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International Seminar on Intelligent technology and Its Applications (ISITIA)

作者： Puput Dani Prasetyo Adi Iwan Purnama Arfanda Anugrah Siregar Angga Putra Juledi Firman Edi Abdul Karim Yuyu Wahyu Fairuz Iqbal Maulana Suhardi Atmoko Budi Susilo Toni Ilham Maliki Harahap Lintang Patria National Research and Innovation Agency (BRIN) Bandung Indonesia Faculty of Science and Technology Labuhanbatu University Labuhanbatu North Sumatra Indonesia Telecommunication Engineering Study Program Politeknik Negeri Medan Medan City North Sumatra Indonesia Department of Engineering Management Faculty of Industrial Technology Batam Institute of Technology Batam City Riau Islands Indonesia Department of Information Technology Budi Darma University Medan North Sumatra Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Teacher Training and Education Labuhanbatu University Labuhanbatu North Sumatra Indonesia Faculty of Engineering Universitas Terbuka Jakarta Indonesia

This research is an approach to intelligent vehicles with a LoRa communication system, LoRaWAN compatible for Long-Range and Outdoor Communication, but in this paper, we will test the ability of LoRa to handle autonomous vehicles, a Blind-Adaptive Data method will be tried on vehicles systems. The system offered is when the vehicle is running, the sensor will send position data in real-time, the number of vehicles is four, and GPS data is sent alternately using the Blind Adaptive Data Rate principle to avoid data collisions, and when the GPS shows a certain position, the value of SF is ascertained, which affects the data rate and ToA, and the output given is RSSI on each car, speed of a car, power consumption of sensor nodes, signal power, SNR, Bit rate or data rate, and sensitivity. With the Blind ADR principle, it is ensured that there is no data collision between car position data that causes packet loss.

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Hit Song Prediction based on Gradient Boosting Decision Tree 7

Hit Song Prediction based on Gradient Boosting Decision Tree

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7th NAFOSTED Conference on information and computer Science, NICS 2020

作者： Pham, Bang-Dang Tran, Minh-Triet Pham, Hoang-Long Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Record companies invest billions of dollars in new talent around the globe each year. Gaining insight into what actually makes a hit song would provide tremendous benefits for the music industry. In this research, we tackle this question by focusing on predicting rank of hit songs in the next 6 months. Our dataset is used in ZALO AI CHALLENGE 2019 in Hit Song Prediction problem including not only songs but also its information such as composer, artist name, released date, etc. Because of that, while most previous work formulates hit song prediction as a regression or classification problem, we present in this paper how to apply Gradient Boosting technique to treat it as a ranking problem. The resulting best model has a good performance when predicting whether a song is a top 10 dance hit versus a lower listed position with 1.48815 Root Mean Square Error - our result dominates most of the solution in this competition (better than 3rd ranked solution of 87 in total). Moreover, it is possible to further improve by extracting chords, tones and more information from each song to obtain the highlights of songs and by using linguistics model to offer high-level features of metadata. © 2020 IEEE.

关键词： Decision trees

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Vehicle Counting: Survey and Experiments 7

Vehicle Counting: Survey and Experiments

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7th NAFOSTED Conference on information and computer Science, NICS 2020

作者： La, Hoang-Phong Ha, Minh-Thao Nguyen, Hai-Long Nguyen, Manh-Thien Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Traffic management needs information about traffic to control the flow of transports. With millions of traffic video cameras acting as sensors around the world, collecting the information about traffic flow in real-time is quite easy, but using that information to process and control the traffic flow is a challenge. For detecting vehicles, old methods like inductive loop detectors (ILD), infrared detectors (IRDs), laser sensors, etc. have problems with high cost, efficiency, difficulty, etc. The methods we use in this paper are detection-based counting, regression-based counting. The authors propose a new method that is the combination of two methods above to achieve better results. We also evaluate the viability of using Deep Learning pre-trained models include Faster R-CNN, SSD, YOLO for detection-based. We experiment on 2018 AI CITY CHALLENGE datasets and Vehicles Nepal datasets. Our results show the effectiveness of the combining method in accuracy compares to using each of the methods separately. © 2020 IEEE.

