Statistical user model supported by R-Tree structure

This paper is about developing a group user model able to predict unknown features (attributes, preferences, or behaviors) of any interlocutor. Specifically, for systems where there are features that cannot be modeled by a domain expert within the human computer interaction. In such cases, statistical models are applied instead of stereotype user models. The time consumption of these models is high, and when a requisite of bounded response time is added most common solution involves summarizing knowledge. Summarization involves deleting knowledge from the knowledge base and probably losing accuracy in the medium-term. This proposal provides all the advantages of statistical user models and avoids knowledge loss by using an R-Tree structure and various search spaces (universes of users) of diverse granularity for solving inferences with enhanced success rates. Along with the formalization and evaluation of the approach, main advantages will be discussed, and a perspective for its future evolution is provided. In addition, this paper provides a framework to evaluate statistical user models and to enable performance comparison among different statistical user models.     

多级安全系统中访问控制新方案

研究了利用密码技术实现多级安全系统中的访问控制的方法。提出了一个新的基于密钥分配的动态访问控制方案。其中的密钥分配方法是基于Rabin公钥体制和中国剩余定理的。在该方案中,系统中每一用户被赋于一个安全权限,具有较高安全权限的用户可以利用自己私有的秘密信息和公共信息导出具有较低安全权限的用户的密钥,而低权限用户则不能导出高权限用户的密钥。这样高权限用户可以读取和存储属于低权限用户的保密信息,而低权限用户则不读取和存储属于高权限用户的保密信息。从而实现了利用密钥分配进行授权的访问控制。而且从系统中添加／删除一用户以及改变用户权限和改变用户密钥都无需变更整个系统。     

The evaluation of user experience of a human walking and a driving simulation in the virtual reality

Virtual reality (VR) has been implemented in various applications such as gaming, e-learning, rehabilitation, etc. Although many studies have been conducted to evaluate the user experiences (UX) of various applications in VR, there are few studies evaluating the UX of VR in a holistic view. Since user experience means holistic feelings caused by attributes like efficiency, effectiveness, pleasure, and attractiveness, it is necessary to evaluate user experience in many respects, including presence, usability, and workload. Therefore, this study aims to evaluate the UX of VR in four various metrics: presence, workload, usability, and flow. In this study, the user experience factor was confirmed through the previous studies comparing visual display terminals (VDT) and head-mounted displays (HMD). In addition, the UX difference between VDT and HMD in two different situations, walking and driving, is analyzed. The data of 26 participants were analyzed and found that there were significant differences in the four studied metrics related to UX. In the driving situation, the usability value was higher in VDT, whereas they were higher in HMD for walking. Comparing the two contexts in HMD, walking was significantly higher in three metrics: presence, usability, and flow. The results show that HMD is better in terms of user experience than VDT, and HMD is more suitable for walking situations than for driving situations. Through this study, in terms of user experience, it is suitable to replace walking tasks with VR when the experiment in a real-world environment is impossible.     

User modeling for flexible inference control and its relevance to decision-making in economics and management

Controlling the order of inference is an important issue for knowledge-based systems in economics and management. Separate from this issue, there is a recent spur on user modeling. In this paper, we establish the connection between these two issues. We investigate the need for flexible control of inference from the perspective of user modelling, and outline the approaches to realize this kind of connection.     

Socio-technical aspects of remote media control for a NG9-1-1 system

9-1-1 emergency calls mostly involve distress situations that cause people to panic while trying to answer questions or follow instructions given by a dispatcher. To obtain precious information with the least user intervention and reduced stress on the user, there is a need for the dispatcher to have a better control and understanding of the condition or situation at the other end. The increasing growth of smartphones embedded with camera, speaker phone, GPS, microphone and various other sensors, extends their usage from merely making calls to life saving gadgets during critical situations. By integrating these sensor rich smartphones and the rapidly growing VoIP technology, we propose a VoIP based Next Generation 9-1-1 (NG9-1-1) system for remote media control. Specifically, we use Session Initiation Protocol (SIP) in the implementation of the system using a mobile and a PC client. The proposed system on the mobile client accounted for less than 25% of CPU utilization even with video transmission. The average network utilization was about 10 and 72 kbps for audio and video, respectively. With these encouraging results, we believe the proposed remote media control system will facilitate information acquisition and decision making in emergency situations.     

