Because of its simplicity and intuitive approach, point-based rendering has been a very popular research area. Recent approaches have focused on hardware-accelerated techniques. By applying a deferred shading scheme, both high-quality images and high-performance rendering have been achieved. However, previous methods showed problems related to depth-based visibility computation. We propose an extended point-based rendering method using a visibility map. In our method we employ a distance-based visibility technique (replacing depth-based visibility), an averaged position map and an adaptive fragment processing scheme, resulting in more accurate and improved image quality, as well as improved rendering performance.

Classification of terrain is one of the most important applications of Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. This paper presents a simple method to classify terrain by the use of the correlation coefficients in the circular polarization basis together with the total power of the scattering matrix in the X-band. The reflection symmetry condition that the co-polarized and the cross-polarized correlations are close to zero for natural distributed scatterers is utilized to extract characteristic parameters of small forests or cluster of trees, and oriented urban building blocks with respect to the direction of the radar illumination. Both of these kinds of scatterers are difficult to identify in high resolution POLSAR images of complex urban areas. The indices employed here are the correlation coefficient, a modified coefficient normalized by the reflection symmetric conditional case, and the total power. It is shown that forest areas and oriented building blocks are easily detected and identified. The terrain classification yielded by these combinations is very accurate as confirmed by photographic ground truth images.

This paper presents an RK-means clustering algorithm which is developed for reliable data grouping by introducing a new reliability evaluation to the K-means clustering algorithm. The conventional K-means clustering algorithm has two shortfalls: 1) the clustering result will become unreliable if the assumed number of the clusters is incorrect; 2) during the update of a cluster center, all the data points belong to that cluster are used equally without considering how distant they are to the cluster center. In this paper, we introduce a new reliability evaluation to K-means clustering algorithm by considering the triangular relationship among each data point and its two nearest cluster centers. We applied the proposed algorithm to track objects in video sequence and confirmed its effectiveness and advantages.

This paper addresses the issue of transmission scheduling in wireless ad hoc networks. We propose a Time Division Multiple Access (TDMA) scheduling scheme based on edge coloring and probabilistic assignment, called CP-TDMA. We categorize the conflicts suffered by wireless links into two types: explicit conflicts and implicit conflicts, and utilize two different strategies to deal with them. Explicit conflicts are avoided completely by a simple distributed edge-coloring algorithm µ-M, and implicit conflicts are minimized by applying probabilistic time slot assignments to links. We evaluate CP-TDMA analytically and numerically, and find that CP-TDMA, which requires only local information exhibits a better performance than previous work.

This paper studies the relations among several definitions of anonymity for ring signature schemes in the same attack environment. It is shown that one intuitive and two technical definitions we consider are asymptotically equivalent, and the indistinguishability-based technical definition is the strongest, i.e., the most secure when achieved, when the exact reduction cost is taken into account. We then extend our result to the threshold case where a subset of members cooperate to create a signature. The threshold setting makes the notion of anonymity more complex and yields a greater variety of definitions. We explore several notions and observe certain relation does not seem hold unlike the simple single-signer case. Nevertheless, we see that an indistinguishability-based definition is the most favorable in the threshold case. We also study the notion of linkability and present a simple scheme that achieves both anonymity and linkability.

Recently Tate pairing and its variations are attracted in cryptography. Their operations consist of a main iteration loop and a final exponentiation. The final exponentiation is necessary for generating a unique value of the bilinear pairing in the extension fields. The speed of the main loop has become fast by the recent improvements, e.g., the Duursma-Lee algorithm and ηT pairing. In this paper we discuss how to enhance the speed of the final exponentiation of the ηT pairing in the extension field F36n. Indeed, we propose some efficient algorithms using the torus T2(F33n) that can efficiently compute an inversion and a powering by 3n + 1. Consequently, the total processing cost of computing the ηT pairing can be reduced by 16% for n=97.

In Shamir's (k,n)-threshold secret sharing scheme [1], a heavy computational cost is required to make n shares and recover the secret from k shares. As a solution to this problem, several fast threshold schemes have been proposed. However, there is no fast ideal (k,n)-threshold scheme, where k ≥ 3 and n is arbitrary. This paper proposes a new fast (3,n)-threshold scheme by using just EXCLUSIVE-OR(XOR) operations to make shares and recover the secret, which is an ideal secret sharing scheme similar to Shamir's scheme. Furthermore, we evaluate the efficiency of the scheme, and show that it is more efficient than Shamir's in terms of computational cost. Moreover, we suggest a fast (k,n)-threshold scheme can be constructed in a similar way by increasing the sets of random numbers constructing pieces of shares.

