动态频谱访问无线网络的连通性分析

与传统无线网络不同,在动态频谱访问无线网络中,授权用户对分配的频段具有优先使用权,非授权用户网络的连通性受授权用户的分布和授权用户对频段的使用行为的影响.基于连续渗流理论,证明当授权用户较为稀疏或者负载较轻时,非授权用户可以构成部分连通的网络;反之,当授权用户较为密集并且负载较重时,无法部署部分连通的非授权用户网络.此外,在授权用户和非授权用户共享1个信道的情况下,给出了非授权用户网络存在部分连通性的必要条件.仿真实验数据验证了理论分析的正确性.     

一种位置服务隐私保护方法

近年来,大多数的位置服务隐私保护转向了基于用户协作的P2P形式,但是此模式最大的弊端在于协作用户存在不诚信的情况,如果出现恶意的协作用户,那么协作组用户信息可能会被泄露.在此前提下,本文通过添加第三方信任机构为移动用户进行网络行为异常检测的方式,提出一种防范位置隐私泄露给恶意用户的方法,并通过二叉树的形式扩展P2P模式下的寻找协作用户的范围.通过实验验证,可以有效地防范非诚信用户加入匿名组,降低了信息泄露的可能.     

LTE-A系统载波聚合情况下改进的PF算法*

为提高边缘用户的吞吐量和用户间的公平性,提出了边缘用户优先比例公平算法。算法思想是让某些成分载波上的RBs以概率a分配给边缘用户,以概率1-a分配给中心用户,分配后再使用传统的比例公平算法进行调度;而其他成分载波上的RBs直接使用传统的比例公平算法进行调度。仿真表明,该算法可以较好地提高边缘用户的吞吐量和用户间的公平性,并且可以通过控制a的大小来调节边缘用户吞吐量和用户间的公平性。     

A low-cost communication security scheme of UAV based on multi-round reverse auction model

In recent years, the security of wireless communication has received more and more attention. However, with the increasing requirements for security performance in the process of wireless communication, the cost of improving security also increases. Therefore, how to improve the security of wireless communication while reducing costs has become a serious challenge. Aiming at the security problems in the UAV-assisted wireless communication link based on the premise of low cost and high profit, this paper studies how to motivate non-offloading users to send jamming power to interfere with eavesdropping UAVs, so efficiently and economically to improve the security performance of wireless communication link. Firstly, the relationship between the security performance of the communication link and the interference power is revealed through the theoretical model. Then, we propose a scenario consisting of a legitimate UAV, a ground user group, and an eavesdrop UAV. In this scenario, we divide the ground users into offloading users and non-offloading users. At the same time, the cost functions for offloading users and utility functions for non-offloading users are defined, and non-offloading users are encouraged to help to offload users unload data safely to a legitimate UAV by obtaining rewards for offloading users. Considering the selfishness of users, a reverse auction algorithm based on multi-user groups is proposed to achieve the optimal mapping between non-offloading users and offloading users. Finally, the effectiveness of the proposed scheme is verified by a large number of simulations. The research results show that the scheme innovative designs a method for users to cooperate to interfere with eavesdroppers, which can reduce costs and improve utility while maximizing the improvement of wireless communication link security.     

干扰受限系统的认知用户功率控制算法

根据认知无线电系统中认知用户的不同通信需求,结合干扰温度模型和非合作博弈理论,以单小区CDMA为系统平台,提出基于SINR的对数效用函数的干扰受限认知无线电系统功率控制算法。仿真实验结果表明,与经典SINR平衡算法及Koskie-Gajic算法相比,该算法在满足认知用户目标SINR和主用户干扰温度限制的前提下,通过适当增大认知用户发射功率,能够满足认知用户高速数据通信的需要。     

挖掘用户浏览网页的兴趣研究

通过挖掘网页的浏览记录来对用户群体兴趣进行分析。对访问网站的兴趣类别、时间、用户数进行统计,得到规律性的结论。其次提出一种改进的基于HAC和k-means的算法对用户根据兴趣进行聚类,挖掘用户的访问模式。最后验证了主导兴趣的稳定性即随着日志的增加,用户的最大兴趣是趋于稳定的。     

