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This paper proposes a method to reduce turn-on and turn-off switching losses of a direct-current-direct-current (DC-DC) buck converter. A passive snubber circuit, which includes one inductor, one resistor, two diodes and three capacitors, was used to increase the power conversion efficiency. The maximum efficiency of the proposed converter for an output power of 120 W was measured as 96.33%, which is 0.62 ~1.46% higher than the conventional buck converter and other buck converters with the passive snubber circuits. The proposed snubber circuit operates stably under sudden changes in the load.

To supplement resistor fail of conduction bridge random access memory (CBRAM), various device fabrication methods have been suggested such as exploiting metal alloy as a cation supply layer or electrode [1]–[2], cation doped electrolyte [3]–[4], and confining cation injection with inserted buffer layer [5]–[6]. In this work, Cu cone structure embedded CBRAM device is suggested for improving switching reliability and uniformity. Along with cone structure fabrication method through wet etching, reliability improvement induced by field concentration is included.

In this paper, the authors report for the first time the outstanding selector performance from an innovative oxide selector. SiO2, one of conventional and common materials in semiconductor industry, was chosen as a matrix oxide material. Metal atoms which are non-mobile and easy to handle were injected into the oxide films. Off-current and threshold voltage (V th ) could be controlled by using arsenic (As), which doping method and concentration were carefully investigated to achieve threshold switching behavior. Finally ReRAM (Resistance switching Random Access Memory) cell array consisted of one selector-one resistor (1S1R) was successfully demonstrated with the full integration of the newly developed selector.

In order for an autonomous vehicle to drive safely, map data with accurate path information is required. Using Latitude and Longitude coordinate information from GPS (Global Positioning System) and GIS (Geographic Information System), an autonomous vehicle generates path data and obeys these data when driving. When the total travel(raw) path is too long, this system divides raw path into multiple sub-sections(segments) using higher degree polynomial equation curve fitting and this method enable efficiently uses path data. However, these curve fitting location data cannot be expressed as perfectly linear line even if raw path is straight, and therefore, these data always include lateral position error compared with raw path. Moreover, gather volume of lateral position error generated by GPS and IMU (Inertial Measurement Unit), oscillation on straight path is inevitable. This research uses moving average and different filter size according to segment size. Finally, via experiment with a real vehicle, system is confirmed to countering oscillation.

In this Paper, to provide the Multi-Layer Based on Path Planning System(MLPPS) for generated optimal path. Previously used path planning system, single-layer based on path planning system, local map of the path in a single situation was ensured by the optimal path. However, there is a problem that continuously local map is acquired to update the more than necessary parts of the map. These problem are due to the continuous path update, can maintain the unnecessary paths, so that it is impossible to ensure optimal path planning system. To solve this problem, we propose MLPPS. Unlike single layer path planning system, MLPPS was divided Under Layer Path Planner and Upper Layer Path Planner. Under Layer Path Planner is generated the local path. And Upper Layer Path Planner is transmitted the optimal path to autonomous vehicle. The Arbiter is present between the two layers. Arbiter through the decision-making local path of the Under Layer Path Planner is to determine whether the optimal path. In the remainder of this paper, it describes how to generate local paths by Under Layer Path Planner and optimal path determined by Arbiter.

In this paper, the authors report that 2x nm cross-point ReRAM with 1S1R structure has been successfully developed. Off-current at 1/2 Vsw of 1S1R is one of key factor for high-density ReRAM. NbO2 was chosen as a selector material and off-current and forming characteristics were improved by using stack engineering of top and bottom barriers as well as spacer materials. Finally array operation was characterized with the integration of selector and resistor materials.