Development and evaluation of an ergonomic software package for predicting multiple-task human performance and mental workload in human–machine interface design and evaluation

Predicting human performance and mental workload in multiple task situations at an early stage of system design can save a significant amount of time and cost. However, existing modeling tools either can only predict human performance or require users of tools to learn a new programming language. Queueing Network-Model Human Processor (QN-MHP) is a new cognitive architecture for modeling both human performance and mental workload in multiple tasks. This paper describes the development of a Visual Basic Application in Excel (VBA) software package and an illustrative case study to evaluate its effectiveness. The software package has an easy-to-use user interface for QN-MHP that assists users of the modeling tool to simulate a dual task including definition of the tasks and interfaces by clicking buttons to select options and filling texts in a table, with no need to learn a simulation language. It allows the model user to intuitively observe the information processing state of the model during simulation, and conveniently compare the simulated human performance and mental workload for different designs. The illustrative case study showed that naïve users without prior simulation language programming experience can model human performance and mental workload in a complex multitask situation within 3 min; and this software package can save 71% of modeling time and reduce 30% of modeling errors. Further developments of the VBA software package of QN-MHP are also discussed on how to make it a comprehensive proactive ergonomic design and analysis tool.     

Machine Learning for User Modeling

At first blush, user modeling appears to be a prime candidate for straightforward application of standard machine learning techniques. Observations of the user's behavior can provide training examples that a machine learning system can use to form a model designed to predict future actions. However, user modeling poses a number of challenges for machine learning that have hindered its application in user modeling, including: the need for large data sets; the need for labeled data; concept drift; and computational complexity. This paper examines each of these issues and reviews approaches to resolving them.     

Context relevance assessment and exploitation in mobile recommender systems

In order to generate relevant recommendations, a context-aware recommender system (CARS) not only makes use of user preferences, but also exploits information about the specific contextual situation in which the recommended item will be consumed. For instance, when recommending a holiday destination, a CARS could take into account whether the trip will happen in summer or winter. It is unclear, however, which contextual factors are important and to which degree they influence user ratings. A large amount of data and complex context-aware predictive models must be exploited to understand these relationships. In this paper, we take a new approach for assessing and modeling the relationship between contextual factors and item ratings. Rather than using the traditional approach to data collection, where recommendations are rated with respect to real situations as participants go about their lives as normal, we simulate contextual situations to more easily capture data regarding how the context influences user ratings. To this end, we have designed a methodology whereby users are asked to judge whether a contextual factor (e.g., season) influences the rating given a certain contextual condition (e.g., season is summer). Based on the analyses of these data, we built a context-aware mobile recommender system that utilizes the contextual factors shown to be important. In a subsequent user evaluation, this system was preferred to a similar variant that did not exploit contextual information.     

Numerical uncertainty management in user and student modeling: An overview of systems and issues

A rapidly growing number of user and student modeling systems have employed numerical techniques for uncertainty management. The three major paradigms are those of Bayesian networks, the Dempster-Shafer theory of evidence, and fuzzy logic. In this overview, each of the first three main sections focuses on one of these paradigms. It first introduces the basic concepts by showing how they can be applied to a relatively simple user modeling problem. It then surveys systems that have applied techniques from the paradigm to user or student modeling, characterizing each system within a common framework. The final main section discusses several aspects of the usability of these techniques for user or student modeling, such as their knowledge engineering requirements, their need for computational resources, and the communicability of their results.     

Visualizing complexities: the human limits of air traffic control

Air traffic management is organized into filters in order to prevent tactical controllers from dealing with complex conflicting situations. In this article, we describe an experiment showing that a dynamic conflict display could improve human performance on complex conflict situations. Specifically, we designed a display tool that represents the conflicting portions of aircraft trajectories and the evolution of the conflict zone when the user adds a maneuver to an aircraft. The tool allows the user to dynamically check the potential conflicting zones with the computer mouse before making a maneuver decision. We tested its utility on a population of forty students: twenty air traffic controller (ATC) students at the end of their initial training and twenty engineering students with the same background but no ATC training. They had to solve conflicts involving 2–5 aircraft with a basic display and with the dynamic visualization tool. Results show that in easy situations (2 aircraft), performance is similar with both displays. However, as the complexity of the situations grows (from 3 to 5 aircraft), the dynamic visualization tool enables users to solve the conflicts more efficiently. Using the tool leads to fewer unsolved conflicts and shorter delays. No significant differences are found between the two test groups except for delays: ATC students give maneuvers that generate less delays than engineering students. These results suggest that humans are better able to manage complex situations with the help of our conflict visualization tool.     

