J. Inf. Process. Syst.最新文献_第2页

Personalized Web Service Recommendation Method Based on Hybrid Social Network and Multi-Objective Immune Optimization 基于混合社会网络和多目标免疫优化的个性化Web服务推荐方法

J. Inf. Process. Syst. Pub Date : 2021-04-01 DOI: 10.3745/JIPS.01.0071

Huashan Cao

引用次数: 5

Power Allocation Method of Downlink Non-orthogonal Multiple Access System Based on α Fair Utility Function 基于α公平效用函数的下行非正交多址系统功率分配方法

J. Inf. Process. Syst. Pub Date : 2021-04-01 DOI: 10.3745/JIPS.03.0157

Jianpo Li, Qiwei Wang

{"title":"Power Allocation Method of Downlink Non-orthogonal Multiple Access System Based on α Fair Utility Function","authors":"Jianpo Li, Qiwei Wang","doi":"10.3745/JIPS.03.0157","DOIUrl":"https://doi.org/10.3745/JIPS.03.0157","url":null,"abstract":"The unbalance between system ergodic sum rate and high fairness is one of the key issues affecting the performance of non-orthogonal multiple access (NOMA) system. To solve the problem, this paper proposes a power allocation algorithm to realize the ergodic sum rate maximization of NOMA system. The scheme is mainly achieved by the construction algorithm of fair model based on α fair utility function and the optimal solution algorithm based on the interior point method of penalty function. Aiming at the construction of fair model, the fair target is added to the traditional power allocation model to set the reasonable target function. Simultaneously, the problem of ergodic sum rate and fairness in power allocation is weighed by adjusting the value of α. Aiming at the optimal solution algorithm, the interior point method of penalty function is used to transform the fair objective function with unequal constraints into the unconstrained problem in the feasible domain. Then the optimal solution of the original constrained optimization problem is gradually approximated within the feasible domain. The simulation results show that, compared with NOMA and time division multiple address (TDMA) schemes, the proposed method has larger ergodic sum rate and lower Fairness Index (FI) values.","PeriodicalId":415161,"journal":{"name":"J. Inf. Process. Syst.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130785960","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: 1

Vehicle Image Recognition Using Deep Convolution Neural Network and Compressed Dictionary Learning

J. Inf. Process. Syst. Pub Date : 2021-04-01 DOI: 10.3745/JIPS.01.0073

Yanyan Zhou

{"title":"Vehicle Image Recognition Using Deep Convolution Neural Network and Compressed Dictionary Learning","authors":"Yanyan Zhou","doi":"10.3745/JIPS.01.0073","DOIUrl":"https://doi.org/10.3745/JIPS.01.0073","url":null,"abstract":"In this paper, a vehicle recognition algorithm based on deep convolutional neural network and compression dictionary is proposed. Firstly, the network structure of fine vehicle recognition based on convolutional neural network is introduced. Then, a vehicle recognition system based on multi-scale pyramid convolutional neural network is constructed. The contribution of different networks to the recognition results is adjusted by the adaptive fusion method that adjusts the network according to the recognition accuracy of a single network. The proportion of output in the network output of the entire multiscale network. Then, the compressed dictionary learning and the data dimension reduction are carried out using the effective block structure method combined with very sparse random projection matrix, which solves the computational complexity caused by high-dimensional features and shortens the dictionary learning time. Finally, the sparse representation classification method is used to realize vehicle type recognition. The experimental results show that the detection effect of the proposed algorithm is stable in sunny, cloudy and rainy weather, and it has strong adaptability to typical application scenarios such as occlusion and blurring, with an average recognition rate of more than 95%.","PeriodicalId":415161,"journal":{"name":"J. Inf. Process. Syst.","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125235080","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 Special Section on Deep & Advanced Machine Learning Approaches for Human Behavior Analysis 关于人类行为分析的深度和高级机器学习方法的特别部分

J. Inf. Process. Syst. Pub Date : 2021-04-01 DOI: 10.3745/JIPS.01.0074

Yizhang Jiang, Kim-Kwang Raymond Choo, Hoon Ko

引用次数: 8

Query Optimization on Large Scale Nested Data with Service Tree and Frequent Trajectory 基于服务树和频繁轨迹的大规模嵌套数据查询优化

J. Inf. Process. Syst. Pub Date : 2021-02-09 DOI: 10.3745/JIPS.04.0205

Li Wang, Guodong Wang

引用次数: 0

Effective and Efficient Similarity Measures for Purchase Histories Considering Product Taxonomy 考虑产品分类的购买历史记录的有效和高效相似度量

