2023 8th International Conference on Computer and Communication Systems (ICCCS)最新文献

Stock Trading Decision Method Based on Stop Loss Double Threshold 基于止损双阈值的股票交易决策方法

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10151355

J. Wu, Shaowei Ma, Ke Wang, Huizhen Yan, Qinghua Zhang

{"title":"Stock Trading Decision Method Based on Stop Loss Double Threshold","authors":"J. Wu, Shaowei Ma, Ke Wang, Huizhen Yan, Qinghua Zhang","doi":"10.1109/ICCCS57501.2023.10151355","DOIUrl":"https://doi.org/10.1109/ICCCS57501.2023.10151355","url":null,"abstract":"Artificial intelligence technology is widely used in stock market stock forecasting, which can help investors achieve “buy at a low price and sell at a high price”. Many scholars are focusing on how to increase investors' returns and reduce their risks. This study takes stocks in the United States and Taiwan as the research objects, and historical data, futures, and options as the data set, in an attempt to find a less risky and more rewarding method of stock trading decisions. Long short-term memory neural networks (LSTM) are used to study stock price fluctuations. The Kelly criterion for fund management is used to calculate the optimal investment ratio, and a stop loss strategy based on double thresholds is added so that investors can sell within a certain period when the stock price falls to a certain range, thereby reducing investors' risks. The particle swarm optimization algorithm (PSO) is used to optimize the critical values of trading threshold and stop loss range. The experimental results show that the stop loss strategy based on double thresholds can effectively reduce investors' risk. The addition of leading indicators such as futures and options can increase the accuracy of stock prediction and increase the return of investors.","PeriodicalId":266168,"journal":{"name":"2023 8th International Conference on Computer and Communication Systems (ICCCS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123135910","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

Secure Aggregation with Uncoded Groupwise Keys Against User Collusion 使用未编码组密钥的安全聚合防止用户合谋

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10151414

Ziting Zhang, Kai Wan, Hua Sun, Mingyue Ji, G. Caire

{"title":"Secure Aggregation with Uncoded Groupwise Keys Against User Collusion","authors":"Ziting Zhang, Kai Wan, Hua Sun, Mingyue Ji, G. Caire","doi":"10.1109/ICCCS57501.2023.10151414","DOIUrl":"https://doi.org/10.1109/ICCCS57501.2023.10151414","url":null,"abstract":"In this paper, we study the information theoretic secure aggregation problem, where the server node aims to aggregate K users' locally trained models, without revealing any other information about the users' local data. To ensure security, some keys are shared among the users, which is referred to as the key sharing phase. Uncoded groupwise keys are considered, where each key is shared by a subset of S users and is independent from other keys. After the key sharing phase, each user masks its trained model and sends to the server, which is referred to as the model aggregation phase. In the presence of users' dropouts (i.e., up to K – U user may drop during the model aggregation phase and the identity of the dropped users cannot be predicted), to guarantee the information theoretic security, two-round transmissions are necessary. Our objective is to characterize the capacity region of the transmission rates (i.e., the normalized numbers of two-round transmissions by each user) in the two rounds. When $mathsf{S}geq mathsf{K}- mathsf{U}+1$, the capacity region was recently characterized. In this paper, we additionally consider the potential effect of user collusion, where there may exist up to T users colluding with the server. With the presence of the colluding users, the security constraint becomes that, except the sum of trained models, the server cannot learn any information about the other users' local data even if it colludes with any set of up to T users. For this new problem, we propose two secure aggregation schemes, which work for the cases of $mathsf{S} = mathsf{K}-mathsf{U}+1$ and of $mathsf{K}-mathsf{U}+1leq mathsf{S}leq mathsf{K} - mathsf{T}$, respectively. The first scheme is then proven to achieve the capacity region.","PeriodicalId":266168,"journal":{"name":"2023 8th International Conference on Computer and Communication Systems (ICCCS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114678165","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

Dictionary-Based Tensor Decomposition-Aided Time-Varying Channel Estimation for Millimeter Wave MU-MIMO Systems 基于字典的张量分解辅助毫米波MU-MIMO系统时变信道估计

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10150749

Tongtong Weng, Wuyang Zhou

引用次数: 0

On the Discussion of the Semantic Communication with the Transmission of MNIST Dataset 基于MNIST数据集传输的语义通信问题探讨

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10151200

Kaijun Liu, Chen Dong, Xiaodong Xu, Geng Liu

{"title":"On the Discussion of the Semantic Communication with the Transmission of MNIST Dataset","authors":"Kaijun Liu, Chen Dong, Xiaodong Xu, Geng Liu","doi":"10.1109/ICCCS57501.2023.10151200","DOIUrl":"https://doi.org/10.1109/ICCCS57501.2023.10151200","url":null,"abstract":"Inspired by the success of artificial intelligence (AI) in various fields, recently, AI-based semantic communication has been studied extensively and achieved great success. However, the existing works may not provide a comprehensive understanding of how channels affect semantic communication from phenomena. In this paper, based on the observations on the MNIST dataset, the following questions are discussed: (1) Why is semantic communication robust? We believe and observe in the experiments that the trade-off learning between the characteristic and common information of data is one of the key properties of semantic communication. The “channel robustness” and “hard generalization” phenomena are explained in this perspective. (2) How does noise affect semantic communication in the AWGN channel? Because of noise, there is a smallest distinguishable unit, called as semantic constellation cluster (SCC), where the features in the SCC are confused by noise and can not be distinguishable. The feature criterion (FC) is analyzed and observed in the experiments, which means the minimum distance of features that the features can just be distinguishable and is also the radius of SCC in the AWGN channel. (3) How does the semantic decoder distinguish noised features under the large noise in the AWGN channel? It is found that the outer edge of the expending space brought by noise is easy to be distinguish for the decoder, thus maintaining fairly good performance under the large noise.","PeriodicalId":266168,"journal":{"name":"2023 8th International Conference on Computer and Communication Systems (ICCCS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121047869","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

