Changes In User Behavior Research Articles

Temporal Pattern of User Behavior in Micro-blog

Temporal pattern provides a novel way to character user behavior in social network from the perspective of time. In this work, we study two types of temporal pattern of user behavior in Micro-blog: Long Term Pattern and Daily Pattern. Long Term Pattern stands for the overall trend of user behavior changes since one starts to use Micro-blog and it provides the global view of user behavior variations. Daily Pattern states about the everyday variation and it represents the microscopic regularity within a day. In order to find out temporal pattern, Wavelet Transformation and Dynamic time warping for K-Medoids algorithm (WT-DKM) is proposed to organize time series into clusters, each cluster corresponding to a pattern. Eventually, 4 long term patterns and 5 daily patterns are discovered. These patterns are various in many terms, which reveal the difference of regularity among users. Almost half users behave randomly without apparent regularity while the others’ behaviors have obvious variation trend along with time. User group is often used to character user behavior according to their status, age, etc. So we study the relationship between temporal pattern and user group to discover whether users in the same user group are more likely to behave with same type of temporal pattern. It turns out that for some user groups temporal pattern of most members are identical, while other groups are not.

Adaptive and personalised body networking

Body networking calls for novel methods and tools for a tight and implicit man machine confluence. One way to achieve this is to make technical systems sensitive and reactive to user personal situation. This paper describes service-oriented software architecture, designed to respond to the user via a biocybernetic loop that transforms changes in user behaviour into services that may be incorporated into a highly personalised user-centric system. These services are used to drive real-time system adaptation tailored to a specific individual in a particular usage context.

An unified VoIP model for workload generation

This paper presents a new model for VoIP workload generation. The novelty of our proposal consists in modeling the sessions by characterizing both the user behavior (session level) and the packet generation for an active call (intra-session level) with easily measured parameters and low computational complexity. This approach also facilitates systematic study of changes in user behavior and voice codec. The session level was modeled by analysis of call-holding time and time interval between successive calls. The model for call-holding time, characterizing the individual user behavior, uses the Pareto type 2 probability distribution. The time interval between calls is obtained from aggregate traffic and can be modeled by exponential probability distribution. Aggregate traffic is obtained by superposition of simultaneous sessions. The data used to characterize the session level were collected at the backbone of two Brazilian telecommunication carriers. The model for intra-session level comprises the characterization of the packet size and the packet inter-arrival time. The intra-session model was based on data generated in a laboratory environment, in order to properly characterize the codec influence on packet generation and to avoid the effects of delay, jitter and loss commonly present in an operational network. Models for constant bit rate and variable bit rate codecs were considered. A simulator was implemented and the results indicate that our model properly mimics the characteristics observed in real traffic and can be used for VoIP modeling and workload generation. Additionally, an application to automate the performance analysis was developed.

PASSENGER PREFERENCE ANALYSIS: LIGHT RAIL TRANSIT OR BUS VERSUS CAR

To begin with, his article studies the user's preferences when faced with the introduction of two completely different public transport systems: the bus and the Light Rail Transit (LRT). Also, it examines how the modal distribution varies between the private car and each of the new systems, in particular. In addition, the most important variables for users when travelling in a congested corridor are individualized and a study is made on how these variables influence on the modal distribution. The results of the stated preferences of surveys are modelled using mixed logit models. Values are estimated for user's time and the demand elasticity is determined with respect to the relevant variables. Different situations are created to analyse how user's behaviour changes with the changes in the most important variables. Furthermore, this article quantifies the effects of the more relevant variables and shows that the LRT can attract more demand than a bus service, but it must guarantee a regular and frequent service, at the same time as charging competitive fares. It is also shown that for the introduction to be more successful any taken action should be accompanied by policies that chastise the use of the private car such as increased parking charges or higher fuel taxes.

The insight-value-perception (iVP) model for user-centered design

Through an inductive, multi-case analysis of eight medical device firms, this paper maps user-centered design and development practices to product performance outcomes. First, the data highlight that designing products under variable use conditions enabled firms to optimize products for widespread use and to increase the predictability of product outcomes. Second, the study shows that product adoption relied on maximizing benefits for multiple product stakeholders with often-conflicting needs, while minimizing required changes in end user behavior. Third, the paper highlights that managing perceptions toward product use through performance data positively influenced product adoption among the cases studied to a greater degree than did market demand or regulatory clearance. Fourth, rival explanations for outcomes involving limited user involvement, indicate that competitive advantages were achieved through maintaining dominant financial and intellectual property positions. From these findings, the insight-value-perception (iVP) model for user-centered design was constructed. This model links design and development practices to outcomes, from a combination of consumer-oriented, technical, and financial perspectives. Although rooted in the experiences of device developers within early stage medical device companies, the iVP Model may be used as a theoretical framework to examine a range of complex systems involving an embedded network of product users and stakeholders.

