2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)最新文献_第9页

Self-Organizing Sustainable Spectrum Management Methodology in Cognitive Radio Vehicular Adhoc Network (CRAVENET) Environment: A Reinforcement Learning Approach 认知无线电车载自组织网络环境下的自组织可持续频谱管理方法:一种强化学习方法

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703268

K. Ghanshala, Sachin Sharma, S. Mohan, Lata Nautiyal, P. Mishra, R. Joshi

{"title":"Self-Organizing Sustainable Spectrum Management Methodology in Cognitive Radio Vehicular Adhoc Network (CRAVENET) Environment: A Reinforcement Learning Approach","authors":"K. Ghanshala, Sachin Sharma, S. Mohan, Lata Nautiyal, P. Mishra, R. Joshi","doi":"10.1109/ICSCCC.2018.8703268","DOIUrl":"https://doi.org/10.1109/ICSCCC.2018.8703268","url":null,"abstract":"The era of new and emerging technologies demand that the new challenges they bring about to be effectively tackled and resolved. One such key challenge is spectrum management, especially in Cognitive Radio Vehicular Adhoc Network (CRAVENET) environment. The large-scale deployment of multimedia and Internet of Things (IoT) applications generate the need to establish an efficient spectrum allocation mechanism. This paper proposes a centralized self-organizing spectrum management in the context of economic and social sustainability using reinforcement learning technique. The objective of the proposed approach facilitates economic and social justice. The social economic justice architecture is developed through a user demand level concepts. The spectrum management methodology has been developed in a CRAVENET environment for better quality of service (QoS) with low average latency. The proposed methodology is expected to be highly effective for its economic feasibility, social impact, user comfort, efficiency, and communication latency minimization requirements.","PeriodicalId":148491,"journal":{"name":"2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"120 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":"126006799","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

Feature Weighting for Improved Classification of Anuran Calls 基于特征加权的改进Anuran呼叫分类

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703371

Dalwinder Singh, Birmohan Singh

{"title":"Feature Weighting for Improved Classification of Anuran Calls","authors":"Dalwinder Singh, Birmohan Singh","doi":"10.1109/ICSCCC.2018.8703371","DOIUrl":"https://doi.org/10.1109/ICSCCC.2018.8703371","url":null,"abstract":"Automatic bioacoustics monitoring has a great potential to assess the ecosystem health. However, such bioacoustics systems are not highly accurate because the classification of data involves a large number of species. In this paper, we have considered the related problem which involves classification of frog and toad species from their sounds. A publicly available large dataset is used for this purpose where performance is evaluated with leave-one-out cross-validation on the k-NN classifier. The dataset was prepared by extracting Mel-frequency cepstral coefficients (MFCCs)features from the recorded anurans calls, and it comprises the classification of anurans at family, genus and species levels. This paper presents the application of feature weighting to improve the classification of anurans calls. It is a continuous search problem where weights are assigned to features with respect to their contribution in classification. These weights are searched with the Ant Lion optimization along with the best parametric values of the k-NN classifier. The outcomes of experiments show that the proposed approach has successfully enhanced the classification accuracy at family, genus and species levels. The maximum classification accuracies of 95.01%, 88.38%,and 88.08% are achieved at family, genus and species levels respectively which has outperformed the feature selection approach as well as existing works.","PeriodicalId":148491,"journal":{"name":"2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"15 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":"127949632","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

A comparative study of classifiers used in facial embedding classification 人脸嵌入分类中分类器的比较研究

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703359

Sourabh Sarkar, Geeta Sikka

引用次数: 1

Vertical Tunnel-FET Analysis for Excessive Low Power Digital Applications 过低功耗数字应用的垂直隧道-场效应管分析

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703312

Shailendra Singh, B. Raj

引用次数: 16

Fog Classification and Accuracy Measurement Using SVM 基于支持向量机的雾分类与精度测量

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703365

M. Anwar, A. Khosla

引用次数: 4

ICSCCC 2018 Author Index ICSCCC 2018作者索引

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/icsccc.2018.8703297

引用次数: 0

Concentric Layered Architecture for Multi-Level Clustering in Large-Scale Wireless Sensor Networks 大规模无线传感器网络中多级聚类的同心分层结构

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703282

Harmanpreet Singh, Damanpreet Singh

引用次数: 4

ICSCCC 2018 Committee and Message ICSCCC 2018委员会及致辞

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/icsccc.2018.8703367

引用次数: 0

Physical Layer Security Approaches in 5G Wireless Communication Networks 5G无线通信网络中的物理层安全方法

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703344

Pooja Singh, Praveen Pawar, A. Trivedi

{"title":"Physical Layer Security Approaches in 5G Wireless Communication Networks","authors":"Pooja Singh, Praveen Pawar, A. Trivedi","doi":"10.1109/ICSCCC.2018.8703344","DOIUrl":"https://doi.org/10.1109/ICSCCC.2018.8703344","url":null,"abstract":"Rapid growth in the fifth generation (5G) wireless network applications demands new requirements on the data storage, computation, and networking. Thus, it will introduce new threats to the integrity, availability, and confidentiality. 5G is advantageous concerning high data rate, low latency, energy and spectrum efficient, higher capacity, and reliable connectivity. Currently, safeguarding information in the 5G wireless networks is the pivotal issue for research. In this paper, the importance of Physical Layer Security (PLS) for secure transmission of information in wireless networks are discussed. Some popular 5G technologies are studied in the context of security during transmission. With all this, significant issues and challenges are identified in the implementation of new technologies into reality. These technologies are mobile-health (m-health), cognitive radio networks (CRNs), constructive interference, massive multiple input multiple output (massive MIMO), non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT). Future challenges and direction for the further study of such technologies are also given. Moreover, one numerical result is presented for the spectral efficiency in MIMO communication system.","PeriodicalId":148491,"journal":{"name":"2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC)","volume":"175 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":"129145338","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: 11

Abnormality detection in ECG using hybrid feature extraction approach 基于混合特征提取方法的心电异常检测

2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC) Pub Date : 2018-12-01 DOI: 10.1109/ICSCCC.2018.8703349

Ritu Singh, N. Rajpal, R. Mehta

引用次数: 4