Mixed reality participants in smart meeting rooms and smart home environments

Human–computer interaction requires modeling of the user. A user profile typically contains preferences, interests, characteristics, and interaction behavior. However, in its multimodal interaction with a smart environment the user displays characteristics that show how the user, not necessarily consciously, verbally and nonverbally provides the smart environment with useful input and feedback. Especially in ambient intelligence environments we encounter situations where the environment supports interaction between the environment, smart objects (e.g., mobile robots, smart furniture) and human participants in the environment. Therefore it is useful for the profile to contain a physical representation of the user obtained by multi-modal capturing techniques. We discuss the modeling and simulation of interacting participants in a virtual meeting room, we discuss how remote meeting participants can take part in meeting activities and they have some observations on translating research results to smart home environments.     

Designing personal attentive user interfaces in the mobile public safety domain

In the mobile computing environment, there is a need to adapt the information and service provision to the momentary attentive state of the user, operational requirements and usage context. This paper proposes to design personal attentive user interfaces (PAUI) for which the content and style of information presentation is based on models of relevant cognitive, task, context and user aspects. Using the police work environment as the application domain, relevant attributes of these aspects are identified based on literature and domain analyses. We present a user-centered design (UCD) method for the iterative development and validation of the proposed PAUI. Application of this approach provided requirements for (1) adaptation to users’ attentive state, (2) notification, (3) information processing and task switching support and (4) user modeling. We aim at refining and validating the models and requirements through continuing empirical evaluation.     

基于辅助特征的Web服务QoS预测

随着互联网以及Web服务技术的快速发展,相同功能的Web服务数量越来越多.在构建面向服务的应用时,服务质量（QoS）作为Web服务的非功能特性开始被越来越多的用户所重视.为了向用户推荐高质量的服务,首先我们需要对服务质量进行预测.现今有很多关于Web服务QoS预测的工作,这些研究大都关注在建模方法的优化上,忽视了辅助特征对于QoS预测的影响.着重分析辅助特征对于QoS预测的影响,例如服务类别和用户地理位置.为了实现此目标,基于因子分解机（Factorization Machines）设计并构建了一个统一的QoS预测架构,该架构可以灵活、方便地考虑进多个辅助特征.结合服务类别和用户地理位置这两类辅助特征,提出了一种QoS预测方法,并通过在真实数据上的实验证明了我们的方法的优越性.     

Efficient peer-to-peer context awareness data forwarding scheme in emergency situations

Recently, we usually use these words “Edge of Innovation”. It is caused by deployment of smartphone and various hand-held device including wearable devices. In most cases, the devices can easily communicate with other people or devices, and most of modern IT services are the converged services. These are very common phenomenon even in management of the disaster and safety fields. Generally, the emergency situations involve extreme situations such as a horrible congestion, bottleneck, some damaged infrastructure, and so on. Nonetheless, the infrastructure should support communications to the users in these situations. In this case, P2P communications and networking can be one of the best alternatives. In addition, if the P2P communications and networking method which is based on the device location can operate, it will be better solution than others. However, these solutions have been developing now, and the technology level is just a toddler stage, especially measuring indoor location. This is why we proposed the efficient peer-to-peer context awareness data forwarding scheme based on the devices location. The proposed P2P scheme has 2 operation modes. One is the normal mode, the other is the emergency mode. In normal mode, although the proposed P2P scheme is almost same as the existing P2P communication and networking scheme, the proposed P2P scheme is based on the synchronization between each peer when they need to communicate with other peers. In addition, the proposed P2P scheme dynamically assigns a bandwidth to users by the traffic types when the scheme is aware of P2P context. This is reason that it is a purpose to increase user throughput and to guarantee minimum user throughput. On the other hand, the propose P2P scheme will operate not only to find a best path, but also to transfer an emergency message, and the operation mode will automatically change to the emergency mode when the scheme is aware of the emergency situations based on P2P context awareness. Based on the proposed P2P scheme, the user can communicate with other people, and relay the message to outside in the emergency mode. To prove the excellence of proposed P2P scheme, we verified that the proposed P2P scheme outperforms than legacy scheme in various aspects, and we show these simulation results.     

