{"title":"A Pattern and Polarization Reconfigurable Antenna For WLAN Application","authors":"D. Niture, Sohan S. Gurame, S. P. Mahajan","doi":"10.1109/IADCC.2018.8692086","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692086","url":null,"abstract":"A pattern and polarization reconfigurable antenna (PPRA) for WLAN applications has been presented in this paper. The proposed antenna has a square ring patch fed by T-shaped microstrip line through gap coupling on upper layer. A defective ground surface has been deployed at the ground for increasing the gain of the antenna. Two diodes PD1 and PD2 have been incorporated in the upper diagonal gap of square ring to achieve polarization reconfigurability and two more switches PD3 and PD4 have been inserted in ground plane to achieve pattern diversity. Depending on diode (ON/OFF) conditions the PPRA can switch to different polarization states viz. horizontal, vertical, S(−45) and Z(45) linear polarization. Also it is able to switch its pattern by 180° in E-plane. Extensive simulations have been performed in CADFEKO for antenna design and optimization. HPND-4005 PIN diodes equivalent circuit for ON and OFF state has been used for simulation purpose. The proposed antenna is able to cover the entire (2.412-2.484) GHz band for IEEE 802.11b/g/n standard.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"9 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":"133689743","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}
Balnarsaiah Battula, Laxminarayana Parayitam, T. S. Prasad, P. Balakrishna, Chandrasekhar Patibandla
{"title":"Classifications of High Resolution Optical Images using Supervised Algorithms","authors":"Balnarsaiah Battula, Laxminarayana Parayitam, T. S. Prasad, P. Balakrishna, Chandrasekhar Patibandla","doi":"10.1109/IADCC.2018.8692132","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692132","url":null,"abstract":"Optical image data have been used by Remote Sensing workforce to study land use and cover, since such data are easily interpretable. The aim of this study is to perform land use classification of optical data using maximum likelihood (ML) and support vector machines (SVM). Essential geo corrections were applied to the images at the pre-processing stage. To appraise the accuracy of the two familiar supervised algorithms, the overall accuracy and kappa coefficient metrics were used. The assessment results demonstrated that the SVM algorithm with an overall accuracy of 88.94% and the kappa-coefficient of 0.87 has a higher accuracy than the ML algorithm. Therefore, the SVM algorithm is suggested to be used as an image classifier for high-resolution optical Remote Sensing images due to its higher accuracy and better reliability.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"53 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":"132425792","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}
C. Verma, A. Tarawneh, Z. Illés, Veronika Stoffová, S. Dahiya
{"title":"Gender Prediction of the European School’s Teachers Using Machine Learning: Preliminary Results","authors":"C. Verma, A. Tarawneh, Z. Illés, Veronika Stoffová, S. Dahiya","doi":"10.1109/IADCC.2018.8692100","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692100","url":null,"abstract":"An experiential study is conducted to solve binary classification problem on big dataset of European Survey of Schools: ICT in Education (known as ESSIE) using IBM modeler version 18.1. The survey was conducted by ESSIE at various levels [1]-[3] of schools ISCED (International Standard Classification of Education). To predict the gender of teachers based on their answers, the authors applied 4 supervised machine learning algorithms filtering out of 12 classifiers using auto classifiers on ISCED-1 and ISCED-2 level of schools. Out of total 158 attributes, self-reduction and auto classifier stabilized only 134 attributes for the Bayesian Network (BN) and Random Tree (RT) at level-1 and 134 attributes for logistic regression and 41 attributes for Decision Tree (C5) at level-2. The MissingValue filter of Weka 3.8.1 tool handled well 55641 in ISCED-2 level and 19415 at the ISCED-1 level and normalization is also applied as well. The outcomes of the study reveal that decision tree (C5) classifier outperformed the logistic regression (LR) after feature extraction at ISCED-2 level schools and Random Tree classifier predicted more accurately gender of the teacher as compare to the Bayesian Network at level-1 schools. Further, presented predictive models stabilized 134 attributes with 2926 instances for predict gender of teachers of level-1 schools and 134 attributes with 7542 instances for level-2 schools.