Pub Date : 2018-12-01DOI: 10.1109/IADCC.2018.8692135
Rupali Khatun, S. Chatterjee
Colon Cancer is one of the most common types of cancer. The treatment is planned to depend on the grade or stage of cancer. One of the preconditions for grading of colon cancer is to segment the glandular structures of tissues. Manual segmentation method is very time-consuming, and it leads to life risk for the patients. The principal objective of this project is to assist the pathologist to accurate detection of colon cancer. In this paper, the authors have proposed an algorithm for an automatic segmentation of glands in colon histology using local intensity and texture features. Here the dataset images are cropped into patches with different window sizes and taken the intensity of those patches, and also calculated texture-based features. Random forest classifier has been used to classify this patch into different labels. A multilevel random forest technique in a hierarchical way is proposed. This solution is fast, accurate and it is very much applicable in a clinical setup.
{"title":"Machine learning approach for segmenting glands in colon histology images using local intensity and texture features","authors":"Rupali Khatun, S. Chatterjee","doi":"10.1109/IADCC.2018.8692135","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692135","url":null,"abstract":"Colon Cancer is one of the most common types of cancer. The treatment is planned to depend on the grade or stage of cancer. One of the preconditions for grading of colon cancer is to segment the glandular structures of tissues. Manual segmentation method is very time-consuming, and it leads to life risk for the patients. The principal objective of this project is to assist the pathologist to accurate detection of colon cancer. In this paper, the authors have proposed an algorithm for an automatic segmentation of glands in colon histology using local intensity and texture features. Here the dataset images are cropped into patches with different window sizes and taken the intensity of those patches, and also calculated texture-based features. Random forest classifier has been used to classify this patch into different labels. A multilevel random forest technique in a hierarchical way is proposed. This solution is fast, accurate and it is very much applicable in a clinical setup.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"10 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":"121121154","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692118
Neha Garg, Damanpreet Singh, Major Singh Goraya
Cloud computing provides various services to the cloud consumers based on demand and pay per use basis. To improve the system performance (such as energy efficiency, resource utilization (RU), etc.) more than one virtual machine (VM) can be deployed on a server. Efficient VM placement policy increases the system performance by utilizing all the computing resources at their maximum threshold limit and reduce the probability to become a server overloaded/underloaded. Overloaded/underloaded servers consume more energy and increase the number of VM migration in comparison to the server which is in a normal state. In this paper, Energy and Resource-Aware VM Placement (ERAP) algorithm is presented. This algorithm considers both, energy as well as central processing unit (CPU) utilization to deploy the VMs on the servers. CloudSim toolkit is used to analyze the behavior of the ERAP algorithm. The effectiveness of the ERAP algorithm is tested on real workload traces of Planet Lab. Results show that ERAP algorithm performs better in comparison to the existing algorithm on the account of the number of VM migrations, total energy consumption, number of servers shutdowns, and average service level agreement (SLA) violation rate. Results show that on average 13.12% energy consumption is minimized in contrast to the existing algorithm.
{"title":"Power and Resource-Aware VM Placement in Cloud Environment","authors":"Neha Garg, Damanpreet Singh, Major Singh Goraya","doi":"10.1109/IADCC.2018.8692118","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692118","url":null,"abstract":"Cloud computing provides various services to the cloud consumers based on demand and pay per use basis. To improve the system performance (such as energy efficiency, resource utilization (RU), etc.) more than one virtual machine (VM) can be deployed on a server. Efficient VM placement policy increases the system performance by utilizing all the computing resources at their maximum threshold limit and reduce the probability to become a server overloaded/underloaded. Overloaded/underloaded servers consume more energy and increase the number of VM migration in comparison to the server which is in a normal state. In this paper, Energy and Resource-Aware VM Placement (ERAP) algorithm is presented. This algorithm considers both, energy as well as central processing unit (CPU) utilization to deploy the VMs on the servers. CloudSim toolkit is used to analyze the behavior of the ERAP algorithm. The effectiveness of the ERAP algorithm is tested on real workload traces of Planet Lab. Results show that ERAP algorithm performs better in comparison to the existing algorithm on the account of the number of VM migrations, total energy consumption, number of servers shutdowns, and average service level agreement (SLA) violation rate. Results show that on average 13.12% energy consumption is minimized in contrast to the existing algorithm.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"39 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":"121221231","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692140
Bhadrachalam Chitturi, S. Balachander, S. Satheesh, Krithic Puthiyoppil
Graphs are discrete objects with myriad applications in science and engineering. Several graph theoretic problems are shown to be hard. However, for restricted versions of graphs based on the type of restriction the problems that are hard to solve for a general graph become tractable. Layered graphs have been defined and are shown to have applications in social networks and computational molecular biology. We define a new class of graphs called cyclic layered graphs that are related to layered graphs. We pose three problems that can be modeled as graph theoretic problems on cyclic layered graphs. We design efficient algorithms for these problems.
