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This poster proposes an Ultra-wideband localization scheme for the smart key system based on a machine learning approach. Previous studies try to use the channel impulse response measurement and apply machine learning to improve the localization accuracy. However, it was found difficult to perform real-time localization in the key fob hardware as these studies require complex computation. In addition, localization accuracy is severely degraded due to frequent NLOS conditions in vehicular environments. In order to solve these problems, we propose vehicular features based on machine learning approach to improve localization accuracy and to support the real-time operation. We evaluate the proposed scheme by deploying Decawave UWB transceivers on an actual vehicle. The proposed scheme showed more than 98% localization accuracy and an average prediction delay of 7.4 milliseconds.

In this work, we propose a sensor localization system assisted by wireless communication and augmented reality (AR) suitable for harsh indoor environments. Future handheld and unattended devices will be equipped with technologies, which have the means to enable localization of various phenomenon in indoor environments. These include visual odometry based on cameras and augmented reality, and communication hardware such as UWB. Integration of such technologies allows us to compensate for each other’s errors in measurements. However, existing work cannot fully exploit these technologies to high extent, often inducing more errors or wasted resources. Furthermore, many other existing indoor localization methods require a pre-defined architecture or building information, which are impossible to acquire in harsh indoor conditions. In our proposed system, we specifically propose an improved method of utilizing virtual anchors for localization of sensor tags in harsh indoor environments, based on a cluster-based selection algorithm that allows the system to improve the positioning accuracy through angular diversity while also improving resource utilization without existing knowledge of the location. Our work has been fully implemented and tested on several indoor environments.

In this work, we utilize multi-hop data fragmentation in energy harvesting wireless sensor networks (EHWSN) for improved security and routing.1 Data fragmentation is a secure data management and data provisioning technique used in unattended sensor networks. However, it compromises energy efficiency for better protection, possibly decreasing the lifetime of a traditional sensor network. Instead, it has potentials to be used in EHWSN, which allows better energy utilization for each sensor node while security of sensed data remains an important factor. In our work, we consider how data fragmentation can be applied in EHWSN, and propose a multi-hop data fragmentation method suitable for EHWSN.

The improvement in hardware capabilities of mobile devices has led to the active use of processor-heavy contents, such as multimedia files, on resource-limited platforms. In addition to simply enjoying such contents on mobile devices, recently commercialized protocols allow the real-time sharing of multimedia (or a mobile device's screen contents) with neighboring devices via wireless connection. However, unlike PC-scale computing platforms, use-case expansions on mobile devices face an additional technical challenge. Specifically, while the improved computation power is capable of handling processor-hungry applications, battery limitations hold back their full utilization. This paper acknowledges the fact that screen sharing on mobile devices can be attractive, but empirically show that minimizing the energy consumption is crutial, and introduces enhancements to the widely used H.264 encoder on mobile devices. Specifically, our enhancements target to minimize the transmission size of multimedia contents by analyzing the screen's dynamics. For contents with high dynamics, our scheme tries to maintain the video quality, while aggressively skipping frames for regions with minimal motion intensity. Our empirical evaluations show that the proposed light-weight enhancements reduce the size of a typical multimedia file by $\sim \hbox{42}$ %, while maintaining a high user-perceived quality (e.g., Structural SIMilarity measure) of 0.925. Wirelessly sharing this video results in $\sim \hbox{31}$ % lower frame transmission rate and up to $\sim \hbox{21}$ % power savings in less dynamic regions.

Vast volumes of time series are becoming more common in part to recent research advancements in big data analytics and sensor/monitoring networks. However, tranmission of time series for visualization services can cause serious bandwidth wastage and extensive network delays if there is no efficient data management. Existing work such as M4 aim to solve this problem by providing high data reduction rates through data aggregation and guaranteeing the reliability of visualization results at the same time. However, current work on M4 does not consider verification in a more practical environment; for example experimentation on web-based servers that are openly accessible by users. In this paper, we propose inter-pixel gradient-based M4 (IGM4) for enhancing the existing M4 scheme, and conduct a study to reduce the amount of data and delay without distorting the results of visualized graph. We build user-friendly web-based system to dealing with the data processing technique, and perform test on the empirical environment. Finally, we present the results of performance evaluation through comparison among the original data, M4, and IGM4 reflecting the various kinds of time series and resolutions.