J. Inf. Process. Syst. Pub Date : 2021-02-09 DOI: 10.3745/JIPS.04.0209

Yu-Jeong Yang, K. Lee

{"title":"Effective and Efficient Similarity Measures for Purchase Histories Considering Product Taxonomy","authors":"Yu-Jeong Yang, K. Lee","doi":"10.3745/JIPS.04.0209","DOIUrl":"https://doi.org/10.3745/JIPS.04.0209","url":null,"abstract":"In an online shopping site or offline store, products purchased by each customer over time form the purchase history of the customer. Also, in most retailers, products have a product taxonomy, which represents a hierarchical classification of products. Considering the product taxonomy, the lower the level of the category to which two products both belong, the more similar the two products. However, there has been little work on similarity measures for sequences considering a hierarchical classification of elements. In this paper, we propose new similarity measures for purchase histories considering not only the purchase order of products but also the hierarchical classification of products. Unlike the existing methods, where the similarity between two elements in sequences is only 0 or 1 depending on whether two elements are the same or not, the proposed method can assign any real number between 0 and 1 considering the hierarchical classification of elements. We apply this idea to extend three existing representative similarity measures for sequences. We also propose an efficient computation method for the proposed similarity measures. Through various experiments, we show that the proposed method can measure the similarity between purchase histories very effectively and efficiently.","PeriodicalId":415161,"journal":{"name":"J. Inf. Process. Syst.","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125918973","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

Default Prediction of Automobile Credit Based on Support Vector Machine 基于支持向量机的汽车信贷违约预测

J. Inf. Process. Syst. Pub Date : 2021-02-09 DOI: 10.3745/JIPS.04.0207

Ying Chen, Ruirui Zhang

引用次数: 1

Multiple Properties-Based Moving Object Detection Algorithm 基于多属性的运动物体检测算法

J. Inf. Process. Syst. Pub Date : 2021-02-09 DOI: 10.3745/JIPS.02.0153

Changjian Zhou, Jinge Xing, Haibo Liu

引用次数: 0

Supply Chain Trust Evaluation Model Based on Improved Chain Iteration Method 基于改进链迭代法的供应链信任评估模型

J. Inf. Process. Syst. Pub Date : 2021-02-09 DOI: 10.3745/JIPS.04.0203

Hongqiang Jiao, Wanning Ding, Xinxin Wang

{"title":"Supply Chain Trust Evaluation Model Based on Improved Chain Iteration Method","authors":"Hongqiang Jiao, Wanning Ding, Xinxin Wang","doi":"10.3745/JIPS.04.0203","DOIUrl":"https://doi.org/10.3745/JIPS.04.0203","url":null,"abstract":"The modern market is highly competitive. It has progressed from traditional competition between enterprises to competition between supply chains. To ensure that enterprise can form the best strategy consistently, it is necessary to evaluate the trust of other enterprises in the supply chain. First, this paper analyzes the background and significance of supply chain trust research, analyzes and expounds on the qualitative and quantitative methods of supply chain trust evaluation, and summarizes the research in this field. Analytic hierarchy process (AHP) is the most frequently used method in the literature to evaluate and rank criteria through data analysis. However, the input data for AHP analysis is based on human judgment, and hence there is every possibility that the data may be vague to some extent. Therefore, in view of the above problems, this study improves the global trust method based on chain iteration. The improved global trust evaluation method based on chain iteration is more flexible and practical, hence, it can more accurately evaluate supply chain trust. Finally, combined with an actual case of Zhaoxian Chengji Food Co. Ltd., the paper qualitatively analyzes the current situation of supply chain trust management and effectively strengthens the supervision of enterprises to cooperative enterprises. Thus, the company can identify problems on time and strategic adjustments can be implemented accordingly. The effectiveness of the evaluation method proposed in this paper is demonstrated through a quantitative evaluation of its trust in downstream enterprise A. Results suggest that the subjective preferences of and historical transactions together affect the final evaluation of trust.","PeriodicalId":415161,"journal":{"name":"J. Inf. Process. Syst.","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122174334","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

Simulation of a Mobile IoT System Using the DEVS Formalism 使用DEVS形式化的移动物联网系统仿真

J. Inf. Process. Syst. Pub Date : 2021-02-09 DOI: 10.3745/JIPS.03.0155

J. Im, Ha-Ryoung Oh, Y. Seong

引用次数: 0