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.     

A Research Overview of Mobile Projected User Interfaces

In the last few years, the miniaturization of projectors has gained certain momentum. Today, projectors are available that can easily fit into the palm of a hand. Moreover, these devices are even being integrated into mobile phones. Mobile projectors allow users to project digital imagery into physical space virtually anywhere and anytime. The unique characteristics of small-scale projectors open up interesting opportunities for mobile user interface research. This article provides a comprehensive overview of research on mobile projected user interfaces according to three pertinent research directions: (i) nomadic, (ii) handheld, and (iii) tangible projection interfaces. Furthermore, the article outlines future research challenges and indicates trends in neighboring research fields that might foster innovation in the mobile projected user interfaces domain.     

Scheduling and development support in the Scavenger cyber foraging system

Cyber foraging is a pervasive computing technique where small mobile devices offload resource intensive tasks to stronger computing machinery in the vicinity.One of the main challenges within cyber foraging is that it is very difficult to develop cyber foraging enabled applications. An application using cyber foraging is working with mobile, distributed and, possibly, parallel computing; fields within computer science notoriously hard for programmers to grasp.This paper presents Scavenger—a cyber foraging system supporting easy development of mobile cyber foraging applications, while still delivering efficient, mobile use of remote computing resources through the use of a custom built mobile code execution environment and a new adaptive, dual-profiling scheduler.     

A two-stage optimization model for road-rail transshipment procurement and truckload synergetic routing

Road-rail multimodal transport has increasing importance in modern cargo transport. This paper presents a novel two-stage model for optimizing auction game strategy and route in container road-rail transshipment. Two critical questions are investigated in the two stages, respectively: (a) In the first stage, what is the best pricing strategy for either large-scale or small-scale carriers in a stochastic bid generation problem? (b) In the second stage, what are the best routes of the container trucks to minimize the total expected profit of the carrier according to its pricing strategy? To deal with the first stage problem, this paper presents an evolutionary game model to capture the long-term strategic behaviors of the carriers and to optimize the choice between historical pricing strategy and combinatorial strategy for each carrier. The equilibrium points of the evolutionary game model and Evolutionary Stability Strategy are derived and discussed. In the second stage, a fleet management problem is presented to determine the routing of the trucks over the whole temporal horizon regarding the transportation price. An A*-based search heuristic is proposed to find the satisfying solution to this difficult problem. To show the efficiency and effectiveness of the proposed method, numerical studies are conducted. The results show that (a) The optimized pricing strategy is impacted by the expected profit rate, the correlation coefficient between different transport ation enterprise carriers, and the probability of winning bids. The equilibrium point of the ordering bidding system depends on whether these critical input parameters exceed a threshold. (b) In the fleet management and route optimization stage, the small-scale carrier has gained about 11.42% more profits than the large-scale carrier.     

Effects of the design of mobile security notifications and mobile app usability on users’ security perceptions and continued use intention

The explosive global adoption of mobile applications (i.e., apps) has been fraught with security and privacy issues. App users typically have a poor understanding of information security; worse, they routinely ignore security notifications designed to increase security on apps. By considering both mobile app interface usability and mobile security notification (MSN) design, we investigate how security perceptions of apps are formed and how these perceptions influence users’ intentions to continue using apps. Accordingly, we designed and conducted a set of controlled survey experiments with 317 participants in different MSN interface scenarios by manipulating the types of MSN interfaces (i.e., high vs. low disruption), the context (hedonic vs. utilitarian scenarios), and the degree of MSN intrusiveness (high vs. low intrusiveness). We found that both app interface usability and the design of MSNs significantly impacted users’ perceived security, which, in turn, has a positive influence on users’ intention to continue using the app. In addition, we identified an important conundrum: disruptive MSNs—a common approach to delivering MSNs—irritate users and negatively influence their perceptions of app security. Thus, our results directly challenge current practice. If these results hold, current practice should shift away from MSNs that interrupt task performance.     

A new paradigm of cloud-based predictive maintenance for intelligent manufacturing

Advances in cloud computing reshape the manufacturing industry into dynamically scalable, on-demand service oriented, and highly distributed cost-efficient business model. However it also poses challenges such as reliability, availability, adaptability, and safety on machines and processes across spatial boundaries. To address these challenges, this paper investigates a cloud-based paradigm of predictive maintenance based on mobile agent to enable timely information acquisition, sharing and utilization for improved accuracy and reliability in fault diagnosis, remaining service life prediction, and maintenance scheduling. In the new paradigm, a low-cost cloud sensing and computing node is firstly developed with embedded Linux operating system, mobile agent middleware, and open source numerical libraries. Information sharing and interaction is achieved by mobile agent to distribute the analysis algorithms to cloud sensing and computing node to locally process data and share analysis results. Comparing to the commonly used client–server paradigm, the mobile agent approach enhances the system flexibility and adaptability, reduces raw data transmission, and instantaneously responds to dynamic changes of operations and tasks. Finally, the presented cloud-based paradigm of predictive maintenance is validated on a motor tested system.     

