Pub Date : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9688060
Rohitha Pasumarty, R. K N
This paper, in all its essence, is a group chat Application, between a variable number of users, who are connected to each other, by virtue of being a member of the same network. A central server acts as a service to accept messages from a user and forward it to all other users, who are participating in the group chat by being connected to the server at that point of time. Given that the server is up and running, new users can join the group chat server at any given time by providing the current local IP address and the port on which the server is running, although, this can only be done if the active members in a group chat does not exceed the specified and declared capacity of the server. If a large number of users is expected, the server can be configured to listen for a higher number of incoming connection requests, which should be carefully determined, since, performing an alteration in the capacity of the server requires the server to be restarted for the new capacity to come into effect. The main aim of this group chat server is that it is a secure group chat server which uses cryptographic algorithms Advances Encryption Standard for encrypting message. When the server is started, a random cipher key is generated for encryption and decryption of messages. This cipher key is the secret key that is confidential within the boundaries of the system. When a message originates from a user, it is encrypted before being sent to the server. The server receives this encrypted message and forwards it to the other users that are currently connected to the group chat server.
{"title":"Secure Chatroom Application using Advanced Encryption Standard Algorithm","authors":"Rohitha Pasumarty, R. K N","doi":"10.1109/CENTCON52345.2021.9688060","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688060","url":null,"abstract":"This paper, in all its essence, is a group chat Application, between a variable number of users, who are connected to each other, by virtue of being a member of the same network. A central server acts as a service to accept messages from a user and forward it to all other users, who are participating in the group chat by being connected to the server at that point of time. Given that the server is up and running, new users can join the group chat server at any given time by providing the current local IP address and the port on which the server is running, although, this can only be done if the active members in a group chat does not exceed the specified and declared capacity of the server. If a large number of users is expected, the server can be configured to listen for a higher number of incoming connection requests, which should be carefully determined, since, performing an alteration in the capacity of the server requires the server to be restarted for the new capacity to come into effect. The main aim of this group chat server is that it is a secure group chat server which uses cryptographic algorithms Advances Encryption Standard for encrypting message. When the server is started, a random cipher key is generated for encryption and decryption of messages. This cipher key is the secret key that is confidential within the boundaries of the system. When a message originates from a user, it is encrypted before being sent to the server. The server receives this encrypted message and forwards it to the other users that are currently connected to the group chat server.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123266139","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9688037
Dhanishtha Patil, Shubham Gaud
E-Commerce is one of the world's most fast-paced industries where the significant aspect of these industries is that they are lacking Customer-Retailer Interaction. Due to the conventional human psychology of bargaining, a product with a lower price is still popular, and some of the products in this sector lack this kind of bargaining, which would be a cause for some of the products. With the advancement of machine learning, automated and Intelligent Agent negotiating system has become a prominent tool in E-Commerce. This paper presents a negotiation technique for establishing a mutually acceptable agreement between the negotiation system which represents supplier and customers, built using Minimum Profit Algorithm designed as per seller requirements and trained on UCI machine learning repository's online retailer dataset using XG Boost regressor for intelligence. This system outperforms the traditional way of negotiation and the model was able to achieve an accuracy of 91.53 percent.
