Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586816
Shree Ram Khaitu, S. Panday
With the rapid growth of multimedia technology, sharing of multimedia components have become a common practice. Thus, compression of image has become an integral approach that motivates the image compression for the efficient and lossless transmission and for storage of digital data. Huffman coding is one of the entropy encoding approach for compression of image. This paper is based on the fractal image in which Canonical Huffman coding is used for better fractal compression than arithmetic encoding. The result obtained shows that Canonical Huffman coding increases the speed of the compression and has good PNSR, as well as it has better compression ratio than standard Huffman coding.
{"title":"Canonical Huffman Coding for Image Compression","authors":"Shree Ram Khaitu, S. Panday","doi":"10.1109/CCCS.2018.8586816","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586816","url":null,"abstract":"With the rapid growth of multimedia technology, sharing of multimedia components have become a common practice. Thus, compression of image has become an integral approach that motivates the image compression for the efficient and lossless transmission and for storage of digital data. Huffman coding is one of the entropy encoding approach for compression of image. This paper is based on the fractal image in which Canonical Huffman coding is used for better fractal compression than arithmetic encoding. The result obtained shows that Canonical Huffman coding increases the speed of the compression and has good PNSR, as well as it has better compression ratio than standard Huffman coding.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"61 1","pages":"184-190"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83810975","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586835
Shruti Pant, Vishal Kumar
Among the various challenges faced by the P2P file sharing systems like BitTorrent, the most common attack on the basic foundation of such systems is: Free-riding. Generally, free-riders are the users in the file sharing network who avoid contributing any resources but tend to consume the resources unethically from the P2P network whereas white-washers are more specific category of free-riders that voluntarily leave the system in a frequent fashion and appearing again and again with different identities to escape from the penal actions imposed by the network. BitTorrent being a collaborative distributed platform requires techniques for discouraging and punishing such user behavior. In this paper, we propose that “Instead of punishing, we may focus more on rewarding the honest peers”. This approach could be presented as an alternative to other mechanisms of rewarding the peers like tit-for-tat [10], reciprocity based etc., built for the BitTorrent platform. The prime objective of BitTrusty is: providing incentives to the cooperative peers by rewarding in terms of cryptocoins based on blockchain. We have anticipated three ways of achieving the above defined objective. We are further investigating on how to integrate these two technologies of distributed systems viz. P2P file sharing systems and blockchain, and with this new paradigm, interesting research areas can be further developed, both in the field of P2P cryptocurrency networks and also when these networks are combined with other distributed scenarios.
{"title":"BitTrusty: A BitCoin incentivized peer-to-peer file sharing system","authors":"Shruti Pant, Vishal Kumar","doi":"10.1109/CCCS.2018.8586835","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586835","url":null,"abstract":"Among the various challenges faced by the P2P file sharing systems like BitTorrent, the most common attack on the basic foundation of such systems is: Free-riding. Generally, free-riders are the users in the file sharing network who avoid contributing any resources but tend to consume the resources unethically from the P2P network whereas white-washers are more specific category of free-riders that voluntarily leave the system in a frequent fashion and appearing again and again with different identities to escape from the penal actions imposed by the network. BitTorrent being a collaborative distributed platform requires techniques for discouraging and punishing such user behavior. In this paper, we propose that “Instead of punishing, we may focus more on rewarding the honest peers”. This approach could be presented as an alternative to other mechanisms of rewarding the peers like tit-for-tat [10], reciprocity based etc., built for the BitTorrent platform. The prime objective of BitTrusty is: providing incentives to the cooperative peers by rewarding in terms of cryptocoins based on blockchain. We have anticipated three ways of achieving the above defined objective. We are further investigating on how to integrate these two technologies of distributed systems viz. P2P file sharing systems and blockchain, and with this new paradigm, interesting research areas can be further developed, both in the field of P2P cryptocurrency networks and also when these networks are combined with other distributed scenarios.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"1 1","pages":"148-155"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78577254","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}
Pub Date : 2018-10-01DOI: 10.1109/cccs.2018.8586807
Phani Kumar Garimella
Emerging industrial IoT presupposes integration of operational technology (OT) networks with information technology (IT) networks which hitherto were isolated. IT networks focus primarily on PAIN (Privacy/Confidentiality, Authentication, Integrity and Non-repudiation) OT networks focus primarily on AIC (Availability, Integrity and Confidentiality). The conflicting requirements of availability and confidentiality is a challenge that needs to be overcome in a balanced way to reap the benefits of IT-OT integration. This balancing act requires understanding of the OT domain. This paper considers electrical utility as the use case and brings out the considerations in achieving an acceptable IT-OT framework.
