Pub Date : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280078
Kushal Anjaria, Arun Mishra
Information security related training is extremely important nowadays for various organizations. But for the trainer, it is difficult to know the existing skill levels of trainees in information security area and their expectations from the training. As a result, to decide the time allocation for each level of training also becomes a difficult task for the trainer. To solve this challenge, present work proposes neuroevolution based algorithm. The algorithm can also be useful for online training or web service/mobile app based training. The trainer needs to execute the algorithm in pre-training time and based on the result he/she can adjust or modify training content and time allocation for each training level.
{"title":"Neuroevolution for effective information security training","authors":"Kushal Anjaria, Arun Mishra","doi":"10.1109/ICSOFTCOMP.2017.8280078","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280078","url":null,"abstract":"Information security related training is extremely important nowadays for various organizations. But for the trainer, it is difficult to know the existing skill levels of trainees in information security area and their expectations from the training. As a result, to decide the time allocation for each level of training also becomes a difficult task for the trainer. To solve this challenge, present work proposes neuroevolution based algorithm. The algorithm can also be useful for online training or web service/mobile app based training. The trainer needs to execute the algorithm in pre-training time and based on the result he/she can adjust or modify training content and time allocation for each training level.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114841362","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280091
Tushar Kant Mudgal, Aditya Gupta, Siddhant U. Jain, Kunal Gusain
This Brain tumor detection and classification is an intrinsic part of any diagnostic system and has witnessed extensive research and procedural advancement over time. The complexity of brain as an organ features to be identified, the presence of noise, poor contrast and intensity inhomogeneity in the images, efficient feature extraction, and accurate classification necessitates the development of an efficacious automated system. We propose a novel automated approach for detection and classification, using the Modified K-Means Clustering algorithm with Mean Shift Segmentation for pre-processing magnetic resonance images (MRI). Detection is done using Marker-Controlled Watershed Transform, and Gray-Level Co-Occurrence Matrix (GLCM) is used for feature extraction. For classification, we use the new and improved version of Gradient Boosted Machines (GBM) called eXtreme GBMs. Implemented using the XGBoost library, this supervised learning model has shown more accurate results and in lesser times, it is being used widely by data scientists and gives state of the art solutions.
{"title":"Automated system for Brain tumour detection and classification using eXtreme Gradient Boosted decision trees","authors":"Tushar Kant Mudgal, Aditya Gupta, Siddhant U. Jain, Kunal Gusain","doi":"10.1109/ICSOFTCOMP.2017.8280091","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280091","url":null,"abstract":"This Brain tumor detection and classification is an intrinsic part of any diagnostic system and has witnessed extensive research and procedural advancement over time. The complexity of brain as an organ features to be identified, the presence of noise, poor contrast and intensity inhomogeneity in the images, efficient feature extraction, and accurate classification necessitates the development of an efficacious automated system. We propose a novel automated approach for detection and classification, using the Modified K-Means Clustering algorithm with Mean Shift Segmentation for pre-processing magnetic resonance images (MRI). Detection is done using Marker-Controlled Watershed Transform, and Gray-Level Co-Occurrence Matrix (GLCM) is used for feature extraction. For classification, we use the new and improved version of Gradient Boosted Machines (GBM) called eXtreme GBMs. Implemented using the XGBoost library, this supervised learning model has shown more accurate results and in lesser times, it is being used widely by data scientists and gives state of the art solutions.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124508497","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280082
Ayush Sharma, Sudhanshu Kulshrestha, S. Daniel
For breast cancer diagnosis in patients, radiologists conduct Fine Needle Aspirate (FNA) procedure of breast tumor. This procedure reveal features such as tumor radius, concavity, texture and fractal dimensions. These features are further studied by medical experts to classify tumor as Benign or Malignant. The cardinal aim of this paper is to predict breast cancer as benign or malignant using data set from Wisconsin Breast Cancer Data using sophisticated classifiers such as Logistic Regression, Nearest Neighbor, Support Vector Machines. Furthermore, using Wisconsin Prognostic data set, probability of recurrence in affected patients in calculated. As a result, a concrete relationship between precision, recall and the number of features in the data set is achieved, which is shown graphically.
