{"title":"An Encryption-then-Compression Scheme Using Autoencoder Based Image Compression for Color Images","authors":"K. Sreelakshmi, Renjith V. Ravi","doi":"10.1109/ICSSS49621.2020.9201967","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9201967","url":null,"abstract":"The goal of this work is to develop an encryption and then compression scheme for the efficient transmission of color images over an untrusted channel. An image encryption scheme based on bidirectional diffusion is used to encrypt the 8-bit RGB color image. Then, lossless, autocoder-based compression of the encrypted image is performed to achieve compression. The compression method is used to reduce the size of the images during transmission, thus speeding up the transmission. The performance of the compression algorithm is evaluated in terms of the compression ratio.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115154161","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":"Efficient Computerized Lung Cancer Detection Using Bag of Words","authors":"Azmira Krishna, P. Rao, C. Zeelan Basha","doi":"10.1109/ICSSS49621.2020.9202039","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202039","url":null,"abstract":"The automatic detection of diseases in the medical field is growing very fast nowadays. It is widely being accepted as this system can reduce the burden on doctors. Among the available examination of diseases, attention on lung cancers is required more as these play a major role in increasing the mortality rate in the present day. Though many computerized cancer detection techniques were proposed earlier, those techniques gets failed in managing the better accuracy rate due to their combinations of filtering techniques, segmentation techniques, and classifiers. An MLP-BPNN(Multi-Layered Perceptron Back Propagation Neural Network based on SIFT(Scale Invariant Feature Transform) feature extraction along with Bag of Words(BOW) is proposed which gives the better accuracy rate of 89% when compared to any other Cancer detection technique proposed earlier. Lung images of 300 are collected from the Rajiv Gandhi Cancer Institute and Research Centre, Delhi as a dataset out of which 100 images are used for testing and 200 images are used for training.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127786253","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}
D. Jayakumar, S. Pragathie, M. Ramkumar, R. Rajmohan
{"title":"Mid Day Meals Scheme Monitoring System in School using Image Processing Techniques","authors":"D. Jayakumar, S. Pragathie, M. Ramkumar, R. Rajmohan","doi":"10.1109/ICSSS49621.2020.9202347","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202347","url":null,"abstract":"The Government of India introduced the Mid – Day meal scheme which is a school meal programme and that also helps to enhance the nutritional standing of school students. This program is designed to support for both primary and secondary school education. This mid day meal scheme provides cost free lunches on all working days for children in primary and upper primary classes in Government schools. In our work Ensuring number of students that took meal is same number as reported. This System monitoring comprise of human face detection through a webcam where identification of image done using an effective algorithm called Viola jones Algorithm. Feature Extraction is a technique that process the captured visual content into image of indexing and retrieval. After face detection, then it checks whether the food is served in plate or not. If food is served then count is increased, else no change in count. Food is recognized through Deep learning approach. With the improvement of deep CNN learning algorithm, Food identification and recognition estimation have been developed. we use Deep Convolutional neural network for visual recognition. So admin can verify lunch served is same as published/reported menu. Alerting in case of discrepancy and capability to centrally see past records / proof (numbers and visual) for any school. In order to observe this activity, we need image processing.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133525050","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":"Dual Band Rejection UWB Antenna Using Slot and a Novel Modified $Psi$-Shaped Parasitic","authors":"V. N. K. R. Devana, A. M. Rao","doi":"10.1109/ICSSS49621.2020.9202357","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202357","url":null,"abstract":"A dual band rejected UWB antenna is suggested. The radiating patch is procured by the convergence of an ellipse with a rectangular structure. The UWB bandwidth of 2.99 to 10.12 GHz is accomplished by etching circular snick at extremity of rectangular structure along with defected ground plane. The rejection bands from 3.12- 3.69 GHz for WiMAX and 5.18- 6.14 GHz for WLAN are realized by etching $U$-shaped slot and a novel modified $mathrm{Psi}$-structured parasitic respectively. The proposed antenna has stable gain, radiation patterns, above 94% of radiation efficiency and linear transmission characteristics makes it satisfactory for portable wireless applications.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133546567","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}
Rajeev Ratna Vallabhuni, Desu Sravya, M. Shalini, G.Uma Maheshwararao
{"title":"Design of Comparator using 18nm FinFET Technology for Analog to Digital Converters","authors":"Rajeev Ratna Vallabhuni, Desu Sravya, M. Shalini, G.Uma Maheshwararao","doi":"10.1109/ICSSS49621.2020.9202164","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202164","url":null,"abstract":"In digital terminology, a device that compares two numbers which are represented in binary format and determines whether one of the two inputs are lesser than or equal to or greater than the other input is called a comparator. Comparators are generally used in Central Processing units (CPUs) and microcontrollers. In this project, a 2-bit magnitude comparator is designed with 18nm FinFET technology. FinFET technology is used to overcome the drawbacks associated with CMOS technology like channel length, power consumption, delay and area of transistors, etc. The proposing magnitude comparator is compared with the existing CMOS comparator in terms of power and delay. Schematic circuit diagrams of greater than, equal to and lesser than circuits have been simulated using the Cadence Virtuoso tool. Power and delay values are calculated and plotted for different values of supply voltage ranging from 0.1v-1.0v. LVT (Low Voltage) and HVT (High Voltage) analysis are performed separately. FinFET comparators can be used where a fast switching rate is required, to improve the efficiency of control devices and to make devices compact.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131855720","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}
U. Palani, Sure Sai Mahesh, D. Vasanthi, D. S. Kumar
