We carried out degradation analysis of a blue phosphorescent organic light emitting diode by both impedance spectroscopy and transient electroluminescence (EL) spectroscopy. The number of semicircles observed in the Cole-Cole plot of the modulus became three to two after the device was operated for 567 hours. Considering the effective layer thickness of the initial and degraded devices did not change by degradation and combining the analysis of the Bode-plot of the imaginary part of the modulus, the relaxation times of emission layer and hole-blocking with electron transport layers changed to nearly the same value by the increase of the resistance of emission layer. Decay time of transient EL of the initial device was coincident with that of the degraded one. These phenomena suggest that no phosphorescence quenching sites are generated in the degraded device, but the number of the emission sites decrease by degradation.

The need for data encryption that protects sensitive data in a database has increased rapidly. However, encrypted data can no longer be efficiently queried because nearly all of the data should be decrypted. Several order-preserving encryption schemes that enable indexes to be built over encrypted data have been suggested to solve this problem. They allow any comparison operation to be directly applied to encrypted data. However, one of the main disadvantages of these schemes is that they expose sensitive data to inference attacks with order information, especially when the data are used together with unencrypted columns in the database. In this study, a new order-preserving encryption scheme that provides secure queries by hiding the order is introduced. Moreover, it provides efficient queries because any user who has the encryption key knows the order. The proposed scheme is designed to be efficient and secure in such an environment. Thus, it is possible to encrypt only sensitive data while leaving other data unencrypted. The encryption is not only robust against order exposure, but also shows high performance for any query over encrypted data. In addition, the proposed scheme provides strong updates without assumptions of the distribution of plaintext. This allows it to be integrated easily with the existing database system.

While the problem of multicast routing and wavelength assignment (MC-RWA) in optical wavelength division multiplexing (WDM) networks has been investigated, relatively few researchers have considered network survivability for multicasting. This paper provides an optimization framework to solve the MC-RWA problem in a multi-fiber WDM network that can recover from a single-link failure with shared protection. Using the light-tree (LT) concept to support multicast sessions, we consider two protection strategies that try to reduce service disruptions after a link failure. The first strategy, called light-tree reconfiguration (LTR) protection, computes a new multicast LT for each session affected by the failure. The second strategy, called optical branch reconfiguration (OBR) protection, tries to restore a logical connection between two adjacent multicast members disconnected by the failure. To solve the MC-RWA problem optimally, we propose an integer linear programming (ILP) formulation that minimizes the total number of fibers required for both working and backup traffic. The ILP formulation takes into account joint routing of working and backup traffic, the wavelength continuity constraint, and the limited splitting degree of multicast-capable optical cross-connects (MC-OXCs). After showing some numerical results for optimal solutions, we propose heuristic algorithms that reduce the computational complexity and make the problem solvable for large networks. Numerical results suggest that the proposed heuristic yields efficient solutions compared to optimal solutions obtained from exact optimization.

This paper proposes an enhanced method for estimating the a priori Signal-to-Disturbance Ratio (SDR) to be employed in the Acoustic Echo and Noise Suppression (AENS) system for full-duplex hands-free communications. The proposed a priori SDR estimation technique is modified based upon the Two-Step Noise Reduction (TSNR) algorithm to suppress the background noise while preserving speech spectral components. In addition, a practical approach to determine accurately the Echo Spectrum Variance (ESV) is presented based upon the linear relationship assumption between the power spectrum of far-end speech and acoustic echo signals. The ESV estimation technique is then employed to alleviate the acoustic echo problem. The performance of the AENS system that employs these two proposed estimation techniques is evaluated through the Echo Attenuation (EA), Noise Attenuation (NA), and two speech distortion measures. Simulation results based upon real speech signals guarantee that our improved AENS system is able to mitigate efficiently the problem of acoustic echo and background noise, while preserving the speech quality and speech intelligibility.

Network intrusion detection systems rely on a signature-based detection engine. When under attack or during heavy traffic, the detection engines need to make a fast decision whether a packet or a sequence of packets is normal or malicious. However, if packets have a heavy payload or the system has a great deal of attack patterns, the high cost of payload inspection severely diminishes detection performance. Therefore, it would be better to avoid unnecessary payload scans by checking the protocol fields in the packet header, before executing their heavy operations of payload inspection. When payload inspection is necessary, it is better to compare a minimum number of attack patterns. In this paper, we propose new methods to classify attack signatures and make pre-computed multi-pattern groups. Based on IDS rule analysis, we grouped the signatures of attack rules by a multi-dimensional classification method adapted to a simplified address flow. The proposed methods reduce unnecessary payload scans and make light pattern groups to be checked. While performance improvements are dependent on a given networking environment, the experimental results with the DARPA data set and university traffic show that the proposed methods outperform the most recent Snort by up to 33%.

Two decoding procedures combined with a belief-propagation (BP) decoding algorithm for low-density parity-check codes over the binary erasure channel are presented. These algorithms continue a decoding procedure after the BP decoding algorithm terminates. We derive a condition that our decoding algorithms can correct an erased bit which is uncorrectable by the BP decoding algorithm. We show by simulation results that the performance of our decoding algorithms is enhanced compared with that of the BP decoding algorithm with little increase of the decoding complexity.

