Pub Date : 2018-12-31DOI: 10.25073/JAEC.201824.213
C. Tran, P. Brandstetter, B. H. Dinh, S. D. Ho, Minh Huu Chau Nguyen
This paper describes a new solution to control the induction motor drive system without current sensors based on improving the Hysteresis Pulse Width Modulation technique. It has proposed a control scheme which uses stator currents estimated from the differential equation of state variables to replace the feedback signal from current sensors applied in the hysteresis current controller. To verify the proposed method, simulations in MATLAB/Simulink have been implemented in various operating conditions of the motor where its speed has been changed under load as well as no load conditions. The simulation results have demonstrated the effectiveness of the proposed control method for inductive motor drives. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
{"title":"Current-Sensorless Method for Speed Control of Induction Motor Based on Hysteresis Pulse Width Modulation Technique","authors":"C. Tran, P. Brandstetter, B. H. Dinh, S. D. Ho, Minh Huu Chau Nguyen","doi":"10.25073/JAEC.201824.213","DOIUrl":"https://doi.org/10.25073/JAEC.201824.213","url":null,"abstract":"This paper describes a new solution to control the induction motor drive system without current sensors based on improving the Hysteresis Pulse Width Modulation technique. It has proposed a control scheme which uses stator currents estimated from the differential equation of state variables to replace the feedback signal from current sensors applied in the hysteresis current controller. To verify the proposed method, simulations in MATLAB/Simulink have been implemented in various operating conditions of the motor where its speed has been changed under load as well as no load conditions. The simulation results have demonstrated the effectiveness of the proposed control method for inductive motor drives. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128957314","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 : 2018-12-31DOI: 10.25073/jaec.201824.214
Ha Che-Ngoc, A. Pham-Chau, Dibya Jyoti Bora
The contrast is a major factor influencing the image quality; therefore, image contrast enhancement technique is more and more widely applied in the field of image processing. In this paper, a new fuzzy rule-based contrast enhancement method using the two-steps automatic clustering algorithm is proposed. Specifically, based on the Automatic clustering algorithm, a state-of-art method in cluster analysis and data mining, this paper proposes a two-steps Automatic clustering method to determine the number of fuzzy sets and locate the critical point in membership functions so that they are suitable for the distribution of pixel intensity values. The experiments on the "Lena" image and other natural images demonstrate that the new method can effectively enhance the contrast of the images and meet the demands of human eyes perception at the same time.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
{"title":"A New Fuzzy Rule Based Contrast Enhancement Method using The Two-Steps Automatic Clustering Algorithm","authors":"Ha Che-Ngoc, A. Pham-Chau, Dibya Jyoti Bora","doi":"10.25073/jaec.201824.214","DOIUrl":"https://doi.org/10.25073/jaec.201824.214","url":null,"abstract":"The contrast is a major factor influencing the image quality; therefore, image contrast enhancement technique is more and more widely applied in the field of image processing. In this paper, a new fuzzy rule-based contrast enhancement method using the two-steps automatic clustering algorithm is proposed. Specifically, based on the Automatic clustering algorithm, a state-of-art method in cluster analysis and data mining, this paper proposes a two-steps Automatic clustering method to determine the number of fuzzy sets and locate the critical point in membership functions so that they are suitable for the distribution of pixel intensity values. The experiments on the \"Lena\" image and other natural images demonstrate that the new method can effectively enhance the contrast of the images and meet the demands of human eyes perception at the same time.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122244805","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 : 2018-12-31DOI: 10.25073/jaec.201824.211
Manel Benaissa, A. Bennia
In this paper, we propose two novel approaches in the field of feature description and matching. The first approach concerns the feature description and matching part, where we proposed an orientation invariant feature descriptor without an additional step dedicated to this task. We exploited the information provided by two representations of the image (intensity and gradient) for a better understanding and representation of the feature point distribution. The provided information is summarized in two cumulative histograms and used in the feature description and matching process. In the context of object detection, we introduced an unsupervised learning method based on k-means clustering. Which we used as an outlier pre-elimination phase after the matching process to improve our descriptor precision. Experiments shown its robustness to image changes and a clear increase in terms of precision of the tested descriptors after the pre-elimination phase.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
