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PurposeTo provide better services to customers, especially immediate responses and 24/7 availability, businesses are implementing text-based automated conversational agents, i.e. chatbots on their social platforms and websites. Chatbots are required to not only provide customers with necessary consultancy and guidance but also communicate friendly and socially. Based on the cognitive fit theory, this study attempts to examine the role of chatbot as a decision aid and how the match between information presentation in forms of decisional guidance and communication style and the shopping task influences consumers' perceived cognitive fit and decision performance outcomes.Design/methodology/approachA 2 x 2 x 2 between subject online experiment was conducted to identify which kind of decisional guidance (suggestive and informative guidance) and communication style (task-oriented vs social-oriented style) are the most appropriate for each type of shopping task (searching vs browsing task).FindingsThe findings show that when customers interact with chatbots, they will perceive higher cognitive fit if the chatbots provide them with suggestive guidance and communicate in a friendly style especially when they perform a searching task.Originality/valueThis study is the first attempt to understand the role of chatbots as a decision aid to customers using the communicative language. This study also tries to explore the cognitive fit theory in a novel way, and we propose the information presentation in forms of communicative language rather than matrices, tables and graphs.

This paper proposes an end-to-end deep learning framework, termed as motion-aid feature calibration network (MFCN), for video object detection. The key idea is to leverage on the temporal coherence of video features while considering their motion patterns as captured by optical flow. To boost detection accuracy, the framework aggregates the calibrated features both at pixel and instance levels across frames to achieve improved robustness despite appearance variations. The aggregation and calibration are efficiently and adaptively conducted based on an integrated optical flow network. Meanwhile, the entire architecture of the proposed method is end-to-end, thus significantly improving its training and inference efficiency when compared to multi-stage methods for video object detection. Evaluations on KITTI and ImageNet VID indicate that MFCN can improve the results of a strong still-image detector by 11.2% and 7.31% respectively. MFCN also outperforms other competitive video object detectors and achieves a better trade-off between accuracy and runtime speed, demonstrating its potential for use in autonomous driving systems.

PurposeThis study aims at investigating the effects of two-way review system and how reach and richness of information influence the perceptions of risks and benefits among service providers and their intention to continue sharing their property on sharing economy.Design/methodology/approachTo generate the variance, a 2 × 2 × 2 full factorial experiment was conducted to collect data. The research model was then tested using the structural equation model technique.FindingsThe study finds that reach of information predicts the social and economic benefits among service providers, while richness of information negatively relates to perceived informational privacy risks, which, in turn, significantly influence the decision of the service providers to continue sharing. The results also suggest that the existence of the two-way review system weakens the effects of reach on perceived social benefits and of richness on perceived informational privacy risks.Originality/valueThe present study investigates the two-way review system as the intervention of platforms to protect the service providers. Also, the emphasis is on the service providers rather than on consumers on sharing economy platforms to investigate their behavioral intention as customers on such platforms.

Periodical time series data can reveal temporal patterns as well as anomalies. Although these patterns appear in different ranges with different measurements, the variables in a dataset can be associated with and affect each other. When the size of datasets becomes large, monitoring and analyzing these data become challenging. We propose a visual analytics framework that is capable of transforming a large number of multivariate time serial data into manageable visual representations that enable analysts to identify and monitor anomalies and trends. After sorting the data in the temporal and categorical directions, we extract the temporal possibility range patterns and anomalies from each variable. Associated variables typically include similar anomalies. Therefore, we employ a hierarchical clustering algorithm to group the variables with similar anomaly appearances. Through our interactive visualization toolset TreeRoses, we find that possibility ranges, anomaly, and its summary, and hierarchical association is perceptible to different degrees. We apply our method to a real-world periodical time series dataset to showcase how our framework effectively monitors anomalies in meteorological data.