{"title":"Intelligent Automated Negotiation System in Business to Consumer E-Commerce","authors":"Dhanishtha Patil, Shubham Gaud","doi":"10.1109/CENTCON52345.2021.9688037","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688037","url":null,"abstract":"E-Commerce is one of the world's most fast-paced industries where the significant aspect of these industries is that they are lacking Customer-Retailer Interaction. Due to the conventional human psychology of bargaining, a product with a lower price is still popular, and some of the products in this sector lack this kind of bargaining, which would be a cause for some of the products. With the advancement of machine learning, automated and Intelligent Agent negotiating system has become a prominent tool in E-Commerce. This paper presents a negotiation technique for establishing a mutually acceptable agreement between the negotiation system which represents supplier and customers, built using Minimum Profit Algorithm designed as per seller requirements and trained on UCI machine learning repository's online retailer dataset using XG Boost regressor for intelligence. This system outperforms the traditional way of negotiation and the model was able to achieve an accuracy of 91.53 percent.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129420239","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9688089
M. Mounisha, Chirunomula Sai Kowshik, M. Reethika, A. Dhanush
Traditionally cognitive radio can be accessed by secondary user only when foremost user is absent, but the subordinate client needs to evacuate the idle spectrum when existence of foremost user is detected. Hence, the bandwidth is reduced in traditional scheme. To overcome the problem, non-orthogonal multiple access is used to increase the efficiency of spectrum in 5G communications. Non-orthogonal multiple access is used in this method to allow the subordinate user to enter into the gamut even when forecast client is attending or not attending the conduit. Foremost client decryption technique and subordinate client decryption technique are introduced to decrypt the non-orthogonal signs. Hence, through the decoding techniques secondary user throughput can be achieved, to increase the primary user throughput duct channel energy must be in a limit. However due to the disturbance caused by the foremost client the subordinate efficiency may be decreased. Orienting towards Foremost user first deciphering and subordinate user first decoding, Here, we come up with two enhancement problems to enhance the efficiency of both primary client and secondary client. This is done using jointly optimizing spectrum resource. This citation embracing how much amount of sub channel transmission power is used and also, it enhances the number of sub channels present in it. This type of citation is to enhance optimization problems. Jointly optimization algorithm is introduced to eliminate the existing problem. This is achieved by accepting the signs and calculating the time needed to sense gamut and the forecast client attending or not attending the conduit to decrypt the data sent while forecast client is absent. The miniature outcomes will be shown the non-orthogonal based multiple access cognitive radio's predominant transmission efficiency.
{"title":"Efficient usage of spectrum by using joint optimization channel allocation method","authors":"M. Mounisha, Chirunomula Sai Kowshik, M. Reethika, A. Dhanush","doi":"10.1109/CENTCON52345.2021.9688089","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688089","url":null,"abstract":"Traditionally cognitive radio can be accessed by secondary user only when foremost user is absent, but the subordinate client needs to evacuate the idle spectrum when existence of foremost user is detected. Hence, the bandwidth is reduced in traditional scheme. To overcome the problem, non-orthogonal multiple access is used to increase the efficiency of spectrum in 5G communications. Non-orthogonal multiple access is used in this method to allow the subordinate user to enter into the gamut even when forecast client is attending or not attending the conduit. Foremost client decryption technique and subordinate client decryption technique are introduced to decrypt the non-orthogonal signs. Hence, through the decoding techniques secondary user throughput can be achieved, to increase the primary user throughput duct channel energy must be in a limit. However due to the disturbance caused by the foremost client the subordinate efficiency may be decreased. Orienting towards Foremost user first deciphering and subordinate user first decoding, Here, we come up with two enhancement problems to enhance the efficiency of both primary client and secondary client. This is done using jointly optimizing spectrum resource. This citation embracing how much amount of sub channel transmission power is used and also, it enhances the number of sub channels present in it. This type of citation is to enhance optimization problems. Jointly optimization algorithm is introduced to eliminate the existing problem. This is achieved by accepting the signs and calculating the time needed to sense gamut and the forecast client attending or not attending the conduit to decrypt the data sent while forecast client is absent. The miniature outcomes will be shown the non-orthogonal based multiple access cognitive radio's predominant transmission efficiency.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127886448","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9687930
T. Trueman, Gopi K, Ashok Kumar J
Artificial intelligence is replacing humans and their employment in different fields in today's technological environment. Researchers are trying to create virtual assistants and robots to mimic human characters as much as possible. Out of many impressive human characters, a sense of humor is a charming one. A virtual assistant or a robot with a great sense of humor will be a better replacement for an actual human. Moreover, natural language processing plays a vital role to capture the sense of humor from online texts. In this paper, we detect humor text from online media with help of a generalized autoregressive model. In specific, we fine-tuned the XLNet base to outperform other models in the same humor detection task with a 200k formal texts dataset. The proposed model applies context dependent features to capture the sense of humor. Our result analysis shows that our proposed work achieved an accuracy of 98.6% which is higher than existing models.
