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

Procedia computer science 2019年 157卷 375-381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

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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Classification of the Structural Integrity by the General Vibration Method

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Procedia computer science 2019年 157卷 382-387页

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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The matter of deep reinforcement learning towards practical ai applications 12

The matter of deep reinforcement learning towards practical ...

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12th International Conference on Ubi-Media Computing, Ubi-Media 2019

作者： Thaipisutikul, Tipajin Chen, Yi-Cheng Hui, Lin Chen, Sheng-Chih Mongkolwat, Pattanasak Shih, Timothy K. Department of Computer Science and Information Engineering National Central University Taiwan Department of Information Management National Central University Taiwan Department of Innovative Information and Technology Tamkang University Taiwan Master's Program of Digital Content and Technologies College of Communication National ChengChi University Taiwan Faculty of Information and Communication Technology Mahidol University Thailand

ISBN: (纸本)9781728128207

Reinforcement Learning (RL) is an extraordinarily paradigm that aims to solve a complex problem. This technique leverages the traditional feedforward networks with temporal-difference learning to overcome supervised and unsupervised real-world problems. However, RL is one of state-of-the-art topic due to the opaque aspects in design and implementation. Also, in which situation we will get performance gain from RL is still unclear. Therefore, This study firstly examines the impact of Experience Replay in Deep Q-Learning agent with Self-Driving Car application. Secondly, The impact of Eligibility Trace in RNN A3C agents with Breakout AI game application is studied. Our results indicated that these two techniques enhance RL performance by more than 20 percent as compared with traditional RL methods. © 2019 IEEE.

关键词： Reinforcement learning

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Predicting Metabolic Syndrome With Machine Learning Models of Hybrid Analysis

Predicting Metabolic Syndrome With Machine Learning Models o...

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Yi-Syuan Wu Wei-Yun Wang Hao-Yi Wu Chao-Wen Chen Chi-Ming Chu Cheng-Wei Wu Department of Surgery Division of Trauma and Surgical Critical Care Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan Master Program of E-Learning for Multimedia and Network Communications National I-Lan University Yilan Taiwan Department of Nursing Tri-Service General Hospital Songshan Branch and School of Nursing National Defense Medical Center Taipei Taiwan Department of Nursing Tri-Service General Hospital National Defense Medical Center Taipei Taiwan Department of Surgery Trauma and Critical Care Service Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung Taiwan School of Public Health National Defense Medical Center Taipei Taiwan Department of Computer Science and Information Engineering National I-Lan University Yilan Taiwan

The study uses machine learning to determine the accuracy of different algorithms for predicting MetS. Early prediction of MetS through routine health screening is an important goal for preventive medicine. The subjects in this study were employees aged 20 to 65 years old who signed a consent form for in-hospital health screening data were collected from 2015 to 2020. Total of 3538 individuals who underwent health screening were included in this study. Baseline characteristics of the 315 participants diagnosed with metabolic syndrome and 3222 participants without metabolic syndrome. This is a machine learning approach to identify metabolic syndrome using biochemical values and lifestyle habits. We found that the F1 score for detection of metabolic syndrome by neural network is the most accurate and higher compared to other models. Our study also identified some new indicators, including heart rhythm, RBC, WBC, Hb, and uric acid, as candidates for better detection of metabolic syndrome.

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Study of runway crosswind and tailwind potential for airport sustainability: A study of Soekarno Hatta airport, Cengkareng, Indonesia

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： W Sardjono Zulkarnain H Kusnoputranto TEB Soesilo DN Utama J Sudirwan Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management BINA NUSANTARA University Jakarta Indonesia 11480 Post Graduate Program School of Environmental Science University of Indonesia Jakarta Indonesia Faculty of Public Health University of Infonesia Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 School of Information Systems Department BINUS Undergraduate Program Bina Nusantara University Jakarta Indonesia 11480

Airport runway designs must consider wind climatology to reduce the potential for crosswind and tailwind events that can cause accidents and aircraft delays. The large potential of crosswind and tailwind on a runway at the airport is very detrimental to aircraft passengers and airlines. Therefore, it is necessary to know the potential of crosswind and tailwind on the runway of Soekarno Hatta Airport and find the right parameters for the approximate direction and speed of the wind on the airport runway. Analysis was carried out using the direction and wind speed data from the Soekarno Hatta meteorological station in 2007-2017 to determine the potential for crosswind and tailwind on the runway of Soekarno Hatta airport and run a Weather Research and Forecasting (WRF) weather model to determine the parameterization of the right weather model for wind forecast at Soekarno Hatta airport. The highest maximum crosswind component in the 2007-2017 period occurred in August 30.53 knots, while the highest maximum tailwind of 25 knots occurred in January for a 250-degree runway and 24 knots occurred in August for a 070-degree runway. The potential for crosswind and tailwind is different every month. The scheme produces forecasts of wind direction and speed with a strong level of correlation with observations of wind direction and speed from the Soekarno Hatta meteorological station, the correlation value is 0.61. The most significant social impact of plane delays is time loss for passengers. While the economic impact on one of the crosswind events at Soekarno Hatta airport was an economic loss for one airline of US $ 43,392.