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"8 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":"129418696","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":"Modelling Search Habits on E-commerce Websites using Supervised Learning","authors":"Sherry‐Ann Singh, Shailja Madhwal, Goutam Datta, Latika Singh","doi":"10.1109/IADCC.2018.8692113","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692113","url":null,"abstract":"Consumers are going through a huge transition in terms of their choices as well as the propensity to spend. People increasingly travel outside the country and understand the spectrum of products or services available in other countries. This has given a huge impetus to E-commerce companies and start-ups offering a variety of products and services. The continuous development of E-commerce platforms and the convenience of purchasing goods and services has increased the customer base continuously. The broad objective of the study is to extract information from consumer searches and use it analytically for driving the business in the future. The purpose of the research is to use supervised classification techniques to categorize product related search queries into category (level 1) and subcategory (level 2), which is further required to derive shopping patterns and trends among the consumers. In this paper, we explore the various multiclass classification techniques, like Naïve Bayes, Random Forests, and SVM. The Naïve Bayes classification at the category (level 1) and subcategory (level 2) outperformed the other algorithms to achieve maximum accuracy of the search query classification.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","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":"115721429","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":"Blind navigation using ambient crowd analysis","authors":"A. Gupta, Sumeet Khandelwal, T. Gandhi","doi":"10.1109/IADCC.2018.8692112","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692112","url":null,"abstract":"Research in assistive technology has been on the rise over the last decade. Numerous solutions and consumer products have flooded the market to guide visually impaired making use of beacon technology, depth cameras and many more. Though certain products and solutions are available for highly structured and regular indoor environments, we are still a long way from an industrial level product for unstructured, dynamic and irregular outdoor environments. Our work harnesses the decision making power of sighted individuals and crowd as a group surrounding the visually impaired. This information extraction from the crowd along with coarse terrain mapping of major obstacles like footpath edges, walls and large pot holes will help the subject to navigate dynamic and irregular environments. This out of the box approach provides us the margin to use low grade equipment and develop algorithms with low computational complexity. The paper explains the theoretical aspects of this approach along with its proof of concept and some remarkable results achieved in real life implementation.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"56 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":"115069060","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":"Algorithm to Quantify the Low and High Resolution HLA Matching in Renal Transplantation","authors":"G. Muthu, S. Mitra","doi":"10.1109/IADCC.2018.8692103","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692103","url":null,"abstract":"HLA matching is conventionally assessed by counting the number of MisMatches (MM) in the class I antigens and class II antigens of the donor and recipient. There is an overlap of matching scores in the MM scoring method. A numerical method has already been developed to quantify the degree of HLA matching in Low Resolution HLA matching. This study has been done to formulate an algorithm for High resolution HLA matching, with a parameter named as HLA Matching (HM) score. Mathematically, 4096 discrete values of HM score existing between 0 and 1 are obtained in 3 loci comparison for renal transplantation. Each value of HM score is unique for every possible matching combination. Donor with the highest percent HM score is considered as the best HLA matched donor. This method overcomes all the disadvantages of the conventional MM scoring method. This algorithm is useful in the donor or recipient selection and the graft survival studies.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","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":"115319355","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":"An Efficient and Secure Authentication Scheme using Markov Chain for Wireless Sensor Networks","authors":"Deepti Singh, B. Kumar, Samayveer Singh, S. Chand","doi":"10.1109/IADCC.2018.8692098","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692098","url":null,"abstract":"Due to varied applications of wireless sensor networks (WSNs), data is required by any user when and wherever they require. Usually, base station gathers all information from the sensor and sends it periodically to the user. But for real-time application, mutual authentication among the communicating nodes is required. During user authentication base station checks that the user is authorized to gather the collected information from the sensor node through an insecure channel. In this paper, we propose an efficient authentication scheme which provides anonymity of user in WSNs that uses Markov chain. The Markov chain is a stochastic process that can be used for a system in which it follows a chain of linked events but next event depends only on the current state of the system. Stationary limit distribution of matrix is created by the base station to help the user to keep their password and identity safe. The security analysis verifies that the proposed scheme is safe against various attacks like forgery, parallel session attacks, user impersonation, etc.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"64 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":"126003549","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}
