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2016 1st India International Conference on Information Processing (IICIP)最新文献

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Ontology based disease diagnosis system with probabilistic inference 基于本体的概率推理疾病诊断系统
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975383
Pankaj Agarwal, R. Verma, Anupama Mallik
{"title":"Ontology based disease diagnosis system with probabilistic inference","authors":"Pankaj Agarwal, R. Verma, Anupama Mallik","doi":"10.1109/IICIP.2016.7975383","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975383","url":null,"abstract":"Disease diagnosis system integrates fragmented and constantly evolving information about diseases from various sources, such as the web, and builds up an ontology model and inference system, which could be used by doctors and researchers in the medical domain. It can also be used to make the information about rare diseases accessible for experts world over, which may not, otherwise, be easily available. This paper presents an ontology-based system that creates a knowledge graph of the extracted information to make it machine understandable. Instead of using deterministic logic, it generates a Bayesian network out of it that can be utilized to infer the most probable diseases given the patient's symptoms, age, gender, lifestyle and personal and parental medical history as input. It further recommends relevant diagnostic tests and pathology labs where the tests could be undertaken. It has a user-friendly interface through which it can take SPARQL query as an input and show the result to the user.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123573045","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}
引用次数: 15
High speed low power wireless signal timing analysis on FPGA using turbo coding and Viterbi algorithm 基于turbo编码和Viterbi算法的FPGA高速低功耗无线信号时序分析
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975300
Shoban Mude, B. Naik
{"title":"High speed low power wireless signal timing analysis on FPGA using turbo coding and Viterbi algorithm","authors":"Shoban Mude, B. Naik","doi":"10.1109/IICIP.2016.7975300","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975300","url":null,"abstract":"As higher and higher speeds are used in wireless appliance, error correction continues to pose a considerable design challenge. Turbo codes exhibit attainment, in terms of bit error probability, that is very close to the Shannon limit and can be efficiently achieved for high-speed use. Turbo encoders and decoders have been introduced, most of which are based on convolution encoding. Here each encoder produces a single check bit for each input bit and that input bit is preserved. In the earlier convolution encoders the input bit is not preserved. In turbo coding the dynamic variation changes in convolution codes is familiar as recursive systematic convolution codes (RSC).","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121567256","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}
引用次数: 1
Educational data mining and its role in determining factors affecting students academic performance: A systematic review 教育数据挖掘及其在影响学生学习成绩的决定因素中的作用:系统综述
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975354
Leena Khanna, S. Singh, Mansaf Alam
{"title":"Educational data mining and its role in determining factors affecting students academic performance: A systematic review","authors":"Leena Khanna, S. Singh, Mansaf Alam","doi":"10.1109/IICIP.2016.7975354","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975354","url":null,"abstract":"Education helps people develop as individuals. It not only helps build social skills but also enhances the problem solving and decision making skills of individuals. With the growing number of schools, colleges and universities around the globe, education now has taken new dimension. The main focus of higher Educational Institutes is to improve the overall quality and effectiveness of education. Predicting the performance of student and Predicting the Future in this world of Big Data is the need of Today in Education. The crude data from educational organizations act as a gold mine which facilitate the analysts and designers to make a system that will improve the overall teaching and learning process. This new field coined as Educational Data mining helps in Predicting the Future and Changing the Future. In this paper we have studied what is Educational Data Mining and what are the Application areas of EDM, various techniques of EDM and the factors affecting the students' Academic Performance and the Teaching-Learning process.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"236 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123261012","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}
引用次数: 23
Flight crash investigation using data mining techniques 利用数据挖掘技术进行飞行事故调查
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975390
Shagun Sharma, A. Sabitha