{"title":"Machine learning approaches for breast cancer diagnosis and prognosis","authors":"Ayush Sharma, Sudhanshu Kulshrestha, S. Daniel","doi":"10.1109/ICSOFTCOMP.2017.8280082","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280082","url":null,"abstract":"For breast cancer diagnosis in patients, radiologists conduct Fine Needle Aspirate (FNA) procedure of breast tumor. This procedure reveal features such as tumor radius, concavity, texture and fractal dimensions. These features are further studied by medical experts to classify tumor as Benign or Malignant. The cardinal aim of this paper is to predict breast cancer as benign or malignant using data set from Wisconsin Breast Cancer Data using sophisticated classifiers such as Logistic Regression, Nearest Neighbor, Support Vector Machines. Furthermore, using Wisconsin Prognostic data set, probability of recurrence in affected patients in calculated. As a result, a concrete relationship between precision, recall and the number of features in the data set is achieved, which is shown graphically.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115339249","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280089
Priyanka Israni, Dippal Israni
Object Oriented Database (OOD) is one of the emerging technologies which replace relational databases as relational databases are not designed to support multimedia data. As there is need to move towards the age of internet, thus dealing with multimedia data is the issue which is solved by Object Oriented Databases. Generally, the data available to us is highly imprecise or uncertain. Thus, there is the need of Fuzziness in databases to deal with uncertainties in data. The extension towards OOD model is Fuzzy OOD which is used to model various Object Oriented features with the representation of uncertainty or impreciseness in data. The Proposed work includes the OOD model which handles fuzziness in data and to enhance performance of the proposed model, an indexing technique using R tree is introduced. Query Processing in proposed model is compared with the Normal Query Processing with respect to time. The results show that the performance of Query Processing in Proposed ITFOOD is better than the normal query processing without Indexing.
{"title":"An indexing technique for fuzzy object oriented database using R tree index","authors":"Priyanka Israni, Dippal Israni","doi":"10.1109/ICSOFTCOMP.2017.8280089","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280089","url":null,"abstract":"Object Oriented Database (OOD) is one of the emerging technologies which replace relational databases as relational databases are not designed to support multimedia data. As there is need to move towards the age of internet, thus dealing with multimedia data is the issue which is solved by Object Oriented Databases. Generally, the data available to us is highly imprecise or uncertain. Thus, there is the need of Fuzziness in databases to deal with uncertainties in data. The extension towards OOD model is Fuzzy OOD which is used to model various Object Oriented features with the representation of uncertainty or impreciseness in data. The Proposed work includes the OOD model which handles fuzziness in data and to enhance performance of the proposed model, an indexing technique using R tree is introduced. Query Processing in proposed model is compared with the Normal Query Processing with respect to time. The results show that the performance of Query Processing in Proposed ITFOOD is better than the normal query processing without Indexing.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114840464","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280094
P. Rajendran, Rufina Sharon
The Question Answering (QA) system is playing a significant role in search engine and information extraction principle. This investigation of research work has performed with an Interface which incorporates the different modules of ontology assistance, template assistance, and user modeling techniques which function as the supporter between the client user and system to deal with the user problems. The latest features which formulate to increase system performance are ontology assisted query template, natural language query mode and keyword based query mode. The experimentation result implies that 85% queries have been accurately identified by the system.
{"title":"Dynamic question answering system based on ontology","authors":"P. Rajendran, Rufina Sharon","doi":"10.1109/ICSOFTCOMP.2017.8280094","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280094","url":null,"abstract":"The Question Answering (QA) system is playing a significant role in search engine and information extraction principle. This investigation of research work has performed with an Interface which incorporates the different modules of ontology assistance, template assistance, and user modeling techniques which function as the supporter between the client user and system to deal with the user problems. The latest features which formulate to increase system performance are ontology assisted query template, natural language query mode and keyword based query mode. The experimentation result implies that 85% queries have been accurately identified by the system.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114285489","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280079
Mrunal K. Pathak, V. Bairagi, N. Srinivasu, Bhavana V. Chavan
Most recently popular biometrie systems are based on recognition and classification of unique sclera and iris patterns. Unique pattern of blood veins explore the interest in sclera recognition for person identification. However sclera segmentation of relaxed eye images in condition such as different stare direction, at-a-distance image and on-the-move image widely enquired. The drawback of iris is off angle imaging where position of iris and center for off angle imagining affect the performance of sclera segmentation in terms of accuracy. Another challenge in sclera segmentation and iris recognition is high resolution and dark images which causes draining process for mobile application. So we proposed a new method which is the fusion of both iris and sclera. In proposed system sclera and iris descriptor value are fuse together for reliable and accurate iris recognition system. The proposed method will test the execution of iris recognition system for different fusion model using iris and sclera descriptor values to ensure the performance of iris recognition for a relaxed imaging.