Road user behaviour changes following a self-explaining roads intervention

The self-explaining roads (SER) approach uses road designs that evoke correct expectations and driving behaviours from road users to create a safe and user-friendly road network. Following the implementation of an SER process and retrofitting of local and collector roads in a suburb within Auckland City, lower speeds on local roads and less variation in speed on both local and collector roads were achieved, along with a closer match between actual and perceived safe speeds. Preliminary analyses of crash data shows that the project has resulted in a 30% reduction crash numbers and an 86% reduction in crash costs per annum, since the road changes were completed. In order to further understand the outcomes from this project, a study was carried out to measure the effects of the SER intervention on the activity and behaviour of all road users. Video was collected over nine separate days, at nine different locations, both before and after SER construction. Road user behaviour categories were developed for all potential road users at different location types and then used to code the video data. Following SER construction, on local roads there was a relatively higher proportion of pedestrians, less uniformity in vehicle lane keeping and less indicating by motorists along with less through traffic, reflecting a more informal/low speed local road environment. Pedestrians were less constrained on local roads following SER construction, possibly reflecting a perceptually safer and more user-friendly environment. These behaviours were not generally evident on collector roads, a trend also shown by the previous study of speed changes. Given that one of the objectives of SER is to match road user behaviour with functionally different road categories, the road user behaviour differences demonstrated on different road types within the SER trial area provides further reinforcement of a successful SER trial.

A Note on the Antitrust of Sustaining Innovation through 'Entreprenurial Handoffs'

Mergers in the startup world, like a Google/Youtube, Amazon/Zappos, or Facebook/Instagram, are often about sustaining the innovation so the acquired company can disrupt the legacy industry. The method of sustaining the innovation is the from innovative founders who may be good at the innovation involved in changing user behavior to a bigger, but still innovative company that can sustain the innovation by applying a business model to it.Antitrust should recognize the entreprenurial handoff when examining acquisitions of certain startups.

Special Issue on Cyber Defense: Methodologies and Techniques for Evaluation

Welcome to this special issue of the Journal of Defense Modeling and Simulation on ‘Cyber Defense: Methodologies and Techniques for Evaluation’. The cyber domain has emerged as a strategic national asset of interest to both military and civilian sectors. The overlap between military and commercial networking resources and infrastructure complicates issues of protection, defense, and offense. The defense community is tasked not only with protecting our military information systems commercially procured, but also in protecting our nation’s strategically vital enterprises. Homeland defense rests squarely on our ability to guard critical infrastructure control systems that have a wide range of exploitable vulnerabilities. In this issue we look at several publications that make contributions related to securing the cyber domain: (1) a formal model to capture human behavior in the cyber realm; (2) modeling results that capture efficacy of Global Information Grid awareness through Network Tasking Orders (NTOs); (3) performance modeling for virtual environments that aid in defensive training scenarios; (4) a model for attack analysis on underlying network control protocols; and (5) simulation results comparing centralization methods used in log-based security systems. Robinson and Cybenko tackle the issue of capturing and analyzing human behavior related to observable actions conducted by users in the cyber domain. Little work has been done in modeling cyber-specific human behavior and their paper presents a novel extension to traditional topic modeling. Using their methodology, more precise data analysis activities may be conducted to extract quantitative information related to cyber security. By translating normal topic models related to document handling, they derive more cyber-appropriate characteristics such as users, sessions, activities, and behaviors. Using weighted probabilities and sampling distributions, appropriate matrices may be derived that are useful for classifying patterns of behavior and probabilistic models for predictive analysis. By analyzing user behaviors in such a way, a key layer of cyber situational awareness is created: changes in historical user behaviors may indicate telltale signs of insider activity or malicious corruption. Cyber planners and operators, particularly in the Department of Defense (DoD), face the problem of how to manage cyber assets to ensure synchronization of efforts and economy of force. Although air planners have longed benefited from the Air Tasking Order (ATO: a daily allocation of air assets to support current mission requirements), the cyber domain has no correlation. Compton et al. propose the use of a NTO to help allocate resources in the DoD’s Global Information Grid, particularly for mobile assets that are part of highly dynamic network topologies. Although NTOs are not a new concept, Compton and colleagues use the concept to specifically optimize network resources as opposed to using them for supporting air missions themselves (the traditional use to date). By building upon the traditional structure of an ATO, this paper providers a clear translation to cyberspecific tasking and shows how a prior knowledge of network resources may be used in simulations during the NTO planning phase to support Quality of Service goals during execution. A major area of research within DoD currently revolves around how to defend host machines and network resources themselves. Grimaila et al. compare methods for collecting, logging, and correlating events used for defensive analysis. Centralized logging, the traditional method for event correlation, comes with shortfalls because it does

Using instructional design process to improve design and development of Internet interventions.

