Due to the prevalence of personal health tracking, cases of self-logged data being utilized in the clinic are gradually increasing. However, obstacles to clinicians' ability to further adopt such data-driven medical consultations in the existing workflow remain, such as lack of time and poor interoperability. In this paper, we conducted a workshop to design a clinician interface supporting the integration of data-driven consultation into the existing workflow and investigate the role of the interface in situ. After implementing the clinician interface designed based on the workshop results, we observed 32 cases of actual use within the clinical context. We found that our interface, DataMD, helped the clinician construct a new workflow, enhanced the clinician's counseling skills, and facilitated more in-depth conversation. This paper contributes to empirically identifying the role of a clinician interface through a user-centered design approach.

By enabling people to track their lifestyles, including activity level, sleeping, and diet, technology helps clinicians to treat patients suffering from "lifestyle diseases." However, despite its importance compared to other lifestyle factors, it is not easy to record food intake consistently. Although researchers have attempted to solve this problem, most have not considered its applicability in the clinical context. In this paper, we aim to (1) understand food-journaling practices and (2) explore the applicability of lifestyle data in the clinical context. By observing 20 patients who recorded data including food logs, steps, and sleeping time, we found that patients recorded their food logs diligently, as they were conscious of clinicians. Clinicians were surprised by the high adherence rate of journaling and tried to overlap food data with other data, such as steps, sleeping time, etc. This paper contributes by providing qualitative insights for designing applicable strategies utilizing lifestyle data in the clinical context.

This paper describes an energy trading model for efficient energy saving and management services. The energy consumers and suppliers in smart factories can trade their energy using the proposed model. First, the market participants register their information and select the roles of the energy suppliers or the consumers. They can change the roles depending on the situation. And the energy suppliers register the energy resources to the market server. And many energy consumers can apply the appropriate tender. When the bidding time ends, the market server calculates and determines the bidding results, and sends them to the bidding participants. According to the results, the consumer who received the winning bidder can use the energy during the appointed time. Using the proposed model, the suppliers and the consumers can easily trade the energy of smart factories, and can save the cost by trading the remained energy with reasonable prices. Also, the nation achieves the overall cost savings for energy by the balance of demand and supply.

While interacting with mobile devices, users may press against touch screens and also exert tangential force to the display in a sliding manner. We seek to guide UI design based on the tangential force applied by a user to the surface of a hand-held device. A prototype of an interface using tangential force input was implemented utilizing a force sensitive layer and an elastic layer and used for the user experiment. We investigated user controllability to reach and maintain target force levels and considered the effects of hand pose and direction of force input. Our results imply no significant difference in performance when applying force holding the device in one hand and in two hands. We also observed that users have more physical and perceived loads when applying tangential force in the left-right direction compared to the up-down direction. Based on the experimental results, we discuss considerations for user interface applications of tangential-force-based interface.

With the advance of various wireless access technologies, the demand for a mobile user equipped with multiple air interfaces simultaneously executing diverse applications emerged. In such network environment, per- application mobility management is a key to allow each application of an end user device to dynamically and fully take advantage of the most suitable access technology. In this paper, we devised a comprehensive architectural platform with cross- layer techniques to realize this disruptive technology, i.e., per- application mobility management. Four core functional modules composing the proposed platform for end user devices are defined: Monitoring Agents, Profile Database, Decision Engine, and IP Agent. We show through simulations that the presented platform provides an improved QoS as it selectively utilizes the best available networks depending on different QoS constraints of different applications.

Current research on robot navigation is focused on clear recognition of the map and optimal path planning. The human cleaning path is, however, not optimal regarding time but optimal to the cleaning purpose. We have analyzed in this paper the cleaning behaviors in home environments and understood the user's path planning behaviors through usage tests of various vacuuming robots. We discovered that the actual user cleans with methods unique to specific areas of the house rather than following an optimal cleaning path. We not only suggest a path planning method for the vacuuming robot by using a layered map, but also a cleaning area designating method reflecting each area's characteristics. Based on these, we have designed a vacuuming robot's actions.

We consider robotic appliances, mobile and intelligent robots that perform household tasks, and study design method for autonomous behaviors of robotic appliances, a key component in human-robot and robot-environment interactions. Specifically, we develop robot behavior diagram, a visualized, robot-centric, chart-based behavior design method that is useful in describing robotic behaviors and transitions among them. This tool enables systematic construction of exhaustive set of autonomous behaviors, within the context of given set of robotic functionalities. First, the set of functionalities for a given robot is defined. Then, employing the defined functionalities, a diagram is constructed with behavioral states and events that can trigger transitions to other behaviors. For any given behavioral state, all plausible events are considered, and this is repeated until the diagram is complete with all the possible behaviors and events. We demonstrate that, via this method, a complete and robust behavioral scenario design is indeed attainable, by applying robot behavior diagram approach to an example household cleaning robot platform.