Speech interfaces have become an increasingly popular input method for smartphone-based virtual assistants, smart speakers, and Internet of Things (IoT) devices. While they facilitate rapid and natural interaction in the form of voice commands, current speech interfaces lack natural methods for command correction. We present ScratchThat, a method for supporting command-agnostic speech repair in voice-driven assistants, suitable for enabling corrective functionality within third-party commands. Unlike existing speech repair methods, ScratchThat is able to automatically infer query parameters and intelligently select entities in a correction clause for editing. We conducted three evaluations to (1) elicit natural forms of speech repair in voice commands, (2) compare the interaction speed and NASA TLX score of the system to existing voice-based correction methods, and (3) assess the accuracy of the ScratchThat algorithm. Our results show that (1) speech repair for voice commands differ from previous models for conversational speech repair, (2) methods for command correction based on speech repair are significantly faster than other voice-based methods, and (3) the ScratchThat algorithm facilitates accurate command repair as rated by humans (77% accuracy) and machines (0.94 BLEU score). Finally, we present several ScratchThat use cases, which collectively demonstrate its utility across many applications.

We present our CareerVis system, an interactive visualization tool to aid career education for high school and freshman college students. In additional to its practical use, we believe our design approach has potential to inspire the design community to develop simple visualizations that convey complex information to novice users.

This article investigates the factors affecting the success of central bank information systems (IS) in Mongolia. Drawing from the DeLone and McLean (2003) IS success models and Seddon and Kiew's (1997) path model, the factors that could potentially affect the success of the external and the internal IS of the central bank of Mongolia were empirically investigated. The data analysis was conducted using a quantitative method for the external IS and a mixed method for the internal IS. This article contributes to the academic literature by integrating DeLone and McLean's (2003) IS success model with Seddon and Kiew's (1997) path model and by validating the two aforementioned models within the context of central bank information systems in a developing country. This article has also important practical contributions, particularly for the central bank of Mongolia's authorities. The results, discussions, and implications of this study are elaborated in the paper.

Purpose Modern Web browsers all provide a history function that allows users to see a list of URLs they have visited in chronological order. The history log contains rich information but is seldom used because of the tedious nature of scrolling through long lists. This paper aims to propose a new way to improve users’ Web browsing experience by analyzing, clustering and visualizing their browsing history. Design/methodology/approach The authors developed a system called Personal Web Library to help users develop awareness of and understand their Web browsing patterns, identify their topics of interest and retrieve previously visited Web pages more easily. Findings User testing showed that this system is usable and attractive. It found that users can easily see patterns and trends at different time granularities, recall pages from the past and understand the local context of a browsing session. Its flexibility provides users with much more information than the traditional history function in modern Web browsers. Participants in the study gained an improved awareness of their Web browsing patterns. Participants mentioned that they were willing to improve their time management after viewing their browsing patterns. Practical implications As more and more daily activities rely on the internet and Web browsers, browsing data captures a large part of users’ lives. Providing users with interactive visualizations of their browsing history can facilitate personal information management, time management and other meta-level activities. Originality/value This paper aims to help users gain insights into and improve their Web browsing experience, the authors hope that the work they conducted can spur more research contributions in this underdeveloped yet important area.

Little is known about the effectiveness of information strategies on energy conservation in developing countries. In this study, we conduct a field experiment in an apartment complex in India to test how information about electricity usage impacts the electricity consumption of urban middle class households. Our results, based on fifteen-minute electricity readings over an academic year, show that non-monetary messages that framed electricity consumption in terms of environmental and health impacts were more effective than messages emphasizing the monetary savings of reducing electricity consumption. Households in the environmental/health group accessed the online energy-monitoring dashboard more frequently and reduced their electricity usage by 18.4% relative to the control group. Households in the monetary group did not significantly alter their usage. These results about revealed preferences are contrasted with stated preferences disclosed in a survey of urban Indians who describe money, not health, as the main motivation for energy conservation. Our findings have important implications for the development non-monetary strategies for energy conservation in developing countries.

The development of in vitro artificial small intestines that realistically mimic in vivo systems will enable vast improvement of our understanding of the human gut and its impact on human health. Synthetic in vitro models can control specific parameters, including (but not limited to) cell types, fluid flow, nutrient profiles and gaseous exchange. They are also “open” systems, enabling access to chemical and physiological information. In this work, we demonstrate the importance of gut surface topography and fluid flow dynamics which are shown to impact epithelial cell growth, proliferation and intestinal cell function. We have constructed a small intestinal bioreactor using 3-D printing and polymeric scaffolds that mimic the 3-D topography of the intestine and its fluid flow. Our results indicate that TEER measurements, which are typically high in static 2-D Transwell apparatuses, is lower in the presence of liquid sheer and 3-D topography compared to a flat scaffold and static conditions. There was also increased cell proliferation and discovered localized regions of elevated apoptosis, specifically at the tips of the villi, where there is highest sheer. Similarly, glucose was actively transported (as opposed to passive) and at higher rates under flow.