Given the wide reach and extensive capabilities of the Internet, it is increasingly being used to deliver comprehensive behavioral and mental health intervention and prevention programs. Their goals are to change user behavior, reduce unwanted complications or symptoms, and improve health status and health-related quality of life. Internet interventions have been found efficacious in addressing a wide range of behavioral and mental health problems, including insomnia, nicotine dependence, obesity, diabetes, depression, and anxiety. Despite the existence of many Internet-based interventions, there is little research to inform their design and development. A model for behavior change in Internet interventions has been published to help guide future Internet intervention development and to help predict and explain behavior changes and symptom improvement outcomes through the use of Internet interventions. An argument is made for grounding the development of Internet interventions within a scientific framework. To that end, the model highlights a multitude of design-related components, areas, and elements, including user characteristics, environment, intervention content, level of intervention support, and targeted outcomes. However, more discussion is needed regarding how the design of the program should be developed to address these issues. While there is little research on the design and development of Internet interventions, there is a rich, related literature in the field of instructional design (ID) that can be used to inform Internet intervention development. ID models are prescriptive models that describe a set of activities involved in the planning, implementation, and evaluation of instructional programs. Using ID process models has been shown to increase the effectiveness of learning programs in a broad range of contexts. ID models specify a systematic method for assessing the needs of learners (intervention users) to determine the gaps between current knowledge and behaviors, and desired outcomes. Through the ID process, designers focus on the needs of learners, taking into account their prior knowledge; set measurable learning objectives or performance requirements; assess learners’ achievement of the targeted outcomes; and employ cycles of continuous formative evaluation to ensure that the intervention meets the needs of all stakeholders. The ID process offers a proven methodology for the design of instructional programs and should be considered an integral part of the creation of Internet interventions. By providing a framework for the design and development of Internet interventions and by purposefully focusing on these aspects, as well as the underlying theories supporting these practices, both the theories and the interventions themselves can continue to be refined and improved. By using the behavior change model for Internet interventions along with the best research available to guide design practice and inform development, developers of Internet interventions will increase their ability to achieve desired outcomes.

Governmental Forest Policy for Sustainable Forest Management in Costa Rica, Guatemala, and Nicaragua: Regulation, Implementation, and Impact

We evaluated how governmental forest regulation in Costa Rica, Guatemala, and Nicaragua has succeeded or failed in fostering changes in forest owner and user behavior that enhance the sustainability of tropical forest management. As expected, sufficient resources and capacity for forest policy implementation are crucial for attaining governmental forest policy objectives, but innovative arrangements for promoting, enforcing, and verifying policy compliance can compensate for limited regulatory resources and processes. The findings also indicate that: the level of governmental commitment to sustainable forest management (SFM) was as important as total funding levels; a mix of government rules and incentives enhanced adoption of SFM; the incorporation of professional forest regents offset limited agency capacity; and forest certification enhanced SFM on forest concessions. Local level inducements and constraints that enhance or impede governmental forest policy adoption and compliance also were identified.

Discovery and diagnosis of behavioral transitions in patient event streams

Users with cognitive impairments use assistive technology (AT) as part of a clinical treatment plan. As the AT interface is manipulated, data stream mining techniques are used to monitor user goals. In this context, real-time data mining aids clinicians in tracking user behaviors as they attempt to achieve their goals. Quality metrics over stream-mined models identify potential changes in user goal attainment, as the user learns his or her personalized emailing system. When the quality of some data-mined models varies significantly from nearby models—as defined by quality metrics—the user's behavior is then flagged as a significant behavioral change. The specific changes in user behavior are then characterized by differencing the data-mined decision tree models. This article describes how model quality monitoring and decision tree differencing can aid in recognition and diagnoses of behavioral changes in a case study of cognitive rehabilitation via emailing. The technique may be more widely applicable to other real-time data-intensive analysis problems.

