2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)最新文献_第2页

A Development Architecture for the Intelligent Animal Care and Management System Based on the Internet of Things and Artificial Intelligence 基于物联网和人工智能的智能动物护理管理系统开发架构

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8669015

Yu-Huei Cheng

{"title":"A Development Architecture for the Intelligent Animal Care and Management System Based on the Internet of Things and Artificial Intelligence","authors":"Yu-Huei Cheng","doi":"10.1109/ICAIIC.2019.8669015","DOIUrl":"https://doi.org/10.1109/ICAIIC.2019.8669015","url":null,"abstract":"The zoo is a local facility where some wild or exotic animals are placed in a fence. The main significance of the zoo is to provide educational and animal conservation functions, and secondly to provide public viewing and entertainment. Animal care and management in the zoo is almost open all year round. Its basic tasks include accommodation, breeding, health care, and medical care etc. Because there are nearly hundreds, thousands, or even ten thousands animals with different body shape and characteristics in the zoo that need to be cared for and managed, animal administrators must be skilled in various tools and real time control the condition of all animals, resulting in the heavy workload of the animal administrators and the huge operating expenses of the zoo. Therefore, it is necessary to find ways to reduce the workload of the animal administrators, but also to immediately control the current state of the animals, while saving animal care and management expenses. This study proposes a development architecture for the intelligent animal management system based on the Internet of Things (IoT) and artificial intelligence (AI). Its main purpose is to automate some tedious procedures for caring animals through the IoT and AI to help animal administrators to take care of them and manage them more systematically.","PeriodicalId":273383,"journal":{"name":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129558086","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: 10

A Bayes Classifier Considering Environmental Change for Multivariate Signal Data 考虑环境变化的多变量信号贝叶斯分类器

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8668977

Itaru Aso, K. Okuhara

引用次数: 0

Blockchain based smart energy trading platform using smart contract 基于区块链的智能能源交易平台，使用智能合约

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8668978

Seung Jae Pee, E. Kang, J. Song, J. Jang

引用次数: 68

Selection of Core Words from Textual Patent Data with DEA based on Citation 基于引文的DEA从专利文本数据中选择核心词

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8668999

Shigeaki Onoda, K. Okuhara

引用次数: 0

Predictive Models of Fire via Deep learning Exploiting Colorific Variation 利用颜色变化的深度学习火灾预测模型

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8669042

JiSeong Han, Gwangsun Kim, ChanSeo Lee, YeongKwang Han, Ung Hwang, Sunghwan Kim

引用次数: 6

Side-Channel Resistance Evaluation Method using Statistical Tests for Physical Unclonable Function 物理不可克隆函数的统计测试侧通道阻力评估方法

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8669053

Y. Nozaki, M. Yoshikawa

{"title":"Side-Channel Resistance Evaluation Method using Statistical Tests for Physical Unclonable Function","authors":"Y. Nozaki, M. Yoshikawa","doi":"10.1109/ICAIIC.2019.8669053","DOIUrl":"https://doi.org/10.1109/ICAIIC.2019.8669053","url":null,"abstract":"To obtain the internet of things (IoT) security, physical unclonable functions (PUFs) have attracted attention. Regarding hardware security, in recent years, the risk of side-channel attacks (SCAs) for PUF is pointed out. Therefore, countermeasures against SCAs have been proposed, and field programmable gate array (FPGA) implementation evaluations have also been reported. On the other hand, the evaluation of PUFs with countermeasures needs actual modeling attacks using many side-channel information; therefore, costs increase. This study proposes a new PUF security evaluation method, which does not need actual modeling attacks. The proposed method verifies the existence of side-channel leakages by applying statistical tests to measured power consumption waveforms during PUF operations. In experiments using an FPGA, by using the proposed method, it was confirmed that there were significant differences in the PUF without countermeasure. Experiments also showed that significant differences did not appear in the PUF with countermeasure and the proposed method could evaluate the PUF security easily without actual modeling attacks.","PeriodicalId":273383,"journal":{"name":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130879808","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: 0