The effects of design,size, and uniqueness of smartwatches: perspectives from current versus potential users

ABSTRACT

This study proposes design, uniqueness, and screen size as the key components of aesthetic appeal and investigates their role in influencing the use behaviour of current smartwatch users and purchase intentions of potential users. Hypotheses were tested using SmartPLS to analyze data collected from 377 current smartwatch users and 361 potential users. Design aesthetics was found to be the most important factor influencing the behavioural intentions of both user groups. Screen size and uniqueness had significant effects on current users’ use behaviour and potential users’ purchase intentions, respectively. Gender moderated the effect of design on the use behaviour of current smartwatch users, such that female users’ behaviour was more likely to be influenced than male users. A subsequent analysis on the moderating effect of brand revealed that the design aesthetics of smartwatches mattered more for Apple than Samsung in terms of promoting use behaviour.     

云模型与用户聚类的个性化推荐

针对传统推荐系统数据稀疏、相似性计算方法导致共同评分用户少的问题,提出利用云模型定性概念与定量数值转换的优势,研究云模型、用户聚类的个性化推荐改进算法。用户对项目属性评价的偏好,转换为用户对加权综合云模型表示的数字特征的偏好。利用改进的聚类算法,对评分数据、原始用户属性标准化后的信息进行聚类;同时考虑用户兴趣的变化,结合用户之间项目属性评价的综合云模型的相似度、用户对项目评分的聚类、用户属性聚类这三种方法产生的邻居用户的并集进行推荐。理论分析和实验结果表明,提出的改进算法不但解决数据稀疏性带来的共同评分用户少的弊端,即使是在新用户的情况下,仍能获得较低的平均绝对误差和平均平方误差     

Do Internet Users Have More Social Ties? A Call for Differentiated Analyses of Internet Use

Research on the impact of Internet use on social ties has generated conflicting results. Based on data from the 2000 General Social Survey, this study finds that different types of Internet usage are differentially related to social connectivity. While nonsocial users of the Internet do not differ significantly from nonusers in network size, social users of the Internet have more social ties than nonusers do. Among social users, heavy email users have more social ties than do light email users. There is indication that, while email users communicate online with people whom they also contact offline, chat users maintain some of their social ties exclusively online. These findings call for differentiated analyses of Internet uses and their effects on interpersonal connectivity.     

A Multimodal Measurement Method of Users’ Emotional Experiences Shopping Online

Emotions play an important role in the design of e‐commerce websites. A website should satisfy its users’ emotional needs. Emotion measurement is a prerequisite to understanding users’ emotional needs; because emotions contain complicated components, they are difficulty to measure. To interpret users’ emotional experiences while the users are interacting with e‐commerce websites, we propose a multimodal measurement method conjoint using questionnaires, eye tracking, and physiological measures. The effects of various websites on users’ emotions and the relationship between users’ subjective emotional ratings, eye movements, and physiological responses, along with the effects of their emotions on behavior intentions, were analyzed. The results indicate that differences in users’ emotional experiences while shopping on various e‐commerce websites are primarily embodied in subjective emotional ratings and eye movements. There is a correlation between users’ subjective emotional ratings, eye movements, and physiological responses, and to some extent, users’ emotional experiences can affect their behavior intentions.     

内部用户行为监管方案

信息安全领域,内部威胁已被认为是一个非常严重的安全问题。因此要建立可信的操作系统环境,必须对登录的内部合法用户的行为进行监管,防止内部威胁的发生。提出了基于用户意图的动态访问控制模型,即依据用户提交的访问意图对内部用户进行访问控制和行为监控,并利用层次分析法AHP对监控得到的用户行为证据进行定量分析评估,然后根据评估结果对内部用户行为进行控制;最后利用Matlab对监管方案进行仿真,实验结果表明该方案可以有效地提高感知内部威胁行为的准确率,克服了难以对内部用户行为进行定量分析的缺点。     

