2019 International Conference on Applied Machine Learning (ICAML)最新文献

Dynamic Cluster Formation Mechanism in Wireless Sensor Networks Using Fuzzy Logic 基于模糊逻辑的无线传感器网络动态簇形成机制

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00061

Mahesh Chowdary Kongara, Venkatanareshbabu Kuppili, D. Edla

引用次数: 3

Application of Cellular Automata for an Efficient Symmetric Key Cryptosystem 元胞自动机在高效对称密钥密码系统中的应用

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00012

Madhusmita Das, Kabita Das, M. Sahu, Rasmita Dash

引用次数: 2

An Empirical Performance Analysis of Brain Image Classification Models Using Variants of Neural Networks 基于神经网络的脑图像分类模型的实证性能分析

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00025

Pranati Satapathy, S. Pradhan, Sarbeswara Hota

引用次数: 2

Detection of Ocular Artifacts Using Bagged Tree Ensemble Model 基于袋树集成模型的眼部伪影检测

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00016

S. Behera, M. Mohanty

引用次数: 1

A Comparative Study on Multilevel Thresholding Using Meta-Heuristic Algorithm 基于元启发式算法的多级阈值比较研究

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00019

Bibekananda Jena, M. K. Naik, Aneesh Wunnava, Rutuparna Panda

引用次数: 0

Title Page i 第1页

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/icaml48257.2019.00001

引用次数: 0

Healthcare 5.0: A Paradigm Shift in Digital Healthcare System Using Artificial Intelligence, IOT and 5G Communication 医疗5.0:使用人工智能、物联网和5G通信的数字医疗系统的范式转变

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00044

Bhagyashree Mohanta, Priti Das, S. Patnaik

{"title":"Healthcare 5.0: A Paradigm Shift in Digital Healthcare System Using Artificial Intelligence, IOT and 5G Communication","authors":"Bhagyashree Mohanta, Priti Das, S. Patnaik","doi":"10.1109/ICAML48257.2019.00044","DOIUrl":"https://doi.org/10.1109/ICAML48257.2019.00044","url":null,"abstract":"The induction of Artificial Intelligence (AI) concept with the application of smart intelligent devices and adoption of high-speed data transmission networking techniques in healthcare unit, set a benchmark in the ideology of healthcare to a new level. Developments and advancement of new technologies in healthcare units and improvement in people's quality lifestyle lead people to live a healthier life. AI embedded machines like smart wearable devices with highly integrated efficient sensors which help to monitor, collect and diagnose disease from the symptoms extracted from the sensory data; robot nurse to timely monitor and record patient's health condition in the absence of medical practitioners help the users to know about the health condition irrespective of the location. Internet of Things (IoT) devices with AI touch cannot be considered as a solution to the limitations in fourth generation healthcare systems. Seamless data transmission rate with least or no data loss, traffic free transmission channels, cost effective, no time data retrieval and machine to machine (M2M) or device to device (D2D) communication in IoT era are the major challenges in healthcare 4.0. Further the healthcare use cases urgency like remote surgeries and Tactile Internet as an internet network that combines ultra-low latency with extremely high availability, reliability and security for the next evolution of IoT, needs human to machine or M2M or D2D communication. The possible solution needs 5G or fifth generation communication as the elementary network infrastructure. The paper summarizes all the fundamental concepts like AI, IoT and 5G communication to model healthcare 5.0.","PeriodicalId":369667,"journal":{"name":"2019 International Conference on Applied Machine Learning (ICAML)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127834809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 48

Weighted Bayesian Association Rule Mining Algorithm to Construct Bayesian Belief Network 构建贝叶斯信念网络的加权贝叶斯关联规则挖掘算法

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00013

S. Kharya, S. Soni, T. Swarnkar

{"title":"Weighted Bayesian Association Rule Mining Algorithm to Construct Bayesian Belief Network","authors":"S. Kharya, S. Soni, T. Swarnkar","doi":"10.1109/ICAML48257.2019.00013","DOIUrl":"https://doi.org/10.1109/ICAML48257.2019.00013","url":null,"abstract":"Bayesian network is an appropriate tool to work with the unpredictability and causality which arises in Clinical Domain. A Bayesian network can learn from medical datasets without explicit access to the knowledge of human experts. Thus, to built Bayesian network by learning method, strong rules are needed from datasets. To express statistical dependence relationships, association rules can be considered. This proposal expects to incorporate two techniques to improve the shortcoming of single technique, so this proposal put forward a Weighted Bayesian Association rule Mining Algorithm (WBAR) for the generation of strong Bayesian association rules for the construction of Bayesian network which combines the weighted concept with Association Rule Mining (ARM) to generate Weighted Two-attributes association rules, Weighted Multi -attributes association rules and Weighted Class Association rules. Two interesting dimensions of association rules mining: Weighted Bayes confidence (WBC) and Weighted Bayes lift (WBL) that assess the relationship between different attributes using conditional dependence and independence based on the joint probabilities which are symbolized and then interpreted by the Weighted Bayesian networks using association rules. The proposed algorithm WBAR results the most significant rules according to WBC and WBL","PeriodicalId":369667,"journal":{"name":"2019 International Conference on Applied Machine Learning (ICAML)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122694566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Binary Dragonfly Algorithm and Fisher Score Based Hybrid Feature Selection Adopting a Novel Fitness Function Applied to Microarray Data 采用一种新的适应度函数的二进制蜻蜓算法和基于Fisher分数的混合特征选择应用于微阵列数据

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00015

Akshata K. Naik, Venkatanareshbabu Kuppili, Damodar Reddy Edla

引用次数: 2

Design of Shunt Active Power Filter with Optimal PI Controller - A Comparative Analysis 最优PI控制器并联型有源电力滤波器的设计——比较分析

2019 International Conference on Applied Machine Learning (ICAML) Pub Date : 2019-05-01 DOI: 10.1109/ICAML48257.2019.00046

Rajat Sinha

{"title":"Design of Shunt Active Power Filter with Optimal PI Controller - A Comparative Analysis","authors":"Rajat Sinha","doi":"10.1109/ICAML48257.2019.00046","DOIUrl":"https://doi.org/10.1109/ICAML48257.2019.00046","url":null,"abstract":"The extreme use of power electronic devices in the power system generates harmonics that leads to power quality issues. Here in this work formulates the design, simulation and tentative investigation on a 3-phase multi-level shunt active power filter to improve power quality by reducing harmonics. In this, the performance of the filter using instantaneous power theory with PI and hysteresis current controller is explained. The parameters of the PI controller are tuned using a modified particle swarm optimization technique (MPSO). The controller is abbreviated and called as PI-MPSO controller. Optimization helps to control the dc-link voltage of the shunt APF which is of great importance and simulated by Matlab simulink. To prove the flexibility, effectiveness and superiority of the MPSO based tuning its simulation results are compared with different other artificial intelligence algorithm. Results obtained by simulation shows that the proposed approach is effective for the mitigation of harmonic currents generated by the non-linear loads with the shunt APF based MPSO tuning. The spectral performance shows that MPSO minimizes the THD below 5% matching with the IEEE-519 standard.","PeriodicalId":369667,"journal":{"name":"2019 International Conference on Applied Machine Learning (ICAML)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133962200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2