{"title":"Flight crash investigation using data mining techniques","authors":"Shagun Sharma, A. Sabitha","doi":"10.1109/IICIP.2016.7975390","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975390","url":null,"abstract":"Data mining refers to extraction of information from huge chunks of the dataset. It's also called information mining. It is exercised in numerous fields like medicine, environment, education, crime, etc. In this research work crash investigation and analysis of the flights are done. Flight crashes may be caused due to pilot error, mechanical failure, bad weather, sabotages or human error. This research paper investigates international flight crashes since 1908 to 2009 through K-Means clustering data mining technique and cosine similarity. Clustering helps to put objects into the same group. Cosine similarity measure helps in finding similarity among different texts. The research work is done for identifying aboard/ground fatality rate with operators and location as well as to find similarity among the plane crashes.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123847670","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}
引用次数: 6
Empirical study of various weight initialization techniques for FFANN FFANN各种权值初始化技术的实证研究
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975370
M. Bhatia, Pravin Chandra
{"title":"Empirical study of various weight initialization techniques for FFANN","authors":"M. Bhatia, Pravin Chandra","doi":"10.1109/IICIP.2016.7975370","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975370","url":null,"abstract":"The weight initialization implementation is related to the convergence of any learning/training algorithm. In this paper we have analyzed Gradient Descent with Momentum Back propagation algorithm using eight different approximation functions and Nguyen & Widrow weight initialization method. We found that the best performance results are obtained using fifth approximation problem. The best performance output is also shown graphically in this paper.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129369268","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}
引用次数: 1
Implementation of temporal functionality in objects with roles model (TF-ORM) 使用角色模型(TF-ORM)在对象中实现时态功能
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975368
Shailender Kumar, R. Rishi, Rupender Duggal
{"title":"Implementation of temporal functionality in objects with roles model (TF-ORM)","authors":"Shailender Kumar, R. Rishi, Rupender Duggal","doi":"10.1109/IICIP.2016.7975368","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975368","url":null,"abstract":"The temporal data models are convenient way to specify the real world applications that presents timely evolution of data. Since last three decades, various temporal data models have been proposed, but no commercial temporal database is available. The only mode of implementation of temporal database is to use traditional databases, by adding temporal extension. This paper presents the implementation of Temporal Object-Oriented Data Model that supports the role concept, i.e. Temporal Functionality in Objects with Roles Model(TF-ORM). Roles are used to describe different perspective of an object evolution. The implementation of the TF-ORM model is done by using PostgreSQL; it is an open source object relational database management system. To implement this data model, initially we start designing the schema of our database, and then a mapping of TF-ORM schema with the underlying relational database (PostgreSQL) is performed. This paper, describes about the TF-ORM model, the schema mapping between the aforementioned model and the relational database, and the implementation of this model.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128770214","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}
引用次数: 0
Iris anti-spoofing under varying illumination conditions 不同光照条件下虹膜抗欺骗
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975358
A. Malhotra, Rashmi Gupta
{"title":"Iris anti-spoofing under varying illumination conditions","authors":"A. Malhotra, Rashmi Gupta","doi":"10.1109/IICIP.2016.7975358","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975358","url":null,"abstract":"Today iris recognition systems are extensively used for security and authentication purposes due to their simplicity and high reliability. But these systems face a major challenge of being spoofed by high quality printed iris images or pictures captured by camera. The problem is aggravated by use of varying illumination conditions in an attack access attempt. This paper investigates spoofing attempts and suggests a simple approach based on statistical parameters to counter against such attacks in the event of varying illumination sources. Self Quotient Image (SQI) is used to combat varying lighting conditions. A feature score is computed based on the statistical parameters. A binary Support Vector Machine (SVM) classifier is used to classify the image under test as real or spoof by matching the feature score of the trained images to that of the test image. The experimental results show that the proposed method performs better than other state-of-the-art techniques.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114502410","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}
引用次数: 1
Sparse coding based robust image denoising via coupled dictionary 基于稀疏编码的耦合字典鲁棒图像去噪
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975357
Kuldeep Singh, D. K. Viswakarma, G. S. Walia, Rajiv Kapoor