{"title":"IT-OT Integration Challenges in Utilities","authors":"Phani Kumar Garimella","doi":"10.1109/cccs.2018.8586807","DOIUrl":"https://doi.org/10.1109/cccs.2018.8586807","url":null,"abstract":"Emerging industrial IoT presupposes integration of operational technology (OT) networks with information technology (IT) networks which hitherto were isolated. IT networks focus primarily on PAIN (Privacy/Confidentiality, Authentication, Integrity and Non-repudiation) OT networks focus primarily on AIC (Availability, Integrity and Confidentiality). The conflicting requirements of availability and confidentiality is a challenge that needs to be overcome in a balanced way to reap the benefits of IT-OT integration. This balancing act requires understanding of the OT domain. This paper considers electrical utility as the use case and brings out the considerations in achieving an acceptable IT-OT framework.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"95 1","pages":"199-204"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78098769","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586815
A. Basnet, Arun K. Timalsina
News classification is the process of grouping news documents into some predefined categories. Due to the increasing volume of the Nepali news content being generated every day by thousands of online news portals, appropriate classification of these news items has become a necessity for the news readers. This research was targeted to improve the Nepali news classification based on Recurrent Neural Networks, that uses deep layers of neural networks to classify the news to an appropriate category. In this research paper, five popular news portals website across eight different categories was used for the purpose of data gathering and their classification accuracies were compared among these websites as well as overall accuracy was measured. The model was compared with the Support Vector Machine based on the parameters Accuracy, Precision, Recall and F1 Score. The use of Long Short Term Memory Recurrent Neural Network has improved the precision with the use of word2vec model. The presented model in the research has achieved a good accuracy of 84.63% and precision of 89% in compared to the SVM where the accuracy was 81.41% and precision 85%. Based on the categories of the news, sports news was classified more accurately by the model and economy was least accurately classified.
{"title":"Improving Nepali News Recommendation Using Classification Based on LSTM Recurrent Neural Networks","authors":"A. Basnet, Arun K. Timalsina","doi":"10.1109/CCCS.2018.8586815","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586815","url":null,"abstract":"News classification is the process of grouping news documents into some predefined categories. Due to the increasing volume of the Nepali news content being generated every day by thousands of online news portals, appropriate classification of these news items has become a necessity for the news readers. This research was targeted to improve the Nepali news classification based on Recurrent Neural Networks, that uses deep layers of neural networks to classify the news to an appropriate category. In this research paper, five popular news portals website across eight different categories was used for the purpose of data gathering and their classification accuracies were compared among these websites as well as overall accuracy was measured. The model was compared with the Support Vector Machine based on the parameters Accuracy, Precision, Recall and F1 Score. The use of Long Short Term Memory Recurrent Neural Network has improved the precision with the use of word2vec model. The presented model in the research has achieved a good accuracy of 84.63% and precision of 89% in compared to the SVM where the accuracy was 81.41% and precision 85%. Based on the categories of the news, sports news was classified more accurately by the model and economy was least accurately classified.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"29 1","pages":"138-142"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78190035","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586803
Ug Singh, M. Shorunke
Communication in the modern day era is predominantly dependent on Information and Communication Technology (ICT). The rise in cybercrime, digital espionage and other cyber-related disturbances is one of great concerns to cyberspace users, both corporate and individual. Radio Frequency technologies and solutions been adopted for in-building, and outdoor wireless coverage solutions for the supply-chains market, including turnkey solutions for optimized communications, are been faced with security issues. This paper suggests a secure network communications route (Li-Fi Technology) alternative for users of radio frequency identification (RFID) technologies and solutions. A communication path that is resilient and resistant to disruptions by mitigating sophisticated network communication attacks such as spoofing and TCP/IP attacks (Man-In-the-middle attacks, Denial of Service attacks). This paper proposes the use of Li-Fi network for a safe and secure cyberspace communication exchange path.
