This paper presents a finger motion estimation based on sparse multi-channel surface electromyography (sEMG) signals using a convolutional neural network (CNN). Although classification with CNNs has achieved high accuracy in gesture recognition, the most cases use a high-density sEMG as the signal acquisition method, which is problematic because this requires many sensors for measuring sEMG signals, resulting in high costs. We therefore propose estimating the finger motion with a sparse multi-channel sEMG method using ring-shaped sensors. The finger motion estimation is performed by classifying images generated from the amplitude variations of sEMG signals, and the image classification is achieved with a simple CNN model featuring two pairs of convolutional and pooling layers and two fully connected layers. Experimental results showed that the test accuracy reached 90% in classifying sEMG signals into four types: thumb opened, thumb closed, fingers (excluding thumb) opened, and fingers (excluding thumb) closed.
{"title":"Finger Motion Estimation Based on Sparse Multi-Channel Surface Electromyography Signals Using Convolutional Neural Network","authors":"K. Asai, Norio Takase","doi":"10.1145/3316551.3316572","DOIUrl":"https://doi.org/10.1145/3316551.3316572","url":null,"abstract":"This paper presents a finger motion estimation based on sparse multi-channel surface electromyography (sEMG) signals using a convolutional neural network (CNN). Although classification with CNNs has achieved high accuracy in gesture recognition, the most cases use a high-density sEMG as the signal acquisition method, which is problematic because this requires many sensors for measuring sEMG signals, resulting in high costs. We therefore propose estimating the finger motion with a sparse multi-channel sEMG method using ring-shaped sensors. The finger motion estimation is performed by classifying images generated from the amplitude variations of sEMG signals, and the image classification is achieved with a simple CNN model featuring two pairs of convolutional and pooling layers and two fully connected layers. Experimental results showed that the test accuracy reached 90% in classifying sEMG signals into four types: thumb opened, thumb closed, fingers (excluding thumb) opened, and fingers (excluding thumb) closed.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117002077","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}
The method for making men's suits has long been established and developed manually. Starting from measuring the customer's body size, tailor drafts the garment patterns and construct then into suit model. With the advance of machine, most of suit making processes have been automatized. However, drafting garment pattern still remains in the manual work. This paper proposes the parameterized garment drafting system for the men's suit utilizing only 5 body sizes. Once user provides required 5 body sizes to the proposed system, garment patterns are generated automatically. After passing through the positioning and sewing process, 2D garment patterns are converted to the 3D garment model. The 3D garment model would be draped on the virtual body model using physically-based simulation. The fitting evaluation would be performed to check the suitability of draped garment. If there were implausible result, then it is required to modify the garment to reduce the implausibility. To modify the fit of the men's suit, this paper proposes pattern modification method using secondary parameters.
{"title":"Parametrized Garment Pattern Manipulation for the Men's Suit","authors":"Wonseop Lee, Hyeongseok Ko","doi":"10.1145/3316551.3316575","DOIUrl":"https://doi.org/10.1145/3316551.3316575","url":null,"abstract":"The method for making men's suits has long been established and developed manually. Starting from measuring the customer's body size, tailor drafts the garment patterns and construct then into suit model. With the advance of machine, most of suit making processes have been automatized. However, drafting garment pattern still remains in the manual work. This paper proposes the parameterized garment drafting system for the men's suit utilizing only 5 body sizes. Once user provides required 5 body sizes to the proposed system, garment patterns are generated automatically. After passing through the positioning and sewing process, 2D garment patterns are converted to the 3D garment model. The 3D garment model would be draped on the virtual body model using physically-based simulation. The fitting evaluation would be performed to check the suitability of draped garment. If there were implausible result, then it is required to modify the garment to reduce the implausibility. To modify the fit of the men's suit, this paper proposes pattern modification method using secondary parameters.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130289988","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}
The identification of stone inscriptions is of great significance to the study of Chinese characters and the exploration of ancient history. The identification and analysis of the stone inscriptions can determine the age when they belong, and can help to study archeology. At present, many fuzzy edge detection methods have been proposed, but most of them use the static fuzzy inference system for edge detection. In order to obtain better results, the membership function must be changed according to the image information. Therefore, to overcome this drawback, we proposed fuzzy logic-based edge detection algorithm with dynamic generation of fuzzy interface system (FIS). The algorithm is compared with the existing algorithms (Sobel, canny), and better results are achieved.