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Data Engineering Pipeline to Analyse Jakarta's Air Quality during COVID-19-Caused Lockdown Periods

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

作者： Reza Rahutomo Bens Pardamean Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Jakarta lifted up lockdown after passing more than 50 days of large-scale social activity restriction and initiated phase opening to new normal. To analyse Jakarta's air quality after passing lockdown, a pipeline of data engineering is needed. By acquiring time series data from ***, a time-series database system is developed with Python programming language and its fundamental libraries namely Pandas, NumPy, SQLite. After PM 2.5 data are pre-processed into average per-hour and grouped by applicable periods (pre-lockdown, lockdown, and phase opening), a pattern of PM 2.5 in South Jakarta is revealed by using data visualization library Matplotlib. The apex of PM 2.5 occurs earlier during lockdown (04:00) and phase opening (02:00) rather than when it was normal or pre-lockdown (08:00) even though the nadir of PM2.5 still occurs at the same time (16:00 – 17:00).

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Design Project Management System Based on SOA Approach

Design Project Management System Based on SOA Approach

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International Conference on Computation in science and Engineering, ICCSE 2017

作者： Girsang, Abba Suganda Jafar, Fahmi Fajar, Ahmad Nurul Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information System Computer Science Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

Application architecture and information technology systems in the company should be able to support the company's policy that leads to their alignment with the business objectives. The alignment of the implementation of information technology systems to the needs and goals of the organization will be able to be answered by taking into account the integration in the development, so that the gap of these two things can be minimized. As a company engaged in IT consulting, project management system is one form of application systems that support core business objective of the company: to produce high-quality software. Nevertheless, the project management system should be able to work together with other supporting information systems, so that the flow of information within the company can run effectively. To achieve these objectives, required the analysis and design of an integrated system, which can be achieved through a service-oriented architecture based system. which includes the stages of requirements and analysis, design and development, and the last is the IT operations. The final result expected is the design of the service-oriented architecture based project management system which built through top-down approach that focuses on improving the effectiveness of business process. © Published under licence by IOP Publishing Ltd.

关键词： Service oriented architecture (SOA)

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Testing Big Data Application

Testing Big Data Application

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Narinder Singh Punn Sonali Agarwal M. Syafrullah Krisna Adiyarta Indian Institute of Information Technology Allahabad Prayagraj India Program of Master of Computer Science Universitas Budi Luhur Indonesia

Today big data has become the basis of discussion for the organizations. The big task associated with big data stream is coping with its various challenges and performing the appropriate testing for the optimal analysis of the data which may benefit the processing of various activities, especially from a business perspective. Big data term follows the massive volume of data, (might be in units of petabytes or exabytes) exceeding the processing and analytical capacity of the conventional systems and thereby raising the need for analyzing and testing the big data before applications can be put into use. Testing such huge data coming from the various number of sources like the internet, smartphones, audios, videos, media, etc. is a challenge itself. The most favourable solution to test big data follows the automated/programmed approach. This paper outlines the big data characteristics, and various challenges associated with it followed by the approach, strategy, and proposed framework for testing big data applications.

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A Third Order based Additional Regularization in Intrinsic Space of the Manifold

A Third Order based Additional Regularization in Intrinsic S...

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Rakesh Kumar Yadav Abhishek Shekhar Verma S Venkatesan M. Syafrullah Krisna Adiyarta Indian Institute of Information Technology-Allahbad Prayagraj India Program of Master of Computer Science Universitas Budi Luhur Indonesia

Second order graph Laplacian regularization has the limitation that the solution remains biased towards a constant which restricts its extrapolation capability. The lack of extrapolation results in poor generalization. An additional penalty factor is needed on the function to avoid its over-fitting on seen unlabeled training instances. The third order derivative based technique identifies the sharp variations in the function and accurately penalizes them to avoid overfitting. The resultant function leads to a more accurate and generic model that exploits the twist and curvature variations on the manifold. Extensive experiments on synthetic and real-world data set clearly shows that the additional regularization increases accuracy and generic nature of model.

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Classification of Physiological Signals for Emotion Recognition using IoT

Classification of Physiological Signals for Emotion Recognit...

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International Conference on Electrical Engineering, computer science and Informatics (EECSI)

作者： Sadhana Tiwari Sonali Agarwal M. Syafrullah Krisna Adiyarta Indian Institute of Information Technology Allahabad Prayagraj India Program of Master of Computer Science Universitas Budi Luhur Indonesia

Emotion recognition gains huge popularity now a days. Physiological signals provides an appropriate way to detect human emotion with the help of IoT. In this paper, a novel system is proposed which is capable of determining the emotional status using physiological parameters, including design specification and software implementation of the system. This system may have a vivid use in medicine (especially for emotionally challenged people), smart home etc. Various Physiological parameters to be measured includes, heart rate (HR), galvanic skin response (GSR), skin temperature etc. To construct the proposed system the measured physiological parameters were feed to the neural networks which further classify the data in various emotional states, mainly in anger, happy, sad, joy. This work recognized the correlation between human emotions and change in physiological parameters with respect to their emotion.

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