This study builds on prior research that examines the IT-coordination costs and firm size relationships using the transaction cost economics perspective. Specifically, this study aims to answer the following research question: Does firm’s industry type—information product industries (IPI) versus physical product industries (PPI) moderately affects the relationships between IT spending, coordination costs, and firm size? To address this research question, this study uses firm-level data from the Information Week and Compustat dataset in the United States, from 2011 to 2013. Further, this study employs the PLS-multigroup analysis (MGA) for both IPI and PPI firms. The overall PLS-MGA path analysis results show that there is a significant difference on the IT impact between the IPI and PPI firms. Indeed, firms in IPI and PPI can utilize the presence of IT pertaining to different information and physical processing activities at large.

Visual clutter is a common challenge when visualizing large rank time series data. WikiTopReader, a reader of Wikipedia page rank, lets users explore connections among top-viewed pages by connecting page-rank behaviors with page-link relations. Such a combination enhances the unweighted Wikipedia page-link network and focuses attention on the page of interest. A set of user evaluations shows that the system effectively represents evolving ranking patterns and page-wise correlation.

The multidimensional nature of spatial data poses a challenge for visualization. In this paper, we introduce Phoenixmap , a simple abstract visualization method to address the issue of visualizing multiple spatial distributions at once. The Phoenixmap approach starts by identifying the enclosed outline of the point collection, then assigns different widths to outline segments according to the segments’ corresponding inside regions. Thus, one 2D distribution is represented as an outline with varied thicknesses. Phoenixmap is capable of overlaying multiple outlines and comparing them across categories of objects in a 2D space. We chose heatmap as a benchmark spatial visualization method and conducted user studies to compare performances among Phoenixmap , heatmap , and dot distribution map . Based on the analysis and participant feedback, we demonstrate that Phoenixmap 1) allows users to perceive and compare spatial distribution data efficiently; 2) frees up graphics space with a concise form that can provide visualization design possibilities like overlapping; and 3) provides a good quantitative perceptual estimating capability given the proper legends. Finally, we discuss several possible applications of Phoenixmap and present one visualization of multiple species of birds’ active regions in a nature preserve.

We present an immersive virtual reality training system cryoVR with passive haptic feedback for training biological scientists preparing bio-sample for Cryo-Electron Microscopy (CryoEM). CryoEM requires the user to conduct careful operations on expensive delicate equipment. To minimize the risk and interruption of crucial research work, we tried to mimic the real lab using VR to let trainer practice in a virtual environment. We used 3D printed objects to provide passive haptic feedback in order to achieve a more realistic training experience. Participants are able to interact with the equipment in the virtual environment by moving or touching physical models. We developed all the necessary operations with haptic feedback, including moving, clicking, pouring, rotating, polling and pushing. By following instructions provided by our virtual reality simulator and interacting with physical objects, trainees will learn how to operate CryoEM with low cost and risk. By developing our training system, we explore the benefits, limitations and precautions of embedding haptic feedback to scientific VR training.

The primary objective of this study is to examine the influence of information technology (IT) on organizational coordination costs using the theoretical lens of transaction cost economics. In doing so, the study addresses the following research questions: Does IT matter? How and why does IT matter to firms? How does coordination cost mediate the relationship between IT spending and firm productivity, and how does it influence IT spending and firm size when considering the information product industries (IPI) and the physical product industries (PPI)? To address these research questions, we use IT spending, coordination costs, firm size, and firm productivity with firm-level data, using Information Week and the Compustat data set in the United States, from 2011 to 2013. A SmartPLS path analysis was used to test the research hypotheses. The results show that use of the firm’s IT spending decreases coordination costs. Likewise, the results show that IT spending also decreases firm size. On the other...