Let us introduce n ( ≥ 2) mappings fi (i=1,,n ≡ 0) defined on reflexive real Banach spaces Xi-1 and let fi:Xi-1 → Yi be completely continuous on bounded convex closed subsets Xi-1(0) ⊂ Xi-1. Moreover, let us introduce n set-valued mappings Fi : Xi-1 Yi → Fc(Xi) (the family of all non-empty compact subsets of Xi), (i=1,,n ≡ 0). Here, we have a fixed point theorem in weak topology on the successively recurrent system of set-valued mapping equations:xi ∈ Fi(xi-1, fi(xi-1)), (i=1,,n ≡ 0). This theorem can be applied immediately to analysis of the availability of system of circular networks of channels undergone by uncertain fluctuations and to evaluation of the tolerability of behaviors of those systems.

This paper describes the application techniques of the latency insertion method (LIM) to CMOS circuit simulations. Though the existing LIM algorithm to CMOS circuit performs fast transient analysis, CMOS circuits are not modeled accurately. As a result, they do not provide accurate simulations. We propose a more accurate LIM scheme for the CMOS inverter circuit by adopting a more accurate model of the CMOS inverter characteristics. Moreover, we present the way to expand the LIM algorithm to general CMOS circuit simulations. In order to apply LIM to the general CMOS circuits which consist of CMOS NAND and NOR, we derive the updating formulas of the explicit form of the LIM algorithm. By using the explicit form of the LIM scheme, it becomes easy to take in the characteristics of CMOS NAND and NOR into the LIM simulations. As a result, it is confirmed that our techniques are useful and efficient for the simulations of CMOS circuits.

When we design a robust vector quantizer (VQ) for noisy channels, an appropriate index assignment function should be contrived to minimize the channel-error effect. For relatively high rates, the complexity for finding an optimal index assignment function is too high to be implemented. To overcome such a problem, we use a structurally constrained VQ, which is called the sample-adaptive product quantizer (SAPQ) [12], for low complexities of quantization and index assignment. The product quantizer (PQ) and its variation SAPQ [13], which are based on the scalar quantizer (SQ) and thus belong to a class of the binary lattice VQ [16], have inherent error resilience even though the conventional affine index assignment functions, such as the natural binary code, are employed. The error resilience of SAPQ is observed in a weak sense through worst-case bounds. Using SAPQ for noisy channels is useful especially for high rates, e.g., > 1 bit/sample, and it is numerically shown that the channel-limit performance of SAPQ is comparable to that of the best codebook permutation of binary switching algorithm (BSA) [23]. Further, the PQ or SAPQ codebook with an affine index assignment function is used for the initial guess of the conventional clustering algorithm, and it is shown that the performance of the best BSA can be easily achieved.

We propose an Edge-write architecture which performs eager update propagation for update requests for the corresponding secondary server, whereas it lazily propagates updates from other secondary servers. Our architecture resolves consistency problems caused by read/update decoupling in the conventional lazy update propagation-based system. It also improves overall scalability by alleviating the performance bottleneck at the primary server in compensation for increased but bounded response time. Such relaxed consistency management enables a read request to choose whether to read the replicated data immediately or to refresh it. We use the age of a local data copy as the freshness factor so that a secondary server can make a decision for freshness control independently. As a result, our freshness-controlled edge-write architecture benefits by adjusting a tradeoff between the response time and the correctness of data.

Switching a communication path from one Access Point (AP) to another in inter-domain WLANs is a critical challenge for delay-sensitive applications such as Voice over IP (VoIP) because communication quality during handover (HO) is more likely to be deteriorated. To maintain VoIP quality during HO, we need to solve many problems. In particular, in bi-directional communication such as VoIP, an AP becomes a bottleneck with the increase of VoIP calls. As a result, packets queued in the AP buffer may experience a large queuing delay or packet losses due to increase in queue length or buffer overflow, thereby causing the degradation of VoIP quality for the Mobile Nodes (MNs) side. To avoid this degradation, MNs need to appropriately and autonomously execute HO in response to the change in wireless network condition, i.e., the deterioration of wireless link quality and the congestion state at the AP. In this paper, we propose an HO decision strategy considering frame retries, AP queue length, and transmission rate at an MN for maintaining VoIP quality during HO. Through simulation experiments, we then show that our proposed method can maintain VoIP quality during HO by properly detecting the wireless network condition.

The notion of anonymous signatures has recently been formalized by [18], which captures an interesting property that a digital signature can sometimes hide the identity of the signer, if the message is hidden from the verifier. However, in many practical applications, e.g., an anonymous paper review system mentioned in [18], the message for anonymous authentication is actually known to the verifier. This implies that the effectiveness of previous anonymous signatures may be unjustified in these applications. In this paper, we extend the previous models, and develop a related primitive called strong anonymous signatures. For strong anonymous signatures, the identity of the signer remains secret even if the challenge message is chosen by an adversary. We then demonstrate some efficient constructions and prove their security in our model.