Active safety systems have been gradually introduced by more car manufacturers, to wider portions of the automotive market. Many of these systems shared hardware and are integrated with other systems that do not involve automated emergency braking, such as adaptive cruise control, forward collision warning and predictive brake assist systems [1]. But in fact, there are many times when we have to face the emergency brake. So it is also necessary to design a high performance braking system. And there are a lot of issue on our unmanned vehicle deceleration controller too. In this paper we focus design of autonomous vehicle advanced braking system using DC smart servo motor torque controller. Vehicle longitudinal control model is established in Labview2012. By the real time experiments on Grandeur HG 330 made in Hyundai Motor Group Co. Ltd

This paper proposes a current-fed two inductor bi-directional DC-DC converter using resonance (CF-TIBCR). The power losses of CF-TIBCR mainly occur in switches, especially the low voltage side switches. To improve the efficiency, the detailed loss analysis of switch and magnetic components is performed from the steady state analysis and operation principles. To verify theoretical loss analysis, it is compared with experiment results using a laboratory prototype converter with 500W. Finally, several method are derived to improve efficiency.

In this paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of vehicle detection base on vision processing system. As a preprocessing for high speed vehicle detection in the night, the vanishing line estimation and the optimal extraction of ROI (region of interest) for can be processed to reduction of detection region in which high speed processing is enabled. In order to get better performance the image need pre-processing. Legally vehicle tail light must be red color, so we use the red plane image with simultaneous processing of noise reduction and edge enhancement using the adv morphology function. And then give Dilation and Erosion eliminating the noise through the process of Morphology. Finally, using the Projection-Histogram information get the center of mass by restricting threshold detects a vehicle in the ROI. This method is more efficient than simply detecting and sliding the entire screen. Finally, the various real road experimental results are presented to evaluate the effectiveness of the proposed method.

This paper proposes current-fed two-inductor bi-directional DC-DC converter using resonance(CF_TIBCR) for high efficiency and high step-up applications. Conventional dual half bridge(DHB) converter have problems of high voltage spikes and unavailable charge/discharge resulting from uni-directional converter. Hence, operating frequency and the efficiency are also limited. To solve these problems and achieve high efficiency, in this paper, the diode of the high voltage side is replaced by metal oxide semiconductor FET(MOSFET). All active switches undergo zero voltage switching(ZVS) condition. Especially, switches of the low voltage side are satisfied with zero current switching(ZCS) condition and ZVS condition. The steady state analysis and operation principle of CF_TIBCR is introduced. The DC voltage conversion ratio is derived based on steady state analysis. Simulation using PSIM is implemented to verify CF_TIBCR.

A rigid motion correction technique is applied to both PET and CT data from the Siemens mCT PET/CT scanner. Motion was applied to a Hoffman brain phantom during both the CT and PET scans, as well as between them. The motion data, which was tracked by an external motion tracker, was used to correct the motion corrupted tomographic data during reconstruction. The motion corrected CT reconstruction was used for attenuation correction in the PET reconstruction. The subsequent reconstructions are compared to scans taken without motion to show the effectiveness of the motion correction.

The waypoint tracking method of many methods is common. The raw-data included information(road shapes, speed bumps, signal lights, stop lines, etc) to need when do autonomous driving in downtown suggest a available method and a effective data-management method. The existing waypoint tracking method is greater reliance on raw-data. That's because of the only latitude and longitude data. This is not flexible in using data, so with INS, the reduction zone of speed and stop live such as speed bumps, intersections, turnings, crosswalks compared to stopping zone like railroad, these data is stored with waypoint data. Data made by this way becomes essential information to speed planning by road shape and activation time of suitable sensor in necessity. Additionally, the waypoints with latitudes and longitudes information include various road information. The real road of in downtown is stored by segment through polynomial fitting. If certain format is stored about all the roads, not only efficient data management, speed planning of road shape and environment perception but also avoidance path planning of multilane road and path planning of in downtown such as lane change based on necessary information can be realized and it can be possible to drive more efficiently.