The computer-aided design process is in a complicated non-linear structure involving selections from a pool of configurations with optimized parameters. In order to understand and improve this decision-making process, this paper conducted a user study on students and expert professionals with more than three years of computer-aided design experience. The study revealed the common design problems and challenges faced by CAD designers. The findings also showed that the design approaches students and expert professionals used were different. Additionally, we found that computer-aided designers expect the system to be able to understand vast quantities of multivariate data, control high-quality products for low costs, manage the knowledge personalization and codification within the company, as well as prevent the design mistakes at the design stages. Our findings may lead to the future development of new approaches to improve the computer-aided design process and close up the gap between student and expert professionals in computer-aided design. This paper provides initial support for this future approach.

We extend the interaction space of low-cost mobile virtual reality (VR) by introducing bidirectional scrolling and discrete selection using magnetic sensing. Our design uses the original Google Cardboard v1 input components, modifying only the cardboard mounted on the side. Users slide the magnetized washer around a circular track on the outer layer, which drags a magnet on the inner layer across asymmetric patterned ridges. The phone's magnetometer detects the position of the magnet as it moves around the track and slots into each ridge, emulating a click wheel. The phone's accelerometer is used to recognize center button taps. We compare our system against the current best practice (gaze) with 12 participants across four VR navigation and selection tasks. Finally, we demonstrate our system robustly handles continuous input, despite some minor deterioration of the cardboard, using a motorized rig over an 8-hour period.

Social data from city level provides unprecedented opportunities to identify urban attributes from various angles. Citizens are likely to evaluate the quality of the neighborhood and make important decisions by their perceptions and the feedback from the environment. In this paper, we studied the correlation between the neighborhood's environment with their properties values and land values. It is profitable to train the algorithm by parallel deep convolutional neural networks on the visual urban scenes data associated with quantitative non-visual urban characteristics in the same views. The result of our approach defines a scenarized profile from building-level details to city-level traits. The main contribution of this work is providing a unique and more accurate perspective to urban valuation estimations, by integrating the scattered sources of pieces of information and implanting into the available images. This urban evaluation approach will be more human-centered, which can be extended to help urban planners and citizens to explore the significant impacts on city decision optimization or spatial economics-related issues like decreasing the cost of properties assessment.

In the face of increased cyber risks, we present our iterative design process and the resulting principles of SpringRain, an information visualization (infoVis) display design concept for large screens in network control rooms (NOCs). It aims to raise team situation awareness by visualizing large-scale multidimensional computer network data sets as a live “rainfall.” We used aesthetic principles and theories of perception to prototype this ambient, yet data-dense, visualization. By applying multiple data dimensions to different properties of a line segment, such as length, motion, and color, the two-dimensional visualization offers analytical affordances (i.e., graphic qualities that make it clear how the display should be “read”) that can be processed pre-attentively (i.e., under 200 ms). This grants that time-sensitive anomalies in the network can be noticed, processed, and addressed in a timely manner. Our design approach was driven by theories rather than existing design works in the hope of encouragi...

The rise of global trade and economic development is not only apparently grown in terms of volume but with value as well. Such spurt has evoked the risk management that is associated with export business, and can allow high-tech items fall into the hands of foreign military programs or terrorist organizations. The internal control compliance for export has set the in-house procedures for firms to adopt, facilitate, and abide with defined national export control requirements. This is crucial for firms to prevent potential violations on export rules and regulations. Introducing internal control program for export compliance can mitigate terrorist activities. This present study has taken Taiwan on board to determine the acquaintance of export risk and the implementation of internal control program through a team effort. Hence, the purpose of this study is to investigate the factors affecting the performance of internal control task team within a firm. The findings show that team-based incentives have a positive impact on team cohesion while knowledge sharing and knowledge integration have a significant impact on team performance. Furthermore, it is found that higher social-related risks and technical-related risks may increase team management risk, and the reduction in team management risk is beneficial to improve team performance.

The data presented in this article are related to the research article entitled: "Information strategies for energy conservation: a field experiment in India" (Chen et al., 2017)[1]. The availability of high-resolution electricity data offers benefits to both utilities and consumers to understand the dynamics of energy consumption for example, between billing periods or times of peak demand. However, few public datasets with high-temporal resolution have been available to researchers on electricity use, especially at the appliance-level. This article describes data collected in a residential field experiment for 19 apartments at an Indian faculty housing complex during the period from August 1, 2013 to May 12, 2014. The dataset includes detailed information about electricity consumption. It also includes information on apartment characteristics and hourly weather variation to enable further studies of energy performance. These data can be used by researchers as training datasets to evaluate electricity usage consumption.