Hybrid-augmented intelligence in predictive maintenance with digital intelligent assistants

Industrial maintenance strategies increasingly rely on artificial intelligence to predict asset conditions and prescribe maintenance actions. The related maintenance software and human maintenance actors can form a hybrid-augmented intelligence system where each side benefits from and enhances the other side's intelligence. This system requires optimized human-machine interfaces to help users express their knowledge and retrieve information from difficult-to-use software. Therefore, this article proposes a novel approach for maintenance experts and operators to interact with a predictive maintenance system through a digital intelligent assistant. This assistant is artificial intelligence (AI) that could help its users interact with the system via natural language and collect their feedback about the success of maintenance interventions. Implementing hybrid-augmented intelligence in a predictive maintenance system faces several technical, social, economic, organizational, and legal challenges. The benefits, limitations, and risks of hybrid-augmented intelligence must be clear to all employees to advocate its use. AI-focused change management and employee training could be techniques to address these challenges. The success of the proposed approach also relies on the continuous improvement of natural language understanding. Such a process will need conversation-driven development where actual interactions with the assistant provide accurate training data for language and dialog models. Future research has to be interdisciplinary and may cover the integration of explainable AI, suitable AI laws, operationalized trustworthy AI, efficient design for human-computer interaction, and natural language processing adapted to predictive maintenance.     

Human interaction with IoT-based smart environments

This paper describes concepts, design, implementation, and performance evaluation of a 3D-based user interface for accessing IoT-based Smart Environments (IoT-SE). The generic interaction model of the described work addresses some major challenges of Human-IoT-SE-Interaction such as cognitive overload associated with manual device selection in complex IoT-SE, loss of user control, missing system image or over-automation. To address these challenges we propose a 3D-based mobile interface for mixed-initiative interaction in IoT-SE. The 3D visualization and 3D UI, acting as the central feature of the system, create a logical link between physical devices and their virtual representation on the end user’s mobile devices. By so doing, the user can easily identify a device within the environment based on its position, orientation, and form, and access the identified devices through the 3D interface for direct manipulation within the scene. This overcomes the problem of manual device selection. In addition, the 3D visualization provides a system image for the IoT-SE, which supports users in understanding the ambience and things going on in it. Furthermore, the mobile interface allows users to control the amount and the way the IoT-SE automates the environment. For example, users can stop or postpone system triggered automatic actions, if they don’t like or want them. Users also can remove a rule forever. By so doing, users can delete smart behaviors of their IoT-SE. This helps to overcome the automation challenges. In this paper, we present the design, implementation and evaluation of the proposed interaction system. We chose smart meeting rooms as the context for prototyping and evaluating our interaction concepts. However, the presented concepts and methods are generic and could be adapted to similar environments such as smart homes. We conducted a subjective usability evaluation (ISO-Norm 9241/110) with 16 users. All in one the study results indicate that the proposed 3D-User Interface achieved a good high score according to the ISO-Norm scores.     

Predicting the passenger demand on bus services for mobile users

Public transport, especially the bus transport, can reduce the private car usage and fuel consumption, and alleviate traffic congestion. However, when traveling in buses, the travelers not only care about the waiting time, but also care about the crowdedness in the bus itself. Excessively overcrowded bus may drive away the anxious travelers and make them reluctant to take buses. So accurate, real-time and reliable passenger demand prediction becomes necessary, which can help determine the bus headway and help reduce the waiting time of passengers. Based on a large database from a real bus system, this paper aims to present a passenger demand prediction system for mobile users. The system includes a server-side bus information data stream processing and mining program and a client-side mobile application for Android smartphones. The server program continuously monitors for each bus stop the number of passengers waiting at the bus stop, the number of passengers that will pass the bus stop, as well as the traffic conditions in the area around the stop. It delivers real time bus and traffic information to mobile users via restful web services. The client-side location-based mobile application consumes these services to help mobile users make informed transportation choices. For example the availability of buses might be a deterrent when they are too crowded. However, there are three major challenges for predicting the passenger demands on bus services: inhomogeneous, seasonal bursty periods and periodicities. To overcome the challenges, we propose three predictive models and further take a data stream ensemble framework to predict the number of passengers. We develop a prototype system with different types of Android based mobile phones and comprehensively experiment over a 22-week period. The evaluation results suggest that the proposed system achieves outstanding prediction accuracy among 86,411 passenger demands on bus services, more than 78% of them are accurately forecasted.     

