To explain the variation of the address discharge during an address period, the wall voltage variation during an address period was investigated as a function of the address-on-time by using the Vt closed curves. It was observed that the wall voltage between the scan and address electrodes was decreased with an increase in the address-on-time. It was also observed that the wall voltage variation during an address period strongly depended on the voltage difference between the scan and address electrodes. Based on this result, the modified driving waveform to raise the level of Vscanw, was proposed to minimize the voltage difference between the scan and address electrodes. However, the modified driving waveform resulted in the increase in the falling time of scan pulse. Finally, the overlapped double scan waveform was proposed to reduce a falling time of scan pulse under the raised voltage level of Vscanw, also.

We propose a 2D display and camera arrangement for video communication systems that supports both spatial information between distant sites and user mobility. The implementation of this arrangement is called the "surrounding back screen method." The method enables users to freely come from and go into other users' spaces and provides every user with the direct pointing capability, since there is no apparent spatial barrier separating users, unlike the case of conventional video communication systems. In this paper, we introduce two properties ("sharedness" and "exclusiveness") and three parameters (a distance and two angles) to represent the geometrical relationship between two users. These properties and parameters are used to classify the shared spaces created by a video communication system and to investigate the surrounding back screen method. Furthermore, to demonstrate and explore our surrounding back screen method, we have developed a prototype system, called t-Room. Taking into account practical situations, we studied a practical case where two t-Rooms with different layouts are connected.

In this paper, a new video frame interpolation method based on image morphing for frame rate up-conversion is proposed. In this method, image features are extracted by Scale-Invariant Feature Transform in each frame, and their correspondence in two contiguous frames is then computed separately in foreground and background regions. By using the above two functions, the proposed method accurately generates interpolation frames and thus achieves frame rate up-conversion.

Combining the sphere decoding (SD) algorithm and the sequential detection method, we propose an adaptive group detection (AGD) scheme based on the sort-descending QRD (S-D-QRD) for V-BLAST architectures over an i.i.d. Rayleigh flat fading channel. Simulation results show that the proposed scheme, which encompasses the SD algorithm and the sequential detection method as two extreme cases in a probability sense, can achieve a very flexible tradeoff between the detection performance and computational complexity by adjusting the group parameter.

With the wide expansion of voice services over the IP networks (VoIP), the volume of this delay sensitive traffic is steadily growing. The current packet schedulers for IP networks meet the delay constraint of VoIP traffic by simply assigning its packets the highest priority. This technique is acceptable as long as the amount of VoIP traffic is relatively very small compared to other non-voice traffic. With the notable expansion of VoIP applications, however, the current packet schedulers will significantly sacrifice the fairness deserved by the non-voice traffic. In this paper, we extend the conventional Deficit Round-Robin (DRR) scheduler by including a packet classifier, a Token Bucket and a resource reservation scheme and propose an integrated packet scheduler architecture for the growing VoIP traffic. We demonstrate through both theoretical analysis and extensive simulation that the new architecture makes it possible for us to significantly improve the fairness to non-voice traffic while still meeting the tight delay requirement of VoIP applications.

Access to information is taken for granted in urban areas covered by a robust communication infrastructure. Nevertheless most of the areas in the world, are not covered by such infrastructures. We propose a DTN publish and subscribe system called Hikari, which uses nodes' mobility in order to distribute messages without using a robust infrastructure. The area of Disruption/Delay Tolerant Networks (DTN) focuses on providing connectivity to locations separated by networks with disruptions and delays. The Hikari system does not use node identifiers for message forwarding thus eliminating the complexity of routing associated with many forwarding schemes in DTN. Hikari uses nodes paths' information, advertised by special nodes in the system or predicted by the system itself, for optimizing the message dissemination process. We have used the Paris subway system, due to it's complexity, to validate Hikari and to analyze it's performance. We have shown that Hikari achieves a superior deliver rate while keeping redundant messages in the system low, which is ideal when using devices with limited resources for message dissemination.

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.

