Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00051
Benting Wan, Yu Qin, W. Song
The RRT algorithm is widely used in the high-dimensional path planning in a dynamic environment, and well adapted to the dynamics of motion of the mobile node needs. However, in large scale wireless sensor networks (WSN), the RRT algorithm lacks stability and is easy to deviate from the optimal path. In this paper we proposes a path planning algorithm called E-RRT to improve the problems that RRT has. The method proposed includes the coverage density of obstacle for initialize searching area for the exploring random tree, and the gradually extended region used to ensure the path to be found. The method also adopts the greedy algorithm to delete the intermediate point in the point sequence of path for an optimal path, and the quadratic Bezier curve to smooth the path for the mobile sensor node. The path found can be the shortest, collision-free and smoothing, and therefore to satisfy the requirement of path planning for mobile sensor nodes. The simulation results show that the E-RRT algorithm outperforms the RRT algorithm.
{"title":"Path Planning Strategy of Mobile Nodes Based on Improved RRT Algorithm","authors":"Benting Wan, Yu Qin, W. Song","doi":"10.1109/ICCIA.2018.00051","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00051","url":null,"abstract":"The RRT algorithm is widely used in the high-dimensional path planning in a dynamic environment, and well adapted to the dynamics of motion of the mobile node needs. However, in large scale wireless sensor networks (WSN), the RRT algorithm lacks stability and is easy to deviate from the optimal path. In this paper we proposes a path planning algorithm called E-RRT to improve the problems that RRT has. The method proposed includes the coverage density of obstacle for initialize searching area for the exploring random tree, and the gradually extended region used to ensure the path to be found. The method also adopts the greedy algorithm to delete the intermediate point in the point sequence of path for an optimal path, and the quadratic Bezier curve to smooth the path for the mobile sensor node. The path found can be the shortest, collision-free and smoothing, and therefore to satisfy the requirement of path planning for mobile sensor nodes. The simulation results show that the E-RRT algorithm outperforms the RRT algorithm.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131693232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00009
Mohammad Andad Ajiz Salam, K. Komarudin, A. R. Destyanto
Conveying product which has a limited shelf-life optimally is the concern of this study. The primary attribute of this product is perishable within a specific time frame. However, the perishable product has a critical issue in the cold chain system which leads dispatching costs inefficiency problems. Regarding this problem, a mathematical model built thru extended a vehicle routing problem, with soft time windows (VRPSTW) by considering energy consumption cost to evaluate its contribution towards the objective function. Model building conducted into computer programming that uses Python Spyder 3 for generating a feasible solution. For the sake of feasibility, a metaheuristic approach of genetic algorithms provided to find the best optimal solution; the results diagnosed that genetic algorithms can generate best feasible solution efficiently within a certain number of variables in case of perishable product delivery.
{"title":"Generating an Efficient Way of Dispatching Perishable Product Optimization through Exact and Metaheuristic Algorithm Comparison","authors":"Mohammad Andad Ajiz Salam, K. Komarudin, A. R. Destyanto","doi":"10.1109/ICCIA.2018.00009","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00009","url":null,"abstract":"Conveying product which has a limited shelf-life optimally is the concern of this study. The primary attribute of this product is perishable within a specific time frame. However, the perishable product has a critical issue in the cold chain system which leads dispatching costs inefficiency problems. Regarding this problem, a mathematical model built thru extended a vehicle routing problem, with soft time windows (VRPSTW) by considering energy consumption cost to evaluate its contribution towards the objective function. Model building conducted into computer programming that uses Python Spyder 3 for generating a feasible solution. For the sake of feasibility, a metaheuristic approach of genetic algorithms provided to find the best optimal solution; the results diagnosed that genetic algorithms can generate best feasible solution efficiently within a certain number of variables in case of perishable product delivery.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131710239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00047
Taichi Umeda, Y. Nozaki, M. Yoshikawa
Recently, the damage caused by semiconductor counterfeit has become a serious problem in our lives. Physical Unclonable Function (PUF) has attracted attention as a countermeasure method. In the countermeasures, a ring oscillator (RO) PUF is one of the most popular PUFs. Regarding tamper resistance of RO PUFs, Genetic Programming (GP) based attacks have been proposed. However, the GP based attacks only apply the basic genetic strategy. To evaluate tamper resistance of RO PUF accurately, improvement of GP based attack for RO PUF is important. Therefore, this study proposes an accurate attack which is based on GP using dynamic adaptive mutation.