{"title":"Dynamic Fuzzy Inference System for Edge Detection of Stone Inscriptions","authors":"Jie Song, Jie Wang, Shanshan Li","doi":"10.1145/3316551.3318231","DOIUrl":"https://doi.org/10.1145/3316551.3318231","url":null,"abstract":"The identification of stone inscriptions is of great significance to the study of Chinese characters and the exploration of ancient history. The identification and analysis of the stone inscriptions can determine the age when they belong, and can help to study archeology. At present, many fuzzy edge detection methods have been proposed, but most of them use the static fuzzy inference system for edge detection. In order to obtain better results, the membership function must be changed according to the image information. Therefore, to overcome this drawback, we proposed fuzzy logic-based edge detection algorithm with dynamic generation of fuzzy interface system (FIS). The algorithm is compared with the existing algorithms (Sobel, canny), and better results are achieved.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132895462","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}
Finding the accurate location of iris is crucial to some applications in biometrics, human computer interaction and medical research. The accuracy of the location will affect the outcome of following iris segmentation, features extraction and measurement, to name a few. This paper presents an accurate vote-based method to detect and localize both irises from color images. The algorithm starts with image filtering steps such as Gaussian filtering to reduce the effect of various lighting conditions. Then, iris candidates will be generated after the detection of reflection in iris. A cost will then be computed for each iris candidate according to the contribution from generic eye template, intensity variation factor, circularity factor and reflective factor. Finally, a pairing process is used to determine the real iris pair in order to locate both irises. Our experiment on Michigan database has reported a promising accuracy of 91.21%.
{"title":"Vote-based Iris Detection System","authors":"Tong-Yuen Chai, B. Goi, Y. Tay, Yik-Herng Khoo","doi":"10.1145/3316551.3316558","DOIUrl":"https://doi.org/10.1145/3316551.3316558","url":null,"abstract":"Finding the accurate location of iris is crucial to some applications in biometrics, human computer interaction and medical research. The accuracy of the location will affect the outcome of following iris segmentation, features extraction and measurement, to name a few. This paper presents an accurate vote-based method to detect and localize both irises from color images. The algorithm starts with image filtering steps such as Gaussian filtering to reduce the effect of various lighting conditions. Then, iris candidates will be generated after the detection of reflection in iris. A cost will then be computed for each iris candidate according to the contribution from generic eye template, intensity variation factor, circularity factor and reflective factor. Finally, a pairing process is used to determine the real iris pair in order to locate both irises. Our experiment on Michigan database has reported a promising accuracy of 91.21%.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123636949","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}
A Data analytics predictive analysis aids to unlock the knowledge of the decision maker in the development of the organization to addressing the malnutrition in implementing government projects in the City of Legazpi, Philippines. Malnutrition is one of the results of poverty in the country mostly the younger age Filipinos. The study aims to apply Data Analytics in analyzing the factor that affects its malnutrition. The researchers evaluated the parameters that have significant contribution in deciding malnutrition. The correlation of the parameters in deciding malnutrition and the level of malnutrition per barangay in the city were also determined. The Rural Health Unit of Legazpi City collects the demographic data of the resident per barangay in determining malnutrition in city. A Data Analytics tool was used in extracting, classifying, analyzing and evaluating data that may cause malnutrition in the city. In the results, it shows that the attribute location under the coastal area is more significant in determining the malnutrition in the city. From these findings, the correlation analysis of the data shows that the malnutrition in the city of Legazpi has decreased by 0.24% over-all. However, in the coastal area increases by 0.3%. It is also show in the prediction analysis that the coastal area is significant to the malnutrition. The paper will lead to the Local Government Unit in addressing the factor of malnutrition increase and implement programs which are actually needed in solving the problem.