{"title":"MIS, MVC and MDS in Cyclic Layered Graphs","authors":"Bhadrachalam Chitturi, S. Balachander, S. Satheesh, Krithic Puthiyoppil","doi":"10.1109/IADCC.2018.8692140","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692140","url":null,"abstract":"Graphs are discrete objects with myriad applications in science and engineering. Several graph theoretic problems are shown to be hard. However, for restricted versions of graphs based on the type of restriction the problems that are hard to solve for a general graph become tractable. Layered graphs have been defined and are shown to have applications in social networks and computational molecular biology. We define a new class of graphs called cyclic layered graphs that are related to layered graphs. We pose three problems that can be modeled as graph theoretic problems on cyclic layered graphs. We design efficient algorithms for these problems.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"100 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":"125521673","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692128
N. Sudhakar Reddy, V. L. Padmalatha, A. Sujith
Enhancing the security of the dual party computation is considered as primitive to establish a secured multiparty computation in the geographically distributed networks. With the advent of variously distributed paradigms like Cloud computing, IoT and Fog computing, securing ubiquitous computation that involves multiparty collaboration is considered an open research area that attains the attention of the researchers to develop novel protocols. Addressing the problem of secured computation over the network this paper presents a novel and hybrid quantum protocol in with Quantum key distribution is integrated with 3DES to enhance the secure computations through a quantum channel within the cloud infrastructure. Simulation results of the proposed protocol show that it outperforms many security protocols developed based on quantum resources.
{"title":"A Novel hybrid Quantum Protocol to enhance secured dual party Computation over Cloud Networks","authors":"N. Sudhakar Reddy, V. L. Padmalatha, A. Sujith","doi":"10.1109/IADCC.2018.8692128","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692128","url":null,"abstract":"Enhancing the security of the dual party computation is considered as primitive to establish a secured multiparty computation in the geographically distributed networks. With the advent of variously distributed paradigms like Cloud computing, IoT and Fog computing, securing ubiquitous computation that involves multiparty collaboration is considered an open research area that attains the attention of the researchers to develop novel protocols. Addressing the problem of secured computation over the network this paper presents a novel and hybrid quantum protocol in with Quantum key distribution is integrated with 3DES to enhance the secure computations through a quantum channel within the cloud infrastructure. Simulation results of the proposed protocol show that it outperforms many security protocols developed based on quantum resources.","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":"128754388","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692120
Gaurav Singal, Anurag Goswami, S. Gupta, Tejalal Choudhary
Pot-holes on road will make transportation slower and costly. India has a big network of roads to connect the villages and cities, the authority persons cannot travel across the region for identification of holes. As per advancement in machine learning in recent time, we can use this technology for the identification and patching the pot-holes. As per the recent survey around 400millions, people have a smartphone in India. We can use smartphone sensors (such as Accelerometer and gyroscope) to identify the pot-holes on road and GPS for the location of the pit. The major task of this problem is to capture the data and annotation. We have developed an android app for capturing the value of displacement while travelling on road. We have applied different classification algorithms to sensor raw-data. SVM is the most suitable classification technique for this problem. The android app will sound an alarm when a pothole is detected.
