The multiobjective route selection problem (m-RSP) is a key research topic in the car navigation system (CNS) for ITS (Intelligent Transportation System). In this paper, we propose an interactive multistage weight-based Dijkstra genetic algorithm (mwD-GA) to solve it. The purpose of the proposed approach is to create enough Pareto-optimal routes with good distribution for the car driver depending on his/her preference. At the same time, the routes can be recalculated according to the driver's preferences by the multistage framework proposed. In the solution approach proposed, the accurate route searching ability of the Dijkstra algorithm and the exploration ability of the Genetic algorithm (GA) are effectively combined together for solving the m-RSP problems. Solutions provided by the proposed approach are compared with the current research to show the effectiveness and practicability of the solution approach proposed.

We propose a scalable parallel interface that provides an ideal aggregated bandwidth link for an application. The scalable parallel interface uses time information to align packets and allows dynamic lane and/or path change, a large difference in transmission delays among lanes, and so on. The basic performance of the scalable parallel interface in 10 Gb/s 2 lanes is verified using an estimation board that is newly developed to evaluate the basic functions used in a Terabit LAN. The evaluation shows that the scalable parallel interface achieves a very low delay variation that is almost the same as that under back-to-back conditions. The difference in the delay variation between the scalable parallel interface and the back-to-back condition is approximately 10 ns when the transmission delay time varies from 10 µs to 1 s.

Localization is an important problem for Wireless Sensor Networks (WSN). The localization method can be categorized as range-free or range-based schemes. Since sensor nodes are usually cheap and small, the range-based schemes that require range measurement unit are unsuitable in WSN. The DV-hop algorithm is one of the range-free localization algorithms in which average hop-distance and hop counts are used for range estimation. But it requires heavy communication cost if the number of nodes increases in the network. Therefore, we propose a simple algorithm to reduce the communication cost and its performance is verified via computer simulations.

Networking technologies have recently been evolving and network applications are now expected to support flexible composition of upper-layer network services, such as security, QoS, or personal firewall. We propose a multi-platform framework called FreeNA* that extends existing applications by incorporating the services based on user definitions. This extension does not require users to modify their systems at all. Therefore, FreeNA is valuable for experimental system usage. We implemented FreeNA on both Linux and Microsoft Windows operating systems, and evaluated their functionality and performance. In this paper, we describe the design and implementation of FreeNA including details on how to insert network services into existing applications and how to create services in a multi-platform environment. We also give an example implementation of a service with SSL, a functionality comparison with relevant systems, and our performance evaluation results. The results show that FreeNA offers finer configurability, composability, and usability than other similar systems. We also show that the throughput degradation of transparent service insertion is 2% at most compared with a method of directly inserting such services into applications.

This paper presents a gate-block selection algorithm, which can synthesize a proper parameter extractor of the pre-computation-based content-addressable memory (PB-CAM) to enhance power efficiency for specific applications such as embedded systems, microprocessor and SOC, etc. Furthermore, a novel CAM cell design with single bit-line is proposed. The proposed CAM cell design requires only one heavy loading bit-line and merely is constructed with eight transistors. The whole PB-CAM design was described in Spice with TSMC 0.35 µm double-poly quadruple-metal CMOS process. We used Synopsys Nanosim to estimate power consumption. With a 128 words by 32 bits CAM size, the experimental results showed that our proposed PB-CAM effectively reduces 18.21% of comparison operations in the CAM and saves 16.75% in power reduction by synthesizing a proper parameter extractor of the PB-CAM compared with the 1's count PB-CAM. This implies that our proposed PB-CAM is more flexible and adaptive for specific applications.

In a Direct-Sequence/Spread-Spectrum (DS/SS) system, a RAKE receiver is used to improve a bit error rate (BER) performance. The RAKE receiver can collect more signal energy through independent paths and achieve path diversity. The RAKE receiver obtains further diversity gain through fractional sampling. However, the power consumption of the RAKE receiver increases in proportion to a sampling rate and does not always maximize the signal-to-noise ratio (SNR). Therefore, sampling rate selection schemes have been proposed to reduce the average sampling rate without degrading the BER. These schemes select the tap positions and the sampling rate depending on channel conditions and the power consumption can be reduced. In this paper, sampling rate selection schemes for the DS/SS system are investigated through an experiment since there have been no numerical results through an experiment. Numerical results show that the power consumption can be reduced even through the experiment without the degradation of the BER.

A new random access channel (RACH) preamble detection scheme using variable coherent correlation intervals (CCIs) is proposed. It is shown first that it is enough to employ two CCIs for supporting a user equipment (UE) velocity of 300 km/h, and then a CCI selection criterion is proposed. Computer simulation results indicate that the proposed scheme can provide a robust detection performance in time-varying fading channel environments.

Cognitive radio systems offer the opportunity to improve the spectrum utilization by detecting unused frequency bands while avoiding interference to primary users. This paper proposes a new algorithm for spectrum sensing, which is an energy detector using a hybrid (adaptive and fixed) threshold, in order to compensate the weak points of the existing energy detector in the distorted communication channel environment. Simulation results are presented which show that the performance of the new proposed scheme is better than the existing scheme using a fixed threshold or an adaptive threshold. Additionally, the performance is investigated in terms of several parameters such as the mobile speed and the probability of false alarms. The simulation results also show that the proposed algorithm makes the detector highly robust against fading, shadowing, and interference.