{"title":"New 2D Feature Descriptor Free from Orientation Compensation with k-Means Clustering","authors":"Manel Benaissa, A. Bennia","doi":"10.25073/jaec.201824.211","DOIUrl":"https://doi.org/10.25073/jaec.201824.211","url":null,"abstract":"In this paper, we propose two novel approaches in the field of feature description and matching. The first approach concerns the feature description and matching part, where we proposed an orientation invariant feature descriptor without an additional step dedicated to this task. We exploited the information provided by two representations of the image (intensity and gradient) for a better understanding and representation of the feature point distribution. The provided information is summarized in two cumulative histograms and used in the feature description and matching process. In the context of object detection, we introduced an unsupervised learning method based on k-means clustering. Which we used as an outlier pre-elimination phase after the matching process to improve our descriptor precision. Experiments shown its robustness to image changes and a clear increase in terms of precision of the tested descriptors after the pre-elimination phase.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122301195","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 : 2018-09-30DOI: 10.25073/JAEC.201823.114
Abdelhakim Bouricha, T. Bouthiba, Samira Seghir, Rebiha Boukhari
This paper presents a method for detecting, classifying and localizing faults in MV distribution networks. This method is based on only two samples of current or voltage signals. The fault detection, faultclassification and fault localization are based on the maximum value of current and voltage as a function of time. A study is presented in this work to evaluate the proposed method.A comparative study between current and voltage method detection has been done to determine which is the fastest. In addition, the classication and localization of faults were made by the same method using two samples signal. Simulation with results have been obtained by using MATLAB / Simulink software. Results are reported and conclusions are drown. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
{"title":"Dynamic Fault Classification and Location in Distribution Networks","authors":"Abdelhakim Bouricha, T. Bouthiba, Samira Seghir, Rebiha Boukhari","doi":"10.25073/JAEC.201823.114","DOIUrl":"https://doi.org/10.25073/JAEC.201823.114","url":null,"abstract":"This paper presents a method for detecting, classifying and localizing faults in MV distribution networks. This method is based on only two samples of current or voltage signals. The fault detection, faultclassification and fault localization are based on the maximum value of current and voltage as a function of time. A study is presented in this work to evaluate the proposed method.A comparative study between current and voltage method detection has been done to determine which is the fastest. In addition, the classication and localization of faults were made by the same method using two samples signal. Simulation with results have been obtained by using MATLAB / Simulink software. Results are reported and conclusions are drown. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124270313","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}
Fethi Demim, A. Nemra, Kahina Louadj, Abdelghani Boucheloukh, M. Hamerlain, A. Bazoula
Simultaneous localization and mapping (SLAM) is an essential capability for Unmanned Ground Vehicles (UGVs) travelling in unknown environments where globally accurate position data as GPS is not available. It is an important topic in the autonomous mobile robot research. This paper presents an Adaptive De-centralized Cooperative Vision-based SLAM solution for multiple UGVs, using the Adaptive Covariance Intersection (ACI) supported by a stereo vision sensor. In recent years, SLAM problem has gotten a specific consideration, the most commonly used approaches are the EKF-SLAM algorithm and the FAST-SLAM algorithm. The primary, which requires an accurate process and an observation model, suffers from the linearization problem. The last mentioned is not suitable for real-time implementation. In our work, the Visual SLAM (VSLAM) problem could be solved based on the Smooth Variable Structure Filter (SVSF) is proposed. This new filter is robust and stable to modelling uncertainties making it suitable for UGV localization and mapping problem. This new strategy retains the near optimal performance of the SVSF when applied to an uncertain system, it has the added benefit of presenting a considerable improvement in the robustness of the estimation process. All UGVs will add data features sorted by the ACI that estimate position on the global map. This solution gives, as a result, a large reliable map constructed by a group of UGVs plotted on it. This paper presents a Cooperative SVSF-VSLAM algorithm that contributes to solve the Adaptive Cooperative Vision SLAM problem for multiple UGVs. The algorithm was implemented on three mobile robots Pioneer 3-AT, using stereo vision sensors. Simulation results show eciency and give an advantage to our proposed algorithm, compared to the Cooperative EKF-VSLAM algorithm mainly concerning the noise quality. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