{"title":"Analyzing the Malnutrition Valuation on Legazpi City using Data Analytics","authors":"R. N. Monreal, T. Palaoag","doi":"10.1145/3316551.3316566","DOIUrl":"https://doi.org/10.1145/3316551.3316566","url":null,"abstract":"A Data analytics predictive analysis aids to unlock the knowledge of the decision maker in the development of the organization to addressing the malnutrition in implementing government projects in the City of Legazpi, Philippines. Malnutrition is one of the results of poverty in the country mostly the younger age Filipinos. The study aims to apply Data Analytics in analyzing the factor that affects its malnutrition. The researchers evaluated the parameters that have significant contribution in deciding malnutrition. The correlation of the parameters in deciding malnutrition and the level of malnutrition per barangay in the city were also determined. The Rural Health Unit of Legazpi City collects the demographic data of the resident per barangay in determining malnutrition in city. A Data Analytics tool was used in extracting, classifying, analyzing and evaluating data that may cause malnutrition in the city. In the results, it shows that the attribute location under the coastal area is more significant in determining the malnutrition in the city. From these findings, the correlation analysis of the data shows that the malnutrition in the city of Legazpi has decreased by 0.24% over-all. However, in the coastal area increases by 0.3%. It is also show in the prediction analysis that the coastal area is significant to the malnutrition. The paper will lead to the Local Government Unit in addressing the factor of malnutrition increase and implement programs which are actually needed in solving the problem.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131687375","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}
With the prevalence of virtual reality, augmented reality and autonomous robots, the high resolution spherical images they produced make the standard convolutional neural networks (CNNs), which have been proven powerful on perspective images, non-trivial. The classic solution to utilize CNNs on spherical images is to project the spherical images onto plane and learning the planar images using conventional CNNs. But the distortion generated by the projection of spherical images to planar images invalidates the projection based models. Besides, these models are not robust to rotations which are the basic transformation of spherical images. Another type of solution based on spherical harmonics recently proposed by Cohen et al. [1] is rotation equivariant, but can't handle high resolution spherical images with its expensive computational cost. To process high resolution spherical images, we proposed the Hybrid CNNs. Our framework is both computationally efficient and rotation equivariant with two kinds of convolution operations defined in this paper. We compared our method with several baseline models in two classification tasks. The experimental results demonstrate the computational efficiency and rotation equivariance of the Hybrid CNNs.
{"title":"Hybrid CNNs: A Rotation Equivariant Framework for High Resolution Spherical Images","authors":"Wei Yu, Daren Zha, Nan Mu, Tianshu Fu","doi":"10.1145/3316551.3316573","DOIUrl":"https://doi.org/10.1145/3316551.3316573","url":null,"abstract":"With the prevalence of virtual reality, augmented reality and autonomous robots, the high resolution spherical images they produced make the standard convolutional neural networks (CNNs), which have been proven powerful on perspective images, non-trivial. The classic solution to utilize CNNs on spherical images is to project the spherical images onto plane and learning the planar images using conventional CNNs. But the distortion generated by the projection of spherical images to planar images invalidates the projection based models. Besides, these models are not robust to rotations which are the basic transformation of spherical images. Another type of solution based on spherical harmonics recently proposed by Cohen et al. [1] is rotation equivariant, but can't handle high resolution spherical images with its expensive computational cost. To process high resolution spherical images, we proposed the Hybrid CNNs. Our framework is both computationally efficient and rotation equivariant with two kinds of convolution operations defined in this paper. We compared our method with several baseline models in two classification tasks. The experimental results demonstrate the computational efficiency and rotation equivariance of the Hybrid CNNs.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121191403","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}
Kowovi Comivi Alowonou, Jianguo Wei, Wenhuan Lu, Zhicheng Liu, K. Honda, J. Dang
It is an evidence that the production of nasal vowels involves not only the opening of the velopharyngeal port but also the lingual gesture variation. We tested the hypothesis that EWE speakers adjust tongue height to enhance the change in F1 due to the nasalization, by investigating simultaneously the physical configuration of the tongue and the acoustic output. It was found that EWE nasal vowels are produced with a higher and more forward tongue position than their oral counterparts, except /ẽ/ produced with a more retracted tongue position, and /õ/ produced with a lower and more retracted tongue position. We concluded that the lingual configuration of EWE nasal vowels differs from that of their oral congeners, enhancing the effect of the velum lowering on nasal vowels. Nevertheless, from the results, we suggested that the acoustic effects of nasalization on formants would not only depend on the adjustment of the tongue but a combination of multiples articulators.