The present paper describes an implementation of an intrusion detection system (IDS) on an FPGA for 10 Gigabit Ethernet. The system includes an exact string matching circuit for 1,225 Snort rules on a single device. A number of studies have examined string matching circuits for IDS. However, implementing a circuit that processes a large rule set at high throughput is difficult. In a previous study, we proposed a method for generating an NFA-based string matching circuit that has expandability of processing data width and drastically reduced resource requirements. In the present paper, we implement an IDS circuit that processes 1,225 Snort rules at 10 Gbps with a single Xilinx Virtex-II Pro xc2vp-100 using the NFA-based method. The proposed circuit also provides packet filtering for an intrusion protection system (IPS). In addition, we developed a tool for automatically generating the Verilog HDL source code of the IDS circuit from a Snort rule set. Using the FPGA and the IDS circuit generator, the proposed system is able to update the matching rules corresponding to new intrusions and attacks. We implemented the IDS circuit on an FPGA board and evaluated its accuracy and throughput. As a result, we confirmed in a test that the circuit detects attacks perfectly at the wire speed of 10 Gigabit Ethernet.

High power consumption is a constraining factor for the growth of programmable logic devices. We propose two techniques in order to reduce power consumption. The first is a technique for creating contexts. This technique uses data-dependent circuits and wire sharing between contexts. The second is a technique for switching the contexts. In this paper, we evaluate the capability of the two techniques to reduce power consumption using a multi-context logic device. As a result, as compared with the original circuit, our multi-context circuits reduced the power consumption by 9.1% on an average and by a maximum of 19.0%. Furthermore, applying our resource sharing technique to these circuits, we achieved a reduction of 10.6% on an average and a maximum reduction of 18.8%.

Our purpose is to estimate conditional probabilities of output labels in multiclass classification problems. Adaboost provides highly accurate classifiers and has potential to estimate conditional probabilities. However, the conditional probability estimated by Adaboost tends to overfit to training samples. We propose loss functions for boosting that provide shrinkage estimator. The effect of regularization is realized by shrinkage of probabilities toward the uniform distribution. Numerical experiments indicate that boosting algorithms based on proposed loss functions show significantly better results than existing boosting algorithms for estimation of conditional probabilities.

A parametric linear filter for a linear observation model usually requires a parameter selection process so that the filter achieves a better filtering performance. Generally, criteria for the parameter selection need not only the filtered solution but also the filter itself with each candidate of the parameter. Obtaining the filter usually costs a large amount of calculations. Thus, an efficient algorithm for the parameter selection is required. In this paper, we propose a fast parameter selection algorithm for linear parametric filters that utilizes a joint diagonalization of two non-negative definite Hermitian matrices.

One challenging issue of sensor networks is extension of overall network system lifetimes. In periodic data gathering applications, the typical sensor node spends more time in the idle state than active state. Consequently, it is important to decrease power consumption during idle time. In this study, we propose a scheduling scheme based on the history of RTS/CTS exchange during the setup phase. Scheduling the transmission during transfer phase enables each node to turn off its RF circuit during idle time. By tracing ongoing RTS/CTS exchange during the steady phase, each node knows the progress of the data transfer process. Thereby, it can wait to receive packets for data aggregation. Simulation results show a 160-260% longer system lifetime with the proposed scheduling scheme compared to the existing approaches.

In this paper, we propose a multipath en-route filtering method to deal with the problems caused by black hole attacks and selective forwarding attacks. Our result shows that the method is more resilient to these problems up to a certain number of compromised nodes than the statistical en-route filtering scheme.

Many devices are expected to be networked with wireless appliances such as radio frequency identification (RFID) tags and wireless sensors, and the number of such appliances will greatly exceed the number of PCs and mobile telephones. This may lead to an essential change in the network architecture. This paper proposes a new network architecture called the appliance defined ubiquitous network (ADUN), in which wireless appliances will be networked without network protocol standards. Radio space information rather than individual appliance signals is carried over the ADUN in the form of a stream with strong privacy/security control. It should be noted that this is different from the architectural principles of the Internet. We discuss a network-appliance interface that is sustainable over a long period, and show that the ADUN overhead will be within the scope of the broadband network in the near future.

