{"title":"An Efficient Semantic based Clustering Algorithm for Textual Documents","authors":"R. Karthika, L. JegathaDeborah","doi":"10.1109/ICCSDET.2018.8821148","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821148","url":null,"abstract":"Documents that are classified into different categories gets flooded in the internet every day. These documents have many links or associations with the other documents in the web. The terms in the document are open to multiple interpretations which are vague and unclear. Hence there is a need to find the semantic understanding of the terms. One of the major application in identifying and applying such semantic measure lies in clustering the related textual documents. However, the traditional clustering algorithms may exhibit reduced performances due to the existence of irrelevant terms in the raw documents. Hence, the proposed algorithm in this paper exploits the use of a feature selection algorithm in order to increase the performance of the clustering algorithm. In this paper, a feature selection algorithm with booster technique is used. Moreover, clustering algorithm based on a fuzzy linguistic variable measure that uses separation and dominance value is used in this paper for precise clustering. Experimental analysis shows that the three performance measures that evaluates the clustering algorithm increases, in comparison to the other existing algorithms.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123454665","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}
{"title":"Recognition of Speed Limit from Traffic Signs Using Naive Bayes Classifier","authors":"Sruthi Nair, A. R P","doi":"10.1109/ICCSDET.2018.8821142","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821142","url":null,"abstract":"The detection and recognition of road speed limit signs is an important task in advanced driver assistance system (ADAS). The speed limit signs are important in informing the driver about allowable speed in a particular area. It increases the safety, as it provides information about the circumstances of the road. Different systems are being implemented by the government authorities to prevent accidents due to over speed. Here the proposed system provides efficient detection and identification of speed limit signs. The system operates in the following way: first it involves the detection of the sign board and then performs segmentation followed by geometric detection. Hough transform algorithm is employed to detect the sign board with saliency based approach. Second the system detects the characters from the extracted sign board. Finally it involves recognition of speed limit sign using Naive Baye’s employed classifier. The algorithm is successfully tested and shows 94% accuracy.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121786063","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}
{"title":"Hand Gesture Recognition Using Artificial Neural Network","authors":"K.V Eshitha, Soniya Jose","doi":"10.1109/ICCSDET.2018.8821076","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821076","url":null,"abstract":"Gesture is one of the most easy and expressive ways of communications between human and computer in a real world. In our day to day life we use various gestures to represent our intention. Hand and face gesture are most important methods for nonverbal communication for human beings. Development in hand gesture recognition using machine interface has got great improvements in recent years. A system is developed for hand gesture recognition in mat lab by using an artificial neural network. Here a dataset is collected with various gestures and through color based segmentation and various morphological operations gestures are segmented from input image. Here feature extraction takes place on the basis of Histogram of Gradient method. After segmentation classifies the gestures into left hand and right hand gestures along with labels. This will passes to the neural network for training and train-rp is the function used for training the gestures. And during the testing face video is given to the system and the system will recognize the corresponding output in the frame and predict it","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129001551","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}
{"title":"Review on Different Techniques used in Selfish Node Detection","authors":"A. S., Tibin Thomas","doi":"10.1109/ICCSDET.2018.8821063","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821063","url":null,"abstract":"In present days, mobile ad hoc networks have grown into an emerging research topic. One of the challenging problem in MANET is securing it in an unsafe environment. In MANET, Innumerable intermediate nodes interchange information without the need of infrastructure. To cooperate with each node all nodes participate in packet forwarding. Due to the inadequate energy of the nodes they do not participate in the routing process correctly. When a node tries to attempts the network reserves for its own gain, but unwilling to use its resources for other nodes in the MANET then these nodes are called selfish nodes. The destruction of basic action of the network can occur due to this selfish behavior of the node. These routing misbehaviors can misuse system resources such as power and bandwidth and it can also reduce the packet delivery ratio. Hence, it is necessary to identify and remove such nodes from the network. There are many methods for the identification of selfish nodes. In, this survey various methods for detecting selfish nodes are discussed with their major advantages.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129173178","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}
Sharon N M, A. R P, Rony B C, Sreedharan Embrandiri
{"title":"Adaptive Scheduling Algorithm for Centralised Building Energy Management System","authors":"Sharon N M, A. R P, Rony B C, Sreedharan Embrandiri","doi":"10.1109/ICCSDET.2018.8821206","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821206","url":null,"abstract":"Electricity is an inevitable part of human being now and all the systems are being converted to function with electric energy. The usage of energy is increasing day by day. So Conservation of energy still persists as a challenging task. More low power devices are being developed, but implementation of these systems are very expensive. In this paper, a new energy management system (E-mats) is presented to reduce the wastage of electricity in building automation. A scheduling mechanism is proposed to control and operate the devices as per its parameters. This system is designed with low power components and it also empowers the usage of renewable energy sources. It measures the usage of electricity by device wise. E-mats present software and hardware controlled operating mechanism with a scheduling algorithm. The user can also configure the operation by setting a schedule. Observe, Learn, and Adapt (OLA) algorithm is used for the scheduling mechanism. The proposed hardware model is designed with the sensors like motion sensor, ultra sound sensor, LDR sensor, temperature sensor, ZigBee, RTC. All the components in the system are labeled with a unique digital address. The system has been successfully tested and shows that it can save up to 20% of power with renewable energy source and 40% up to non-renewable source.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129277187","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}