{"title":"Dynamic Adaptive Mutation Based Genetic Programming for Ring Oscillator PUF","authors":"Taichi Umeda, Y. Nozaki, M. Yoshikawa","doi":"10.1109/ICCIA.2018.00047","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00047","url":null,"abstract":"Recently, the damage caused by semiconductor counterfeit has become a serious problem in our lives. Physical Unclonable Function (PUF) has attracted attention as a countermeasure method. In the countermeasures, a ring oscillator (RO) PUF is one of the most popular PUFs. Regarding tamper resistance of RO PUFs, Genetic Programming (GP) based attacks have been proposed. However, the GP based attacks only apply the basic genetic strategy. To evaluate tamper resistance of RO PUF accurately, improvement of GP based attack for RO PUF is important. Therefore, this study proposes an accurate attack which is based on GP using dynamic adaptive mutation.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130617608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00056
Pornsiri Chatpreecha, Sasiporn Usanavasin
The Attention Deficit Hyperactivity Disorder (ADHD) is a complex mental health disorder that affects children's learning activities and also their relationships with other children. There are various types of ADHD symptoms, which some of them can be easily recognized as indicators of having ADHD and some of them are difficult to specify as symptoms. Generally, the average age for diagnosing ADHD in children is around seven years old. It is better to early discover these symptoms in children and classify their ADHD types so appropriate and necessary treatments can be effectively applied to improve ADHD children’s behaviors and learning activities. The ADHD diagnosis takes a lot longer for children under six years old. This research aims to improve the ADHD diagnosis and attempt to discover symptoms and behavioral activities that can be the important indicators for classifying ADHD types of the children. Today, many parents share knowledge and experiences about their children in social networks. These shareable contents can be useful to help identify some ADHD symptoms as well as recommended treatments or activities for the children. Thus, in this work, we propose an approach to extract contents from social media (e.g., Facebook contents) in order to discover the information regarding ADHD symptoms and use this extracted information to classify ADHD types based on the behavioral symptoms and activities. To verify our results, we use three sets of criteria from the Diagnostic and Manual of Mental Disorders (DSM) that are used by many ADHD specialists and medical doctors. The three sets of criteria include SNAP-IV, Vanderbilt Assessment Scale, and KUS-SI. Our research goal is to provide a way to help parents to find relevant information and learn about ADHD types and their related symptoms as well as recommended activities for improving ADHD conditions in children.
{"title":"Extracting Social Network Contents to Classify ADHD Types Based on Behavioral Symptoms and Activities","authors":"Pornsiri Chatpreecha, Sasiporn Usanavasin","doi":"10.1109/ICCIA.2018.00056","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00056","url":null,"abstract":"The Attention Deficit Hyperactivity Disorder (ADHD) is a complex mental health disorder that affects children's learning activities and also their relationships with other children. There are various types of ADHD symptoms, which some of them can be easily recognized as indicators of having ADHD and some of them are difficult to specify as symptoms. Generally, the average age for diagnosing ADHD in children is around seven years old. It is better to early discover these symptoms in children and classify their ADHD types so appropriate and necessary treatments can be effectively applied to improve ADHD children’s behaviors and learning activities. The ADHD diagnosis takes a lot longer for children under six years old. This research aims to improve the ADHD diagnosis and attempt to discover symptoms and behavioral activities that can be the important indicators for classifying ADHD types of the children. Today, many parents share knowledge and experiences about their children in social networks. These shareable contents can be useful to help identify some ADHD symptoms as well as recommended treatments or activities for the children. Thus, in this work, we propose an approach to extract contents from social media (e.g., Facebook contents) in order to discover the information regarding ADHD symptoms and use this extracted information to classify ADHD types based on the behavioral symptoms and activities. To verify our results, we use three sets of criteria from the Diagnostic and Manual of Mental Disorders (DSM) that are used by many ADHD specialists and medical doctors. The three sets of criteria include SNAP-IV, Vanderbilt Assessment Scale, and KUS-SI. Our research goal is to provide a way to help parents to find relevant information and learn about ADHD types and their related symptoms as well as recommended activities for improving ADHD conditions in children.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133016624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00027
Heng Wang, Mingzhi Mao
The goal of knowledge representation learning is to embed entities and relations into a low-dimensional, continuous vector space. How to push a model to its limit and obtain better results is of great significance in knowledge graph's applications. We propose a simple and elegant method, Trans-DLR, whose main idea is dynamic learning rate control during training. Our method achieves remarkable improvement, compared with recent GAN-based method. Moreover, we introduce a new negative sampling trick which corrupts not only entities, but also relations, in different probabilities. We also develop an efficient way, which fully utilizes multiprocessing and parallel computing, to speed up evaluation of the model in link prediction tasks. Experiments show that our method is effective.