{"title":"Lingual and Acoustic Differences in EWE Oral and Nasal Vowels","authors":"Kowovi Comivi Alowonou, Jianguo Wei, Wenhuan Lu, Zhicheng Liu, K. Honda, J. Dang","doi":"10.1145/3316551.3316569","DOIUrl":"https://doi.org/10.1145/3316551.3316569","url":null,"abstract":"It is an evidence that the production of nasal vowels involves not only the opening of the velopharyngeal port but also the lingual gesture variation. We tested the hypothesis that EWE speakers adjust tongue height to enhance the change in F1 due to the nasalization, by investigating simultaneously the physical configuration of the tongue and the acoustic output. It was found that EWE nasal vowels are produced with a higher and more forward tongue position than their oral counterparts, except /ẽ/ produced with a more retracted tongue position, and /õ/ produced with a lower and more retracted tongue position. We concluded that the lingual configuration of EWE nasal vowels differs from that of their oral congeners, enhancing the effect of the velum lowering on nasal vowels. Nevertheless, from the results, we suggested that the acoustic effects of nasalization on formants would not only depend on the adjustment of the tongue but a combination of multiples articulators.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115473509","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}
Q. Miao, Lei Wang, Dingyang Duan, Xiaobo Guo, Xiang Li
With the prosperity of online social networks, more and more users have multiple social accounts at the same time in heterogeneous social networks. Associating the same user identity between different social networks is beneficial for applications such as across-network information diffusion and cross-domain recommendation. User identity association across distinct social networks is to find accounts belonging to the same user without knowing the real identity of the users. Most of the existing identity correlation methods, including supervised learning and unsupervised learning methods, only use user's entity information in social networks, such as user attribute information and content information, nevertheless the inherent structural information of the networks is not fully used, so their effectiveness is often sensitive to the high dimension and sparsity of feature spaces. In this paper, we propose a novel model, called EUIA, which employs network embedding method to learn two low-dimensional representations of nodes of the two original networks respectively. Besides, we learn a mapping function across the learned two low-dimensional spaces, supervised by observed anchor links, for further predicting. In addition, we propose an effective optimization program to improve the accuracy of the model. Through experiments on the dataset of Facebook, we prove that the proposed EUIA model performs much better in accuracy than other baseline methods in cross-network user identity association problem.