Enabling effective design of multimodal interfaces for speech-to-speech translation system: An empirical study of longitudinal user behaviors over time and user strategies for coping with errors

The study provides an empirical analysis of long-term user behavioral changes and varying user strategies during cross-lingual interaction using the multimodal speech-to-speech (S2S) translation system of USC/SAIL. The goal is to inform user adaptive designs of such systems. A 4-week medical-scenario-based study provides the basis for our analysis. The data analyzed includes user interviews, post-session surveys, and the extensive system logs that were post-processed and annotated. The annotations measured the meaning transfer rates using human evaluations and a scale defined here called the concept matching score.First, qualitative data analysis investigates user strategies in dealing with errors, such as repeat, rephrase, change topic, start over, and the participants’ self-reported longitudinal adaptation to errors. Post-session surveys explore participant experience with the system and point to a trend of user-perceived increased performance over time.The log data analysis provides further insightful results. Users chose to allow some degradation (84% of original concepts) of their intended meaning to proceed through the system, even after they observed potential errors in the visual output from the speech recognizer. The rejected utterances, on average, had only 25% of the original concepts. This user-filtered outcome, after the complete channel transfer through the S2S system, is that 91% of the successful turns result in transfer of at least half the intended concepts while 90% of the user rejected turns would have conveyed less than half the intended meaning.The multimodal interface results in 24% relative improvement in the confirmation mode and in 31% relative improvement in the choice mode compared to the speech-only modality. Analysis also showed that users of the multimodal interface temporally change their strategies by accepting more system-produced choices. This user behavior can expedite communication seeking an operating balance between user strategies and system performance factors. Lastly, user utterance length is analyzed. Longer utterances in general imply more information delivered per utterance but potentially at the cost of increased processing degradation. The analysis demonstrates that users reduce their utterance length after unsuccessful turns and increase it after successful turns and that there is a learning effect that increases this behavior over the duration of the study.

A classifier ensemble approach to the TV-viewer profile adaptation problem

For the past few years the digital video broadcasting (DVB) and Internet TV (IP-TV) market has experienced a significant growth throughout the world. As a result of this trend, many broadcasters offer such services, and many homes now feature a set-top box in their living rooms providing them with a myriad of digital TV channels. This plethora of choices dictates the need for a system that can autonomously monitor a user’s choices on TV and be able to predict what content the user is likely to appreciate. We describe a system called CPACE (continuous profile adaptation via classifier ensembles) that continuously monitors user choices, and using machine learning techniques, it classifies not-seen-before content from an electronic program guide (EPG) and suggests to the user content that he/she is likely to be interested in viewing. Since we use no collaborative filtering at all, our architecture is fundamentally different from other commercially successful approaches such as Ti-Vo or the winners of the Netflix Prize that utilize collaborative filtering techniques that necessarily suffer from privacy related issues. We use time-windows combined with online learning to adapt to changing user behavior and classifier ensemble techniques to enhance classification accuracy. As a result, the system after a short training period is capable of classifying new broadcasted content with very high accuracy reaching up to 86%. The system has been shown to exhibit very high precision in its recommendations in a real-world installation where it usually achieves rates of more than 90%, and for a significant fraction of the user population it achieves 100% correct recommendations.

Reference, Readers' Advisory, and Relevance

There is general agreement that the nature of reference services in academic and public libraries is undergoing dramatic change as a result of technological advancements and changes in user behaviors. Readers' advisory services offer libraries an opportunity to continue to remain relevant to their users. This article explores the similarities between the reference and the readers' advisory encounters and offers suggestions on more closely integrating these two essential services in both library practice and library and information science education.

Digital Storytelling in Museums: Observations and Best Practices

Abstract The museum landscape has changed dramatically over the last 20 years. Technology has made possible new kinds of interactions, visitor expectations have broadened, competition for time and resources has become increasingly intense, and the buildings serve ever‐more‐complex roles. As a result, interactive designers, including those of us at Second Story, have evolved our skills and approaches to keep pace. This article summarizes many of our observations while sharing some of the best practices that we have evolved to create engaging interactive installations, websites, and experiences. Despite changes in technology and user behavior, a core focus on great storytelling should drive interactive design and serve as the critical element for museums communication and connecting with their visitors.

Enhancing civilian protection from use of explosive weapons in populated areas: building a policy and research agenda

AbstractEvery day, and in a range of contexts, the use of explosive weapons in populated areas harms civilians. Evidence is growing that elevated levels of civilian harm fit a recurrent pattern, suggesting that more coherent and effective humanitarian responses are needed to enhance civilian protection, especially changes in behaviour of users of explosive weapons. This article describes the effects of explosive violence, critically examines how the existing humanitarian law regime tends to address this issue and explores some current developments in building a research and policy agenda to try to reduce civilian harm from the use of explosive weapons.