Ontology-Based User Modeling in an Augmented Audio Reality System for Museums

Ubiquitous computing is a challenging area that allows us to further our understanding and techniques of context-aware and adaptive systems. Among the challenges is the general problem of capturing the larger context in interaction from the perspective of user modeling and human–computer interaction (HCI). The imperative to address this issue is great considering the emergence of ubiquitous and mobile computing environments. This paper provides an account of our addressing the specific problem of supporting functionality as well as the experience design issues related to museum visits through user modeling in combination with an audio augmented reality and tangible user interface system. This paper details our deployment and evaluation of ec(h)o – an augmented audio reality system for museums. We explore the possibility of supporting a context-aware adaptive system by linking environment, interaction objects and users at an abstract semantic level instead of at the content level. From the user modeling perspective ec(h)o is a knowledge-based recommender system. In this paper we present our findings from user testing and how our approach works well with an audio and tangible user interface within a ubiquitous computing system. We conclude by showing where further research is needed.     

Modelling Reliability-adaptive Multi-system Operation

This contribution discusses the concept of Reliability-Adaptive Systems (RAS) to multi-system operation. A fleet of independently operating systems and a single maintenance unit are considered. It is the objective in this paper to increase overall performance or workload respectively by avoiding delay due to busy maintenance units. This is achieved by concerted and coordinated derating of individual system performance, which increases reliability. Quantification is carried out by way of a convolution-based approach. The approach is tailored to fleets of ships, aeroplanes, spacecraft, and vehicles (trains, trains, buses, cars, trucks, etc.) - Finally, the effectiveness of derating is validated using different criteria. The RAS concept makes sense if average system output loss due to lowered performance level (yielding longer time to failure) is smaller than average loss due to waiting for maintenance in a non-adaptive case.     

Experiences of usability evaluation of the IMAGINE speech-based interaction system

IMAGINE is a recently completed multi-partner, multi-national European 5th Framework project aimed at developing systems for interaction with e-business applications through a multilingual natural language interface from mobile and other devices. The vision embodied in IMAGINE is universal access to electronic services by anyone (including disabled users) at any time. Since this long-term vision is not achievable with current capabilities in speech and natural language technologies, we have concentrated initially on a monolingual (English) application, namely a speech-enabled interface to an Online Shop. This paper is primarily concerned with usability evaluation of a prototype system for this application. The principal finding is that considerable challenges and barriers remain against the successful deployment of speech systems in real applications. The problems are not just technical, but systemic (to do with the nature of speech) and are exacerbated by lack of shared background and difficulties of communication between different professionals involved in the design, commissioning and maintenance of speech systems. Formerly Royal National Institute of the Blind.     

基于GIS的共享单车站点最优选择查询系统设计

随着智能手机的快速发展,将自行车系统加入到智能手机中就可以加快自行车的发展,提高自行车的利用率。在此基础上,利用地理信息系统更够开发出功能非常强大的软件。因为移动GIS是目前的发展趋势,在主流的移动操作系统上开发移动GIS能使软件更容易的让用户接受并使用,借助移动操作系统的界面友好性,使应用更加容易使用。本系统利用了ArcGIS for Android开发了自行车租赁系统的一个部分,自行车的站点查询。同时利用面向对象的程序设计方法进行开发移动GIS,系统具有良好的用户界面与灵活性,能够满足用户的需求。     

一种移动开发中间件的设计和实现

移动开发正成为一个迅速发展的领域,然而由于移动环境的种种限制,为开发移动应用带来巨大挑战。中间件是一种行之有效的处理分布式异构平台的技术,可用于解决移动开发中碰到的很多问题。在J2EE架构之上提出了一种移动应用系统框架,并基于这种框架在传统中间件的基础上设计和实现了一种移动开发中间件。这种中间件能够屏蔽移动设备和运行平台的多样性,并能够处理移动网络的延迟和出错,使得移动系统的开发与在普通网络环境上一样便捷,从而达到提高移动应用开发效率的目的。     

