2015 International Conference on Intelligent Networking and Collaborative Systems最新文献_第5页

A Model of Mining Noise-Tolerant Frequent Itemset in Transactional Databases 事务数据库中容噪频繁项集的挖掘模型

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.87

Xiaomei Yu, Hong Wang, Xiangwei Zheng, Shuang Liu

引用次数: 0

New Compact CCA Secure Elgamal Scheme in the Random Oracle Model 随机Oracle模型下的新型紧凑型CCA安全密码方案

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.41

Xu An Wang, Jianfeng Ma, Xiaoyuan Yang

引用次数: 1

Evolutionary Algorithm Based on Partition Crossover (EAPX) for the Vehicle Routing Problem 基于分区交叉的车辆路径进化算法

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.89

Takwa Tlili, F. Chicano, S. Krichen, E. Alba

引用次数: 1

Fuzzy Partition Rules for Heart Arrhythmia Detection 心律失常检测的模糊划分规则

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.50

Omar Behadada

引用次数: 0

Proposing an Extended iBeacon System for Indoor Route Guidance 一种用于室内路径引导的扩展iBeacon系统

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.72

A. Fujihara, Takuma Yanagizawa

引用次数: 39

A Smart Competence-Based Prioritisation for Learning Programmes 学习计划的智能能力优先排序

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.61

M. Gaeta, Antonio Marzano, Sergio Miranda, K. Sandkuhl

{"title":"A Smart Competence-Based Prioritisation for Learning Programmes","authors":"M. Gaeta, Antonio Marzano, Sergio Miranda, K. Sandkuhl","doi":"10.1109/INCoS.2015.61","DOIUrl":"https://doi.org/10.1109/INCoS.2015.61","url":null,"abstract":"In public and local administration contexts, the organizational structures depend on bureaucratic aspects. This often implies that people are engaged in offices and their allocation come from emergencies and political factors instead of rational motivations related to knowledge, competences and profiles. In most cases, such situations become gangrenous and generate dissatisfaction and low productivity. The objective of our work is applying competence management, skill gap analysis and a study of the existing organizational structures to point out the functional unit with the most critical situation in terms of allocated employees and to suggest a solution according to the complex laws, internal regulation for the staff management and trade-union influences. The proposed approach identifies the real gaps that create inefficiencies and suggests the people to engage in learning programs by focusing exactly on what the organizations need with respect to what the employees have. It happens by elaborating a priority scale on the base of existing hierarchies, relationships, logistic constraints and other aspects with the aim, above all, of enhancing the identified unit and the local administration itself.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122604680","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

Muzzle-Based Cattle Identification Using Speed up Robust Feature Approach 基于快速鲁棒特征的牛口识别方法

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.60

Shaimaa A. El-said, T. Gaber, A. Tharwat, A. Hassanien, V. Snás̃el

{"title":"Muzzle-Based Cattle Identification Using Speed up Robust Feature Approach","authors":"Shaimaa A. El-said, T. Gaber, A. Tharwat, A. Hassanien, V. Snás̃el","doi":"10.1109/INCoS.2015.60","DOIUrl":"https://doi.org/10.1109/INCoS.2015.60","url":null,"abstract":"Starting from the last century, animals identification became important for several purposes, e.g. tracking, controlling livestock transaction, and illness control. Invasive and traditional ways used to achieve such animal identification in farms or laboratories. To avoid such invasiveness and to get more accurate identification results, biometric identification methods have appeared. This paper presents an invariant biometric-based identification system to identify cattle based on their muzzle print images. This system makes use of Speeded Up Robust Feature (SURF) features extraction technique along with with minimum distance and Support Vector Machine (SVM) classifiers. The proposed system targets to get best accuracy using minimum number of SURF interest points, which minimizes the time needed for the system to complete an accurate identification. It also compares between the accuracy gained from SURF features through different classifiers. The experiments run 217 muzzle print images and the experimental results showed that our proposed approach achieved an excellent identification rate compared with other previous works.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124715191","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: 30

Semi-automatic Generation of an Object-Oriented API Framework over Semantic Repositories 基于语义库的面向对象API框架的半自动生成

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.22

Daniele Toti, Marco Rinelli

引用次数: 5

Human Thermal Face Recognition Based on Random Linear Oracle (RLO) Ensembles 基于随机线性预测集(RLO)的人体热人脸识别

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.67

T. Gaber, A. Tharwat, Abdelhameed Ibrahim, V. Snás̃el, A. Hassanien

引用次数: 23

Fine-Grained Privacy-Preserving Spatiotemporal Matching in Mobile Social Networks 移动社交网络中保护隐私的细粒度时空匹配

2015 International Conference on Intelligent Networking and Collaborative Systems Pub Date : 2015-09-02 DOI: 10.1109/INCoS.2015.73

Xiuguang Li, Kai Yang, Hui Li

{"title":"Fine-Grained Privacy-Preserving Spatiotemporal Matching in Mobile Social Networks","authors":"Xiuguang Li, Kai Yang, Hui Li","doi":"10.1109/INCoS.2015.73","DOIUrl":"https://doi.org/10.1109/INCoS.2015.73","url":null,"abstract":"With the rapid popularization of mobile smartphone and its built-in location-aware devices, people are possible to establish trust relationships with each other by matching their interests, hobbies, experiences, or spatiotemporal profiles. However, the contradiction between the possibility of personal sensitive information leaking and the growing privacy concerns of users restricts the widespread use of direct matching schemes. To addressthis problem, lots of privacy-preserving matching schemes were proposed recently years. These schemes ensure users find the perfect matcher(s) without revealing extra unnecessary personal information. And yet, at the same time, it is inevitable that they produce more computation amount and communication traffic compare with former direct matching schemes. For mobile application scenarios, it is a heavy burden since power is limited. Particularly, for spatiotemporal matching, the situation is much worse due to the number of elements in users' spatiotemporal profiles will be very large as time goes on. Another outstanding issue in spatiotemporal matching is that how to define two users are neighboring. So, how to achieve an efficient and exactly privacy-preserving spatiotemporal matching remains an open question. In this paper, we propose a fine-grained privacypreserving spatiotemporal matching in Mobile Social Networks. Our scheme decreases the spatiotemporal matching error, as well as promotes the efficiency of matchmaking. Thorough security analysis and evaluation results indicate that our scheme is effective and efficient.","PeriodicalId":345650,"journal":{"name":"2015 International Conference on Intelligent Networking and Collaborative Systems","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132671194","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