Location Based Services (LBS) are expected to become one of the major drivers of ubiquitous services due to recent inception of GPS-enabled mobile devices, the development of Web2.0 paradigm, and emergence of 3G broadband networks. Having this vision in mind, Community Context-attribute-oriented Collaborative Information Environment (CCCIE) based Autonomous Decentralized Community System (ADCS) is proposed to enable provision of services to specific users in specific place at specific time considering various context-attributes. This paper presents autonomous community construction technology that share service discovered by one member among others in flexible way to improve timeliness and reduce network cost. In order to meet crucial goal of real-time and context-aware community construction (provision of service/ service information to users with common interests), and defining flexible service area in highly dynamic operating environment of ADCS, proposed progressive ripple based service discovery technique introduces novel idea of snail's pace and steady advancing search followed by swift boundary confining mechanism; while service area construction shares the discovered service among members in defined area to further improve timeliness and reduce network cost. Analysis and empirical results verify the effectiveness of the proposed technique.

This Paper presents the design of a wideband variable gain amplifier (VGA) using 0.18 µm standard CMOS technology. The proposed VGA realizes wideband flat gain using wideband flat negative capacitance. It achieves a 3 dB gain bandwidth of 1 GHz with a maximum gain of 23 dB. Also, it shows P1 dB of -33 to -6 dBm over the gain range of -28 to 23 dB. The overall current consumption is 5.5 mA under a 1.5 V supply.

We propose a complexity-reducing algorithm for serial scheduled min-sum decoding that reduces the number of check nodes to process during an iteration. The check nodes to skip are chosen based on the reliability, a syndrome and a log-likelihood-ratio (LLR) value, of the incoming messages. The proposed algorithm is evaluated by computer simulations and shown to reduce the decoding complexity about 20% compared with a conventional serial scheduled min-sum decoding with small fractional decibel degradation in error correction performance.

An ICI (Inter-Cell Interference) mitigation algorithm for exploiting macroscopic diversity for an up-link OFDMA (Orthogonal Frequency Division Multiple Access) system is proposed. To reduce the influence of carrier collision, the order of resource allocation is coordinated based on the location of each MS (Mobile Station) and the associated carrier group. This consideration significantly reduces ICI and enhances throughput at the boundary region.

In 1999, Gennaro, Halevi and Rabin proposed a signature which achieves provable security without assuming the random oracles, and it is the first RSA-type signature whose security is proved in the standard model. Since that time, several signatures have been proposed to achieve better efficiency or useful property along with the provable security in the standard model. In this paper, we construct a trapdoor hash function, and design an efficient online/offline signature by using the trapdoor hash function. Our signature scheme requires only one non-modular multiplication of two small integers for online signing, and it provides the fastest online signing among all online/offline signatures that achieve provable security in the standard model.

Recently, Kempf and Koodli have proposed a security protocol for Fast Mobile IPv6 (FMIPv6). Through the SEcure Neighbor Discovery (SEND) protocol, it achieves secure distribution of a handover key, and consequently becomes a security standard for FMIPv6. However, it is still vulnerable to redirection attacks. In addition, due to the SEND protocol, it suffers from denial of service attacks and expensive computational cost. In this paper, we present a security protocol, which enhances Kempf-Koodli's one with the help of the AAA infrastructure.

To realize huge-scale information services, many Distributed Hash Table (DHT) based systems have been proposed. For example, there are some proposals to manage item-level product traceability information with DHTs. In such an application, each entry of a huge number of item-level IDs need to be available on a DHT. To ensure data availability, the soft-state approach has been employed in previous works. However, this does not scale well against the number of entries on a DHT. As we expect 1010 products in the traceability case, the soft-state approach is unacceptable. In this paper, we propose Distributed-to-Distributed Data Copy (D3C). With D3C, users can reconstruct the data as they detect data loss, or even migrate to another DHT system. We show why it scales well against the number of entries on a DHT. We have confirmed our approach with a prototype. Evaluation shows our approach fits well on a DHT with a low rate of failure and a huge number of data entries.