{"title":"Cooperative Visual SLAM based on Adaptive Covariance Intersection","authors":"Fethi Demim, A. Nemra, Kahina Louadj, Abdelghani Boucheloukh, M. Hamerlain, A. Bazoula","doi":"10.25073/JAEC.201823.91","DOIUrl":"https://doi.org/10.25073/JAEC.201823.91","url":null,"abstract":"Simultaneous localization and mapping (SLAM) is an essential capability for Unmanned Ground Vehicles (UGVs) travelling in unknown environments where globally accurate position data as GPS is not available. It is an important topic in the autonomous mobile robot research. This paper presents an Adaptive De-centralized Cooperative Vision-based SLAM solution for multiple UGVs, using the Adaptive Covariance Intersection (ACI) supported by a stereo vision sensor. In recent years, SLAM problem has gotten a specific consideration, the most commonly used approaches are the EKF-SLAM algorithm and the FAST-SLAM algorithm. The primary, which requires an accurate process and an observation model, suffers from the linearization problem. The last mentioned is not suitable for real-time implementation. In our work, the Visual SLAM (VSLAM) problem could be solved based on the Smooth Variable Structure Filter (SVSF) is proposed. This new filter is robust and stable to modelling uncertainties making it suitable for UGV localization and mapping problem. This new strategy retains the near optimal performance of the SVSF when applied to an uncertain system, it has the added benefit of presenting a considerable improvement in the robustness of the estimation process. All UGVs will add data features sorted by the ACI that estimate position on the global map. This solution gives, as a result, a large reliable map constructed by a group of UGVs plotted on it. This paper presents a Cooperative SVSF-VSLAM algorithm that contributes to solve the Adaptive Cooperative Vision SLAM problem for multiple UGVs. The algorithm was implemented on three mobile robots Pioneer 3-AT, using stereo vision sensors. Simulation results show eciency and give an advantage to our proposed algorithm, compared to the Cooperative EKF-VSLAM algorithm mainly concerning the noise quality. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130971268","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 : 2018-09-30DOI: 10.25073/JAEC.201823.198
KhoaNguyen Tran
Device-to-Device (D2D) has attracted substantial research attention recently and has been recognized as an essential approach to performance improvement in 5G networks, due to its potential to improve coverage, spectrum efficiency, and energy within the existing cellular network. In this paper, we refer to an LTE-A scenario in which the underlay mode is adopted to allow D2D pairs to communicate directly by sharing sub-channels with Cellular Users (CUEs) and cellular mode (CELLM), where two D2D users communicate through the eNB as conventional CUEs and no direct D2D link is established. In this case, the eNB is used as a relay. Our aim is to propose heuristic resource allocation schemes to distribute radio resources among CUEs and D2Ds in a cell taking the interference because of pairing into account. Finally, an analytical approach is proposed to characterize CUE and D2D capacity as well as outage probability for D2D cellular mode. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
{"title":"Resource allocation in D2D communication in cellular mode","authors":"KhoaNguyen Tran","doi":"10.25073/JAEC.201823.198","DOIUrl":"https://doi.org/10.25073/JAEC.201823.198","url":null,"abstract":"Device-to-Device (D2D) has attracted substantial research attention recently and has been recognized as an essential approach to performance improvement in 5G networks, due to its potential to improve coverage, spectrum efficiency, and energy within the existing cellular network. In this paper, we refer to an LTE-A scenario in which the underlay mode is adopted to allow D2D pairs to communicate directly by sharing sub-channels with Cellular Users (CUEs) and cellular mode (CELLM), where two D2D users communicate through the eNB as conventional CUEs and no direct D2D link is established. In this case, the eNB is used as a relay. Our aim is to propose heuristic resource allocation schemes to distribute radio resources among CUEs and D2Ds in a cell taking the interference because of pairing into account. Finally, an analytical approach is proposed to characterize CUE and D2D capacity as well as outage probability for D2D cellular mode. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115040789","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 : 2018-09-30DOI: 10.25073/JAEC.201823.203