{"title":"Dynamic Voltage Stability Enhancement of A Wind Farm Connected To Grid Using Facts- A Comparison","authors":"K. Latha, M. Kumar","doi":"10.1109/iccsdet.2018.8821136","DOIUrl":"https://doi.org/10.1109/iccsdet.2018.8821136","url":null,"abstract":"","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127753265","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}
R. Singh, R. Sugandhi, G. Kaur, D. Trivedi, P. Srivastav, L. M. Awasthi
{"title":"Development of digital control system in LabVIEW for stepper motor drives","authors":"R. Singh, R. Sugandhi, G. Kaur, D. Trivedi, P. Srivastav, L. M. Awasthi","doi":"10.1109/ICCSDET.2018.8821122","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821122","url":null,"abstract":"A digital control system has been developed for three dimensional (or less) motion control applications using three sets of stepper motors, drive controller and encoder on RS485 4-wire communication interface. This system is simple to program, economical and flexible to enhance. The communication protocol is a customized ASCII protocol for control and monitoring of essential parameters on serial communication. It is an example of handling systems which are based on serial communication and simple communication artifacts. It also demonstrates an integration of system using modern data flow programming such as LabVIEW. This development is capable of handling 3-axis motion (or less) when coupled with the suitable mechanical structure. Although, this development is carried out, keeping in mind the motion control applications of a laboratory plasma device, called as large volume plasma device (LVPD) but this can also be used for any other experimental system in general. The paper discusses the requirements, software and hardware architecture, obtained results and future application perspectives.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129919602","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}
{"title":"Learning Robotic Grasp using Visual-Tactile model","authors":"Shamin Varkey, Chikku Achy","doi":"10.1109/ICCSDET.2018.8821091","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821091","url":null,"abstract":"The practice of grasping an object in humans, depend greatly on the feedback from tactile sensors. Nevertheless, the recent works of grasping in robotics, has been constructed only from visual input, but in this case the feedback after instigating contact cannot be easily benefited. A survey is done and presented in this paper to explore how the tactile information is used by the robot to learn to adjust its grasp proficiently. Additionally, an action-conditional model which uses raw visual- tactile data that learns grasping strategies is presented. The model presented iteratively selects the most favorable actions which implements the grasp. The approach does not require any analytical modeling of contact forces nor calibration of the tactile sensors, thereby decreasing the engineering requirements for obtaining a competent grasp strategy. The model, a two-finger gripper with tactile sensors of high-resolution on each finger was trained with data from various grasping trials. After a number of rigorous testing, it was seen that the approach had effectively learned useful and interpretable grasping behaviors. To conclude, the selections made by the model were studied and it was seen that it had effectively learned suitable and apt behaviors for grasping.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121487713","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}
{"title":"Lattice representation of Complete Graph and Perfect Difference Network (PDN)","authors":"T. A. Shiekh, Jitendra Seethalani","doi":"10.1109/ICCSDET.2018.8821111","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821111","url":null,"abstract":"In this paper we have evaluated the links of Complete Graph and Perfect Difference Network (PDN) of (δ2 + δ+1) nodes in order to derive a relation which gives us the total number of disjoint lattices formed in a Complete Graph and Perfect Difference Network (PDN) of (δ2 + δ +1) nodes. In this paper we have also seen that the smallest lattice formed in a Complete Graph and PDN of (δ2+δ+1) includes only three nodes and the biggest lattice formed in a Complete Graph and PDN includes all the nodes of the Complete Graph and PDN i.e. (δ2 + δ+1) nodes. In this paper we have also seen the effect of removal of diagonal links in the Perfect Difference Network in lattice formation.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124340886","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}
{"title":"Chronic Diseases Diagnosis using Machine Learning","authors":"S. Ganiger, K. Rajashekharaiah","doi":"10.1109/ICCSDET.2018.8821235","DOIUrl":"https://doi.org/10.1109/ICCSDET.2018.8821235","url":null,"abstract":"As the chronicle disease is long lasting diseases, it takes the long period to diagnosis. The chronicle disease is a threatening disease all over the world, its cost more to diagnosis, as some of the chronicle diseases are unable to diagnose, the patient has to suffer throughout his lifetime. This kind disease data are available hugely in the medical field, to make easier for healthcare system the data mining approaches are applied. As in this project, five chronicle dataset are taken and the machine learning approaches are applied, the machine learning algorithms such as decision tree, random forest, and the support vector machine are applied and the predicted whether the patient is suffering from a disease. The chronicle disease such as heart disease, liver disease, diabetes, disease dataset is retrieved from the open source and applied the data mining process to all the dataset. As we get the result by comparing all algorithms performance on all dataset the random forest predicts with high accuracy.","PeriodicalId":157362,"journal":{"name":"2018 International Conference on Circuits and Systems in Digital Enterprise Technology (ICCSDET)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124232845","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}