{"title":"Online Text-Based Humor Detection","authors":"T. Trueman, Gopi K, Ashok Kumar J","doi":"10.1109/CENTCON52345.2021.9687930","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9687930","url":null,"abstract":"Artificial intelligence is replacing humans and their employment in different fields in today's technological environment. Researchers are trying to create virtual assistants and robots to mimic human characters as much as possible. Out of many impressive human characters, a sense of humor is a charming one. A virtual assistant or a robot with a great sense of humor will be a better replacement for an actual human. Moreover, natural language processing plays a vital role to capture the sense of humor from online texts. In this paper, we detect humor text from online media with help of a generalized autoregressive model. In specific, we fine-tuned the XLNet base to outperform other models in the same humor detection task with a 200k formal texts dataset. The proposed model applies context dependent features to capture the sense of humor. Our result analysis shows that our proposed work achieved an accuracy of 98.6% which is higher than existing models.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"258263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116419155","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9688087
Leo Raj Solay, S. Anand, S. Amin, Pradeep Kumar
In this paper, Gate-All-Around (GAA) Charge Plasma (CP) Nanowire Field Effect Transistor (NW FET) structure design and analysis using Triple Material Gate (TMG) technique making it as a Gate-All-Around Triple Material Gate Charge Plasma Nanowire Field Effect Transistor (GAA TMG CP NW FET) is proposed. The proposed structure GAA TMG CP NW FET is compared with GAA Single Material Gate CP NW FET (GAA SMG CP NW FET) and GAA Double Material Gate CP NW FET (GAA DMG CP NW FET) structures. With the contrast made in between three structures i.e., SMG, DMG & TMG, the proposed structure GAA TMG CP NW FET resulted with promising outcomes in terms of ON-state current (ION), OFF-state current (IOFF) and their current ratios (ION/IOFF). The Analog and RF analysis were made for the proposed structure and compared with SMG & DMG which gave improved results such as Drain current with gate voltage (ID-VGS), Drain current with drain voltage (ID-VDS), Transconductance (gm), Output conductance (gd), Total gate capacitance (CGG) etc. The proposed device is then compared with the structure results such as Band energy, potential, electric field etc. A fair comparison is drawn from the SMG, DMG and TMG structures to prove its ability towards the Nanoscale device structures.
{"title":"Design And Analysis Of Gate-All-Around (GAA) Triple Material Gate Charge Plasma Nanowire FET","authors":"Leo Raj Solay, S. Anand, S. Amin, Pradeep Kumar","doi":"10.1109/CENTCON52345.2021.9688087","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688087","url":null,"abstract":"In this paper, Gate-All-Around (GAA) Charge Plasma (CP) Nanowire Field Effect Transistor (NW FET) structure design and analysis using Triple Material Gate (TMG) technique making it as a Gate-All-Around Triple Material Gate Charge Plasma Nanowire Field Effect Transistor (GAA TMG CP NW FET) is proposed. The proposed structure GAA TMG CP NW FET is compared with GAA Single Material Gate CP NW FET (GAA SMG CP NW FET) and GAA Double Material Gate CP NW FET (GAA DMG CP NW FET) structures. With the contrast made in between three structures i.e., SMG, DMG & TMG, the proposed structure GAA TMG CP NW FET resulted with promising outcomes in terms of ON-state current (ION), OFF-state current (IOFF) and their current ratios (ION/IOFF). The Analog and RF analysis were made for the proposed structure and compared with SMG & DMG which gave improved results such as Drain current with gate voltage (ID-VGS), Drain current with drain voltage (ID-VDS), Transconductance (gm), Output conductance (gd), Total gate capacitance (CGG) etc. The proposed device is then compared with the structure results such as Band energy, potential, electric field etc. A fair comparison is drawn from the SMG, DMG and TMG structures to prove its ability towards the Nanoscale device structures.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127140955","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9687884
Sravanthi Kantamaneni, Charles, T. Babu
In this paper, one of the proposed ResNet model is used for denoising of RB noise. In fact, ResNet is one of the advanced deep learning methods for analysing and improving various 1D and 2D signals. Accuracy decreases due to the vanishing gradients in plain networks. The model Mozilla common speech data set is used. These are 48kHz recordings of all short sentence speaking subjects. They are all fixed at the same length and the same sampling frequency. The training course for this model uses an Adam optimizer/solver. This model is implemented in scheduling the learning rate “with a division” of 0.9 drop factor and a period of one. About 50 noise samples are available in the data set. Similarly, noise signals are acquired under various environmental conditions. Therefore, one separate data set is prepared for the T&T of the signal. When the T&T data set is small, the problem of overcompliance arises. In other words, since we are only trying to collect all data points from our dataset, we have used one proposed model to manage this dataset more efficiently. In the RMSE and precision validation values, you can feel the over- compliance issues here. Overfitting means that by 1 point of travel, the learning plot starts to deteriorate after loss and an increase in accuracy in terms of the identification. Similarly, if we are trying to pick a simple model for denoising, i.e. there is another problem - underfitting. Underfitting means that the model is either oversized or this model is oversized so that it doesn't learn enough about the dataset using that model. Each time various types of noises tries to rip off the amount added to the voice signal. Improvements in terms of denoising, RMSE and validation precision with the help of this model was given in the following sections.