In this paper, we propose a monocular camera-based vehicle detection system for use in autonomous vehicles. In order to accurately and rapidly detect a vehicle on the real road, we have designed a vehicle detection system that follows two basic steps namely; Hypothesis Generation and Hypothesis Verification. In the hypothesis generation step, a candidate region of vehicles is set by using the shadow properties of the vehicle. In the hypothesis verification step, based on the candidate regions, we are able to distinguish between the vehicle and the non-vehicle. For the hypothesis verification, we use histograms of oriented gradients (HOG) feature and support vector machine (SVM) classifier. To fit the vehicle detection system, detailed settings of the HOG such as the cell, block and bin were selected.

In this paper, we present a method for the vehicle suddenly cut-in from the lateral direction during the preceding vehicle tracking. In the longitudinal direction tracking, if there is no prediction of the interruption located in lateral position vehicles, sudden braking causes when the vehicle cut-in from the longitudinal direction, it is possible to increase anxiety of passengers and reduce the reliability of the autonomous vehicle system. In order to ensure the safe braking distance and smooth braking control, in this paper, we present the tracking method. If lateral position vehicle cut in front of ego vehicle, while ego vehicle follows the preceding vehicle in the region of interest, we can calculate lateral relative distance and relative velocity of the vehicle located in the lateral position by the laser scanner. As an alternative, we put the relative distance data and the relative speed data from the lateral position vehicle in the fuzzy logic system. If probability that the lateral position vehicle cut-in on ego vehicle lane is more than threshold value and lateral distance closed than side lane, the system dertermines the new situation, perform distance control for safety braking with new tagets.

In this paper, energy storage system(ESS) operation algorithm for economics considering battery degradation properties is proposed. Hourly electricity charge according to real-time pricing (RTP) and battery properties are analyzed for high profit through ESS operation. Especially, hourly electricity charge of Illinois State is analyzed. Characteristics of battery accounts for a high percentage of ESS configuration. Thus, degradation properties of the battery for the price considering the loss of battery usage is considered. The algorithm is proposed for the highest profit through analysis of the battery degradation properties and electricity charge, and the proposed algorithm is verified by mathematical analysis.

Method of improving the safety of autonomous vehicles are diverse. In particular, Path Tracking phase which is the last step and important to operate an autonomous vehicle. Method of Path tacking are diverse. Kinematic and dynamic methods is typically methods. In this study, Among Kinematic method, Pure pursuit is used by using the path tracking. Commonly pure pursuit is used to path tracking of mobile robots. Pure pursuit is selected target point and is path traced When selecting the tracking target point, the traveling speed is low or, in certain cases, to extract the following target point at a fixed distance. However, the speed and the path of autonomous vehicle is continually changing. Therefore, the selection method of tracking a target point of the fixed distance, can inhibit the behavioral stability of the vehicle. Also affect the path tracking performance. Therefore, changing of the tracking target point is advantageous.

This paper is research about unmanned ground vehicle for path planning. based on global path to optimal path generating. The proposed algorithm was used to D*Lite and lateral avoidance algorithm. This algorithm used to global map and search obstacle. Presented safety avoidance path planning thought Velocity of autonomous vehicle. safety obstacle avoidance according to velocity. Current Autonomous vehicles are safety and reliable for driving research. In this paper, autonomous vehicle as a way of escaping the lateral avoidance D * Lite algorithm was used. according to the speed of the vehicle for optical lateral avoidance control for steering for the purpose of path generation. The proposed study is one of the driving research of the UGV to explore and avoid unknown obstacles on the unlimited path.

The general frame size in an IEEE 802.11 wireless LAN environment is often much smaller than the specified MTU size. The small size of the frames increases the MAC layer traffic and can cause degradation in network performance. In this paper, we propose new IP packet concatenation methods that are able to merge two or more IP packets with same destination addresses into a MPDU. Our method provides a continuous monitoring of the channel state. If there are IP packets that can be concatenated, the concatenation is carried out at the same time as the channels are allocated to other nodes. At the receiving end, the data size of the received MPDU and the total length field in the IP header are compared to determine whether the received frame is concatenated or not. Our proposed method avoids any packet concatenation delay. When MAC layer traffic is low, our method provides a similar performance to existing wireless LANs. Our method can also improve the transmission performance as an increase in MAC layer traffic results in a decrease in the total traffic.