{"title":"Sparse coding based robust image denoising via coupled dictionary","authors":"Kuldeep Singh, D. K. Viswakarma, G. S. Walia, Rajiv Kapoor","doi":"10.1109/IICIP.2016.7975357","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975357","url":null,"abstract":"This paper addresses the image denoising problem using the recent advancements in sparse representation based image restoration. This novel approach is based on sparse coding using a pre-learned coupled dictionary. Prior research suggests that it is possible to represent every image patch as a sparse linear combination of dictionary elements learned from a set of example patches. Joint training of coupled dictionaries for clear and noisy images helps to enforce self-similarity between noisy and latent images. The sparsity measure over such a coupled dictionary is used as a regularisation constraint to recover a denoised image patch from a noisy image patch. The experimental results indicate that the proposed method appears to be competitive with other denoising methods.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115360064","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}
引用次数: 2
Fuzzy logic based decision support system 基于模糊逻辑的决策支持系统
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975310
Jagannath Wadgaonkar, Kalyani Bhole
{"title":"Fuzzy logic based decision support system","authors":"Jagannath Wadgaonkar, Kalyani Bhole","doi":"10.1109/IICIP.2016.7975310","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975310","url":null,"abstract":"Anaesthesia practice might involve instances proving to be life threatening. Hence one has to be cautious and at the same time be able to avert any danger if any of such situation prevails But humans can make some errors based on their decision which may lead to loss of life. Hence there is a need to introduce an decision support system (DSS), which would take correct decisions based on the inputs. This paper presents the design and implementation of fuzzy logic based decision support system. Fuzzy logic mimics the human decisions as per the inputs. So the chances of propofol being infused wrongly are minimized. Also various parameters like heart rate, oxygen saturation, blood pressure is continuously monitored. Based upon these inputs to the fuzzy decision support system and Lab-view Graphical user interface (GUI) will give appropriate decision as the depth of anesthesia. Hence the risk to life is attenuated to great extent. This type of decision support system can be used in hospitals and health-care facilities and will prove useful not only to professionals but also to the newcomers in the field of anesthesia. Another advantage of this system is cost effective and viable for human society. Experts based decision support system is designed and implemented using Lab-view. Developed GUI is validated from experts for 270 different conditions. Out of 270 experts 3 decisions accepting given by DSS.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116238408","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}
引用次数: 6
Personalizing healthcare services to support decision making in treatment of cancer patients using ontology alignment 使用本体对齐实现个性化医疗保健服务以支持癌症患者治疗中的决策制定
2016 1st India International Conference on Information Processing (IICIP) Pub Date : 2016-08-01 DOI: 10.1109/IICIP.2016.7975308
Anirban Chakrabarty, S. Roy
{"title":"Personalizing healthcare services to support decision making in treatment of cancer patients using ontology alignment","authors":"Anirban Chakrabarty, S. Roy","doi":"10.1109/IICIP.2016.7975308","DOIUrl":"https://doi.org/10.1109/IICIP.2016.7975308","url":null,"abstract":"The foremost medium of information exchange has been text since ages but with the swift increase in volume of documents it has become a tedious task to organize and retrieve relevant information without the use of text-mining applications. Ontologies are a formal way of representing conceptual knowledge and can be related to text data to assist in this task. There is always a need for accurate interpretation of medical records of cancer patients in deciding intervention plans for proper treatment. However due to the ever changing demand in healthcare services such information sources can be highly variable and may not be suitable for all patients. In this situation the most challenging problem is personalizing healthcare treatment adapted to the patient's medical, social and economic conditions. To manage this problem efficiently the work suggests an ontology alignment model using context aware properties of the system and the patient to facilitate decision making. A patient ontology is mapped to the disease ontology to dynamically transform general treatment options into individual intervention plans most suitable for the patient. The proposed method can be used by medical professionals in recognizing incorrect diagnosis, preventive actions or in identifying co-occurring diseases in the patient.","PeriodicalId":220344,"journal":{"name":"2016 1st India International Conference on Information Processing (IICIP)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124866886","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}
引用次数: 2
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