In this poster, we propose a sensor localization system assisted by wireless communication and augmented reality (AR) suitable for disaster relief applications. Generally, disaster environments are considered extremely hazardous and deteriorated, with unpredictable effects to human mobility and digital devices. To maximize the safety and efficiency of first responders, deployment of wireless sensors are of utmost importance, as sensor nodes can provide sensing information as well as location information. We analyze the issues and challenges that need to be tackled for high accuracy localization of sensor nodes in such environments, and then propose a system that we plan to develop in the near future.

In this paper, we study and analyze data fragment placement techniques to exploit their problems and design an energy-aware fragment placement method in Unattended Wireless Sensor Networks (UWSN). In UWSN, the survivability of data is of utmost importance because sensed data cannot be immediately transmitted and must reside in the storage of sensor nodes for extended periods of time. The data, which have delay-tolerant characteristics, can be exploited by attackers that access the storage to erase or steal the data. Even though data fragmentation methods have been designed to solve this problem, these works do not consider a critical issue of where to place data fragments in the sensor network. In this work, we show that basic existing methods of data fragment placement have some problems, especially in terms of energy efficiency and data survival probability. Based on our analysis, we propose a lightweight method that allows us to efficiently select sensor nodes that are used to safely distribute and place data fragments. We show through simulation and preliminary testbed analysis that our proposed method can improve the overall performance of data fragmentation.

This paper proposes a mutual node evaluation method in mobile ad hoc networks to recognize and reliably remove attacker nodes from deteriorating the network. We focus on a tactical networking environment, where the network is generally maintained in harsh and hostile areas while the applications require stringent service requirements. In these kinds of environments, it is desirable to utilize proactive routing methods such as Optimized Link State Routing (OLSR). However, OLSR have weaknesses against various security attacks. To solve this problem, we provide a trust-based evaluation approach where node evaluate each other based on the packet forwarding capabilities. We prove the performance of our proposed method through NS-3.

This paper proposes a modified subcarrier design of the orthogonal frequency-division multiplexing (OFDM) scheme for supporting the concept of partially overlapped channels (POC) in wireless local area networks. Our proposed scheme, named as “channel-overlapped OFDM (CO-OFDM)”, enables the POC in OFDM by reconfiguring its subcarrier alignment and creating subcarrier subsets that allow clear transmission between nodes by using different non-orthogonal channels. This makes the nodes maintain connectivity with each other through beaconing even though they use adjacent channels. In addition, simultaneous data transmission can be achieved via channel switching and MIMO-based data transmission, thereby increasing the overall throughput of the network. Further, we integrate our CO-OFDM into IEEE 802.11a/g/n/ac-based wireless networks and analyse its superiority over existing protocols through mathematical modelling. Evaluation results show that the proposed CO-OFDM guarantees over 300% performance increase in network capacity.

This letter proposes a novel buffer management scheme for improving the packet delivery of Universal Serial Bus (USB) services in wireless networks. In the future, USB may be used with various wireless services, most notably Wi-Fi, thus realizing Wi-Fi USB (WSB). However, data transmission of Wi-Fi and USB is asynchronous due to differences in their Medium Access Control (MAC), resulting in buffer overflow. To alleviate this problem, we propose an overflow prevention scheme where rates of USB transmission are varied depending on status of Wi-Fi. The proposed scheme is evaluated via the NS-3 simulator, showing that the packet delivery ratio of USB data can reach near 100% even in wireless transmission.

The research presented in this paper proposes methods for enhancing the energy efficiency and quality of service (QoS) for WLAN-based Device-to-Device communications. We focus specifically on the research related to Wi-Fi Direct technology in order to provide better services for a wider range of Wi-Fi D2D applications. Although Wi-Fi Direct defines two power management schemes for providing energy efficiency in P2P devices, neither is sufficient for meeting the power efficiency and reliability requirements for various services. In order to alleviate this problem, the proposed scheme, which is referred to as Dynamically Synchronized Power Management (DSPM), proposes a method for synchronizing the active time slots with the data transmission intervals and adjusts the sleep and active cycles accordingly. Furthermore, transmission time slots are adjusted dynamically depending on the status of data transmission in order to further enhance the energy efficiency of D2D services while maintaining their service quality. Mathematical analysis and simulations are used to compare the proposed scheme with the existing power schemes for Wi-Fi Direct and analyze its effectiveness.

This paper presents a performance analysis of Wi-Fi Direct power management schemes and exploits their problems to design a novel, enhanced power management for future wireless USB (WSB) applications. Wi-Fi Direct will become a key technology for the support of future WSB services that require high standards of service quality and power efficiency at the same time. To provide this, Wi-Fi Direct defines two power management schemes, opportunistic power save mode and notice-of-absence. Even though each scheme has its own characteristics and advantages, specification does not have any definition of how to select the schemes and its parameters based on the type of WSB application being serviced. We analyze the properties of the two power management schemes of Wi-Fi Direct, and discover that their performance can greatly vary depending on the number and type of WSB applications that is being transmitted in the network. To solve this problem, we propose a novel power saving algorithm that can dynamically change the power management of Wi-Fi Direct. Our work is extensively evaluated using the Wi-Fi Direct module implemented in the NS-3 simulator.