{"title":"A Comparative Analysis of Progressive Loss Functions with Multi Layered Resnet Model","authors":"Sravanthi Kantamaneni, Charles, T. Babu","doi":"10.1109/CENTCON52345.2021.9687884","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9687884","url":null,"abstract":"In this paper, one of the proposed ResNet model is used for denoising of RB noise. In fact, ResNet is one of the advanced deep learning methods for analysing and improving various 1D and 2D signals. Accuracy decreases due to the vanishing gradients in plain networks. The model Mozilla common speech data set is used. These are 48kHz recordings of all short sentence speaking subjects. They are all fixed at the same length and the same sampling frequency. The training course for this model uses an Adam optimizer/solver. This model is implemented in scheduling the learning rate “with a division” of 0.9 drop factor and a period of one. About 50 noise samples are available in the data set. Similarly, noise signals are acquired under various environmental conditions. Therefore, one separate data set is prepared for the T&T of the signal. When the T&T data set is small, the problem of overcompliance arises. In other words, since we are only trying to collect all data points from our dataset, we have used one proposed model to manage this dataset more efficiently. In the RMSE and precision validation values, you can feel the over- compliance issues here. Overfitting means that by 1 point of travel, the learning plot starts to deteriorate after loss and an increase in accuracy in terms of the identification. Similarly, if we are trying to pick a simple model for denoising, i.e. there is another problem - underfitting. Underfitting means that the model is either oversized or this model is oversized so that it doesn't learn enough about the dataset using that model. Each time various types of noises tries to rip off the amount added to the voice signal. Improvements in terms of denoising, RMSE and validation precision with the help of this model was given in the following sections.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134325157","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9687988
A. V, S. Kulkarni
With the increasing economical-developments and urban population, the number of vehicles on road is increasing as well and hence the traffic. There comes the need to lower the congestion of roads caused due to vehicular traffic. Out of numerous vehicle detection and tracking techniques, this paper deals with Image- processing-based methods simulated using MATLAB Simulink. Few such methods are Background subtraction with gaussian and Kalman Filter, Blob analysis, Horn- Schunck, Particle Filter and Monte Carlo method. Background subtraction is the most familiar one these days followed by the Morphological operations. It depends on certain parameters like accuracy, time for processing, segmenting, and complexity. The various traffic parameters like the speed of the car, count, and its tracking are calculated using its threshold values in some of the detection methods. The work proposed is done in real-time taking the challenging examples. The results mentioned throw light on the lustiness of the study proposed.