一个移动应用个性化集成框架的研究及其在Android平台的实现

随着互联网和智能手机的日益普及,移动应用数量呈现爆炸式增长,海量的移动应用既是机遇也是挑战。从开发者角度看,基于大量的已有移动应用快捷构造新的移动应用成为了可能,但当前大部分的开发工具对移动应用集成的支持仅停留在应用编程接口和底层运行机制上,尚未出现更高层次的面向执行流程的集成支持;从用户角度看,从众多移动应用中选择符合自己个性化需求的应用成为了可能,但目前大量的移动应用推荐系统集中在单个应用的个性化推荐问题上,未见面向用户个性化需求的移动应用执行序列推荐方法。为此,提出一个移动应用个性化集成框架,主要包括:1)定义了一套意图流程描述执行语言,以便开发者从更为自然的执行流程角度完成新移动应用的构造;2)给出了一个移动应用序列偏好度预测算法,用于解决移动应用执行序列的个性化推荐问题。在当前典型的移动应用平台Android上,实现了相应的移动应用个性化集成开发工具和运行支撑机制,并通过实例初步验证了上述方法的合理性。     

Determinants of Mobile Wallet Intentions to Use: The Mental Cost Perspective

Mobile wallet has become the predominant form of electronic commerce in many countries, and India is no exception. It is imperative to understand the behavior of users of mobile wallets as it can help service providers to attract new users and retain their existing ones. For predicting intentions to use from a mental cost perspective, this empirical study focuses on evaluating different competing models using relevant, vital constructs rooted in theories of Diffusion of Innovation, Planned Behavior, and Technology Acceptance Model and Trust. Results point to the supremacy of the Perceived Behavioral Control construct over other constructs in predicting the intentions, to use mobile wallets. Among the competing models, the best predictive model explained 50.81% of the changes in intentions to use.     

A survey of models and algorithms for winter road maintenance. Part I: system design for spreading and plowing

Winter road maintenance operations involve a host of decision-making problems at the strategic, tactical, operational, and real-time levels. Those operations include spreading of chemicals and abrasives, snow plowing, loading snow into trucks, and hauling snow to disposal sites. As the first of a four-part survey, this paper reviews optimization models and solution algorithms for the design of winter road maintenance systems for spreading and plowing operations. System design problems for snow disposal operations are discussed in the second paper. The two last parts of the survey mainly address vehicle routing, depot location, and fleet sizing models for winter road maintenance. The present paper surveys research on determining the level of service policy and partitioning a region or road network into sectors for spreading and plowing operations. We also describe the applied setting in which these problems arise.     

Privacy‐preserving targeted mobile advertising: requirements,design and a prototype implementation

With the continued proliferation of mobile devices, the collection of information associated with such devices and their users—such as location, installed applications and cookies associated with built‐in browsers—has become increasingly straightforward. By analysing such information, organisations are often able to deliver more relevant and better focused advertisements. Of course, such targeted mobile advertising gives rise to a number of concerns, with privacy‐related concerns being prominent. In this paper, we discuss the necessary balance that needs to be struck between privacy and utility in this emerging area and propose privacy‐preserving targeted mobile advertising as a solution that tries to achieve that balance. Our aim is to develop a solution that can be deployed by users but is also palatable to businesses that operate in this space. This paper focuses on the requirements and design of privacy‐preserving targeted mobile advertising and also describes an initial prototype. We also discuss how more detailed technical aspects and a complete evaluation will underpin our future work in this area. Copyright © 2016 John Wiley & Sons, Ltd.     

Intemal correction of dead-reckoning errors with a dual-drive compliant linkage mobil robot

This paper presents internal position error correction (IPEC)—a new method for accurate and reliable dead-reckoning with mobile robots. The IPEC method has been implemented on our recently developed multi-degree-of-freedom (MDOF) mobile platform, a vehicle in which two differential-drive mobile robots (called trucks) are physically connected through a compliant linkage. In addition to its four wheel encoders, the MDOF platform has one linear and two rotary internal encoders, which allow measurement of the relative distance and bearing between the two trucks. During operation, both trucks perform conventional dead-reckoning with their wheel encoders. But, in addition, the IPEC method uses information from the internal encoders to detect and correct dead-reckoning errors as soon as they occur. Our system, called compliant linkage autonomous platform with position error recovery (CLAPPER), requires neither external references (such as navigation beacons, artificial landmarks, known floorplans, or satellite signals), nor inertial navigation aids (such as accelerometers or gyros). Nonetheless, the experimental results included in this article show one to two orders of magnitude better positioning accuracy than systems based on conventional dead-reckoning. The CLAPPER corrects not only systematic errors, such as different wheel diameters, but also non-systematic errors, such as those caused by floor roughness, bumps, or cracks in the floor. These features are made possible by exploiting the new growth-rate concept for dead-reckoning errors that is introduced in this article for the first time. The growth-rate concept distinguishes between certain dead-reckoning errors that develop slowly and other dead-reckoning errors that develop quickly. Based on this concept, truck A frequently measures a property with slow-growing error characteristics on reference truck B (thus admitting a small error) to detect a fast-growing error on truck A (thus correcting a large error), and vice versa. © 1995 John Wiley & Sons, Inc.