International audience; In this paper, we propose data clustering techniques to predict temporal characteristics of data consumption behavior of different mobile applications via wireless communications. While most of the research on mobile data analytics focuses on the analysis of call data records and mobility traces, our analysis concentrates on mobile application usages, to characterize them and predict their behavior. We exploit mobile application usage logs provided by a Wi-Fi local area network service provider to characterize temporal behavior of mobile applications. More specifically, we generate daily profiles of " what " types of mobile applications users access and " when " users access them. From these profiles, we create usage classes of mobile applications via aggregation of similar profiles depending on data consumption rate, using three clustering techniques that we compare. Furthermore, we show that we can utilize these classes to analyze and predict future usages of each mobile application through progressive comparison using distance and similarity comparison techniques. Finally, we also detect and exploit outlying behavior in application usage profiles and discuss methods to efficiently predict them.

This paper presents a novel design and practical experiments of adaptive wireless mesh networks based on 802.11 based Wireless Local Area Networks for supporting public video surveillance. A network of video cameras and sensors can be equipped with wireless communication modules to form wireless surveillance at only a small expense of cost and labor. However, large and redundant multimedia data transmitted through the wireless medium pose challenging problems such as decrease in Quality of Service (QoS) and system reliability. To support seamless transmission of surveillance data through wireless means, we propose a wireless surveillance network design based on the protocols and functions of IEEE 802.11 mesh standard. One of the key functions of our adaptive mesh network is the “Multi-Gateway Routing with Congestion Avoidance”, which provides enhanced QoS support via adaptive congestion control. Network congestion is predicted in a distributed manner and amounts of data traffic transmitted to the congested path are redirected to multiple gateways. Redirection of traffic flows are made in such a way to provide quicker transmission for more time critical packets. Experimental studies via practical testbed implementation and simulation via NS-3 are conducted to prove the superiority of our proposed scheme.

A challenge faced by smart grid systems is providing highly reliable transmissions to better serve different types of electrical applications and improve the energy efficiency of the system. Although wireless networking technologies can provide highspeed and cost-effective solutions, their performance may be impaired by various factors that affect the reliability of smart grid networks. Here, we first suggest the use of IEEE 802.11s-based wireless LAN mesh networks as high-speed wireless backbone networks for smart grid infrastructure to provide high scalability and flexibility while ensuring low installation and management costs. Thereafter, we analyze some vital problems of the IEEE 802.11s default routing protocol (named hybrid wireless mesh protocol; HWMP) from the perspective of transfer reliability, and propose appropriate solutions with a new routing method called HWMP-reliability enhancement to improve the routing reliability of 802.11s-based smart grid mesh networking. A simulation study using ns-3 was conducted to demonstrate the superiorityof the proposed schemes.

Purpose: The PTEN gene, a novel tumor suppressor, is localized to chromosome 10q23.3 and shares extensive homology with the cytoskeletal protein, tensin. A high frequency of mutations at the PTEN locus has been described in a variety of neoplasms including breast cancer and Cowden Disease. However, the role of PTEN alterations and its association with clinicopathological factors have not been well established. We investigated the relationship between the PTEN expression and clinicopathological factors. Materials and Methods: Formalin-fixed, paraffin-embedded tissues from 105 women with breast cancer were evaluated for the PTEN expression and were scored semi-quantitatively based on staining intensity and distribution. Results were statistically compared with clinicopathological factors. Results: Forty-seven (45%) of the 105 breast cancers had a loss of the PTEN expression. In the recurrent group, 19 of 32 (59%) patients showed a loss of the PTEN expre- ssion, whereas in the non-recurrent group, only 28 of 73 (38%) patients showed a loss of the PTEN expression. The loss of PTEN expression correlated with estrogen receptors (ER) (p=0.027), recurrence (p=0.046), HER-2/neu overexpression (p=0.016), disease-free survival (p=0.0163), and overall survival (p=0.0357). In particular, when HER-2/ neu was overexpressed, the overall survival rate correlated with the loss of PTEN expression statistically (p=0.0454), whereas when HER-2/neu was negative, there was no correlation (p=0.9808). Progesterone receptor (PR) and disease stage had no relationship with the PTEN expression. Conclusion: Our results support that PTEN plays a role as a tumor suppressor in breast cancer and is a prognostic factor in predicting recurrence.

