This paper presents an efficient diagnosis scheme for RAMs. Three March-based algorithms are proposed to diagnose simple functional faults of RAMs. A March-15N algorithm is used for locating and partially diagnosing faults of bit-oriented or word-oriented memories, where N represents the address number. Then a 3N March-like algorithm is used for locating the aggressor words (bits) of coupling faults (CFs) in word-oriented (bit-oriented) memories. It also can distinguish the faults which cannot be identified by the March-15N algorithm. Thus, the proposed diagnosis scheme can achieve full diagnosis and locate aggressors with (15N + 3mN) Read/Write operations for a bit-oriented RAM with m CFs. For word-oriented RAMs, a March-like algorithm is also proposed to locate the aggressor bit in the aggressor word with 4 log2B Read/Write operations, where B is the word width. Analysis results show that the proposed diagnosis scheme has higher diagnostic resolution and lower time complexity than the previous fault location and fault diagnosis approaches. A programmable built-in self-diagnosis (BISD) design is also implemented to perform the proposed diagnosis algorithms. Experimental results show that the area overhead of the BISD is small--only about 2.17% and 0.42% for 16 K8-bit and 16 K128-bit SRAMs, respectively.

We describe a way to write state machines inductively. The proposed method makes it possible to use the standard techniques for proving theorems on inductive types to verify that state machines satisfy invariant properties. A mutual exclusion protocol using a queue is used to exemplify the proposed method.

In this paper, we propose a sequential type-based detection scheme for wireless sensor networks in the case of spatially and temporally identically and independently distributed observations. First, we investigate the optimal sequential detection rule of the proposed scheme, and then with the motivation of reducing the computational complexity of the optimal detection rule, we consider an approximation scheme and derive a suboptimal detection rule. We also compare the performances of the type-based sequential detection scheme with those of the non-sequential type-based detection scheme in terms of both average number of observations and total energy consumption, and determine the region of individual node power where the proposed scheme outperforms the non-sequential scheme. In addition, we show that the approximated detection rule provides the similar results as the optimal detection rule with a significant reduction of the computational complexity, which makes the approximated detection rule useful for real-time applications.

FeedForward (FF-) Blind Source Separation (BSS) systems have some degree of freedom in the solution space. Therefore, signal distortion is likely to occur. First, a criterion for the signal distortion is discussed. Properties of conventional methods proposed to suppress the signal distortion are analyzed. Next, a general condition for complete separation and distortion-free is derived for multi-channel FF-BSS systems. This condition is incorporated in learning algorithms as a distortion-free constraint. Computer simulations using speech signals and stationary colored signals are performed for the conventional methods and for the new learning algorithms employing the proposed distortion-free constraint. The proposed method can well suppress signal distortion, while maintaining a high source separation performance.

A wideband NRD guide and rectangular waveguide H-plane transition is proposed to transfer millimeter waves from a dielectric strip to the outer conductor surface of NRD guide through a short length of waveguide made through the conductor plate. As a result, it has a bandwidth about 6.7 GHz of |S11| -15 dB and a low transition loss about 0.35 dB at 60 GHz band.

Owing to frequency diversity gain and simplicity, a chip interleaved multi-carrier code division multiple access (MC-CDMA) system has been considered in a multi-cell environment, and combining it with multiple input multiple output (MIMO) schemes offers high spectral efficiency. In spite of the advantages, the system is highly affected by inter code interferences. To control them, this letter analyzes the asymptotic performance of a MIMO MC-CDMA system with a symbol level MMSE receiver in a multi-cell environment and presents an appropriate multiplexed code ratio satisfying a required error rate.

We propose LPDD (Lifetime Prediction Directed Diffusion), a novel energy-aware routing protocol for sensor networks that aims at increasing network survivability without a significant increase in latency. The key concept behind the protocol is the adaptive selection of routes by predicting the battery lifetime of the minimum energy nodes along the routes.

Owing to simple structure, low cost and high performance, NRD-guide millimeter wave circuits have attracted much attention in recent years. In this paper, a variety of NRD-guide passive components are reviewed with emphasis on design techniques and performance estimation in the 60 GHz frequency band where the license-free advantage is available. The passive components to be discussed here include compact bends, wideband hybrid couplers, practical three-port junctions, versatile E-plane filters, and effective feeding structures for lens antennas. Some of them are employed to construct millimeter wave transceivers. Eye patterns observed at 1.5 Gbps confirm the potential ability of the fabricated NRD-guide transceivers for high bit-rate, wireless applications.