基于人物角色的用户建模研究

在以用户为中心的软件设计中,需要通过对用户建模来明确和分析用户,了解用户的特定需求.介绍用户建模的相关概念,阐述基于人物角色的用户建模原理、详细介绍基于人物角色的用户建模过程,指出人物角色在以用户为中心的软件设计过程中的应用.     

Interval Finite Elements as a Basis for Generalized Models of Uncertainty in Engineering Mechanics

Latest scientific and engineering advances have started to recognize the need for defining multiple types of uncertainty. Probabilistic modeling cannot handle situations with incomplete or little information on which to evaluate a probability, or when that information is nonspecific, ambiguous, or conflicting [12], [47], [50]. Many interval-based uncertainty models have been developed to treat such situations. This paper presents an interval approach for the treatment of parameter uncertainty for linear static structural mechanics problems. Uncertain parameters are introduced in the form of unknown but bounded quantities (intervals). Interval analysis is applied to the Finite Element Method (FEM) to analyze the system response due to uncertain stiffness and loading. To avoid overestimation, the formulation is based on an element-by-element (EBE) technique. Element matrices are formulated, based on the physics of materials, and the Lagrange multiplier method is applied to impose the necessary constraints for compatibility and equilibrium. Earlier EBE formulation provided sharp bounds only on displacements [32]. Based on the developed formulation, the bounds on the system’s displacements and element forces are obtained simultaneously and have the same level of accuracy. Very sharp enclosures for the exact system responses are obtained. A number of numerical examples are introduced, and scalability is illustrated.     

Inferring user interests in microblogging social networks: a survey

With the growing popularity of microblogging services such as Twitter in recent years, an increasing number of users are using these services in their daily lives. The huge volume of information generated by users raises new opportunities in various applications and areas. Inferring user interests plays a significant role in providing personalized recommendations on microblogging services, and also on third-party applications providing social logins via these services, especially in cold-start situations. In this survey, we review user modeling strategies with respect to inferring user interests from previous studies. To this end, we focus on four dimensions of inferring user interest profiles: (1) data collection, (2) representation of user interest profiles, (3) construction and enhancement of user interest profiles, and (4) the evaluation of the constructed profiles. Through this survey, we aim to provide an overview of state-of-the-art user modeling strategies for inferring user interest profiles on microblogging social networks with respect to the four dimensions. For each dimension, we review and summarize previous studies based on specified criteria. Finally, we discuss some challenges and opportunities for future work in this research domain.     

Modeling default reasoning using defaults

User modeling research can benefit from formal automated reasoning tools. However existing formal tools may need to be modified to suit the needs of user modeling. Theorist is a simple framework for default reasoning. It can be used as a tool for building and maintaining a user model, and as a model of a user's default reasoning. To apply Theorist to both tasks, we develop Nested Theorist (NT), a simple tool based on Theorist that allows default reasoning on arbitrarily-many levels. We extend NT in two ways: we allow prioritized defaults, and we allow reasoning about agents with limited reasoning capabilities. This paper focusses on applications, and uses wide-ranging examples from user-modeling literature to illustrate the usefulness of the tools presented.     

An Empirical Investigation Into Text Input Methods for Interactive Digital Television Applications

Nowadays there is a huge market emerging in the interactive digital TV realm. In this context, we need new and effective methods of user interaction, as the main interaction device is still the classical remote control. Remote controls are especially problematic when it comes to writing text, something needed in most applications. Thus, we have carried out an empirical investigation to find effective methods of text entry with remote controls. We analyze several methods by performing experiments based on a methodology in which a heterogeneous set of real users carries out several sequential tasks in an incremental process. We analyze entry speeds, error rates, learning profiles, and subjective impressions, taking into account the particular characteristics of the users. Our results show, for instance, that Multitap is a good method for simple texts. It is between 12% and 34% faster than the fastest virtual keyboard, depending on the age of the user. Nevertheless, when complex texts need to be written, virtual keyboards present the same or even better writing speeds (QWERTY is 13% faster) and with significant lower error rates (Multitap is 347% worse than QWERTY). We consider that our results are very interesting for researchers, designers of TV applications, and hardware vendors.