D. Dinh-Cong, Sang Pham-Duy, T. Nguyen-Thoi
The article presents an effective method for damage assessment of 2D frame structures using incomplete modal data by optimization procedure and model reduction technique. In this proposed method, the structural damage detection problem is defined as an optimization problem, in which a hybrid objective function and the damage severity of all elements are considered as the objective function and the continuous design variables, respectively. The teaching-learning-based optimization (TLBO) algorithm is applied as a powerful optimization tool to solve the problem. In addition, owing to the use of incomplete measurements, an improved reduction system (IRS) technique is adopted to reduce the mass and stiffness matrices of structural finite element model. The efficiency and robustness of the proposed method are validated with a 4-storey (3 bay) steel plane frame involving several damage scenarios without and with measurement noise. The obtained results clearly demonstrate that even the incompleteness and noisy environment of measured modal data, the present method can work properly in locating and estimating damage of the frame structure by utilizing only the first five incomplete modes' data. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
{"title":"Damage detection of 2D frame structures using incomplete measurements by optimization procedure and model reduction","authors":"D. Dinh-Cong, Sang Pham-Duy, T. Nguyen-Thoi","doi":"10.25073/JAEC.201823.203","DOIUrl":"https://doi.org/10.25073/JAEC.201823.203","url":null,"abstract":"The article presents an effective method for damage assessment of 2D frame structures using incomplete modal data by optimization procedure and model reduction technique. In this proposed method, the structural damage detection problem is defined as an optimization problem, in which a hybrid objective function and the damage severity of all elements are considered as the objective function and the continuous design variables, respectively. The teaching-learning-based optimization (TLBO) algorithm is applied as a powerful optimization tool to solve the problem. In addition, owing to the use of incomplete measurements, an improved reduction system (IRS) technique is adopted to reduce the mass and stiffness matrices of structural finite element model. The efficiency and robustness of the proposed method are validated with a 4-storey (3 bay) steel plane frame involving several damage scenarios without and with measurement noise. The obtained results clearly demonstrate that even the incompleteness and noisy environment of measured modal data, the present method can work properly in locating and estimating damage of the frame structure by utilizing only the first five incomplete modes' data. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129421046","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 : 2018-09-30DOI: 10.25073/JAEC.201823.200
Doan Quoc Anh Nguyen
When the features of remote phosphor structure are compared with these of conformal phosphor or in-cup phosphor, it is recognized that it is more outstanding than the rest about luminous flux but the quality of color tends to be worse. Through that we have grasped these disadvantages and find out many studies in order to improve the color of the remote phosphor structure. In this study, we propose a dual-layer remote phosphor structure that could improve the color rendering index (CRI) and color quality scale (CQS) for WLEDs. In this study, three similar WLEDs structures but having different color temperatures including 5600 K, 6600 K and 7700K are applied. The principal idea is putting a red phosphoric layer SrwFxByOz:Eu2+,Sm2+ on the yellow phosphorus layer YAG:Ce3+. The results show that SrwFxByOz:Eu2+,Sm2+ brings great benefits to increasing CRI and CQS. Specifically, the greater the concentration of SrwFxByOz:Eu2+,Sm2+ has, the higher CRI and CQS get. However, the declining trend of luminous flux occurs when the SrwFxByOz:Eu2+,Sm2+ concentration exceeds the level. This can be demonstrated through the results of the study and be explained by the Mie dispersion theory and the Lambert-Beer law. The results of this article are important in making WLEDs of higher color quality. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