{"title":"Pitfree: Pot-holes detection on Indian Roads using Mobile Sensors","authors":"Gaurav Singal, Anurag Goswami, S. Gupta, Tejalal Choudhary","doi":"10.1109/IADCC.2018.8692120","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692120","url":null,"abstract":"Pot-holes on road will make transportation slower and costly. India has a big network of roads to connect the villages and cities, the authority persons cannot travel across the region for identification of holes. As per advancement in machine learning in recent time, we can use this technology for the identification and patching the pot-holes. As per the recent survey around 400millions, people have a smartphone in India. We can use smartphone sensors (such as Accelerometer and gyroscope) to identify the pot-holes on road and GPS for the location of the pit. The major task of this problem is to capture the data and annotation. We have developed an android app for capturing the value of displacement while travelling on road. We have applied different classification algorithms to sensor raw-data. SVM is the most suitable classification technique for this problem. The android app will sound an alarm when a pothole is detected.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"96 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":"128379553","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692143
H. Kale, Prathamesh Mandke, Hrishikesh Mahajan, Vedant Deshpande
This paper proposes the use of artificial neural networks(ANNs) to classify human postures, using an invasive(intrusive) approach, into 6 categories namely standing, sitting, sleeping and bending - forward and backward. Human posture recognition has numerous applications in the field of healthcare analysis like patient monitoring, lifestyle analysis, elderly care etc. Most importantly, our solution is capable of classifying the aforementioned postures in real-time, by wirelessly(Wi-Fi) acquiring and processing the sensor data on a Raspberry-Pi device with minimal lag. A data-set of 44,800 samples was collected - from 3 subjects - which was used to train and test the neural network. After experimenting and testing with a plethora of network architectures, an optimal neural network architecture(6-9-6) with suitable hyper-parameters was determined which gave an overall accuracy of 97.589%.
{"title":"Human Posture Recognition using Artificial Neural Networks","authors":"H. Kale, Prathamesh Mandke, Hrishikesh Mahajan, Vedant Deshpande","doi":"10.1109/IADCC.2018.8692143","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692143","url":null,"abstract":"This paper proposes the use of artificial neural networks(ANNs) to classify human postures, using an invasive(intrusive) approach, into 6 categories namely standing, sitting, sleeping and bending - forward and backward. Human posture recognition has numerous applications in the field of healthcare analysis like patient monitoring, lifestyle analysis, elderly care etc. Most importantly, our solution is capable of classifying the aforementioned postures in real-time, by wirelessly(Wi-Fi) acquiring and processing the sensor data on a Raspberry-Pi device with minimal lag. A data-set of 44,800 samples was collected - from 3 subjects - which was used to train and test the neural network. After experimenting and testing with a plethora of network architectures, an optimal neural network architecture(6-9-6) with suitable hyper-parameters was determined which gave an overall accuracy of 97.589%.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"20 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":"116513739","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692093
Megha Agarwal, Somya Jain
Image classification technique analyzes images and its features to unmask the underlined facts. The estimation of age via faces is an area of prime research relevance that deals with several challenges because of its rapid emergent flow in real world applications. In this paper a classifier is built which scans the upper body image i.e. facial images of a person to classify a image to detect the age group namely child, adult and old. The sole purpose of the research is to detect the underage people for enhancing the security system. Taking into account the geometrical features along with wrinkle features, underage is detected using three techniques namely KNN (k-nearest neighbor), ANN (Artificial Neural Network), and SVM (Support Vector Machine) classification algorithm.