Chaitanya Kartheek Tarini, Bhujanga Rao Vepakomma, S. Panchumarthy
{"title":"Clinical Programming Software to Evaluate Auditory Performance in Cochlear Implant Patients using Smartphone","authors":"Chaitanya Kartheek Tarini, Bhujanga Rao Vepakomma, S. Panchumarthy","doi":"10.1109/IADCC.2018.8692110","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692110","url":null,"abstract":"Cochlear Implant (CI) system is an auditory prosthesis that provides the perception of hearing sensation to the sensorineural deafened people by surgically implanting and electrically stimulating the auditory nerve. Four to six weeks after surgical implantation of CI, audiologist activates the implant and systematically stimulates the auditory nerve through dedicated software usually called ‘clinical programming software (CPS)’, to fine tune the electrodes so that the patient perceives the sound. It is understood that every cochlear implanted child needs to visit the audiologist periodically up to an age of 18 to undergo routine evaluations. This paper presents a new smartphone-based CPS developed to address the requirements of audiologist with attended advantages to the patients to carry CPS with previous history of stimulated values commonly referred as ‘MAP’ in CI programming. Besides, it provides flexibility to the patient by especially in the case of emergency or visiting nearest doctor for creating a new MAP or attend for routine evaluations, which is not the case provided by the contemporary CI manufacturers.The Smartphone-based CI Programme (SCIP) was developed using Android Studio IDE. SCIP assists audiologist to perform audiological evaluations such as (i) finding electrode status (Active, Short or Open), (ii) impedance measurement, (iii) fine tuning of, threshold and maximum audible level values for each electrode and (iv) updating the speech processor with the fine tuned values. The performance of SCIP software application was validated against a standard Electrode Impedance Tester device during in vitro testing of the developed Indian cochlear implant prosthesis, which is expected to undergo human clinical trials soon.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"23 9 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":"131972761","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 New Paradigm For Generation Of Fuzzy Membership Function","authors":"Anagha Vaidya, P. Metkewar, S. Naik","doi":"10.1109/IADCC.2018.8692089","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692089","url":null,"abstract":"A membership function (MF) is a curve that defines how each point in the input space is mapped to a membership value (or degree of membership) between 0 and 1. The input space is sometimes referred to as the universe of discourse. This paper further develops the fuzzy-based algorithm to add the feature of automatic membership function generation in the fuzzy logic module of the algorithm. From this context, a short review of related work in membership function generation is given, and rules associated with it have been incorporated. In this paper, a one step ahead to the nature of the fuzzy logic-based design, a fitness finding method has been proposed. This paper also evaluates the proposed algorithm for deriving membership function based on association rule using control parameters with its implementation. The algorithm is applied by considering a case study of share market data and results are analyzed and compared with the intuitive cases","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"121 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120814604","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":"Comparative Analysis of Position-Based Routing Protocols for VANETs","authors":"A. Saggu, Kavita Pandey","doi":"10.1109/IADCC.2018.8692111","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692111","url":null,"abstract":"Vehicular ad hoc networks (VANETs) have fetched great interest in both industry and research oriented fields owing to the highly mobile nature and randomly changing topology exhibited by these networks. These characteristics make them susceptible to frequent disconnections, contention and collision related problems. Designing a set of protocols which would cater to the characteristic features of VANETs is a very daunting task. This paper presents a detailed survey of a wide variety of Position-based routing (PBR) protocols. PBR protocols exploit the on-board global positioning receivers to acquire location information of vehicles. Moreover on-board maps are used to fetch the details regarding layout of the road thereby purging the need to set up and maintain routes between the vehicular nodes, making these protocols highly desirable for VANETs. Further a novel classification methodology of the protocols under study along with a comparative analysis depicting their similarity and dissimilarities has been presented.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"31 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":"122345921","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}