Understanding and designing for intermediated information tasks in India

It's important to consider both primary and secondary users when designing for intermediated interaction scenarios in India and elsewhere in the developing world. However, most of this research has focused on supporting users in the developed world who are voluntarily collaborating on a computing task. Many users in India, especially those from disadvantaged classes, have only partial or no physical access to computing devices. We refer to these users as secondary users to distinguish them from the primary users that the interface design process traditionally considers. Secondary users must interact with information resources via a proxy primary user who has the required access rights and skills. The proxy's filtering and funneling decisions limit the secondary users' information-seeking behavior; the secondary user might also have an unequal power relationship with the proxy. Therefore, secondary users might never know the full scope of actions and knowledge available to them. If we are to realize the egalitarian potential of computing, we must consider secondary users in the design process. We must develop technologies that recognize the needs and aspirations of all classes of users, including those without direct access to the user interface. In fact, by designing user interfaces explicitly supporting intermediated tasks, both primary and secondary users can benefit.     

基于大尺度衰落系数的联合用户分组和导频分配策略

导频长度受限会导致相同的导频复用给不同的小区用户,由此引起导频污染问题。导频污染将使得信道状态信息估计不准,从而降低系统性能。针对小区内不同区域用户遭受导频污染程度不同的问题,分析图着色和部分导频交替复用（AFPR）2种导频分配方案,在这2种方案的基础上进行折中,提出一种基于大尺度衰落系数的联合用户分组以及导频分配方案。对用户与本基站之间的大尺度衰落系数大小进行升序排序,将所有小区用户根据所受导频污染严重程度的不同,依次分类为安全边缘用户、危险边缘用户和中心用户,对于安全边缘用户和非安全边缘用户,分别采用加权图着色方案和AFPR方案进行导频分配。仿真结果表明,相比原有AFPR方案,该方案的用户平均上行可达和速率提高约2.2%,其能够有效利用不同区域用户信道质量的差异性来完成导频分配,并通过具有较低复杂度的策略降低导频污染对用户的影响。     

Latent grouping models for user preference prediction

We tackle the problem of new users or documents in collaborative filtering. Generalization over users by grouping them into user groups is beneficial when a rating is to be predicted for a relatively new document having only few observed ratings. Analogously, generalization over documents improves predictions in the case of new users. We show that if either users and documents or both are new, two-way generalization becomes necessary. We demonstrate the benefits of grouping of users, grouping of documents, and two-way grouping, with artificial data and in two case studies with real data. We have introduced a probabilistic latent grouping model for predicting the relevance of a document to a user. The model assumes a latent group structure for both users and items. We compare the model against a state-of-the-art method, the User Rating Profile model, where only the users have a latent group structure. We compute the posterior of both models by Gibbs sampling. The Two-Way Model predicts relevance more accurately when the target consists of both new documents and new users. The reason is that generalization over documents becomes beneficial for new documents and at the same time generalization over users is needed for new users.     

Lessons from Ideation: Where Does User Involvement Lead Us?

Firms are increasingly involving users in new product development (NPD). Their product users frequently provide solution information, such as new product ideas. However, these users are often considered a homogeneous group of ordinary users; their individual abilities and the specific input they provide for NPD are not yet well understood. The goal of this paper is to determine whether different types of users are differently predisposed to produce ideas. We derive hypotheses regarding the possible outcome of involving different user types in idea generation tasks from the current literature on customer integration into NPD. In a quasi‐experimental setting, we test our assumptions on 93 users, who generate ideas in a smart home context. The results indicate that users’ contribution depends on their specific domain knowledge, which is broadly understood as knowledge of a specific area that influences ideation towards solutions in this domain. We distinguish between four types of users: those with high trend awareness, high technical skills, high technical innovativeness, and high ethical reflectiveness. We find that users with high technical skills are more likely to produce ideas that are technically feasible. Trend‐aware and technically innovative users produce ideas of greater originality. Ethically reflective users tend to come up with ideas that will have a positive impact on society.     