{"title":"Image Classification for Underage Detection in Restricted Public Zone","authors":"Megha Agarwal, Somya Jain","doi":"10.1109/IADCC.2018.8692093","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692093","url":null,"abstract":"Image classification technique analyzes images and its features to unmask the underlined facts. The estimation of age via faces is an area of prime research relevance that deals with several challenges because of its rapid emergent flow in real world applications. In this paper a classifier is built which scans the upper body image i.e. facial images of a person to classify a image to detect the age group namely child, adult and old. The sole purpose of the research is to detect the underage people for enhancing the security system. Taking into account the geometrical features along with wrinkle features, underage is detected using three techniques namely KNN (k-nearest neighbor), ANN (Artificial Neural Network), and SVM (Support Vector Machine) classification algorithm.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"29 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":"126569315","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692139
Ashwani Kumar, Sangeeta Gupta
Now a day’s the uses of digital content or media is increasing rapidly. So, there is a need to secure the digital document from both unauthorized users and authorized users. In this paper a secure technique of image fusion using hybrid domain for copyright protection and data distribution is proposed. The proposed method provides a secure technique for the digital content in cloud environment. Two services of cloud are used to develop this work which eliminates the role of trusted third party (TTP). Previously the user and content provider rely on this TTP. First is the design of an infrastructure as a Service (IaaS) to store different images with encryption process to speed up the image fusion process and save storage. Second is a Platform as a Service (PaaS) to enable the digital content to achieve great computation power and to increase the bandwidth. These two services provided by the cloud plays a very important role because it reduces communication overhead in the process of image fusion. Imperceptibility and robustness measures are used to calculate the performance of the proposed approach.
{"title":"A Secure Technique of Image Fusion Using Cloud Based Copyright Protection for Data Distribution","authors":"Ashwani Kumar, Sangeeta Gupta","doi":"10.1109/IADCC.2018.8692139","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692139","url":null,"abstract":"Now a day’s the uses of digital content or media is increasing rapidly. So, there is a need to secure the digital document from both unauthorized users and authorized users. In this paper a secure technique of image fusion using hybrid domain for copyright protection and data distribution is proposed. The proposed method provides a secure technique for the digital content in cloud environment. Two services of cloud are used to develop this work which eliminates the role of trusted third party (TTP). Previously the user and content provider rely on this TTP. First is the design of an infrastructure as a Service (IaaS) to store different images with encryption process to speed up the image fusion process and save storage. Second is a Platform as a Service (PaaS) to enable the digital content to achieve great computation power and to increase the bandwidth. These two services provided by the cloud plays a very important role because it reduces communication overhead in the process of image fusion. Imperceptibility and robustness measures are used to calculate the performance of the proposed approach.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"27 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":"125756687","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8692107
S. Prakash, Harshit Agarwal, Urvi Agarwal, Prantik Biswas, Suma Dawn Jaypee
Motif discovery also known as motif finding is a challenging problem in the field of bioinformatics that deals with various computational and statistical techniques to identify short patterns, often referred to as motifs that corresponds to the binding sites in the DNA sequence for transcription factors. Owing to the recent growth of bioinformatics, a good number of algorithms have come into limelight. This paper proposes a competent algorithm that extracts binding sites in set of DNA sequences for transcription factors, using successive iterations on the sequences provided. The motif we work on are of unknown length, un-gapped and non-mutated. The algorithm uses suffix trie for finding such sites. In this approach the first sequence is used as base for constructing the suffix trie and is mapped with other sequences which results in extraction of the motif. Additionally, this algorithm can also be applied to related problems in the field of data mining, pattern detection, etc.
