept. of Mathematics and Statistics U. of San Francisco USA Dept. of Computer Science and of Mathematics Skidmore College USA Dept. of Computer Science and of Psychology Mount Holyoke College USA Dept. of Biomedical Engineering U. of Houston USA Dept. of Information Systems U. of Maryland Baltimore County Dept. of Mathematics and Statistics U. of Maryland Baltimore County Medical Physics Graduate Program Duke University USA Dept. of Radiation Oncology U. of Maryland School of Medicine USA Department of Radiation Oncology U. of Maryland School of Medicine USA Dept. of Physics U. of Cape Town South Africa H3D Inc. USA

Proton beam therapy is an advanced form of cancer radiotherapy that uses high-energy proton beams to deliver precise and targeted radiation to tumors. This helps to mit-igate unnecessary radiation exposure in healthy tissues. Real-time imaging of prompt gamma rays with Compton cameras has been suggested to improve therapy efficacy. However, the camera's non-zero time resolution leads to incorrect interaction classifications and noisy images that are insufficient for accurately assessing proton delivery in patients. To address the challenges posed by the Compton camera's image quality, machine learning techniques are employed to classify and refine the generated data. These machine-learning techniques include recurrent and feedforward neural networks. A PyTorch model was designed to improve the data captured by the Compton camera. This decision was driven by PyTorch's flexibility, powerful capabilities in handling sequential data, and enhanced G PU usage. This accelerates the model's computations on large-scale radiotherapy data. Through hyperparameter tuning, the validation accuracy of our PyTorch model has been improved from an initial 7 % to over 60 %. Moreover, the PyTorch Distributed Data Parallelism strategy was used to train the RNN models on multiple G PU s, which significantly reduced the training time with a minor impact on model accuracy.

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Ecological Footprint Model of Soekarno-Hatta International Airport from the Perspective of the Local Community

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IOP Conference Series: Earth and Environmental Science 2021年第1期794卷

作者： Wahyu Sardjono Haryoto Kusnoputranto Tri Edhi Budhi Soesilo Kristanto Gabriel A. Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Department of Environmental Health Faculty of Public Health University of Indonesia Indonesia Post Graduate Program School of Environmental Science University of Infonesia Jakarta Indonesia Environmental Engineering Department Faculty of Engineering University of Indonesia Jakarta Indonesia

Soekarno-Hatta International Airport is prone to various environmental problems. The problem of population growth has an impact on increasing economic activity which directly impacts the environment. In every production activity from the environmental side, it will bring up the carrying capacity of the environment and the carrying capacity of the environment or ecological footprint. The problem will be difficult if it turns out that the ecological footprint that occurs exceeds the capacity of the existing environmental carrying capacity, also for airport problems. This will result in the airport being unsustainable. This article will discuss the model of the airport environmental footprint that is currently occurring at Soekarno-Hatta International Airport by utilizing the opinions of respondents who live and have activities around the airport. The factor analysis method is used to process the respondent's data to obtain the factors that influence the environmental footprint and then through these findings a model can be developed which is expected to be able to abstract the current conditions. The research results show that the dominant environmental footprint at Soekarno-Hatta airport is overload airport activities impact, operational slot time optimization, and renewable of airport energy, which can then be built as an instrument to evaluate, build and develop airport control policies that are environmentally friendly and sustainable.

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