Faced with the challenge of information explosion, almost everyone have been exposed to some kind of information visualization in varies of forms. Understanding how people read, understand, interpret and distinguish various forms of visualizations helps designers and developers think about how to improve the designs from the perspectives of users. This paper applied a mixed research method of quantitative and qualitative to explore how the designs of visualization forms evolved, and whether those kinds of graphs and charts are easy for users to understand, and how much information the users can get from the visualization. By testing if users are able to easily and accurately reach the information and providing the scales of simple to complex, and easy to hard, we see that basic visualizations like bar, pie, bubble, line, and scatter charts have been distributed in areas which are relatively simple in design and easy to read. Nonetheless, visualizations like the tree, parallel coordinate, sunburst, heat map, box plot and Sankey graphs have been concentrated in the regions of relatively complex in design, and are difficult to understand. In addition, the visualizations, including stacked bar, word cloud, box plot, and theme river that frequently appeared in the middle region of the grid, embodied the transitions of visualization design from simple to complex, and easy to hard.

Visual conventions are perceptually efficient graphic agreements with common-sense like referents and are commonly used in what we interact with in daily life. It becomes a studying-worthy issue on whether such conventions can enhance performances and reduce cognitive load when we perceive and reason about new knowledge. Furthermore, whether the visual conventions can affect experts, who have prior knowledge and design experience about different visual encoding principles the same degree as novice who have no background knowledge in this area, is another research focus in this study. Our research is carried out according to action features when we read visualizations. Four task features are extracted, based on which behavioral and eye-tracking measurement were conducted, that is data localization, simple and complex data comparison, and knowledge inference. Both expert and novice participants were enrolled in our experiment. The result indicates that conventional elements in visualizations can hugely improve performances in more complex tasks involving higher-level cognition, like making comparisons and reasoning about new knowledge. The performance improvement can be seen from shorter response time on achieving conclusions and higher accuracy rates. Meanwhile, cognitive load, which can be measured from shorter total fixation duration and fewer fixation counts in AOIs, is reduced through applying visually conventional features. No statistically significant difference is found in comparing perceptual and inferential outputs of expert and novice group. We draw conclusions that visual conventions in visualizations can better performance in relatively complex activities, and it can be equally perceived and acquired regardless of the user’s knowledge background is. What we conclude in this study can be extended to areas of dynamic data visualization and layout design in the digital interface domain.

Used car online trading is a new trend developed in the vehicle trading market recently. In this paper, we focus on user experience of car searching in a used-car website. The datasets of used vehicles are complicated and multidimensional. To find a satisfying car within the budget, the car buyer needs to compare many cars by exploring and comparing data include but not limit to car maker, type, mileage, price, and key features. Within most current e-commerce systems, to search and evaluate different cars, users often have to jump across detail pages to search pages repeatedly. Due to constraints set in the searching process, it may result in uncontrollable information overload or deficiency. With a user-centered design approach, we first analyzed the car searching behaviors through the user study, then designed a data visualization interface that helps a customer to (1) achieve an overall understanding of the used car market such as relations of car type to price, mileage/model-year to price, and features, and (2) search, filter, and compare cars of interest through simple interactions. The goal of this research is to help users to find out an ideal candidate car through an innovative interface and enhance user experience on used-car trading websites.

Radial visualization is an important technique to depict serial periodic data. Circle clock design is intuitive to encode 24-hour cyclical data. However, the biggest limitation of the design is the accuracy of reading time points on circle. Dodecagon is another way to represent time series data. We empirically evaluated the effectiveness of circle and dodecagon clock design in perceiving specific points in time. A post-testing interview was also conducted to understand participants’ strategies to read the times. Results show that dodecagon is more accurate than circle in terms of reading time points. Dodecagon was voted as a powerful approach to read the time points and circle was regarded as a better beautiful visualization method.

In order to explore the icon controlled digital interface for brain-computer interaction, we use Event-Related Potential technology, first of all, collect the icons from various digital interfaces, use the image processing software to process the icon images, the method comprises the following steps: communication between EEG and test computer, EEG experiment, off-line analysis of the original signal, time domain and frequency domain feature extraction of the group average EEG signal, microprocessor processing, and obtain the user computer function control command of the icon picture, then extract time domain and frequency domain characteristics of target icon picture EEG signal, and calculate the similarity between them, finally realize the triggering of control instruction of the target icon picture. This method can effectively realize icon brain-computer control of the digital interface, and provide the important reference for other elements to interact with the digital interface brain-computer interaction.