{"title":"Image Processing Based Vehicle Detection and Tracking: A Comparative Study","authors":"A. V, S. Kulkarni","doi":"10.1109/CENTCON52345.2021.9687988","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9687988","url":null,"abstract":"With the increasing economical-developments and urban population, the number of vehicles on road is increasing as well and hence the traffic. There comes the need to lower the congestion of roads caused due to vehicular traffic. Out of numerous vehicle detection and tracking techniques, this paper deals with Image- processing-based methods simulated using MATLAB Simulink. Few such methods are Background subtraction with gaussian and Kalman Filter, Blob analysis, Horn- Schunck, Particle Filter and Monte Carlo method. Background subtraction is the most familiar one these days followed by the Morphological operations. It depends on certain parameters like accuracy, time for processing, segmenting, and complexity. The various traffic parameters like the speed of the car, count, and its tracking are calculated using its threshold values in some of the detection methods. The work proposed is done in real-time taking the challenging examples. The results mentioned throw light on the lustiness of the study proposed.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121106597","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9688098
Madam Chakradar, Alok Aggarwal
T2DM is a large challenge because it's predicted to affect 693 million people by 2045. There is currently no simple or non-invasive method to measure and quantify insulin resistance. Following the release of non-invasive devices that track glucose levels, one might be able to identify insulin resistance without having to use invasive medical tests. In this work, insulin resistance is recognized based on non-invasive techniques. Eighteen parameters are used to identify a person with a high likelihood of insulin resistance: consisting of age, gender, waist size, height, etc., and an aggregate of those parameters. Each output of a function choices technique is modeled using a range of algorithms, including logistic regression, CARTs, SVM, LDA, KNN, etc on CALERIE study dataset and the findings are verified over stratified cross-validation. And in comparison, to 66% Bernardini et al & Stawiski et al, 61% Zheng et al, and 83% Farran et al, the accuracy of different variations for the identification of insulin resistance. Another advantage of the proposed approach is that an individual can also predict insulin resistance daily, which in turn will allow physicians to monitor diabetes risk more accurately. While the identical isn't always almost feasible with medical procedures.
2型糖尿病是一个巨大的挑战，因为预计到2045年将有6.93亿人受到影响。目前还没有简单或无创的方法来测量和量化胰岛素抵抗。随着追踪血糖水平的非侵入性设备的发布，人们可能能够在不使用侵入性医学测试的情况下识别胰岛素抵抗。在这项工作中，胰岛素抵抗是基于非侵入性技术识别的。18个参数用于识别胰岛素抵抗可能性高的人:包括年龄、性别、腰围大小、身高等，以及这些参数的总和。函数选择技术的每个输出都使用一系列算法建模，包括CALERIE研究数据集上的逻辑回归，cart, SVM, LDA, KNN等，并通过分层交叉验证验证结果。相比之下，66% Bernardini et al & Stawiski et al, 61% Zheng et al, 83% Farran et al，不同变异对胰岛素抵抗识别的准确性。该方法的另一个优点是，个人还可以每天预测胰岛素抵抗，从而使医生能够更准确地监测糖尿病风险。然而，在医疗过程中，这并不总是可行的。
{"title":"A Machine Learning Model to Identify Insulin Resistance in Humans","authors":"Madam Chakradar, Alok Aggarwal","doi":"10.1109/CENTCON52345.2021.9688098","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688098","url":null,"abstract":"T2DM is a large challenge because it's predicted to affect 693 million people by 2045. There is currently no simple or non-invasive method to measure and quantify insulin resistance. Following the release of non-invasive devices that track glucose levels, one might be able to identify insulin resistance without having to use invasive medical tests. In this work, insulin resistance is recognized based on non-invasive techniques. Eighteen parameters are used to identify a person with a high likelihood of insulin resistance: consisting of age, gender, waist size, height, etc., and an aggregate of those parameters. Each output of a function choices technique is modeled using a range of algorithms, including logistic regression, CARTs, SVM, LDA, KNN, etc on CALERIE study dataset and the findings are verified over stratified cross-validation. And in comparison, to 66% Bernardini et al & Stawiski et al, 61% Zheng et al, and 83% Farran et al, the accuracy of different variations for the identification of insulin resistance. Another advantage of the proposed approach is that an individual can also predict insulin resistance daily, which in turn will allow physicians to monitor diabetes risk more accurately. While the identical isn't always almost feasible with medical procedures.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129725444","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9688114
P. William, Pardeep Kumar, Gurpreet Singh Chhabra, K. Vengatesan
In the 21st century, agile software development (ASD) has emerged as one of the prominent software development techniques. Every major global company has moved to ASD as a means of reducing costs. In pursuit of huge markets and cheap cost of labour, the industry has shifted to a Distributed Agile Software Development (DASD) environment. As a consequence of improper job allocation, clients may refuse to accept the project, team members may be demonized, and the project may collapse. Numerous scholars have spent the past decade researching different techniques for work allocation in Distributed Agile settings, and the results have been promising. Ontologies and Bayesian networks were among the techniques they employed. This is a list of brute force techniques that may be useful in certain situations. Additionally, these methods have not been used to distributed Agile software development job allocation. The purpose of this article is to design and implement a method for job allocation in distributed Agile software development that is based on machine learning. The findings indicate that the suggested model is more accurate in terms of task assignment.