{"title":"The Impacts of Red-Emitting SrwFxByOz: Eu2+, Sm2+ Phosphor on Color Quality of Dual-Layer Phosphor Geometry","authors":"Doan Quoc Anh Nguyen","doi":"10.25073/JAEC.201823.200","DOIUrl":"https://doi.org/10.25073/JAEC.201823.200","url":null,"abstract":"When the features of remote phosphor structure are compared with these of conformal phosphor or in-cup phosphor, it is recognized that it is more outstanding than the rest about luminous flux but the quality of color tends to be worse. Through that we have grasped these disadvantages and find out many studies in order to improve the color of the remote phosphor structure. In this study, we propose a dual-layer remote phosphor structure that could improve the color rendering index (CRI) and color quality scale (CQS) for WLEDs. In this study, three similar WLEDs structures but having different color temperatures including 5600 K, 6600 K and 7700K are applied. The principal idea is putting a red phosphoric layer SrwFxByOz:Eu2+,Sm2+ on the yellow phosphorus layer YAG:Ce3+. The results show that SrwFxByOz:Eu2+,Sm2+ brings great benefits to increasing CRI and CQS. Specifically, the greater the concentration of SrwFxByOz:Eu2+,Sm2+ has, the higher CRI and CQS get. However, the declining trend of luminous flux occurs when the SrwFxByOz:Eu2+,Sm2+ concentration exceeds the level. This can be demonstrated through the results of the study and be explained by the Mie dispersion theory and the Lambert-Beer law. The results of this article are important in making WLEDs of higher color quality. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116983972","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 : 2018-09-30DOI: 10.25073/JAEC.201823.194
Ngoc Diem Tran, Tom Vinant, ThéO Marc Colombani, Kieu Diem Ho
This paper aims to present a code for implementation of non-hierarchical algorithm to cluster probability density functions in one dimension for the first time in R environment. The structure of code consists of 2 primary steps: executing the main clustering algorithm and evaluating the clustering quality. The code is validated on one simulated data set and two applications. The numerical results obtained are highly compatible with that on MATLAB software regarding computational time. Notably, the code mainly serves for educational purpose and desires to extend the availability of algorithm in several environments so as having multiple choices for whom interested in clustering. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
{"title":"An R code for implementing non-hierarchical algorithm for clustering of probability density functions","authors":"Ngoc Diem Tran, Tom Vinant, ThéO Marc Colombani, Kieu Diem Ho","doi":"10.25073/JAEC.201823.194","DOIUrl":"https://doi.org/10.25073/JAEC.201823.194","url":null,"abstract":"This paper aims to present a code for implementation of non-hierarchical algorithm to cluster probability density functions in one dimension for the first time in R environment. The structure of code consists of 2 primary steps: executing the main clustering algorithm and evaluating the clustering quality. The code is validated on one simulated data set and two applications. The numerical results obtained are highly compatible with that on MATLAB software regarding computational time. Notably, the code mainly serves for educational purpose and desires to extend the availability of algorithm in several environments so as having multiple choices for whom interested in clustering. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.","PeriodicalId":250655,"journal":{"name":"J. Adv. Eng. Comput.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134479776","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 : 2018-09-11DOI: 10.25073/JAEC.201931.226
T. Brandejsky
In herein presented work, the relation between a number of ES iterations and convergence of the whole GPA-ES hybrid algorithm will be studied due to increasing needs to analyze and model large data sets. Evolutionary algorithms are applicable in the areas which are not covered by other artificial intelligence or soft computing techniques like neural networks and deep learning like a search of an algebraic model of data. The difference between time and algorithmic complexity will be also mentioned as well as the problems of multitasking implementation of GPA, where external influences complicate increasing of GPA efficiency via Pseudo Random Number Generator (PRNG) choice optimization. Hybrid evolutionary algorithms like GPA-ES uses GPA for solution structure development and Evolutionary Strategy (ES) for parameters identification are controlled by many parameters. The most significant are sizes of GPA population and sizes of ES populations related to each particular individual in GPA population. There is also a limit of ES algorithm evolutionary cycles. This limit plays two contradictory roles. On one side the bigger number of ES iterations means less chance to omit good solution for wrongly identified parameters, on the opposite side large number of ES iterations significantly increases computational time and thus limits application domain of GPA-ES algorithm. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
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