We study data structures in the presence of adversarial noise. We want to encode a given object in a succinct data structure that enables us to efficiently answer specific queries about the object, even if the data structure has been corrupted by a constant fraction of errors. We measure the efficiency of a data structure in terms of its length (the number of bits in its representation) and query-answering time, measured by the number of bit-probes to the (possibly corrupted) representation. The main issue is the trade-off between these two. This new model is the common generalization of (static) data structures and locally decodable error-correcting codes (LDCs). We prove a number of upper and lower bounds on various natural error-correcting data structure problems. In particular, we show that the optimal length of $t$-probe error-correcting data structures for the Membership problem (where we want to store subsets of size $s$ from a universe of size $n$ such that membership queries can be answered efficiently) is approximately the optimal length of $t$-probe LDCs that encode strings of length $s$. It has been conjectured that LDCs with small $t$ must be superpolynomially long. This bad probes-versus-length trade-off carries over to error-correcting data structures for Membership and many other data structure problems. We then circumvent this problem by defining so-called relaxed error-correcting data structures, inspired by the notion of “relaxed locally decodable codes” developed in the PCP literature. Here the decoder is required to answer most queries correctly with high probability, and for the remaining queries the decoder with high probability either answers correctly or declares “don't know.” Furthermore, if there is no noise on the data structure, it answers all queries correctly with high probability. We obtain positive results for the following two data structure problems: (1) Membership. We construct a relaxed error-correcting data structure for this problem with length nearly linear in $s\log n$ that answers membership queries with $O(1)$ bit-probes. This nearly matches the asymptotically optimal parameters for the noiseless case: length $O(s\log n)$ and one bit-probe, due to Buhrman et al. (2) Univariate Polynomial Evaluation (namely, we want to store a univariate polynomial $g$ of degree $\deg(g)\leq s$ over the integers modulo $n$ such that evaluation queries can be answered efficiently; i.e., we can evaluate the output of $g$ on a given integer modulo $n$). We construct a relaxed error-correcting data structure for this problem with length nearly linear in $s\log n$ that answers evaluation queries with ${\mbox{polylog}}(s)\cdot\log^{1+o(1)}(n)$ bit-probes. This nearly matches the parameters of the best known noiseless construction due to Kedlaya and Umans.

User experience remains a crucial consideration when assessing the successfulness of information visualization systems. The theory of affordances provides a robust framework for user experience design. In this article, we demonstrate a design case that employs an affordance-based framework and evaluate the information visualization display design. SolarWheels is an interactive information visualization designed for large display walls in computer network control rooms to help cybersecurity analysts become aware of network status and emerging issues. Given the critical nature of this context, the status and performance of a computer network must be precisely monitored and remedied in real time. In this study, we consider various aspects of affordances in order to amplify the user experience via visualization and interaction design. SolarWheels visualizes the multilayer multidimensional computer network issues with a series of integrated circular visualizations inspired by the metaphor of the solar system. To amplify user interaction and experience, the system provides a three-zone physical interaction that allows multiple users to interact with the system. Users can read details at different levels depending on their distance from the display. An expert evaluation study, based on a four-layer affordance framework, was conducted to assess and improve the interactive visualization design.

3D modeling is used in Computer Graphics in various fields. Since the growth of gestures, virtual reality and embodied cognition, there have been various new technologies developed to either improve the modeling efficiency, or to provide more nature intuitive experience to the users. In this paper, from the user experience perspective, we try to compare these methods for navigation of 3D objects in the virtual modeling environment including: simple bare hand gestures, tangible user interfaces (TUI) with object in hand, as well as mouse/keyboard as the primary input. Based on embodied cognition theory, we hypothesis that the object-in-hand method might bring better user experience since the interaction between the object and hand can enhance the user's cognition while navigating a model. We present a conceptual design, with two approaches and three design models which demonstrate differences in user interaction with 3D modeling software.