{"title":"Match score level fusion of iris and sclera descriptor for iris recognition","authors":"Mrunal K. Pathak, V. Bairagi, N. Srinivasu, Bhavana V. Chavan","doi":"10.1109/ICSOFTCOMP.2017.8280079","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280079","url":null,"abstract":"Most recently popular biometrie systems are based on recognition and classification of unique sclera and iris patterns. Unique pattern of blood veins explore the interest in sclera recognition for person identification. However sclera segmentation of relaxed eye images in condition such as different stare direction, at-a-distance image and on-the-move image widely enquired. The drawback of iris is off angle imaging where position of iris and center for off angle imagining affect the performance of sclera segmentation in terms of accuracy. Another challenge in sclera segmentation and iris recognition is high resolution and dark images which causes draining process for mobile application. So we proposed a new method which is the fusion of both iris and sclera. In proposed system sclera and iris descriptor value are fuse together for reliable and accurate iris recognition system. The proposed method will test the execution of iris recognition system for different fusion model using iris and sclera descriptor values to ensure the performance of iris recognition for a relaxed imaging.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"07 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129420996","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280080
N. Solanki, J. Patel
For the generation of electricity with less impact on the environment, utilization of renewable energy resources is growing worldwide as a clean energy source. With the increasing penetration of renewable based Distributed Generators (DG) on the distribution grid can create power quality issues like voltage variations, relay malfunctioning, and reverse power flow during lightly loaded condition which rises the voltage level beyond the limit. To control the voltage variables, there is a need to install power electronics converter based FACTs devices like STATCOM. Now a days, a new way to utilize the PV inverter working as a STATCOM for the grid voltage regulation while the PV plant cannot generate power during night time and cloudy days. This new technology called as PV STATCOM. This paper introduces the fuzzy logic based control scheme of PV STATCOM for the grid voltage regulation and controls the voltage rise during a reverse power flow condition.
{"title":"Fuzzy logic based PV STATCOM operation for grid voltage regulation in night","authors":"N. Solanki, J. Patel","doi":"10.1109/ICSOFTCOMP.2017.8280080","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280080","url":null,"abstract":"For the generation of electricity with less impact on the environment, utilization of renewable energy resources is growing worldwide as a clean energy source. With the increasing penetration of renewable based Distributed Generators (DG) on the distribution grid can create power quality issues like voltage variations, relay malfunctioning, and reverse power flow during lightly loaded condition which rises the voltage level beyond the limit. To control the voltage variables, there is a need to install power electronics converter based FACTs devices like STATCOM. Now a days, a new way to utilize the PV inverter working as a STATCOM for the grid voltage regulation while the PV plant cannot generate power during night time and cloudy days. This new technology called as PV STATCOM. This paper introduces the fuzzy logic based control scheme of PV STATCOM for the grid voltage regulation and controls the voltage rise during a reverse power flow condition.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127257583","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280097
Sourabrata Mukherjee
In this article, a methodology has been presented to enhance the generalization of the probabilistic neural network (PNN). For the purpose, in this article, I have performed a noise based training over the PNN classifier. Here, while training the PNN, I have injected random Gaussian multiplicative noise in the samples of the data set. This external noise injection mechanism improves the classification accuracy of the data set. Furthermore, to reduce the storage requirement of the network, I have used k-means clustering algorithm, and through this algorithm I have selected a subset of class samples from each class. It reduces the number of stored pattern in the pattern layer. The entire process generates a advanced classifier based on fusion neural network model. To test the classification rightness of the proposed method, eight standard data sets have been used. Proposed model has been compared with conventional PNN classifier. Comparison of result exhibit the ascendancy of the presented method. Wilcoxon signed rank trial also manifests that proposed method improves the performance of the classifier.
{"title":"Improving generalization of k-means clustering based probabilistic neural network using noise injection","authors":"Sourabrata Mukherjee","doi":"10.1109/ICSOFTCOMP.2017.8280097","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280097","url":null,"abstract":"In this article, a methodology has been presented to enhance the generalization of the probabilistic neural network (PNN). For the purpose, in this article, I have performed a noise based training over the PNN classifier. Here, while training the PNN, I have injected random Gaussian multiplicative noise in the samples of the data set. This external noise injection mechanism improves the classification accuracy of the data set. Furthermore, to reduce the storage requirement of the network, I have used k-means clustering algorithm, and through this algorithm I have selected a subset of class samples from each class. It reduces the number of stored pattern in the pattern layer. The entire process generates a advanced classifier based on fusion neural network model. To test the classification rightness of the proposed method, eight standard data sets have been used. Proposed model has been compared with conventional PNN classifier. Comparison of result exhibit the ascendancy of the presented method. Wilcoxon signed rank trial also manifests that proposed method improves the performance of the classifier.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128768952","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280077
Bhavana Mehta, Jonti Talukdar, S. Gajjar
Increasing development in embedded system, VLSI and processor design have given rise to increased demands from the system in terms of power, speed, area, throughput etcetera. Most of the sophisticated embedded system applications consist of processors; which now need an arithmetic unit with the ability to execute complex division operations with maximum efficiency. Hence the speed of the arithmetic unit is critically dependent on division operation. Most of the dividers use the SRT division algorithm for division. In IoT and other embedded applications typically radix 2 and radix 4 division algorithms are used. The proposed algorithm lies on parallel execution of various steps so as to reduce time critical path, use fuzzy logic to solve the overlap problem in quotient selection; hence reducing maximum delay and increasing the accuracy. Every logical circuit has a maximum delay on which the timing of the circuit is dependent and the path, causing the maximum delay is known as the critical path. Our approach uses the previous SRT algorithm methods to make a highly parallel pipelined design and use Mamdani model to determine a solution to the overlapping problem to reduce the overall execution time of radix 4 SRT division on 64 bits double precision floating point numbers to 281ns. The design is made using Bluespec System Verilog, synthesized and simulated using Vivado v.2016.1 and implemented on Xilinx VirtexUltraScale FPGA board.