Quality of service (QoS) in the Internet depends on queuing and sophisticated scheduling in routers. In this paper, we address the issue of managing traffic flows with different priorities. In our reference model, incoming packets are first classified based on their priority, placed into different queues with different capacities, and then multiplexed onto one router link. The fuzzy nature of the information on Internet traffic makes this problem particularly suited to fuzzy methodologies. We propose a new solution that employs a fuzzy inference system to dynamically and efficiently schedule these priority queues. The fuzzy rules are derived to minimize the selected Lyapunov function. Simulation experiments show that the proposed fuzzy scheduling algorithm outperforms the popular weighted round Robin (WRR) queue scheduling mechanism

In this paper, we propose a wireless network domain structure which deploys a special cell, called a gray cell. The boundaries of wireless network regions are surrounded by the gray cells, and the gray cells are supposed to belong to all of its neighboring regions. Based on this wireless domain structure, we propose a mechanism which completely removes the waste of redundant resource reservation in the wireless network domain while greatly reducing the risk of reservation disruption caused by inter-region handovers. Using simulation, it is shown that the proposed mechanism can deal with inter-region handover as effectively as it does with intra-region handover. It is also shown that the proposed mechanism outperforms existing mechanisms with respect to reservation disruption time and packet losses caused by handovers.

In order to provide continuous QoS guarantees to a mobile user, it is required to deploy a mechanism which reserves resources in advance at the locations to which the mobile user is expected to move. An important issue with regards to these mechanisms is to minimize the waste of resources caused by redundant reservations while keeping up the QoS services to the user. In this paper, we propose a wireless network domain structure which deploys a special cell, called a gray cell. The boundaries of wireless network regions are surrounded by the gray cells, and the gray cells are supposed to belong to all of their neighboring regions. Based on this structure, we propose a mechanism which completely removes the waste of redundant resource reservation while greatly reducing the risk of reservation disruption caused by inter-region handovers. Using simulation, it is shown that the proposed mechanism can deal with inter-region handover as effectively as it does with intra-region handover. It is also presented that the proposed mechanism outperforms existing mechanisms with respect to reservation disruption time and packet losses caused by handovers.

This work presents a novel utility-based routing (UBR) algorithm for wireless ad hoc networks. In multi-hop ad hoc networks, each node may be responsible for forwarding data packets for others. Thus, some nodes may consume more energy than others, and consequently die earlier This leads to unbalanced usage of the power among the nodes, network partition, and the decrease in network lifetime. The UBR algorithm we develop takes into account not only the status of each intermediate node but also the characteristic of applications. Specifically, each application is assumed to be associated with a utility function, which maps to the quality of service (QoS). Each intermediate node sets a price to signal its willingness to participate, and then the cost for involving this intermediate node is calculated as price times the transmit power. Instead of choosing the shortest routing path, the destination node picks up the routing path that gives the maximum surplus defined as utility minus cost. Our performance study based on the PARSEC simulator shows that the proposed utility based algorithm improves the energy balance when compared with the original DSR.

The emergence of multiprotocol label switching (MPLS) with its efficient support of explicit routing provides basic mechanisms for facilitating traffic engineering. Exploiting this capability of MPLS, we propose an adaptive multipath traffic engineering mechanism named LDM (load distribution over multipath). The main goal of LDM is to enhance the network utilization as well as the network performance by adaptively splitting traffic load among multiple paths. LDM takes pure dynamic approach not requiring any a priori traffic load statistics. Routing decisions are made at the flow level, and traffic proportioning reflects both the length and the load of a path. LDM also dynamically selects a few good label switched paths (LSPs) according to the state of the entire network. We use simulation to compare the performance of LDM with the performance of several representative dynamic load distribution approaches as well as the traditional static shortest path only routing. The numerical results show that LDM outperforms the compared approaches in both the blocking ratio as well as the performance of the accepted traffic flows.

We consider the layer scheduling problem associated with a multiple-layer self-organizing low-power wireless network. Each layer has a root node, which maintains a rooted spanning tree through which data messages are routed to the root. Each root node is capable of broadcasting a message to its destination node directly. We exploit layer scheduling algorithms that adapt to network load fluctuations in order to optimize the performance. For optimality we consider a load balancing objective and a minimum delay objective respectively, the former attempts to optimize the overall network performance while the latter strives to optimize the per-message performance. Four algorithms are presented with the associated load information exchange protocols and simulations were used to evaluate and compare their performance. We show that the presented algorithms have superior performance in terms of data throughput and/or message delay, compared to a heuristic approach that does not account for network load fluctuations. Policies with a load balancing objective do Indeed yield a superior overall network performance over the policy based on a minimum delay objective.

A multi-hop wireless network using a rooted spanning tree as routing backbone has to deal with reliability and congestion problem when the network size increases. In this paper, we consider the problem of adding a new root with its own rooted spanning tree to the network to alleviate such problems. Based on minimum-depth and minimum-load metrics, we present efficient algorithm that achieves optimum selection of root(s).