关键词： Object detection

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Automated Waste Sorting Using Convolutional Neural Network 7

Automated Waste Sorting Using Convolutional Neural Network

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7th NAFOSTED Conference on information and computer Science, NICS 2020

作者： Huynh, Minh-Hieu Pham-Hoai, Phu-Thinh Tran, Anh-Kiet Nguyen, Thanh-Dat Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

The waste classification has become a crucial mission for sustaining worldwide economic growth and preserving the environment. Using deep learning to sort solid waste automatically is necessary since it could minimize the time taken to categorize a large amount of rubbish manually and health risks created by working with polluted waste. In this study, we take advantage of several Convolutional Neural Networks such as VGG, Resnet, Efficientnet, etc. to solve this problem. The test accuracies achieved by training Resnet101, EfficientNet-B0, and EfficientNet-B1 on the dataset of 6640 images are 92.43%, 90.02%, and 91.53% respectively. We also build an ensemble model on the base of these three models, which attains an accuracy of 94.11%. The dataset is from the Trashnet dataset of Stanford and images collected on the Internet. This approach can be potentially applied to real-life environmental problems. © 2020 IEEE.

关键词： Statistical tests

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Efficient One-Shot Video Object Segmentation 7

Efficient One-Shot Video Object Segmentation

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7th NAFOSTED Conference on information and computer Science, NICS 2020

作者： Hoang-Xuan, Nhat Nguyen, E-Ro Pham-Le, Thuy-Dung Hoang-Nguyen, Khoi Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Video object segmentation is the problem of labelling the foreground object of interest that has widespread applications. We reevaluate One-shot Video Object Segmentation (OSVOS), a simple method that adapts VGG to image segmentation using a structure similar to a Fully Convolutional Network. We propose a range of improvements to make OSVOS competitive to newer methods while keeping its simplicity. Specifically, we replace VGG with EfficientNet, and adopt the U-net architecture. We also utilize Focal Loss and Dice Loss to handle the imbalanced binary classification, and finally we remove the boundary snapping module. With our amendments, we achieve 82.4% J&F on DAVIS 2016 validation set, an improvement over the original 80.2% of OSVOS. We also achieve much faster inference time per frame than OSVOS. © 2020 IEEE.

关键词： Image segmentation

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Facial Expression Recognition in the Wild: Efficiency of Modified-Category and Ensemble Learning Methods 7

Facial Expression Recognition in the Wild: Efficiency of Mod...

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7th NAFOSTED Conference on information and computer Science, NICS 2020

作者： Bui-Xuan, Bao Nguyen-Hoang, Bao-Minh Truong, Cong-Anh Nguyen-Tran, Quang-Duy Advanced Program in Computer Science Faculty of Information Technology University of Science Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9780738105536

Human facial expression plays a significant role in the medical field, the automotive industry, and so on. Recent research and achievements in recognizing the expressions by using CNNs have been published, conducted on old datasets, i.e. CKP, FER+, etc. However, those are unnatural and less challenging. We authors propose two methods to deal with a new and more realistic dataset called CAER-S first introduced in ICCV 2019. Instead of using the original images of CAER-S, we prepare our dataset by extracting the faces to focus mainly on facial expressions. The first method is to merge some categories sharing the most mispredictions mutually. Nonetheless, the results are indecisive to conclude this method's efficiency. The other is to use plenty of pre-trained models to find the best three of them for ensembles. The ensembles are weighted majority voting and soft voting. These are applied to fuse the three models' results to return the final one whose accuracy is higher than each's separately. This work contributes to advanced facial expression recognition research, especially with using the new dataset CAER-S. © 2020 IEEE.

关键词： Automotive industry

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A model to optimize palm oil biomass supply chain by considering production traceability information

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AIP Conference Proceedings 2023年第1期2714卷

作者： Heru Pranoto Muhammad Zarlis Syahril Efendi Herman Mawengkang Doctoral Program of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Faculty of Mathematics and Natural Sciences Universitas Sumatera Utara Medan Indonesia

Due to the global situation, it is necessary for an industrial company to integrate production scheduling and traceability planning, in a way to get more reliable stand and to make economics advantages. This paper presents biomass supply chain company which could produce a renewable energy. Traceability is a tracking requirement to check whether the quality of the product is satisfied. The supply chain of biomass planning problem aims to meet customer demand subject to traceability and other restrictions. The problem is modelled as a mixed integer linear program, and then it is solved using neighborhood search approach.