随着嵌入式系统、超大规模集成电路和处理器设计的不断发展，对系统在功率、速度、面积、吞吐量等方面提出了越来越高的要求。大多数复杂的嵌入式系统应用程序由处理器组成;现在需要一个能够以最高效率执行复杂除法运算的算术单元。因此，算术单元的速度严重依赖于除法运算。大多数除法使用SRT除法算法进行除法。在物联网和其他嵌入式应用中，通常使用基数2和基数4除法算法。该算法通过并行执行各步骤以减少时间关键路径，利用模糊逻辑解决商选择中的重叠问题;因此减少了最大延迟，提高了精度。每个逻辑电路都有一个最大延迟，电路的时序依赖于此，导致最大延迟的路径称为关键路径。我们的方法使用之前的SRT算法方法进行高度并行的流水线设计，并使用Mamdani模型确定重叠问题的解决方案，从而将64位双精度浮点数上的基数4 SRT除法的总执行时间减少到281ns。本设计采用Bluespec System Verilog进行设计，使用Vivado v.2016.1进行综合仿真，并在Xilinx VirtexUltraScale FPGA板上实现。
{"title":"High speed SRT divider for intelligent embedded system","authors":"Bhavana Mehta, Jonti Talukdar, S. Gajjar","doi":"10.1109/ICSOFTCOMP.2017.8280077","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280077","url":null,"abstract":"Increasing development in embedded system, VLSI and processor design have given rise to increased demands from the system in terms of power, speed, area, throughput etcetera. Most of the sophisticated embedded system applications consist of processors; which now need an arithmetic unit with the ability to execute complex division operations with maximum efficiency. Hence the speed of the arithmetic unit is critically dependent on division operation. Most of the dividers use the SRT division algorithm for division. In IoT and other embedded applications typically radix 2 and radix 4 division algorithms are used. The proposed algorithm lies on parallel execution of various steps so as to reduce time critical path, use fuzzy logic to solve the overlap problem in quotient selection; hence reducing maximum delay and increasing the accuracy. Every logical circuit has a maximum delay on which the timing of the circuit is dependent and the path, causing the maximum delay is known as the critical path. Our approach uses the previous SRT algorithm methods to make a highly parallel pipelined design and use Mamdani model to determine a solution to the overlapping problem to reduce the overall execution time of radix 4 SRT division on 64 bits double precision floating point numbers to 281ns. The design is made using Bluespec System Verilog, synthesized and simulated using Vivado v.2016.1 and implemented on Xilinx VirtexUltraScale FPGA board.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123131858","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 : 2017-12-01DOI: 10.1109/ICSOFTCOMP.2017.8280092
C. Sabharwal, R. Prasath
Transformations are integral part of graphics programs for visualization. Rotation transformations allow viewing objects from different angles. Rotations about the principal axes are straightforward whereas the rotation about an arbitrary axis is complex. We present a new algorithm simpler than the existing techniques for creating arbitrary rotation matrix. It builds upon the change of basis instead of a sequence of rotations based on the angles it makes with the principal axes/planes. We compare it with the existing proofs. Finally, we give an example by creating an axis interactively and 3D object created by rotation a mouse drive polygonal curve. The application developers and practitioners will find this intuitive and simpler algorithm useful.
{"title":"An intuitive algorithm for rotation about an arbitrary axis","authors":"C. Sabharwal, R. Prasath","doi":"10.1109/ICSOFTCOMP.2017.8280092","DOIUrl":"https://doi.org/10.1109/ICSOFTCOMP.2017.8280092","url":null,"abstract":"Transformations are integral part of graphics programs for visualization. Rotation transformations allow viewing objects from different angles. Rotations about the principal axes are straightforward whereas the rotation about an arbitrary axis is complex. We present a new algorithm simpler than the existing techniques for creating arbitrary rotation matrix. It builds upon the change of basis instead of a sequence of rotations based on the angles it makes with the principal axes/planes. We compare it with the existing proofs. Finally, we give an example by creating an axis interactively and 3D object created by rotation a mouse drive polygonal curve. The application developers and practitioners will find this intuitive and simpler algorithm useful.","PeriodicalId":118765,"journal":{"name":"2017 International Conference on Soft Computing and its Engineering Applications (icSoftComp)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114678839","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}
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