PURPOSE The dual-specificity phosphatase PTEN/ MMAC1/TEP1 has recently been identified as the tumor suppressor gene most frequently mutated and/or deleted in human tumors. However, PTEN mutations have rarely been detected in sporadic thyroid cancers. Therefore, this study investigated the PTEN expression of thyroid cancer and the relationship between PTEN, clinical status and other biologic factors such as HER-2/neu and p53. MATERIALS AND METHODS The study samples consisted of 62 thyroid cancer specimens and 24 benign thyroid tumor specimens from patients who were operated on the Department of Surgery, Uijongbu St. Mary's hospital during the 5 years from January 1995 until January 2000. All tumors were studied by immunohistochemical staining using monoclonal antibodies against PTEN, HER-2/neu and p53. The results were analyzed statistically. RESULTS PTEN protein was found to be under-expressed more frequently in thyroid cancers (29%) than in benign thyroid tumors (4.2%). The reduction in PTEN expression in thyroid cancers was not significantly related with the recorded clinical factors such as size, age, lymph node metastasis and p53, except for HER-2 which was found to be significantly related (p=0.001). HER-2 over- expression was noted in thyroid cancer (83.8%) more frequently than in benign tumors (16.7%). CONCLUSION This study has demonstrated that the under-expression of PTEN protein and the over-expression of HER-2 protein may play a role in the carcinogenesis and development of thyroid cancer.

In wireless sensor network applications for surveillance and reconnaissance, large amounts of redundant sensing data are frequently generated. It is important to control these data with efficient data aggregation techniques to reduce energy consumption in the network. Several clustering methods were utilized in previous works to aggregate large amounts of data produced from sensors in target tracking applications (Park in A dissertation for Doctoral in North Carolina State University, 2006). However, such data aggregation algorithms show effectiveness only in restricted environments, while posing great problems when adapting to other various situations. To alleviate these problems, we propose two hybrid clustering based data aggregation mechanisms. The combined clustering-based data aggregation mechanism can apply multiple clustering techniques simultaneously in a single network depending on the network environment. The adaptive clustering-based data aggregation mechanism can adaptively choose a suitable clustering technique, depending on the status of the network. The proposed mechanisms can increase the data aggregation efficiency as well as improve energy efficiency and other important issues compared to previous works. Performance evaluation via mathematical analysis and simulation has been made to show the effectiveness of the proposed mechanisms.

Conjunction of USB applications with wireless technologies leads us to USB over Wi-Fi through the means of Wireless Serial Extension (WSE). However, USB and Wi-Fi has distinct data prioritization methods, which causes problems in existing QoS protocols when the two technologies are used together. To solve this problem, this poster proposes and evaluates the dynamic QoS adaptation scheme, which intelligently maps the data of USB with the weighted transmission queues of enhanced distributed channel access (EDCA) mechanism.

We present a case of an intraperitoneal bronchogenic cyst located at inferior surface of the liver, next to the gallbladder which clinically mimicked a gallbladder tumor. This is the first case reported in Korea, and we offer reviews of the related literatures. A 48-yr-old woman was admitted to our hospital because of intermittent abdominal pain in right upper quadrant. Computed tomography showed a large mass alongside the gallbladder. During laparotomy, the mass showed an ovoid cystic nature, which was attached to the normal gallbladder and liver bed. Cyst excision with cholecystectomy was performed, and histopathological examination revealed a bronchogenic cyst. Most bronchogenic cysts have a benign nature, but malignant changes have also been reported. Therefore, if a cystic tumor in the abdomen is suspected during preoperative diagnosis, a bronchogenic cyst should be considered in the differential diagnosis.

Topology control offers many advantages for wireless networks such as reduced energy cost, simplified communication graph and network-wide connectivity. There are mainly two methods for managing the network topology. In clustering, a hierarchy of backbone nodes is selected to improve on the systems scalability and network lifetime whereas in power control each node adjusts its transmission power to achieve certain desirable properties of the resulting topology. While the focus of the former approach is to find an ideal number of the backbone nodes, the main objective of the later approach is to estimate a minimal power level which can solve multi-objective design problem. There have been several topology control protocols proposed however they miss the potential of combining both approaches. In this paper we propose Two-Tiered Topology Control (TTTC) protocol, a generic framework which combines the clustering and power control approach towards topology control and evaluate different conditions under which it performs well. TTTC operation is divided into two phases. During the first phase, a parameterized clustering algorithm is executed to obtain clusters of varying properties. At the end of first phase, the network is organized into two tiers. The backhaul-tier consists of cluster-head nodes while the connectivity-tier contains the cluster-members. In the second phase, each cluster-head runs a local MST-based power control algorithm. Simulation results show that proposed framework achieves efficient trade-off in terms of energy cost, neighbor count and hop count while maintaining fully connected network. Moreover, the framework relies on local available information with lower communication overhead.