{"title":"Li-Fi Technology: Bridging The Radio Frequency Communication Gap","authors":"Ug Singh, M. Shorunke","doi":"10.1109/CCCS.2018.8586803","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586803","url":null,"abstract":"Communication in the modern day era is predominantly dependent on Information and Communication Technology (ICT). The rise in cybercrime, digital espionage and other cyber-related disturbances is one of great concerns to cyberspace users, both corporate and individual. Radio Frequency technologies and solutions been adopted for in-building, and outdoor wireless coverage solutions for the supply-chains market, including turnkey solutions for optimized communications, are been faced with security issues. This paper suggests a secure network communications route (Li-Fi Technology) alternative for users of radio frequency identification (RFID) technologies and solutions. A communication path that is resilient and resistant to disruptions by mitigating sophisticated network communication attacks such as spoofing and TCP/IP attacks (Man-In-the-middle attacks, Denial of Service attacks). This paper proposes the use of Li-Fi network for a safe and secure cyberspace communication exchange path.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"15 1","pages":"30-34"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73756062","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586819
D. Naik, Lyla B. Das, T. Bindiya
In this paper, the use of sensor networks in environmental monitoring, vehicle monitoring and traffic management, which are important in a smart city are discussed. Sensors in Zigbee and Wi Fi networks form the back bone of this work. Low power networks like Zigbee and connectivity provided by WiFi are needed to realize the concept of Internet of Things (IoT). The main cause of environmental pollution in most cities are industries and automobiles emitting poisonous gases. This paper discusses the implementation of a unit which senses the presence of such gases and uploads the information to a website, and also sends messages to the concerned people. The second part of this work is a vehicle monitoring unit, that can be fixed in vehicles. This system tracks the location of the vehicle, detects accidents to the vehicle and monitors its engine temperature and the presence of poisonous gases from its exhaust. In the case of the vehicle is stolen, it also has the feature to locate the vehicle and prevent it from moving until a message is sent by the owner. The third part of the work, in which, vehicles which do signal jumping are detected and penalised. This feature is very relevant to the countries like India where traffic rules are regularly violated. The density of the traffic around traffic junctions is measured and information updated in the website. An Android app is developed so that all the required information is easily available. The paper describes the hardware and software implementation of the prototype system.
{"title":"Wireless Sensor networks with Zigbee and WiFi for Environment Monitoring, Traffic Management and Vehicle Monitoring in Smart Cities","authors":"D. Naik, Lyla B. Das, T. Bindiya","doi":"10.1109/CCCS.2018.8586819","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586819","url":null,"abstract":"In this paper, the use of sensor networks in environmental monitoring, vehicle monitoring and traffic management, which are important in a smart city are discussed. Sensors in Zigbee and Wi Fi networks form the back bone of this work. Low power networks like Zigbee and connectivity provided by WiFi are needed to realize the concept of Internet of Things (IoT). The main cause of environmental pollution in most cities are industries and automobiles emitting poisonous gases. This paper discusses the implementation of a unit which senses the presence of such gases and uploads the information to a website, and also sends messages to the concerned people. The second part of this work is a vehicle monitoring unit, that can be fixed in vehicles. This system tracks the location of the vehicle, detects accidents to the vehicle and monitors its engine temperature and the presence of poisonous gases from its exhaust. In the case of the vehicle is stolen, it also has the feature to locate the vehicle and prevent it from moving until a message is sent by the owner. The third part of the work, in which, vehicles which do signal jumping are detected and penalised. This feature is very relevant to the countries like India where traffic rules are regularly violated. The density of the traffic around traffic junctions is measured and information updated in the website. An Android app is developed so that all the required information is easily available. The paper describes the hardware and software implementation of the prototype system.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"51 1","pages":"46-50"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81550346","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586826
Swagat Ranjit, S. Shrestha, S. Subedi, S. Shakya
Foreign currency exchange plays a vital role for trading of currency in the financial market. Due to its volatile nature, prediction of foreign currency exchange is a challenging task. This paper presents different machine learning techniques like Artificial Neural Network (ANN), Recurrent Neural Network (RNN) to develop prediction model between Nepalese Rupees against three major currencies Euro, Pound Sterling and US dollar. Recurrent Neural Network is a type of neural network that have feedback connections. In this paper, prediction model were based on different RNN architectures, feed forward ANN with back propagation algorithm and then compared the accuracy of each model. Different ANN architecture models like Feed forward neural network, Simple Recurrent Neural Network (SRNN), Gated Recurrent Unit (GRU) and Long Short Term Memory (LSTM) were used. Input parameters were open, low, high and closing prices for each currency. From this study, we have found that LSTM networks provided better results than SRNN and GRU networks.