Design for Socially Responsible Behavior: A Classification of Influence Based on Intended User Experience

Introduction Whether a result of the financial crisis, the public perception of massive overconsumption, or global climate change, designers are increasingly motivated “to do good for society.” This interest seems to manifest itself primarily in two ways. First, designers and design companies are behaving in more socially responsible ways in their product development. A focus on the use of recyclable materials, the rejection of child labor, and the use of sheltered workshops are possible consequences of such an attitude. Second, designers are using their design skills to tackle social problems. In these cases, designers apply design thinking and design methodologies to social issues to create innovative solutions. With this interest, education, safety, and health care have become domains for designers.1 Because many, if not all, social issues involve behaviors that play a crucial role in initiating a desired change, the power of design as a deliberate means to change behavior has garnered increased interest. This interest is currently and prominently present in the field of sustainable design. The conventional goal of sustainable design initially was to design products that require the least energy to be produced and used and that could be recycled. Currently, the idea is growing that to really effect change, sustainable design must be capable of changing user behavior. For example, there is simply little to be optimized in our kettle’s heating system, but if the amount of unnecessary water we repeatedly boil could be reduced, a substantial reduction in energy loss could be achieved. This notion of the significance of user behavior in terms of environmental implications has led to design for what is called “sustainable behavior.”2 While our knowledge about how design can change behavior is rapidly expanding, the way a user might potentially experience this influence is rarely discussed. However, the user’s experience of that influence does play an important role in the effectiveness of the design intervention. When a person tries to persuade another to act differently, attitude, tone of voice and expressions affect the experience of the one being persuaded and, thus, his or her motivation to act. In this article, we propose a classification of

Investigating the potential of a novel low-energy house concept with hybrid adaptable thermal storage

In conventional buildings thermal mass is a permanent building characteristic depending on the building design. However, none of the permanent thermal mass concepts are optimal in all operational conditions. We propose a concept that combines the benefits of buildings with low and high thermal mass by applying hybrid adaptable thermal storage (HATS) systems and materials to a lightweight building. The HATS concept increases building performance and the robustness to changing user behavior, seasonal variations and future climate changes. Building performance simulation is used to investigate the potential of the novel concept for reducing heating energy demand and increasing thermal comfort. Simulation results of a case study in the Netherlands show that the optimal quantity of the thermal mass is sensitive to the change of seasons. This implies that the building performance will benefit from implementing HATS. Furthermore, the potential of HATS is quantified using a simplified HATS model. Calculations show heating energy demand reductions of up to 35% and increased thermal comfort compared to conventional thermal mass concepts.

Environmental impact of building-related and user-related energy consumption in dwellings

Energy consumption in dwellings contributes significantly to their total negative environmental impact. This paper quantitatively assesses the environmental impact of building-related and user-related gas and electricity consumption in a Dutch apartment dwelling using life cycle assessment (LCA) methodology. Several scenarios for gas and electricity consumption are compared to assess what effect changes in building characteristics and user behaviour have on the environmental impacts of energy consumption. This study shows that gas consumption significantly contributes to four environmental impact categories, which can be most effectively countered by reducing the heat demand of the dwelling. A 23% reduction in gas consumption leads to up to 13% less overall environmental impacts. Particularly in buildings with low heat demand, electricity consumption dominates all environmental impact categories. These can most effectively be reduced by changing the electricity demand of the user: 47% less electricity consumption leads to a 9–45% reduction in the total environmental impact. However, since electricity consumption continues to rise, the environmental effects of electricity use may be better reduced by changing the environmental impact of the electricity supply. Theoretically, when electricity consumption remains the same, over 90% less environmental impact could be reached by using 100% wind power to generate electricity.

Governmental regulation and nongovernmental certification of forests in the tropics: Policy, execution, uptake, and overlap in Costa Rica, Guatemala, and Nicaragua

We analyzed how and why governmental forest regulation and nongovernmental forest certification in Costa Rica, Guatemala, and Nicaragua and their execution lead to, or fail to produce desired changes in forest owner and user behavior toward the enhanced sustainability of tropical forests. The findings confirmed not only that sufficient resources and capacity for forest policy execution are crucial for attaining policy objectives, but also that innovative arrangements for promoting, verifying, and enforcing policy compliance can compensate for limited resources and processes. Such arrangements incorporate a mixture of policy tools and actors that go beyond the traditional command-and-control approach, including the establishment of positive fiscal incentives for sustainable forest management, provision of technical assistance, participation of private-sector forest stewards, and support from nongovernmental organizations. The results also shed light on the mitigating effects of local-level inducements and constraints to governmental and nongovernmental forest policy adoption and compliance, such as forest size and composition, available resources, technical capacity, and attitudes toward forest policy and implementers.