This poster proposes an adaptive flow control scheme for reliable packet delivery of Universal Serial Bus (USB) services when they are transmitted through wireless medium. In the future, USB can be utilized with the Wi-Fi technology to provide Wi-Fi USB (WSB). However, the data transmission of Wi-Fi and USB are asynchronous due to their different Medium Access Control (MAC) characteristics, which may result in buffer overflow. To prevent buffer overflow, we propose an adaptive flow control scheme that can select between the various transmission speeds of USB to match with the bandwidth provided by the Wi-Fi layer. Preliminary results of the proposed scheme evaluated via the NS-3 shows that the packet delivery ratio of USB data can be substantially increased, thus providing better USB reliability.

We present a patient with phakomatosis pigmentovascularis (PPV) type IIb accompanied with venous hypoplasia, from the inferior vena cava to the superficial femoral vein. Although it is not obvious whether this vascular anomaly, which is probably congenital, is coincidental or not, it is possible that the 2 diseases have some relationship each other, because PPV is thought to result from abnormal vasomotor activity during the embryonic period. In the diagnosis of type II PPV, careful examination and several studies are required to determine systemic involvement that may include large vessel changes.

This paper focuses on enhancing IEEE 802.11e EDCA for improving reliability in Smart grid networks. 802.11e can support prioritized QoS to differentiate traffic and guarantee fairness for delay-stringent applications. However, this may pose serious problems when applied to Smart Grid environments which support applications that have strict reliability requirements. To solve this problem, we suggest a contention mitigated EDCA algorithm (CM-EDCA), which utilizes packet collision and MAC retransmission parameters to change the packet priority and reduce packet collisions. The proposed scheme is compatible with IEEE 802.11e and easy to implement for Smart grid devices. Simulation studies show improved reliability compared to the existing methods in IEEE 802.11e.

We propose and demonstrate an adaptive wireless mesh network architecture for public surveillance and monitoring. The proposed architecture is based on IEEE 802.11s WLAN mesh network, which is enhanced to provide adaptation depending on the environment of the network. We first introduce the implementation architecture of the adaptive mesh, and then describe the demonstration of the network on the wireless mesh camera sensor testbed.

This paper proposes a practical lightweight scheme for channel problem detection and adaptation in energy-constrained multi-hop wireless networks. Generally, handheld devices such as smart phones have functional constraints that limit them from utilizing multiple radio interfaces. Even with these limits, these nodes must be able to efficiently detect and avoid interfered channels. We propose a novel channel sensing and adaptation method that is suitable for these environments, and analyze it through implementation to prove its superiority.

Soldier-based tactical radio systems in the battlefield have tendencies to be severely affected by various phenomenon such as signal jamming and environment deterioration. This is because many types of wireless handheld and manpack devices carried by soldiers may not have efficient algorithms or the hardware for adapting the device to these conditions. Taking on the advantage that most of these devices use software-defined radios but do not fully utilize its functionalities, we present channel quality estimation and channel adaptation algorithms that can solve the problems of these devices. We utilize simple and practical channel problem detection methods by constantly monitoring the channel quality parameters such as signal-to-interference-noise ratio and clear channel assessment value while inducing low overhead. Furthermore, we propose efficient channel adaptation methods that can quickly sense and avoid deteriorated channel conditions. Via the experimental studies, we implement our proposed scheme on actual testbeds and show that it can improve the performance and mission-criticality of the tactical networks.

In video surveillance and monitoring systems based on wireless mesh networks, large volumes of multimedia data with different priorities and time demands are generated by video cameras and wireless sensors. Hence, one of the key issues is how to alleviate network congestion for highly reliable transfer of multimedia data towards gateways. This paper proposes a solution for utilizing multiple gateways to divert data streams and alleviate traffic congestion near a specific gateway. With a new routing protocol, named “Multi-Gateway Routing with Congestion Avoidance (MGR-CA)”, network congestion can be predicted in a distributed manner and amounts of data traffic transmitted to the congested path are redirected to an alternative gateway based on the severity of congestion. Preliminary testbed experiments are made to show the performance of our scheme.