{"title":"Comparison of algorithms in Foreign Exchange Rate Prediction","authors":"Swagat Ranjit, S. Shrestha, S. Subedi, S. Shakya","doi":"10.1109/CCCS.2018.8586826","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586826","url":null,"abstract":"Foreign currency exchange plays a vital role for trading of currency in the financial market. Due to its volatile nature, prediction of foreign currency exchange is a challenging task. This paper presents different machine learning techniques like Artificial Neural Network (ANN), Recurrent Neural Network (RNN) to develop prediction model between Nepalese Rupees against three major currencies Euro, Pound Sterling and US dollar. Recurrent Neural Network is a type of neural network that have feedback connections. In this paper, prediction model were based on different RNN architectures, feed forward ANN with back propagation algorithm and then compared the accuracy of each model. Different ANN architecture models like Feed forward neural network, Simple Recurrent Neural Network (SRNN), Gated Recurrent Unit (GRU) and Long Short Term Memory (LSTM) were used. Input parameters were open, low, high and closing prices for each currency. From this study, we have found that LSTM networks provided better results than SRNN and GRU networks.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"1 1","pages":"9-13"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89953213","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586805
G. Bhandari, Ratneshwer Gupta
In the conventional techniques, it requires prior knowledge of faults or a special structure, which may not be realistic in practice while detecting the software faults. To deal with this problem, in this work, the proposed approach aims to predict the faults of the software utilizing the source code metrics. In addition, the purpose of this paper is to measure the capability of the software fault predictability in terms of accuracy, f-measure, precision, recall, Area Under ROC (Receiver Operating Characteristic) Curve (AUC). The study investigates the effect of the feature selection techniques for software fault prediction. As an experimental analysis, our proposed approach is validated from four publicly available datasets. The result predicted from Random Forest technique outperforms the other machine learning techniques in most of the cases. The effect of the feature selection techniques has increased the performance in few cases, however, in the maximum cases it is negligible or even the worse.
在传统的故障检测技术中，需要预先了解故障或特定的结构，这在实际的软件故障检测中是不现实的。为了解决这个问题，本文提出的方法旨在利用源代码度量来预测软件的错误。此外，本文的目的是从准确度、f-measure、精密度、召回率、ROC曲线下面积(Area Under ROC, Receiver Operating Characteristic Curve, AUC)等方面衡量软件故障可预测性的能力。研究了特征选择技术在软件故障预测中的作用。作为实验分析，我们提出的方法从四个公开可用的数据集进行了验证。在大多数情况下，随机森林技术预测的结果优于其他机器学习技术。特征选择技术的效果在少数情况下提高了性能，但在大多数情况下，它可以忽略不计甚至更糟。
{"title":"Machine learning based software fault prediction utilizing source code metrics","authors":"G. Bhandari, Ratneshwer Gupta","doi":"10.1109/CCCS.2018.8586805","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586805","url":null,"abstract":"In the conventional techniques, it requires prior knowledge of faults or a special structure, which may not be realistic in practice while detecting the software faults. To deal with this problem, in this work, the proposed approach aims to predict the faults of the software utilizing the source code metrics. In addition, the purpose of this paper is to measure the capability of the software fault predictability in terms of accuracy, f-measure, precision, recall, Area Under ROC (Receiver Operating Characteristic) Curve (AUC). The study investigates the effect of the feature selection techniques for software fault prediction. As an experimental analysis, our proposed approach is validated from four publicly available datasets. The result predicted from Random Forest technique outperforms the other machine learning techniques in most of the cases. The effect of the feature selection techniques has increased the performance in few cases, however, in the maximum cases it is negligible or even the worse.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"13 1","pages":"40-45"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89427833","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586801
K. Mohan, K. Chandra Sekharaiah, P. Premchand, Gopal Upakaram Pullaiah, B. Malathi
In this paper the authors described the importance of Schizophrenia in Medical Systems versus Computer Systems. Dissimilar Schizophrenias were identified. The schizophrenia is thoughtful, consequently it could be discovered in future. But there is no Intelligence Quotient (IQ). The author contrasting this perception with present research work i.e., Cybercrimes in Higher Educations. This encouraging Psycho-Neuro-Computer Systems are very essential things to control and prevent the Cybercrimes in Cyber space. On each successive day the thoughts, feelings, behavior of humans are going in destructive manner. Especially in internet by using this Communication Technologies and facilities the Cybercrimes are ever-increasing very quickly. The Online Networking Systems are anguish, the people who have Schizophrenia is a serious psychological disorder in which people understand reality abnormally. Schizophrenia may result in some combination of illusions and tremendously disordered thinking and behavior that damages daily functioning, and can be disabling. The author developing positive psychology between the higher education students and faculties to reduce the Online Cybercrimes. In our research Cognitive Systems are showing main role which is interrelated with computer science and psychology. It provides us with a systematic foundation in the principles, ethics, morals, values and techniques used by intelligent systems (both natural and artificial) to interact with the web world. My research required Emotional Intelligence (or) Knowledge (or) Emotional Quotient (EQ) use emotions to enhance positive thoughts. People with high emotions can control, evaluate towards negative thoughts and perceive others emotions and thoughts, uniform estimation calculated of cleverness.