In this paper, we propose a method of controlling personal data disclosure based on LooM (Loosely Managed Privacy Protection Method) that prevents a malicious third party from identifying a person when he/she gets context-aware services using personal data. The basic function of LooM quantitatively evaluates the anonymity level of a person who discloses his/her data, and controls the personal-data disclosure according to the level. LooM uses a normalized entropy value for quantifying the anonymity. In this version of the LooM, the disclosure control is accomplished by adding two new functions. One is an abstracting-function that generates abstractions (or summaries) from the raw personal data to reduce the danger that the malicious third party might identify the person who discloses his/her personal data to the party. The other function is a unique-value-masking function that hides the unique personal data in the database. These functions enhance the disclosure control mechanism of LooM. We evaluate the functions using simulation data and questionnaire data. Then, we confirm the effectiveness of the functions. Finally, we show a prototype of a crime-information-sharing service to confirm the feasibility of these functions.

Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes, with the goal of deceiving the base station or depleting the resources of forwarding nodes. Several research solutions have been recently proposed to detect and drop such forged reports during the forwarding process. Each design can provide the equivalent resilience in terms of node compromising. However, their energy consumption characteristics differ from each other. Thus, employing only a single filtering scheme for a network is not a recommendable strategy in terms of energy saving. In this paper, we propose a fuzzy-based adaptive filtering scheme selection method for energy saving. A fuzzy rule-based system is exploited to choose one of three filtering schemes by considering the false traffic ratio, the security threshold value, distance, and the detection power of the filtering scheme. The adaptive selection of the filtering schemes can conserve energy, and guarantee sufficient resilience.

This paper addresses a new surface reconstruction scheme for approximating the isosurface from a set of tomographic cross sectional images. Differently from the novel Marching Cubes (MC) algorithm, our method does not extract the iso-density surface (isosurface) directly from the voxel data but calculates the iso-density point (isopoint) first. After building a coarse initial mesh approximating the ideal isosurface by the cell-boundary representation, it metamorphoses the mesh into the final isosurface by a relaxation scheme, called shrink-wrapping process. Compared with the MC algorithm, our method is robust and does not make any cracks on surface. Furthermore, since it is possible to utilize lots of additional isopoints during the surface reconstruction process by extending the adjacency definition, theoretically the resulting surface can be better in quality than the MC algorithm. According to experiments, it is proved to be very robust and efficient for isosurface reconstruction from cross sectional images.

In this study, a wideband 3/4 elliptical ring patch operating millimeter wave band is proposed. Using this structure, the patch antenna is designed for circular polarization and wide-band operation at about 32.1-40 GHz for millimeter wave communication. Simulated and measured results for main parameters such as voltage standing wave ratio (VSWR), impedance bandwidth, axial ratio, radiation patterns and gains are also discussed. The study shows that modeling of such antennas, with simplicity in designing and feeding, can well meet the requirements of millimeter-wave wireless communication systems.

Wireless content sharing where peers share content and services via wireless access networks requires user contributions, as in fixed P2P content sharing. However, in wireless access environments, since the resources of mobile terminals are strictly limited, mobile users are not as likely to contribute as ones in fixed environments. Therefore, incentives to encourage user contributions are more significant in wireless access environments. Although an incentive service differentiation architecture where the content transfer rate is adjusted according to the contributions of each downloading user has been already proposed for fixed P2P, it may not work well in wireless access environments because several factors effect wireless throughput. In this paper, we propose a novel architecture for contribution-based transfer-rate differentiation using wireless quality of service (QoS) techniques that motivates users to contribute their resources for wireless content sharing. We also propose a radio resource assignment method for our architecture. Computer simulations and game-theoretic calculations validate our architecture.

In this paper, we investigate a detection ordering scheme of OSIC (Ordered Successive Interference Cancellation) systems suitable for power controlled MIMO transmission. Most studies about power controlled systems have mainly focused on strategies for transmitter, while the ordering scheme optimized at open-loop system has not been modified. In a conventional ordering scheme, the ordering process is done according to the largeness and smallness relation of each sub-stream's SNR. Unlike the conventional scheme, we derive an optimized detection ordering scheme that uses proximity to the optimal SNR. Because of error propagation, our proximity based algorithm is not valid for open-loop MIMO system in many cases. An optimization problem analysis and simulation results show that the system using the proposed ordering scheme outperforms the system using the conventional ordering scheme. Furthermore, due to the nature of QR decomposition, the proposed scheme shows not only lower implementation complexity but also better BER performance compared with the conventional scheme based on pseudo-inverse.