The time division duplex cellular system can support various downlink and uplink traffic ratios by setting the downlink and uplink transmission periods appropriately. However, it causes severe co-channel interference problem when some cells are active in the downlink while the others are in the uplink [2]. To mitigate this problem, a resource allocation scheme combined with sectorization is proposed for orthogonal frequency division multiple access. Simulations demonstrate that the proposed scheme improves both spectral efficiency and outage performance compared to the conventional allocation schemes.

We extend the framework of cost-sensitive classification to mitigate risks of huge costs occurring with low probabilities, and propose an algorithm that achieves this goal. Instead of minimizing the expected cost commonly used in cost-sensitive learning, our algorithm minimizes conditional value-at-risk, also known as expected shortfall, which is considered a good risk metric in the area of financial engineering. The proposed algorithm is a general meta-learning algorithm that can exploit existing example-dependent cost-sensitive learning algorithms, and is capable of dealing with not only alternative actions in ordinary classification tasks, but also allocative actions in resource-allocation type tasks. Experiments on tasks with example-dependent costs show promising results.

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.

Exploiting layer7 context is an effective approach to improving the accuracy of detecting malicious messages in network intrusion detection/prevention systems (NIDS/NIPSs). Layer7 context enables us to inspect message formats and the message exchanged order. Unfortunately, layer7-aware NIDS/NIPSs pose crucial implementation issues because they require full TCP and IP reassembly without losing 1) complete prevention, 2) performance, 3) application transparency, or 4) transport transparency. Complete prevention means that the NIDS/NIPS should prevent malicious messages from reaching target applications. Application transparency means not requiring any modifications to and/or reconfiguration of server and client applications. Transport transparency is not to disrupt the end-to-end semantics of TCP/IP. To the best of our knowledge, none of the existing approaches meet all of these requirements. We have developed an efficient mechanism for layer7-aware NIDS/NIPSs that does meet the above requirements. Our store-through does this by forwarding each out-of-order or IP-fragmented packet immediately after copying the packet even if it has not been checked yet by an NIDS/NIPS sensor. Although the forwarded packet might turn out to be a part of an attack message, the store-through mechanism can successfully defend against the attack by blocking one of the subsequent packets that contain another part of attack message. Testing of a prototype in Linux kernel 2.4.30 demonstrated that the overhead of our mechanism is negligible compared with that of a simple IP forwarder even with the presence of out-of-order and IP-fragmented packets. In addition, the experimental results suggest that the CPU and memory usage incurred by our store-through is not significant.

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.

Most learning-based super-resolution methods neglect the illumination problem. In this paper we propose a novel method to combine blind single-frame super-resolution and shadow removal into a single operation. Firstly, from the pattern recognition viewpoint, blur identification is considered as a classification problem. We describe three methods which are respectively based on Vector Quantization (VQ), Hidden Markov Model (HMM) and Support Vector Machines (SVM) to identify the blur parameter of the acquisition system from the compressed/uncompressed low-resolution image. Secondly, after blur identification, a super-resolution image is reconstructed by a learning-based method. In this method, Logarithmic-wavelet transform is defined for illumination-free feature extraction. Then an initial estimation is obtained based on the assumption that small patches in low-resolution space and patches in high-resolution space share a similar local manifold structure. The unknown high-resolution image is reconstructed by projecting the intermediate result into general reconstruction constraints. The proposed method simultaneously achieves blind single-frame super-resolution and image enhancement especially shadow removal. Experimental results demonstrate the effectiveness and robustness of our method.

Simple-relay aided resource allocation (SRARA) schemes are incorporated with throughput guarantee scheduling (TGS) in IEEE 802.16 type time division duplex--orthogonal frequency division multiple access (TDD-OFDMA) downlink in order to enhance service coverage, where the amount of resources at each relay is limited due to either its available power which is much smaller than base station (BS) power or the required overhead. The performance of SRARA schemes is evaluated with both proportional fair (PF) and TGS schedulers at 64 kbps and 128 kbps user throughput requirements when total RS power is set to 500 mW or 1 W. For SRARA with RSs of relatively lower power (500 mW), schemes that put total power into only one subchannel offer larger coverage than when both subchnnels are used with equal power allocation, while the RS with evenly power-allocated two subchannels could provide larger coverage gain for a relatively higher power (1 W). Depending upon the target throughputs it is shown which of the relay scheme or scheduler design would play more important role in improving coverage. In a lower target (64 kbps), more improvement comes from relay scheme rather than scheduler design. For a relatively higher level (128 kbps), it comes from scheduler design rather than relay due to the fact that simple relay can't help using strictly limited amount of resources.