{"title":"Defeats GAN: A Simpler Model Outperforms in Knowledge Representation Learning","authors":"Heng Wang, Mingzhi Mao","doi":"10.1109/ICCIA.2018.00027","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00027","url":null,"abstract":"The goal of knowledge representation learning is to embed entities and relations into a low-dimensional, continuous vector space. How to push a model to its limit and obtain better results is of great significance in knowledge graph's applications. We propose a simple and elegant method, Trans-DLR, whose main idea is dynamic learning rate control during training. Our method achieves remarkable improvement, compared with recent GAN-based method. Moreover, we introduce a new negative sampling trick which corrupts not only entities, but also relations, in different probabilities. We also develop an efficient way, which fully utilizes multiprocessing and parallel computing, to speed up evaluation of the model in link prediction tasks. Experiments show that our method is effective.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122944973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00029
Xiaoan Yan, M. Jia
This paper develops a novel fault detection method for rolling bearing based on morphological multiscale dispersion entropy (MMDE). MMDE is mainly made up of two parts (i.e. morphological filtering and multiscale dispersion entropy (MDE)). Concretely, the original vibration data under different fault status is first preprocessed by morphology-hat product operation (MHPO). Afterwards, MDE of the filtered signal is calculated for the purpose of feature extraction under multi-fault conditions. Finally, the constructed fault feature matrix is fed into particle swarm optimization-based support vector machine (PSO-SVM) for realizing the identification of different bearing fault conditions. The efficacy of the presented method is validated by applying the experimental examples. Results demonstrate that MMDE can work more effectively in recognizing bearing fault type than several popular entropies (e.g. MDE, MPE and MSE).
{"title":"A Novel Intelligent Fault Detection Scheme for Rolling Bearing Based on Morphological Multiscale Dispersion Entropy","authors":"Xiaoan Yan, M. Jia","doi":"10.1109/ICCIA.2018.00029","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00029","url":null,"abstract":"This paper develops a novel fault detection method for rolling bearing based on morphological multiscale dispersion entropy (MMDE). MMDE is mainly made up of two parts (i.e. morphological filtering and multiscale dispersion entropy (MDE)). Concretely, the original vibration data under different fault status is first preprocessed by morphology-hat product operation (MHPO). Afterwards, MDE of the filtered signal is calculated for the purpose of feature extraction under multi-fault conditions. Finally, the constructed fault feature matrix is fed into particle swarm optimization-based support vector machine (PSO-SVM) for realizing the identification of different bearing fault conditions. The efficacy of the presented method is validated by applying the experimental examples. Results demonstrate that MMDE can work more effectively in recognizing bearing fault type than several popular entropies (e.g. MDE, MPE and MSE).","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128473235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.1109/ICCIA.2018.00023
Kailun He, Wenbo Xia, Xiuli Bao, Zhiyi Jiang
Enterprise bargaining power index is an important basis for solving the problem of alliance profit by using game theory. Study on bargaining ability evaluation is beneficial to logistics alliance development and the optimization and integration of logistics resources. This paper designs the evaluation index system of enterprise bargaining power in logistics alliance from five aspects: alliance enterprise value, learning ability, resources and skills input, skills dependence and termination cost. Using the experts evaluation to provide the index data and the analytic hierarchy process to determine the index weight. Fuzzy comprehensive evaluation is carried out to get the evaluation value of the bargaining power of ten enterprises in a regional logistics alliance. Taking index data and evaluation results of fuzzy evaluation as input and output item, using the BP neural network training fuzzy evaluation system, and then it will provide enterprises with a powerful evaluation tool.
{"title":"Research on Evaluation of Bargaining Ability in Logistics Alliance Enterprises","authors":"Kailun He, Wenbo Xia, Xiuli Bao, Zhiyi Jiang","doi":"10.1109/ICCIA.2018.00023","DOIUrl":"https://doi.org/10.1109/ICCIA.2018.00023","url":null,"abstract":"Enterprise bargaining power index is an important basis for solving the problem of alliance profit by using game theory. Study on bargaining ability evaluation is beneficial to logistics alliance development and the optimization and integration of logistics resources. This paper designs the evaluation index system of enterprise bargaining power in logistics alliance from five aspects: alliance enterprise value, learning ability, resources and skills input, skills dependence and termination cost. Using the experts evaluation to provide the index data and the analytic hierarchy process to determine the index weight. Fuzzy comprehensive evaluation is carried out to get the evaluation value of the bargaining power of ten enterprises in a regional logistics alliance. Taking index data and evaluation results of fuzzy evaluation as input and output item, using the BP neural network training fuzzy evaluation system, and then it will provide enterprises with a powerful evaluation tool.","PeriodicalId":297098,"journal":{"name":"2018 3rd International Conference on Computational Intelligence and Applications (ICCIA)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116749933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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