{"title":"Approving Psycho-Neuro-Computer Systems to prevent (Systemic Vs Individualistic Perspective) Cybercrimes in Information Highway","authors":"K. Mohan, K. Chandra Sekharaiah, P. Premchand, Gopal Upakaram Pullaiah, B. Malathi","doi":"10.1109/CCCS.2018.8586801","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586801","url":null,"abstract":"In this paper the authors described the importance of Schizophrenia in Medical Systems versus Computer Systems. Dissimilar Schizophrenias were identified. The schizophrenia is thoughtful, consequently it could be discovered in future. But there is no Intelligence Quotient (IQ). The author contrasting this perception with present research work i.e., Cybercrimes in Higher Educations. This encouraging Psycho-Neuro-Computer Systems are very essential things to control and prevent the Cybercrimes in Cyber space. On each successive day the thoughts, feelings, behavior of humans are going in destructive manner. Especially in internet by using this Communication Technologies and facilities the Cybercrimes are ever-increasing very quickly. The Online Networking Systems are anguish, the people who have Schizophrenia is a serious psychological disorder in which people understand reality abnormally. Schizophrenia may result in some combination of illusions and tremendously disordered thinking and behavior that damages daily functioning, and can be disabling. The author developing positive psychology between the higher education students and faculties to reduce the Online Cybercrimes. In our research Cognitive Systems are showing main role which is interrelated with computer science and psychology. It provides us with a systematic foundation in the principles, ethics, morals, values and techniques used by intelligent systems (both natural and artificial) to interact with the web world. My research required Emotional Intelligence (or) Knowledge (or) Emotional Quotient (EQ) use emotions to enhance positive thoughts. People with high emotions can control, evaluate towards negative thoughts and perceive others emotions and thoughts, uniform estimation calculated of cleverness.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"35 1","pages":"205-209"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87960618","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}
Pub Date : 2018-10-01DOI: 10.1109/CCCS.2018.8586829
Harmeet Kaur, Satish Kumar
The advancements in technology have touched many domains and Medical Domain is one such beneficiary with advancements like Radiation Oncology, Real time imaging, 4-D respiratory gating etc. This paper deals with the Multi-Modality images and its fusion so that efficient, accurate and especially low cost high-end treatment is available to all. For Diagnostic and Treatment Planning, Medical images are the vital source of information. In this study we have employed the Harvard Database. The Medical images come with different modalities like CT, PET, MRI are medical images with different modality. These modalities are fused such that the best information is available in the fused image and to fulfill that, this paper puts forward Fuzzy Logic Inference system based image fusion. The proposed technique uses CT and MRI as input and the fusion is applied using Fuzzy Logic. The evaluation of output is done by the metrics: PSNR, SNR and MSE. The fused image attained through fuzzy logic is more informative when compared with the wavelet based fusion method.
{"title":"Fusion Of Multi-Modality Medical Images: A Fuzzy Approach","authors":"Harmeet Kaur, Satish Kumar","doi":"10.1109/CCCS.2018.8586829","DOIUrl":"https://doi.org/10.1109/CCCS.2018.8586829","url":null,"abstract":"The advancements in technology have touched many domains and Medical Domain is one such beneficiary with advancements like Radiation Oncology, Real time imaging, 4-D respiratory gating etc. This paper deals with the Multi-Modality images and its fusion so that efficient, accurate and especially low cost high-end treatment is available to all. For Diagnostic and Treatment Planning, Medical images are the vital source of information. In this study we have employed the Harvard Database. The Medical images come with different modalities like CT, PET, MRI are medical images with different modality. These modalities are fused such that the best information is available in the fused image and to fulfill that, this paper puts forward Fuzzy Logic Inference system based image fusion. The proposed technique uses CT and MRI as input and the fusion is applied using Fuzzy Logic. The evaluation of output is done by the metrics: PSNR, SNR and MSE. The fused image attained through fuzzy logic is more informative when compared with the wavelet based fusion method.","PeriodicalId":6570,"journal":{"name":"2018 IEEE 3rd International Conference on Computing, Communication and Security (ICCCS)","volume":"70 1","pages":"112-115"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77166659","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：