{"title":"Embedding Based Cross-network User Identity Association Technology","authors":"Q. Miao, Lei Wang, Dingyang Duan, Xiaobo Guo, Xiang Li","doi":"10.1145/3316551.3316571","DOIUrl":"https://doi.org/10.1145/3316551.3316571","url":null,"abstract":"With the prosperity of online social networks, more and more users have multiple social accounts at the same time in heterogeneous social networks. Associating the same user identity between different social networks is beneficial for applications such as across-network information diffusion and cross-domain recommendation. User identity association across distinct social networks is to find accounts belonging to the same user without knowing the real identity of the users. Most of the existing identity correlation methods, including supervised learning and unsupervised learning methods, only use user's entity information in social networks, such as user attribute information and content information, nevertheless the inherent structural information of the networks is not fully used, so their effectiveness is often sensitive to the high dimension and sparsity of feature spaces. In this paper, we propose a novel model, called EUIA, which employs network embedding method to learn two low-dimensional representations of nodes of the two original networks respectively. Besides, we learn a mapping function across the learned two low-dimensional spaces, supervised by observed anchor links, for further predicting. In addition, we propose an effective optimization program to improve the accuracy of the model. Through experiments on the dataset of Facebook, we prove that the proposed EUIA model performs much better in accuracy than other baseline methods in cross-network user identity association problem.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128769964","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}
This project is attempting to solve the issue of unfair and inconsistent food price being charged in economy rice or mixed rice that widely seen in the café of hawker stall in Malaysia. The main cause of the problem is the absence of standardized price list of the food which causes the pricing of the mixed rice remains unknown. Hence, the authors had decided to propose this project by utilizing convolutional neural network (CNN) algorithm and develop a web application to ease the vendor as well as to provide transparency to the buyer on the food price being charged. CNN model is trained to classify the different types of food. The food price will be stored in a database of the web application in order to calculate the food price with the recognized food in the machine learning model. The outcome of this project is a customized web application for Village 3 Café, UTP with a trained CNN classification model at the backend.
{"title":"Food Image Recognition for Price Calculation using Convolutional Neural Network","authors":"Md. Jan Nordin, Ooi Wei Xin, Norshakirah Aziz","doi":"10.1145/3316551.3316557","DOIUrl":"https://doi.org/10.1145/3316551.3316557","url":null,"abstract":"This project is attempting to solve the issue of unfair and inconsistent food price being charged in economy rice or mixed rice that widely seen in the café of hawker stall in Malaysia. The main cause of the problem is the absence of standardized price list of the food which causes the pricing of the mixed rice remains unknown. Hence, the authors had decided to propose this project by utilizing convolutional neural network (CNN) algorithm and develop a web application to ease the vendor as well as to provide transparency to the buyer on the food price being charged. CNN model is trained to classify the different types of food. The food price will be stored in a database of the web application in order to calculate the food price with the recognized food in the machine learning model. The outcome of this project is a customized web application for Village 3 Café, UTP with a trained CNN classification model at the backend.","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123762144","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}
In the Philippines, cooperative transition to becoming technology-driven actors in the development sector by initiating the development of ICT solutions specifically catered to cooperatives and their operations. Without data mining behind crucial decision making in a cooperative management, the fate of these cooperatives may be likened to banks on the verge of bankruptcy. Therefore, cooperative basic business data mining to discover patterns and trends helpful in decision making is being introduced in this study. All districts than can be equated to municipalities are well represented by members of the multipurpose cooperative. There is an equally efficient collection measures of the cooperative management on equity and Mutual Aid System (MAS).
{"title":"Exploration and Mining of Multipurpose Cooperative Business Data","authors":"J. T. Trinidad","doi":"10.1145/3316551.3316561","DOIUrl":"https://doi.org/10.1145/3316551.3316561","url":null,"abstract":"In the Philippines, cooperative transition to becoming technology-driven actors in the development sector by initiating the development of ICT solutions specifically catered to cooperatives and their operations. Without data mining behind crucial decision making in a cooperative management, the fate of these cooperatives may be likened to banks on the verge of bankruptcy. Therefore, cooperative basic business data mining to discover patterns and trends helpful in decision making is being introduced in this study. All districts than can be equated to municipalities are well represented by members of the multipurpose cooperative. There is an equally efficient collection measures of the cooperative management on equity and Mutual Aid System (MAS).","PeriodicalId":300199,"journal":{"name":"Proceedings of the 2019 3rd International Conference on Digital Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123226001","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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