Adaptive Magnetic Resonance Wireless Power Transfer System with Optimum frequency and Power-Leve Tracking for maintaining highly efficient 自适应磁共振无线电力传输系统，具有最佳频率和功率级跟踪，保持高效率

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8669004

N. Kim

引用次数: 3

Feature Image-Based Automatic Modulation Classification Method Using CNN Algorithm 基于CNN算法的特征图像自动调制分类方法

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8669002

Jung Ho Lee, Kwang-Yul Kim, Y. Shin

引用次数: 38

A Novel Case-Based Reasoning Method for Cognitive Frequency Allocation 一种基于案例的认知频率分配推理方法

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8669068

J. Park, D. Yun, Joo-Pyoung Choi, W. Lee

{"title":"A Novel Case-Based Reasoning Method for Cognitive Frequency Allocation","authors":"J. Park, D. Yun, Joo-Pyoung Choi, W. Lee","doi":"10.1109/ICAIIC.2019.8669068","DOIUrl":"https://doi.org/10.1109/ICAIIC.2019.8669068","url":null,"abstract":"In this paper, a cognitive radio engine platform is proposed for exploiting available frequency channels for a tactical wireless sensor network while aiming to protect incumbent communication devices, known as the primary user (PU), from undesired harmful interference. In the field of tactical communication networks, there is an urgent need to identify available frequencies for opportunistic and dynamic access to channels on which the PU is active. This paper introduces a cognitive engine platform for determining the available channels on the basis of case-based reasoning technique deployable as a core functionality on a cognitive radio engine to enable dynamic spectrum access (DSA) with high fidelity. To this end, a plausible learning engine to characterize channel usage pattern is introduced to extract the best channel candidate for the tactical cognitive radio node (TCRN). The performance of the proposed cognitive engine was verified by simulation tests that confirmed the reliability of the functional aspect, which includes the learning engine, as well as the case-based reasoning engine. Moreover, the efficacy of the TCRN with regard to the avoidance of collision with the PU operation, considered the etiquette secondary user (SU), was demonstrated.","PeriodicalId":273383,"journal":{"name":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":"165 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132045857","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: 0

SAOR-Based Precoding with Enhanced BER Performance for Massive MIMO Systems 大规模MIMO系统中基于saor的增强误码率预编码

2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Pub Date : 2019-02-01 DOI: 10.1109/ICAIIC.2019.8668984

Yanjun Hu, Jiayu Wu, Yi Wang

{"title":"SAOR-Based Precoding with Enhanced BER Performance for Massive MIMO Systems","authors":"Yanjun Hu, Jiayu Wu, Yi Wang","doi":"10.1109/ICAIIC.2019.8668984","DOIUrl":"https://doi.org/10.1109/ICAIIC.2019.8668984","url":null,"abstract":"The iterative precoding scheme is a common algorithm for downlink massive MIMO systems. Due to the large number of system antennas, traditional linear precoding schemes are usually involve the large-scale matrix inversion and leads to high computational complexity. The complexity of the linear precoding algorithm greatly reduced when the iterative algorithm is proposed, but it caused a decline in Bit Error Rate (BER) performance. Improving the BER performance of the iterative algorithm and ensuring the convergence rate has always been the focus of attentions. Currently, there are many iterative methods that only have mathematical theory and not applied to precoding yet. To solve the aforementioned problem, we proposes a precoding scheme based on Symmetric Accelerated Over Relaxation (SAOR) method, which achieve the enhancement BER performance compared to other iterative algorithms. Combined with the actual system, the selection of optimal acceleration factor and relaxation factor are discussed, which is only related to system parameters. The simulation results show that SAOR-based precoding can achieve good BER performance with less iterations and guarantee the convergence rate.","PeriodicalId":273383,"journal":{"name":"2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124393237","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: 0