In this study, it starts to plan speed unmanned ground vehicle is stabilized in accordance with the state of the road surface. Through the interlocking speed control system that utilizes a slip ratio of the tire becomes unmanned ground vehicles, and accessed. After confirming the state of the road surface or wet road surface was dry, it was planned speed. The experimental results to determine the state of the road surface or wet road surface and dry tire slip ratio, it was definitely velocity control.

This paper is an overview of the UGV (Unmanned Ground Vehicle)'s technical aspects. Among them, it contains information on the vision sensor which is responsible for the visual part using input image data. First, it describes role of vision sensor in Unmanned Ground Vehicle. Next, it explains image processing system applied to the necessary algorithms about UGV's obstacle detection.

In this research, began to research for create local map for the unmanned ground vehicle to create efficient driving path. Detected space that car can drive freely and to create local map based on information of the free-driving space. Generate disparity image using stereo image and by utilizing the uv-disparity domain that has been converted from disparity image to classify surrounding environment, obstacles space and ground space. Finally, create local map by using the free-driving space that classified so can it be referenced when generate driving path.

In this research, there is not only the success of the parking area by Unmanned Ground Vehicles , the purpose of Efficient parking within parking areas are intended to lead. Multiple unmanned Ground vehicles and private vehicles to target studies are carried out based on the proposed Cost map. Cost map is generated by the steps that can be used in a path planning algorithm and Topological map is built in the form of parking area is used to generate optimal path for vehicle guidance.

This paper describes the 3D map generation for UGV(Unmanned Ground Vehicle) using 2D laser scanner. We have developed the 3D mapping system by integrating 2D laser scanner and motor driven revolution device. This platform has advantageous that one 3D laser scanner can displace multiple 2D laser scanners; 2D laser scanner could obtain limited data from terrain. The approach presented in this paper describes the mapping of driving environments and obstacle detecting of UGV by using a 3D mapping system

Patient motion is a significant problem in pediatric PET/CT, and motion correction techniques could potentially remove the need for anaesthesia or sedation that are normally required for very young patients. Effective methods exist for motion correction of neurological PET images, and although there is a scarcity of equivalent methods for CT, a potential method of correcting for rigid head motion during the CT scan has recently been proposed. In this study, we describe a motion tracking method for CT using an optical motion tracking system. Since pose is reported in tracker coordinates, and motion correction requires motion in CT scanner coordinates, a calibration is required to determine the transformation needed to convert between the coordinate systems. We describe such a calibration method, and evaluate it by acquiring two CT scans of a Hoffman 3D brain phantom, with a tracker target attached, in different poses. The applied motion between two scans was calculated from the change in target pose measured by the tracker, and converted to scanner coordinates. This motion was applied to one of the reconstructed image volumes, which was then compared with the other image volume. The mean registration error of the two volumes was estimated from landmark analysis to be less than 0.3 mm on average in all directions, which agreed well with a calculated maximum uncertainty of 0.7 mm. Errors of this magnitude could be acceptable if the CT scans were only used for attenuation correction, but may need to be further reduced for motion correction applications. We anticipate that this will be achievable with improvements to our technique, and intend in future work to use motion data to attempt motion correction in spiral CT studies.

These Ordered mesoporous aluminum oxide films with porosity ranges of 5 to 37% were synthesized by evaporation-induced self-assembly (EISA) using surfactant templating. To investigate the effects of mesoporous structure on mechanical properties, changes in pore structure properties including pore distribution and porosity were monitored as functions of surfactant concentration (Pluronic P-123, PEO 20 PPO 70 PEO 20 ). The structural properties were analysed using powder X-ray diffractometer and grazing-incidence small-angle x-ray scattering in PLS 4C2 beamline. These alumina films had body-centered cubic pore structure or random-oriented pore structure depending on the surfactant concentration used, and different mechanical properties were obtained depending on the pore structure. Therefore, a control of pore structure in mesoporous materials is the important factor to strengthen the porous structural materials.