{"title":"Ethereum blockchain based healthcare Industry ecosystem","authors":"U. Palani, Sure Sai Mahesh, D. Vasanthi, D. S. Kumar","doi":"10.1109/ICSSS49621.2020.9202232","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202232","url":null,"abstract":"Thirty-five % of the US population is affected by data breach occurred in the healthcare industry. It is a total of 114 million people affected in 2015. On average of 4 data breaches happens per week. Health care industry is losing 300 billion dollars each year in poor data integration. we can overcome this problem by bringing a decentralized system in the hospital organization. This prototype helps us to stop and prevent data breaching in the health care industry and to remove fake patient IDs in the hospital data base.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131874369","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}
V. Thirunavukkarasu, A. Senthil kumar, D. Josephine, T. Arasu
{"title":"Selection of Optimistic Nodes for Reputation Based Routing in Wireless Networks","authors":"V. Thirunavukkarasu, A. Senthil kumar, D. Josephine, T. Arasu","doi":"10.1109/ICSSS49621.2020.9202350","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202350","url":null,"abstract":"Trust based routing in wireless networks helps in providing secured routes for data transmission. Since wireless networks are subjected to several security threats while processing and transmission of data. Therefore, a system called Node Reputation based Energy Aware Routing (NREAR) scheme is proposed here to provide efficient and secured transmissions of information from one end to other end. NREAR consists of node behaviour monitoring phase and node's energy value monitoring phase together. Nodes behaviour monitoring includes detection of trusted and un-trusted nodes on basis of optimistic and pessimistic behaviours of nodes. In second phase after the detection of optimistic nodes the energy value is calculated. By selecting high energy remained optimistic (trusted) nodes, the data gets transmitted from source to the destination. Simulation results are derived and the performance of the proposed mechanism is proved to be better in terms of achieving higher data packets, accuracy in false node detection and throughput.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115513235","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":"A Literature Review on Feature Selection using Evolutionary Algorithms","authors":"P. Sekhar, B. Sujatha","doi":"10.1109/ICSSS49621.2020.9202257","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202257","url":null,"abstract":"Feature Selection is an optimization problem, where a subset of relevant features are derived from a set of features. It's a pre-processing technique performed before training an algorithm. Features/Attributes provide information about the labels/targets, so we may think that more attributes means more information about the target, but this is not the case always. Initially, the algorithm's performance may go up, but gradually it may come down; this is because of the irrelevant and redundant attributes present in the dataset. This phenomenon is called a Curse of Dimensionality. Feature Selection problem can be optimized using Evolutionary algorithms. This paper emphasizes on use of Evolutionary algorithms in optimizing the feature selection problem. This is a review paper where all the works relating to the application of Evolutionary algorithms in the field of Feature Selection are reviewed and presented.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124474210","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}
G. Bharathy, V. Rajendran, T. Tamilselvi, M. Meena
{"title":"A Study and Simulation of Spectrum Sensing Schemes for Cognitive Radio Networks","authors":"G. Bharathy, V. Rajendran, T. Tamilselvi, M. Meena","doi":"10.1109/ICSSS49621.2020.9202296","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9202296","url":null,"abstract":"The under - deployment dilemma of the allocated radio spectrum has made the Cognitive Radio (CR) communications to evolve as a trustworthy and valuable solution. Spectrum sensing is one of the schema to accomplish the essential Quality of Service (QoS). Spectrum sensing offers the critical data to facilitate the interweave communications which does not authorize the primary and secondary to utilize the medium simultaneously. Cognitive Radio Networks (CRNs) in addition include the suppleness to amend its own transmission parameters in accordance with the requirements of multimedia services or applications. This paper concentrates on various schemes for spectrum sensing such as Energy Based Detection scheme, Autocorrelation Based Detection scheme, Euclidean Distance Based Detection scheme, Wavelet Based Detection scheme, Matched Filter Detection scheme for the Cognitive Radio Networks.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122745778","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":"Feature Based Sentimental Analysis for Prediction of Mobile Reviews Using Hybrid Bag-Boost algorithm","authors":"Siva Kumar Pathuri, N. Anbazhagan, G. Prakash","doi":"10.1109/ICSSS49621.2020.9201990","DOIUrl":"https://doi.org/10.1109/ICSSS49621.2020.9201990","url":null,"abstract":"Sentiment analysis or opinion mining is one of the major challenge of NLP (natural language processing). Business Analytics plays a key role in the current scenario with a perception that people wants to enhance their enterprise. In particular, these people rely on feedback of their goods to withstand the competition and knowledge mining that can give them an outstanding view into what to expect in the future. Few words or phrases may decide results or outcomes. As a majority of these people seek to boost their company in order to achieve full benefit by providing premium goods. In this aspect, sentiment analysis has gained a lot of interest in the current years. SA is an area of research of NLP that is used to classify a specific feature's opinion or perspective within a text. This paper is based on the different methods used to identify a particular text according to the opinions conveyed by the user's i.e. whether the overall sentiment of a individual is negative or positive or neutral. We are also looking at the two advance approaches adopted (feature classification pursued by polarity classification) along with the experimental results. Finally in this paper we compared 3 ML classification techniques 1) Logistic Regression, 2) Hybid Bag-Boost algorithm 3) SVM in which hybrid algorithm provides more accuracy compared to the other 3 ML algorithms. The Main objective of the proposed method is to predict the user reviews for choosing a best mobile using several classification Algorithms.","PeriodicalId":286407,"journal":{"name":"2020 7th International Conference on Smart Structures and Systems (ICSSS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123885893","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}