{"title":"Task Allocation in Distributed Agile Software Development using Machine Learning Approach","authors":"P. William, Pardeep Kumar, Gurpreet Singh Chhabra, K. Vengatesan","doi":"10.1109/CENTCON52345.2021.9688114","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688114","url":null,"abstract":"In the 21st century, agile software development (ASD) has emerged as one of the prominent software development techniques. Every major global company has moved to ASD as a means of reducing costs. In pursuit of huge markets and cheap cost of labour, the industry has shifted to a Distributed Agile Software Development (DASD) environment. As a consequence of improper job allocation, clients may refuse to accept the project, team members may be demonized, and the project may collapse. Numerous scholars have spent the past decade researching different techniques for work allocation in Distributed Agile settings, and the results have been promising. Ontologies and Bayesian networks were among the techniques they employed. This is a list of brute force techniques that may be useful in certain situations. Additionally, these methods have not been used to distributed Agile software development job allocation. The purpose of this article is to design and implement a method for job allocation in distributed Agile software development that is based on machine learning. The findings indicate that the suggested model is more accurate in terms of task assignment.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128904562","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 : 2021-11-19DOI: 10.1109/CENTCON52345.2021.9688193
S. Vadlamudi, Jenifer Sam
Large enterprises work upon countless strategies for creating value with acquisitions as they enter a transformational merger. Cloud-native applications, being loosely coupled and designed to deliver user requirements at the pace a business needs are the natural choice for enterprise acquisitions. Culture change management and process compliance are some key areas where acquisitions find it difficult to adapt to the enterprise standards. To make this journey smooth, it is important to have a guided journey methodology with simplified engagement between both parties. One of the key dimensions where such a collaboration-centric approach is required is in security. In this paper, we examine the current challenges in onboarding cloud-native acquisitions to bring their security compliance posture at par with the current enterprise standards. We explore areas such as secure software development lifecycle management, tools and processes followed and provide recommendations around improving the overall security stance of the acquired product.
{"title":"A Novel Approach to Onboarding Secure Cloud-Native Acquisitions into Enterprise Solutions","authors":"S. Vadlamudi, Jenifer Sam","doi":"10.1109/CENTCON52345.2021.9688193","DOIUrl":"https://doi.org/10.1109/CENTCON52345.2021.9688193","url":null,"abstract":"Large enterprises work upon countless strategies for creating value with acquisitions as they enter a transformational merger. Cloud-native applications, being loosely coupled and designed to deliver user requirements at the pace a business needs are the natural choice for enterprise acquisitions. Culture change management and process compliance are some key areas where acquisitions find it difficult to adapt to the enterprise standards. To make this journey smooth, it is important to have a guided journey methodology with simplified engagement between both parties. One of the key dimensions where such a collaboration-centric approach is required is in security. In this paper, we examine the current challenges in onboarding cloud-native acquisitions to bring their security compliance posture at par with the current enterprise standards. We explore areas such as secure software development lifecycle management, tools and processes followed and provide recommendations around improving the overall security stance of the acquired product.","PeriodicalId":103865,"journal":{"name":"2021 International Conference on Disruptive Technologies for Multi-Disciplinary Research and Applications (CENTCON)","volume":"158 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133925704","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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