Decision diagrams (DDs) are data structures commonly used for representation of discrete functions with large number of variables. Binary DDs (BDDs) are used for representation and manipulation with Boolean functions. Complexity of a BDD is usually measured by its size, that is defined as the number of non-terminal nodes in the BDD. Minimization of the sizes of DDs is a problem greatly considered in literature and many related algorithms (exact and heuristic) have been proposed. However, there are many functions for which BDDs when minimized are still large and can have even an exponential size in the number of variables. An approach to derive compact decision diagram representations for such functions is transformation of BDDs into Multi-valued DDs (MDDs) and Heterogeneous MDDs (HMDDs). Complexity of MDDs and HMDDs is measured by the cost which is a generalization of the notion of the size by taking into account complexity of nodes in MDDs and HMDDs. This paper presents a method for transformation of BDD into HMDD with minimal cost. The proposed method reduces the time for determination of the type of nodes in HMDDs by introducing a matrix expressing dependency (interconnections) among nodes at different levels. Comparing to other methods for conversion of BDDs into HMDDs, the method reduces the number of traverses of a BDD necessary for collecting enough information to construct an equivalent HMDD. For an experimental verification of its efficiency, the method is applied to construction of HMDDs for some benchmark functions and their arithmetic and Walsh spectra.

Following the last proposal of the nonlinear Piece in Hand method, which has 3-layer structure, 2-layer nonlinear Piece in Hand method is proposed. Both of them aim at enhancing the security of existing and future multivariate public key cryptosystems. The new nonlinear Piece in Hand is compared with the 3-layer method and PMI+, which was proposed by Ding, et al.

This letter proposes a new hybrid EM wave absorber with the crossed-wedge shape, which can be applied to 3 m semi anechoic chambers. In this study, we designed a new hybrid EM wave absorber with the crossed-wedge shape, which consisted of the inorganic and organic thin corrugated dielectric lossy sheet containing organic conductive fibers. Then the 3 m semi anechoic chamber is constructed in the size of 9.0 m6.0 m5.7 m (LWH) using these absorbers, and also the normalized site attenuation (NSA) is measured according to ANSI C63.4 in the frequency range of 30 MHz to 1 GHz. As a result, the measured NSA is obtained within 3 dB of the theoretical one.

The single input rule modules connected fuzzy inference method (SIRMs method) by Yubazaki et al. can decrease the number of fuzzy rules drastically in comparison with the conventional fuzzy inference methods. Moreover, Seki et al. have proposed a functional-type SIRMs method which generalizes the consequent part of the SIRMs method to function. However, these SIRMs methods can not be applied to XOR (Exclusive OR). In this paper, we propose a "kernel-type SIRMs method" which uses the kernel trick to the SIRMs method, and show that this method can treat XOR. Further, a learning algorithm of the proposed SIRMs method is derived by using the steepest descent method, and compared with the one of conventional SIRMs method and kernel perceptron by applying to identification of nonlinear functions, medical diagnostic system and discriminant analysis of Iris data.

In this paper, first the temperature distribution of the pyramidal EM-wave absorber is calculated in the coupled method. Next, the injected power to the EM-wave absorber is changed to estimate the maximum power density that the EM-wave absorber can resist. As a result, the limitation of the injecting power density to a pyramidal EM-wave absorber is achievable.

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.

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.

This paper proposes an integrated approach to simultaneous detection and localization of multiple object categories using both generative and discriminative models. Our approach consists of first generating a set of hypotheses for each object category using a generative model (pLSA) with a bag of visual words representing each object. Based on the variation of objects within a category, the pLSA model automatically fits to an optimal number of topics. Then, the discriminative part verifies each hypothesis using a multi-class SVM classifier with merging features that combines spatial shape and appearance of an object. In the post-processing stage, environmental context information along with the probabilistic output of the SVM classifier is used to improve the overall performance of the system. Our integrated approach with merging features and context information allows reliable detection and localization of various object categories in the same image. The performance of the proposed framework is evaluated on the various standards (MIT-CSAIL, UIUC, TUD etc.) and the authors' own datasets. In experiments we achieved superior results to some state of the art methods over a number of standard datasets. An extensive experimental evaluation on up to ten diverse object categories over thousands of images demonstrates that our system works for detecting and localizing multiple objects within an image in the presence of cluttered background, substantial occlusion, and significant scale changes.

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.

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.

Orthogonal frequency division multiplexing (OFDM) is a critical technology in 3G evolution systems, which can effectively avoid intra-cell interference, but may bring with serious inter-cell interference. Inter-cell interference cancellation is one of effective schemes taken in mitigating inter-cell interference, but for many existing schemes in inter-cell interference cancellation, various generalized spatial diversities are taken, which always bring with extra interference and blind spots, or even need to acquire extra information on source and channel. In this paper, a novel inter-cell interference mitigation method is proposed for 3G evolution systems. This method is based on independent component analysis in blind source separation, and the input signal to interference plus noise ratio (SINR) is set as objective function. By generalized eigenvalue decomposition and algorithm iterations, maximum signal noise ratio (SNR) can be obtained in output. On the other hand, this method can be worked with no precise knowledge of source signal and channel information. Performance evaluation shows that such method can mitigate inter-cell interference in a semi-blind state, and effectively improve output SNR with the condition that lower input SINR, higher input SNR and longer lengths of the processing frame.

An approach to image thresholding based on the plausibility of object and background regions by adopting a co-occurrence matrix and category utility is presented. The effectiveness of the proposed method is shown through the experimental results tested on several images and compared with conventional methods.