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Convolutional Neural Network-based Keyword Classification for Mixer Control

Convolutional Neural Network-based Keyword Classification fo...

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International SoC Design Conference, ISOCC

作者： Ying-Hsiu Hung Yen-Ching Chang Suz-Ting Wang Jeng-Dao Lee Wen-Ho Juang Ming-Hwa Sheu Shin-Chi Lai Dept. Electronics Engineering National Yunlin University of Science and Technology Douliu Taiwan Dept. Doctor’s Program of Smart Industry Technology Research and Design National Formosa University Huwei Taiwan Dept. Doctor’s Program of Smart Industry National Yunlin University of Science and Technology Douliu Taiwan Dept. Automation Engineering National Formosa University Huwei Taiwan Dept. Computer Science and Information Engineering National Formosa University Huwei Taiwan Dept. Automation Engineering & Smart Machinery and Intelligent Manufacturing Research Center National Formosa University Huwei Taiwan

This study proposed a keyword recognition of microphone feed-in, achieving the effect of allowing users to control the real-time mixer system intelligently. The proposed system structure includes a front-end circuit to capture voice and Mel-scale Frequency Cepstral Coefficients (MFCC) features in conjunction with a Convolutional Neural Network (CNN) algorithm. The testing results show that the lightweight CNN model achieves a keyword recognition accuracy rate of 96.4%.

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Energy Preservation in MANET Using Self-Adaptive CH Selection with Advanced Genetic Algorithm

Energy Preservation in MANET Using Self-Adaptive CH Selectio...

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Advanced Engineering and Technologies (ICONNIC), International Conference on

作者： Bonifacius Vicky Indriyono Natalinda Pamungkas Fatima Hashim Abbas Ery Mintorini Mohammed Almohamadi Sarmad Nozad Mahmood Sameer Alani Ahmed H. Alkhayyat Eko Hari Rachmawanto Information System University of Dian Nuswantoro Kediri Indonesia Medical Laboratories Techniques Department Al-Mustaqbal University College Hillah Babil Iraq Visual Communication Design University of Dian Nuswantoro Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq Medical Laboratories Techniques University of Mashreq Research center Baghdad Iraq College of technical engineering University of Mashreq The Islamic University Najaf Iraq Study Program in Informatics Engineering University of Dian Nuswantoro Semarang Indonesia

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments; they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD.

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FluxProg 2.0 - Teaching Introductory programming Using Flowcharts with Real and Simulated Robots for The Brazilian Robotics Olympiad (OBR)

FluxProg 2.0 - Teaching Introductory Programming Using Flowc...

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IEEE Latin American Robotics Symposium, LARS

作者： João Alberto Fabro Matheus Biscaya Gutierrez Fernando Henrique Ratusznei Caetano DAINF - Academic Department of Informatica PPGCA - Graduate Program on Applied Computing LASER-Laboratory for Advanced Robotics and Embedded Systems UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Information Systems academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil Computer Engineering academic - UTFPR - Federal University of Technology - Paraná Curitiba PR - Brazil

ISBN: (数字)9781665462808

ISBN: (纸本)9781665462815

In this paper, an approach to aid in introductory programming courses is presented, focused on students that had never had any contact with computer programming. The approach, that was introduced in a previous paper [3], presents programming concepts using icons and “flowcharts”, and a 3D robotics simulator (CoppeliaSim), that has free educational use. This time, a real version of the simulated robot, built using Arduino and cheap, easily obtainable electronic components, is also presented. The programs to control the robot are developed by graphically constructing flowcharts on the visual editor, and then following the execution of programs using the simulated (or real) robot, step by step. This graphic program editor is named “FluxProg”, and its 2nd version is now available online, with new features comprising variables, arithmetic and logic expressions, thus providing a complete programming environment.

关键词： Flowcharts Visualization Three-dimensional displays Conferences Education Electronic components Robots

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