Recently, the block cipher is one of the most common security primitive for the data-confidentiality. In this paper, we present an efficient implementation method of block cipher in the Android platform by using the Native Development Kit(NDK). We also compare performance result of our implementation with Bouncy Castle library.

As Graphic Processing Units (GPUs) are increasingly being used for general purpose computing, researches on applying GPUs for processing a number of crypto operations have been conducted. In this paper, we present an efficient implementation of Korean Certificate-based Digital Signature Algorithm (KCDSA) on GPU using CUDA platform. Using modern GTX285, throughput of up to 10,600 signings per second can be reached. At this time, the proposed software can achieve 25 times of improvement on GTX285 compared with KCDSA software on CPU-side. Our software can be used for Cloud-computing and distributed server computing environments which have to process a number of crypto operations in short time period as a crypto accelerator.

This paper suggests a longitudinal control algorithm for vehicles which drive on the slope road. Having uneven or Slope road, actual driving conditions could be changed frequently. Driving vehicles, people can perceive the road condition with their visual organ and sense of balance. And then they control their vehicles more safely by reflecting various conditions on operating. Without this process, the driving-stabilization on slope roads would fall considerably, and the problem could be directly connected to terrible accident. This thesis, therefore, we will show that how to acquire unmanned vehicle quite information of slope road, and developing an algorism that is reflecting it on driving, and verifying the performance of the suggested algorism through on-road vehicle test.

The existing path plan algorithms repeat process until reach to goal position (from the start position). As result of process, path plan algorithms create the optimal paths. From the algorithm point of view, created paths are optimal paths because paths are the shortest and lowest. But this path does not consider unit's moving characteristics. The current path plan algorithms have been developing that solving and supplementing the part of problems about the grid map environment. According to the passage, methods of the solving and supplementing can divide two ways. First method is path smoothing, second method is the Field D∗ algorithm. If the path smoothing is adapted in Global size (Global path in Global map), in such that case, the time constraint is not important but the optimal path will be modified. And modification of the optimal path like to has serious problems. Field D∗ algorithm is powerful path plan algorithm and this algorithm is not postprocessing like a path smoothing. And in a way it guarantees real-time path creations. But local size (local path in local map)'s real-time do not guarantee perfectly. On the basis of facts, we suggest the Unmanned Ground Vehicle (we abbreviate the word by 'UGV')'s new path plan algorithm that included UGV's moving characteristics.

This paper would like to design the failsafe architecture to ensure the stability and safety of unmanned ground vehicle (UGV). Because the failure in the unmanned systems can cause a nasty accident. So, first, we limit the discussion to the UGV in the unmanned systems. And then we find out failure for the UGV which consists of the variety of the hardware, and discuss the danger. And we define the level and the measurement for the failure. Lastly, we design the failsafe architecture based on the Joint Architecture for Unmanned Systems (JAUS).

Position based routing protocols have been a great deal of attention in vehicular ad hoc networks. The routing protocols are very efficient in high mobility ad hoc network since the path to a destination can be proactively determined by location information of neighbor and destination nodes. However, this causes the leakage of the private information of drivers, such as a vehicle identifier or location information of a vehicle. Hence, providing privacy of a user should be considered in the protocol. In this paper, we design a novel routing protocol, called SARC, which provides efficient path discovery and privacy protection in route discovery and data forwarding phase. To achieve this goal we present a street-based path calculation algorithm for route discovery, and define and analyze the identity, location, and route anonymity in our protocol.