位置服务社交网络用户行为相似性分析

基于位置的社交网络(LBSN)能够支持用户分享地理位置信息,网站中保存用户访问真实世界地理位置的记录构成用户的行为轨迹,但LBSN用户相似性的分析并没有从用户的地理位置轨迹上加以考虑。为此,提出基于划分层次,在不同的邻域半径下密度聚类的方法,探索基于位置的服务(LBS)平台上用户地理位置上相似性的度量。该方法在不同空间位置比例尺下观察用户访问各个聚类区域的次数,进而利用向量空间模型(VSM)计算用户在各个层级的相似性,最终以不同权重叠加各层级的用户相似性值,得出用户在地理空间行为上的相似性。基于国内某大型位置社交网站真实用户数据的实验结果表明,该方法能有效识别出访问地理位置相似的用户。     

Socialized healthcare service recommendation using deep learning

Socialized recommender system recommends reliable healthcare services for users. Ratings are predicted on the healthcare services by merging recommendations given by users who has social relations with the active users. However, existing works did not consider the influence of distrust between users. They recommend items only based on the trust relations between users. We therefore propose a novel deep learning-based socialized healthcare service recommender model, which recommends healthcare services with recommendations given by recommenders with both trust relations and distrust relations with the active users. The influences of recommenders, considering both the node information and the structure information, are merged via the deep learning model. Experimental results show that the proposed model outperforms the existing works on prediction accuracy and prediction coverage simultaneously, even for cold start users or users with very sparse trust relations. It is also computational less expensive.

     

Psychophysiology of the passive user: Exploring the effect of technological conditions and personality traits

This purpose of this study was to investigate physiological response patterns of passive users versus active users under varying technological conditions. The relationship between user personality traits and physiological responses was also explored. In work systems, different types of users interact with technologies in different ways. Active users may control technologies, while passive users may watch the active user and the technology. While they are both important stakeholders in the system, little empirical research has been conducted to understand the passive users to date. A mixed design experiment was conducted to investigate passive user psychophysiological state, while active and passive users operated a technology under varying technological states (normal, unreliable, and difficult). Physiological measures were collected from passive users while technologies were being operated, these included electrodermal and cardiovascular (heart rate and heart rate variability). Results show that individual active users and passive users have distinct physiological response patterns in heart rate and heart rate variability while using the technology. Exploratory analyses indicated that conscientiousness was positively related to individual active users' task performance; openness, agreeableness, and extraversion were associated with passive users' electrodermal and cardiovascular responses. In addition, social interaction is more influential for passive users' physiological responses, compared to task performing. The effects of active and passive user personality traits on technology interactions are illustrated through distinctive physiological responses.Relevance to industryFindings from this study suggest that to improve passive user experience, systems that include both active and passive users should be designed to facilitate communication and information sharing between users.     

提高边缘吞吐量的软频率复用改进方案研究

对于固定软频率复用算法在小区边缘用户分布不均匀时,无法动态地分配频率资源而造成系统整体频谱资源浪费的问题,提出一种动态软频率复用算法。在此算法中,以边缘用户在相邻小区间的分布为依据,将小区边缘频段进一步划分,将频率资源动态地分配给用户,分布较多边缘用户的小区将会分配到较多的频率资源,而分布较少边缘用户的小区就会分配到较少的资源。通过仿真可知,与固定软频率复用算法相比,动态软频率复用算法在几乎不影响中心用户吞吐量的同时提高了边缘用户的吞吐量。因此,动态软频率复用算法能够在小区边缘用户分布不均匀时,有效解决系统整体频谱资源浪费的问题。     

基于博弈论与区块链融合的◢k◣-匿名位置隐私保护方案

基于移动用户的位置服务中,通常采用位置k-匿名技术保护用户的隐私安全性。然而,用户协作构建k-匿名组中难以保证请求用户和协作用户的诚信合作行为。针对以上问题,首先基于完全信息静态博弈理论分析请求用户和诚信用户的行为策略,计算请求用户的诚信阈值,协作用户根据请求阈值与协同阈值的比较决定是否参与匿名组构建;其次,构建信誉机制将用户的近期表现与收益结合,约束参与匿名组构建的请求用户及协作用户的不诚信行为;最后,使用区块链存储博弈过程和协作用户的位置信息,当发现请求用户和协作用户的不诚信行为时,对不诚信的用户进行信誉值和收益降低的处罚。安全分析表明,该方案能有效保护用户的位置隐私,促进请求用户与协作用户的诚信合作,同时激励更多的人参与匿名组的构建。