Our ageing energy grid, the fundamental resource for human activity, remains one of the great societal challenges. Governments and the energy industry are visioning a future of an engaged society that sustainably produces and consumes energy via a shared multi-directional Smart Grid. This vision; however, depends on our current efforts to increase public’s awareness and comprehension of energy as a limited consumer product, involving personal choice. Energy monitoring and feedback, along with home automation, are fast emerging markets to support this vision. We reviewed 75 currently available home energy-monitoring systems (HEMS) and discussed their pitfalls and potentials. We hope to encourage discussions about the role user experience design could play in personal information visualization, and in addressing fundamental societal problems. We call for experience centric explorations into HEMS’ design to address the energy feedback needs of the future.

Many elderly people are living apart from their children. We want to develop a system that can reinforce the connection and emotional feelings between aged parents and their children by combing new digital technologies with soft and warm leather material. Through an iterative design process that includes user interview and observation, design exploration, low-fidelity and high-fidelity prototypes, and usability testing, we present a small digital screen attached to an existing leather wallet of the aged parent to receive and display pictures or videos sent from their adult children. By attaching LINK, the old leather wallet serves as an invisible channel, sharing and connecting beautiful family memories without interrupting the private life of either side.

This paper presents the design rationale of a color-changing and olfactory scarf to affect people’s emotional states in a group environment. The goal of the design is to cheer up depressed individuals or calm down those who are overexcited. Our design uses a heart rate sensor and a skin conductance sensor to detect and recognize emotional information. The scarf will change its color and emit an odor to enhance positive emotions or reduce negative ones. We went through a user-centered design process and discussed different forms of design. Given the wearability and comfort characteristics of scarves, we decided to choose scarves as the solution to regulate emotions.

Location-based social network sites (LBSNS) are the integrations of social network service and location-based service. In this study, we examine two opposite factors, the benefits and privacy concerns, which affect the disclosure intention of users on LBSNS in a mobile environment. We utilise the privacy calculus perspective framework on the disclosure intention of location information. Also, the Big Five model is used to examine the impacts of dispositional factors, such as personality traits, on the concern for privacy. The privacy control, legislation awareness and privacy invasion are control variables for both disclosure intention and privacy concern. Data were collected from 298 respondents residing in Ho Chi Minh City, Vietnam. The results indicate that the legislation awareness does not seem to exert a significant influence on both privacy concerns and disclosure intention; it can be explained by the poor effectiveness of legislation in a developing country like Vietnam. However, we clearly found that the benefits and privacy concerns have the opposite influence on behavioural decisions of social network users, with the former positively affecting disclosure intention and latter negatively. Moreover, findings in the study show that perceived benefits such as connectedness, locatability and personalisation have stronger effects than privacy concerns do.

The very rapid adoption of mobile devices has attracted Open Source Mobile Application (OSMA) developers to create OSMAs and deliver them to the market. However, the majority of mobile communication studies have examined mobile applications from the end-users' perspective, and relatively little is known from the developers' side. As such, this research aims to investigate the developers' knowledge sharing behaviours within the context of OSMA development project. Drawing from social capital theory and the team cognition literature, the present study developed a research framework that viewed OSMA development project as involving both a virtual community and virtual team. We found that some dimensions of social capital and team cognition positively affect knowledge sharing. Meanwhile, social capital is found to positively influence team cognition. The implications and contributions of this study to the literature are discussed in the article.

This paper reports the first application of iterative experimental design methodology for high spatiotemporal resolution characterization of river and lake aquatic systems performed using mobile robot sensing systems. Both applications involve dynamic phenomena spread over large spatial domain: 1) Characterization of contaminant concentration and flow at the confluence of two major rivers displaying dynamics due to flow of the water; and 2) Characterization of rapidly evolving biological processes such as phytoplankton dynamics in a lake system. We describe the development and application of a new general purpose method for mobile robot sensing in such environments - Iterative experiment Design for Environmental Applications (IDEA). IDEA introduces in-field adaptation of mobile robotic sensing system. Analysis of the complex spatial and temporal structures associated with each observed environment is presented. Detailed characterization of the observed environment using IDEA methodology is used as an informed prior to improve the performance of the existing adaptive experimental design approaches for mobile robotic systems - stratified adaptive sampling and hierarchical non-stationary Gaussian Processes.