Design automation of LCD driver circuits is not sophisticatedly established. Display fineness of an LCD panel depends on a performance metric, ratio of pixel voltage to video voltage (RPV). However, there are several other important metrics, such as area, and the best circuit cannot be decided uniquely. This paper proposes a design automation technique for a LCD column driver to provide several circuit design results with different performance so that designers can select an appropriate design among them. The proposed technique is evaluated with an actual design data, and experimental results show that the proposed method successfully performs technology migration by transistor sizing. Also, the proposed technique is experimentally verified from points of solution quality and computational time.

In this paper, the expectation maximization (EM) algorithm is used for unsupervised classification of polarimetric synthetic aperture radar (SAR) images. The EM algorithm provides an estimate of the parameters of the underlying probability distribution functions (pdf's) for each class. The feature vector is 9-dimensional, consisting of the six magnitudes and three angles of the elements of a coherency matrix. Each of the elements of the feature vector is assigned a specific parametric pdf. In this work, all the features are supposed to be statistically independent. Then we present a two-stage unsupervised clustering procedure. The EM algorithm is first run for a few iterations to obtain an initial partition of, for example, four clusters. A randomly selected sample of, for example, 2% pixels of the polarimetric SAR image may be used for unsupervised training. In the second stage, the EM algorithm may be run again to reclassify the first stage clusters into smaller sub-clusters. Each cluster from the first stage will be processed separately in the second stage. This approach makes further classification possible as shown in the results. The training cost is also reduced as the number of feature vector in a specific cluster is much smaller than the whole image.

In ubiquitous networks, Mobile Nodes (MNs) often suffer from performance degradation due to the following two reasons: (1) reduction of signal strength by the movement of an MN and intervening objects, and (2) radio interference with other WLANs. Therefore, handover initiation based on quick and reliable detection of the deterioration in a wireless link condition arising from the above two reasons is essential for achieving seamless handover. In previous studies, we focused on a handover decision criterion and described the problems related to the two existing decision criteria. Furthermore, we showed the effectiveness of the number of frame retransmissions through simulation experiments. However, a comparison of the signal strength and the number of frame retransmissions could not be examined due to the unreliability of the signal strength in simulations. Therefore, in the present paper, by employing FTP and VoIP applications, we compare the signal strength and the number of frame retransmissions as a handover decision criterion with experiments in terms of (1) and (2) in a real environment. Finally, we clarify the problem of the signal strength in contrast to the effectiveness of the number of frame retransmissions as a handover decision criterion.

In this paper, we consider consecutive burst transmission with burst loss recovery based on Forward Error Correction (FEC) in which redundant data is transmitted with multiple bursts. We propose two burst generation methods: Out-of Burst Generation (OBG) and In-Burst Generation (IBG). The OBG generates a redundant burst from redundant data, while the IBG reconstructs a burst from an original data block and a part of the redundant data. For both methods, the resulting bursts are transmitted consecutively. If some bursts among the bursts are lost at an intermediate node, the lost bursts can be recovered with the redundant data using FEC processing at the destination node. We evaluate by simulation the proposed methods in a uni-directional ring network and NSFNET, and compare the performances of the proposed methods with the extra-offset time method. Numerical examples show that the proposed methods can provide a more reliable transmission than the extra-offset time method for the OBS network where the maximum number of hops is large. Moreover, it is shown that the end-to-end transmission delay for our proposed methods can be decreased by enhancing the FEC processor or by increasing the number of FEC processors.

Recently, many studies reported various advanced e-Health service systems in patient care monitoring utilizing sensor networks and questionnaire systems. We propose an informant driven e-Health service system for the identification of heart rate related mental stress factors with a simple operation of informant-client model. Through performance analysis, we show that the proposed system is a cost-effective stress identification system applicable to mobile wireless networks.