In this paper, an image restoration method using the Wiener filter is proposed. In order to bring the theory of the Wiener filter consistent with images that have spatially varying statistics, the proposed method adopts the locally adaptive Wiener filter (AWF) based on the universal Gaussian mixture distribution model (UNI-GMM) previously proposed for denoising. Applying the UNI-GMM-AWF for deconvolution problem, the proposed method employs the stationary Wiener filter (SWF) as a pre-filter. The SWF in the discrete cosine transform domain shrinks the blur point spread function and facilitates the modeling and filtering at the proceeding AWF. The SWF and UNI-GMM are learned using a generic training image set and the proposed method is tuned toward the image set. Simulation results are presented to demonstrate the effectiveness of the proposed method.

The RFID tag system has received attention as an identification source. Each RFID tag is attached to some object. With the unique ID of the RFID tag, a user identifies the object provided with the RFID tag, and derives appropriate information about the object. One of important applications of the RFID technology is the position estimation of RFID tags. It can be very useful to acquire the location information concerning the RFID tags. It can be applied to navigation systems and positional detection systems for robots etc. In this paper, we propose a new position estimation method of RFID tags by using a probabilistic approach. In this method, mobile objects (person and robot, etc.) with RFID readers estimate the positions of RFID tags with multiple communication ranges. We show the effectiveness of the proposed method by computer simulations.

In PKC 2004, Choi et al. proposed an ID-based authenticated group key agreement (AGKA) protocol using bilinear pairings. Unfortunately, their protocol suffered from an impersonation attack and an insider colluding attack. In 2008, Choi et al. presented an improvement to resist insider attacks. In their modified protocol, they used an ID-based signature scheme on transcripts for binding them in a session to prevent replay of transcripts. In particular, they smartly used the batch verification technique to reduce the computational cost. In this paper, we first show that Choi et al.'s modified AGKA protocol still suffers from an insider colluding attack. Then, we prove that the batch verification of the adopted ID-based signature scheme in their modified protocol suffers from a forgery attack.

Packet classification categorizes incoming packets into multiple forwarding classes based on pre-defined filters. This categorization makes information accessible for quality of service or security handling in the network. In this paper, we propose a scheme which combines the Aggregate Bit Vector algorithm and the Pruned Tuple Space Search algorithm to improve the performance of packet classification in terms of speed and storage. We also present the procedures of incremental update. Our scheme is evaluated with filter databases of varying sizes and characteristics. The experimental results demonstrate that our scheme is feasible and scalable.

Boundary-based corner detection has been widely applied in spline curve fitting, automated optical inspection, image segmentation, object recognition, etc. In order to obtain good results, users usually need to adjust the length of region of support to resist zigzags due to quantization and random noise on digital boundaries. To automatically determine the length of region of support for corner detection, Teh-Chin and Guru-Dinesh presented adaptive approaches based on some local properties of boundary points. However, these local-property based approaches are sensitive to noise. In this paper, we propose a new approach to find the optimum length of region of support for corner detection based on a statistic discriminant criterion. Since our approach is based on the global perspective of all boundary points, rather than the local properties of some points, the experiments show that the determined length of region of support increases as the noise intensity strengthens. In addition, the detected corners based on the optimum length of region of support are consistent with human experts' judgment, even for noisy boundaries.

An ISI-free power roll-off pulse, the roll-off characteristic of which is tunable with one power parameter, is proposed. It is shown that the proposed pulse is advantageous in terms of the probability of error for pulse detection in the presence of a timing error among currently known good pulses, among which the raised cosine pulse, "better than" raised cosine pulse, and polynomial pulse are considered.

In this paper, for systematically evaluating estimation methods of node characteristics, we first propose a social network generation model called LRE (Linkage with Relative Evaluation). LRE is a network generation model, which aims to reproduce the characteristics of a social network. LRE utilizes the fact that people generally build relationships with others based on relative evaluation, rather than absolute evaluation. We then extensively evaluate the accuracy of the estimation method called SSI (Structural Superiority Index). We reveal that SSI is effective for finding good nodes (e.g., top 10% nodes), but cannot be used for finding excellent nodes (e.g., top 1% nodes). For alleviating the problems of SSI, we propose a novel scheme for enhancing existing estimation methods called RENC (Recursive Estimation of Node Characteristic). RENC reduces the effect of noise by recursively estimating node characteristics. By investigating the estimation accuracy with RENC, we show that RENC is quite effective for improving the estimation accuracy in practical situations.

To enable fine-grained delegations for proxy re-encryption systems, in AsiaCCS'09, Weng et al.'s introduced the concept of conditional proxy re-encryption (C-PRE), in which the proxy can convert a ciphertext only if a specified condition is satisfied. Weng et al. also proposed a C-PRE scheme, and claimed that their scheme is secure against chosen-ciphertext attack (CCA). In this paper, we show that their scheme is not CCA-secure under their defined security model.