This research proposes a navigation algorithm using multiple GPS units and a differential GPS (DGPS) unit simultaneously, a compass, encoders, and optimized global mapping. GPS systems sometimes lose their signals and receive inaccurate position data due to many factors, such as obstructions. This paper shows that GPS failure can be solved by using a DR navigation method with encoders and a compass, and that position errors can be decreased by using multiple GPS units and a DGPS unit. In addition to this method, a smoothing algorithm will be used to improve the UGVpsilas driving ability, and an expanded-route data definition file (Ex-RDDF) will be created to compare with current data to estimate GPS error.

This paper introduces an optimal algorithm through analyzing and studying various algorithms used in DARPA Urban Challenge 2007 and making a numerical statement about each algorithm. The top eleven teams that passed the NQE (national qualifying event) used Dijkstra, A*, RRTs, and D*. Therefore, this research will focus on those algorithms and study a method to apply an optimal algorithm.

This article describes the design of a vision sensing system with application to the urban operation of unmanned ground vehicles. This paper details a procedure for the detection, classification, and localization of lane markings and speed bumps to safely and autonomously navigate an urban roadway. The detection algorithm was developed using National Instruments LabVIEW tool using a CCD camera over 1394 data interface. To demonstrate the algorithmpsilas effectiveness, experimental results were obtained when applying the algorithm in extreme lighting conditions including shadow, noise, and bright scenarios which showed the approach as responsive and robust to such variations.

This paper describes a system for estimating various driving environments using multiple laser measurement scanners (LMS) which are part of the obstacle estimation system on an unmanned ground vehicle (UGV). An LMS is an important and popular sensor for obstacle and terrain detection on a UGV system. The obstacle and terrain detection system is a critical system for a UGV to reach its final goal point. The obstacle and terrain detection system implemented consists of one processing unit and five laser scanners. In this paper, the UGV system configuration will be introduced and terrain estimation using fused data from all of the laser scanners will be explained.

Polymer random access memory is a next-generation nonvolatile memory device possessing two stable states of which their respective resistances differ by more than a factor of 100. This memory device is easy to integrated and mass produce because it has a sandwich-like One-Resister structure forming a cross-point cell array. The previous cell array structure makes it difficult to read data correctly because of current interference between cells. In this paper, to solve these problems, a new cell array called a ldquorow chain cell arrayrdquo is suggested that does not produce current interference. To the multi-cell read data, especially we have adjusted this structure. They are verified by simulation. Furthermore, to write/erase data, we propose a new architecture and verify that the required voltages are applied to the selected cell.

According to augmentation about interests for privacy in mobile network over the past few years, researches that provide the anonymity have been conducted in a number of applications. Ad hoc routing protocols with the provisions for anonymity both protect the privacy of nodes and also restrict the collection of network information by malicious nodes. Until recently, quite a number of anonymous routing protocols have been proposed. Many of them, however, do not make allowance for authentication. Thus, vulnerabilities such as modifications to packet data and denial of service attacks can be more easily exploited. In this paper, we propose the anonymous routing protocol also furnishing authentication in the mobile ad hoc network. This protocol supports these anonymity properties which should be provided in ad hoc network. In addition, authentication is also provided by group signature for both nodes and packets during route discovery phase.

In packet communication systems, a header is attached to the transmitted packet at each layer. The overhead due to the transmission of the individual header can have significant impact on the performance of the communication system especially when the system operates in the heavy load. In order to increase data throughput, a number of packets can be aggregated into a frame in a particular OSI layer. In this paper, we present a queuing model with batch service which describes a packet aggregation process for Poisson arrivals and Phase-type service time distributions of the transmitted packets. We focus on the asymptotic behavior of such systems providing a significant reduction in the numerical complexity of their solution and provide analysis of the end-to-end delay of a packet transmitted by the system. Simple expressions for bounds on the average total delay of a packet are obtained. Based on results of experiments with the analytical model, we provide the minimum header size for which packet aggregation improves the system performance. It is numerically shown that the impact of the variability of the packet service time is rather insignificant when the system load is moderate or low. We also examine numerically the accuracy of the bound on the average total packet delay.