Applications usually have their own phases in heap memory usage. The traditional garbage collector fails to match various application phases because the same heuristic on the object behavior is used throughout the entire execution. This paper introduces a phase-adaptive garbage collector which reorganizes the heap layout and adjusts the invocation time of the garbage collection according to the phases. The proposed collector identifies phases by detecting the application methods strongly related to the phase boundaries. The experimental results show that the proposed phase-adaptive collector successfully recognizes application phases and improves the garbage collection time by as much as 41%.

It is known that the schedulability of a non-preemptive task set with fixed priority can be determined in pseudo-polynomial time. However, since Rate Monotonic scheduling is not optimal for non-preemptive scheduling, the applicability of existing polynomial time tests that provide sufficient schedulability conditions, such as Liu and Layland's bound, is limited. This letter proposes a new sufficient condition for non-preemptive fixed priority scheduling that can be used for any fixed priority assignment scheme. It is also shown that the proposed schedulability test has a tighter utilization bound than existing test methods.

This paper proposes a robust adaptive fuzzy PID control scheme augmented with a supervisory controller for unknown systems. In this scheme, a generalized fuzzy model is used to describe a class of unknown systems. The control strategy allows each part of the control law, i.e., a supervisory controller, a compensator, and an adaptive fuzzy PID controller, to be designed incrementally according to different guidelines. The supervisory controller in the outer loop aims at enhancing system robustness in the face of extra disturbances, variation in system parameters, and parameter drift in the adaptation law. Furthermore, an H∞ control design method using the fuzzy Lyapunov function is presented for the design of the initial control gains that guarantees transient performance at the start of closed-loop control, which is generally overlooked in many adaptive control systems. This design of the initial control gains is a compound search strategy called conditional linear matrix inequality (CLMI) approach with IROA (Improved random optimal algorithm), it leads to less complex designs than a standard LMI method by fuzzy Lyapunov function. Numerical studies of the tracking control of an uncertain inverted pendulum system demonstrate the effectiveness of the control strategy. From results of this simulation, the generalized fuzzy model reduces the rule number of T-S fuzzy model indeed.

We present a novel model named Integrated Latent Topic Model (ILTM), to learn and recognize natural scene category. Unlike previous work, which considered the discrepancy and common property separately among all categories, Our approach combines universal topics from all categories with specific topics from each category. As a result, the model is implemented to produce a few but specific topics and more generic topics among categories, and each category is represented in a different topics simplex, which correlates well with human scene understanding. We investigate the classification performance with variable scene category tasks. The experiments have shown our model outperforms latent-space methods with less training data.

Scheduling algorithms are crucial in radio resource management especially for multimedia networks. Many scheduling algorithms are based on the assumption of error-free connections, which is not suitable for wireless networks. Therefore, a scheduling algorithm based on the modification of Static Priority (SP) algorithm and Earliest-Due-Date (EDD) algorithm is proposed for wireless multimedia networks with link adaptation in this paper. In the proposed algorithm, various quality of service requirements, such as delay, throughput, and packet loss ratio, are considered. Particularly, the influence of error tolerance of voice communications, which is usually ignored in most scheduling algorithms, is taken into account. Simulation results show that the proposed algorithm, compared with SP, EDD, and other scheduling algorithms, succeeds in meeting the delay and packet loss ratio (PLR) requirements at much heavier traffic load.

This paper describes a reading miscue detection system based on the conventional Large Vocabulary Continuous Speech Recognition (LVCSR) framework [1]. In order to incorporate the knowledge of reference (what the reader ought to read) and some error patterns into the decoding process, two methods are proposed: Dynamic Multiple Pronunciation Incorporation (DMPI) and Dynamic Interpolation of Language Model (DILM). DMPI dynamically adds some pronunciation variations into the search space to predict reading substitutions and insertions. To resolve the conflict between the coverage of error predications and the perplexity of the search space, only the pronunciation variants related to the reference are added. DILM dynamically interpolates the general language model based on the analysis of the reference and so keeps the active paths of decoding relatively near the reference. It makes the recognition more accurate, which further improves the detection performance. At the final stage of detection, an improved dynamic program (DP) is used to align the confusion network (CN) from speech recognition and the reference to generate the detecting result. The experimental results show that the proposed two methods can decrease the Equal Error Rate (EER) by 14% relatively, from 46.4% to 39.8%.