{"title":"Discovering Motifs in DNA Sequences: A Suffix Tree Based Approach","authors":"S. Prakash, Harshit Agarwal, Urvi Agarwal, Prantik Biswas, Suma Dawn Jaypee","doi":"10.1109/IADCC.2018.8692107","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8692107","url":null,"abstract":"Motif discovery also known as motif finding is a challenging problem in the field of bioinformatics that deals with various computational and statistical techniques to identify short patterns, often referred to as motifs that corresponds to the binding sites in the DNA sequence for transcription factors. Owing to the recent growth of bioinformatics, a good number of algorithms have come into limelight. This paper proposes a competent algorithm that extracts binding sites in set of DNA sequences for transcription factors, using successive iterations on the sequences provided. The motif we work on are of unknown length, un-gapped and non-mutated. The algorithm uses suffix trie for finding such sites. In this approach the first sequence is used as base for constructing the suffix trie and is mapped with other sequences which results in extraction of the motif. Additionally, this algorithm can also be applied to related problems in the field of data mining, pattern detection, etc.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"35 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113936887","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 : 2018-12-01DOI: 10.1109/IADCC.2018.8691943
Trisha Singhal, Akshat Khare, Nikhil Gupta, T. Gandhi
With the increasing applications of 3D printing, podiatric research has received considerable attention from researchers worldwide. 3D-printed customized soles came into use to mitigate a patient foot’s pain and ameliorate comfortability. The presented work is aimed to provide customized foot sole with variable infills and appropriate depths in order to get the adequate pressure and comfort on the precise nerve areas, which are the origins of pain.In the proposed work, a 3D-sole is reconstructed conceptualizing variable infill density and appropriate depth fitting using foot plantar pressure measurements. The given work comprised of four phases: attaining foot plantar pressure readings, data processing, infill density distribution and 3D printing of the sole. Initially, the foot plantar data is obtained by a platform using an array of 32 X 32 piezo-electric sensors. Secondly, the input data is corrected with the removal of the rigid pattern from the foot sole via median filtering and interpolated via bicubic interpolation to obtain the smooth surface. Thereafter, modifiers are created to dispense different densities to distinct portions of the model. At last, the model is 3D-printed using fused deposition modeling (FDM) technology. The novel work can be extremely considerable in various medical and commercial applications.
随着3D打印技术的应用越来越广泛，足病研究受到了世界范围内研究者的广泛关注。3d打印定制鞋底开始用于减轻患者足部疼痛并改善舒适度。本研究旨在提供具有不同填充物和适当深度的定制足底，以便在疼痛的精确神经区域获得足够的压力和舒适度。在提出的工作中，利用足底压力测量重建了3d鞋底，概念上定义了可变填充密度和适当的深度拟合。这项工作包括四个阶段:获得足底压力读数、数据处理、填充密度分布和鞋底3D打印。最初，脚底数据是由一个使用32 X 32压电传感器阵列的平台获得的。其次，对输入数据进行校正，通过中值滤波去除鞋底的刚性图案，并通过双三次插值进行插值，得到光滑表面;然后，修改器被创建来分配不同的密度到模型的不同部分。最后，采用熔融沉积建模(FDM)技术对模型进行3d打印。这项新工作在各种医学和商业应用中具有极其重要的意义。
{"title":"3D-Printed Sole with Variable Density using Foot Plantar Pressure Measurements","authors":"Trisha Singhal, Akshat Khare, Nikhil Gupta, T. Gandhi","doi":"10.1109/IADCC.2018.8691943","DOIUrl":"https://doi.org/10.1109/IADCC.2018.8691943","url":null,"abstract":"With the increasing applications of 3D printing, podiatric research has received considerable attention from researchers worldwide. 3D-printed customized soles came into use to mitigate a patient foot’s pain and ameliorate comfortability. The presented work is aimed to provide customized foot sole with variable infills and appropriate depths in order to get the adequate pressure and comfort on the precise nerve areas, which are the origins of pain.In the proposed work, a 3D-sole is reconstructed conceptualizing variable infill density and appropriate depth fitting using foot plantar pressure measurements. The given work comprised of four phases: attaining foot plantar pressure readings, data processing, infill density distribution and 3D printing of the sole. Initially, the foot plantar data is obtained by a platform using an array of 32 X 32 piezo-electric sensors. Secondly, the input data is corrected with the removal of the rigid pattern from the foot sole via median filtering and interpolated via bicubic interpolation to obtain the smooth surface. Thereafter, modifiers are created to dispense different densities to distinct portions of the model. At last, the model is 3D-printed using fused deposition modeling (FDM) technology. The novel work can be extremely considerable in various medical and commercial applications.","PeriodicalId":365713,"journal":{"name":"2018 IEEE 8th International Advance Computing Conference (IACC)","volume":"28 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":"125759875","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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