Intelligent Reflecting Surface-Aided MU-MISO Communication Systems with Constructive Interference Precoding 具有建设性干扰预编码的智能反射表面辅助MU-MISO通信系统

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10150722

Jinhui Hua, Guanghui Zhang, Tuanwei Tian, Hao Deng

引用次数: 0

Joint Subcarrier and Power Allocation in Mobile Scenario of the OFDM Systems Based on Deep Reinforcement Learning 基于深度强化学习的OFDM系统移动场景联合子载波和功率分配

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10150951

Xiaodong Li, Weixi Zhou, Hongjie Zhang, Jing Zhao, Dongcai Zhao, Zhicheng Dong

{"title":"Joint Subcarrier and Power Allocation in Mobile Scenario of the OFDM Systems Based on Deep Reinforcement Learning","authors":"Xiaodong Li, Weixi Zhou, Hongjie Zhang, Jing Zhao, Dongcai Zhao, Zhicheng Dong","doi":"10.1109/ICCCS57501.2023.10150951","DOIUrl":"https://doi.org/10.1109/ICCCS57501.2023.10150951","url":null,"abstract":"The increasing number of base station (BS) service users has made spectrum resources more valuable, leading to the need for efficient resource allocation. To address this issue, this paper proposes a novel deep reinforcement learning (DRL) architecture that solves the subcarrier-user matching and subcarrier power allocation problem in orthogonal frequency division multiple (OFDM) systems. This approach improves the system spectral efficiency (SE) by reducing inter-subcarrier interference (ICI) through subcarrier matching and power allocation, while ensuring that the minimum rate requirements for users (mobile or stationary) are met. We approach this problem by dividing it into two interconnected components: the subcarrier matching part (SMP) and the subcarrier power allocation part (SPAP). To address these two parts, the paper proposes a DRL method based on joint allocation of resources by three agents (JAoR-TA). In SMP, the REINFORCE algorithm is used to match subcarriers, and the results are then given to SPAP. In SPAP, two Actor-Critic network frameworks are proposed to address the subcarrier power allocation problem. Based on the simulation results, it has been observed that the JAoR-TA algorithm outperforms the REINFORCE algorithm in mobile scenarios, as it achieves a higher system SE.","PeriodicalId":266168,"journal":{"name":"2023 8th International Conference on Computer and Communication Systems (ICCCS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125528340","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

A Robust Control Algorithm of Deformable Network with Composite Geometric Constraints 具有复合几何约束的可变形网络鲁棒控制算法

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10151004

Bin Zhang, X. Chen, Jin Zhou

引用次数: 0

Secure IoV in Nakagami-m Fading Scenarios 安全的IoV在nakagami衰落场景

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10150525

Yunkang Liu, Shu Li, Min Yan, Shuai Wang, Gaofeng Pan, Jianping An

引用次数: 0

ALRS: An Attention Loss Function based on Row-Sparsity for Incremental Learning 基于行稀疏的增量学习注意损失函数

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10151382

Yingying Xia, Bo Lu, Jianmin Ji

{"title":"ALRS: An Attention Loss Function based on Row-Sparsity for Incremental Learning","authors":"Yingying Xia, Bo Lu, Jianmin Ji","doi":"10.1109/ICCCS57501.2023.10151382","DOIUrl":"https://doi.org/10.1109/ICCCS57501.2023.10151382","url":null,"abstract":"Incremental learning has received significant attention, but the problem of catastrophic forgetting remains a major challenge for existing approaches. This issue hinders models from accumulating knowledge over long stretches. To address this problem, we propose a new approach called Attention Loss function based on Row-Sparsity (ALRS) that mines significant patches by simultaneously learning patch weights and logits (class vectors) using the same parameters. We integrate the attention mechanism with the novel loss function to avoid catastrophic forgetting. This innovative approach enables the model to conflate the newly introduced classes with the existing ones, without the need to store any data or models from the previous steps' base classes. To assess its efficacy, we incorporate ALRS into the distillation loss for validation and conduct a thorough evaluation of the approach's performance on three datasets: CIFAR-100, Caltech-101, and CUBS-200-2011. Compared to LWM, which also does not store data, our method achieves an average improvement of more than 8 percentage points with an absolute advantage on CIFAR-100. Additionally, on Caltech-101 and CUBS-200-2011, our new approach provides comparable accuracy to baseline.","PeriodicalId":266168,"journal":{"name":"2023 8th International Conference on Computer and Communication Systems (ICCCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128725524","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

Thai Handwritten Character Recognition Using Deep Convolutional Neural Network 使用深度卷积神经网络的泰文手写字符识别

2023 8th International Conference on Computer and Communication Systems (ICCCS) Pub Date : 2023-04-21 DOI: 10.1109/ICCCS57501.2023.10151078

Suwanee Kulkarineetham, Vipa Thananant

引用次数: 0