In 1973, Arimoto proved the strong converse theorem for the discrete memoryless channels stating that when transmission rate R is above channel capacity C, the error probability of decoding goes to one as the block length n of code word tends to infinity. He proved the theorem by deriving the exponent function of error probability of correct decoding that is positive if and only if R>C. Subsequently, in 1979, Dueck and Körner determined the optimal exponent of correct decoding. Arimoto's bound has been said to be equal to the bound of Dueck and Körner. However its rigorous proof has not been presented so far. In this paper we give a rigorous proof of the equivalence of Arimoto's bound to that of Dueck and Körner.

The RO (Ring-Oscillator)-based sensor is one of easily-implementable variation sensors, but for decomposing the observed variability into multiple unique device-parameter variations, a large number of ROs with different structures and sensitivities to device-parameters is required. This paper proposes an area efficient device parameter estimation method with sensitivity-configurable ring oscillator (RO). This sensitivity-configurable RO has a number of configurations and the proposed method exploits this property for reducing sensor area and/or improving estimation accuracy. The proposed method selects multiple sets of sensitivity configurations, obtains multiple estimates and computes the average of them for accuracy improvement exploiting an averaging effect. Experimental results with a 32-nm predictive technology model show that the proposed averaging with multiple estimates can reduce the estimation error by 49% or reduce the sensor area by 75% while keeping the accuracy. Compared to previous work with iterative estimation, 23% accuracy improvement is achieved.

The crossbar-based switch fabric is widely used in today's high performance switches, due to its internally nonblocking and simply implementation properties. Usually there are two main switching architectures for crossbar-based switch fabric: internally bufferless crossbar switch and crosspoint buffered crossbar switch. As internally bufferless crossbar switch requires a complex centralized scheduler which limits its scalability to high speeds, crosspoint buffered crossbar switch has gained more attention because of its simpler distributed scheduling algorithm and better switching performance. However, almost all the scheduling algorithms proposed previously for crosspoint buffered crossbar switch either have unsatisfactory scheduling performance under non-uniform traffic patterns or show poor service fairness between input traffic flows. In order to overcome the disadvantages of existing algorithms, in this paper we propose two novel high performance scheduling algorithms named MCQF_RR and IMCQF_RR for crosspoint buffered crossbar switches. Both algorithms have a time complexity of O(log N), where N is the number of input/output ports of the switch. MCQF_RR takes advantage of the combined weight information about queue length and service waiting time of input queues to perform scheduling. In order to further reduce the scheduling complexity and make it feasible for high speed switches, IMCQF_RR uses the compressed queue length information instead of original queue length information to schedule cells in input VOQs. Simulation results show that our novel scheduling algorithms MCQF_RR and IMCQF_RR can demonstrate excellent delay performance comparable to existing high performance scheduling algorithms under both uniform and non-uniform traffic patterns, while maintain good service fairness performance under severe non-uniform traffic patterns.

We present a low-voltage digitally-controlled oscillator (DCO) with the third-order ΔΣ modulator utilized in the medical implant communication service (MICS) frequency band. An optimized DCO core operating in the subthreshold region is designed, based on the gm/ID methodology. Thermometer coder with the dynamic element matching and ΔΣ modulator are implemented for the frequency tuning. High frequency resolution is achieved by using the ΔΣ modulator. The ΔΣ-modulator-based LC-DCO implemented in a 130-nm CMOS technology has achieved the phase noise of -115.3 dBc/Hz at 200 kHz offset frequency with the tuning range of 382 MHz to 412 MHz for the MICS band. It consumes 700 µW from a 0.7-V supply voltage and has a high frequency resolution of 18 kHz.

Camellia is a block cipher jointly developed by Mitsubishi and NTT of Japan. It is designed suitable for both software and hardware implementations. One of the design-for-test techniques using scan chains is called scan-path test, in which testers can observe and control the registers inside the LSI chip directly in order to check if the LSI chip correctly operates or not. Recently, a scan-based side-channel attack is reported which retrieves the secret information from the cryptosystem using scan chains. In this paper, we propose a scan-based attack method on the Camellia cipher using scan signatures. Our proposed method is based on the equivalent transformation of the Camellia algorithm and the possible key candidate reduction in order to retrieve the secret key. Experimental results show that our proposed method sucessfully retrieved its 128-bit secret key using 960 plaintexts even if the scan chain includes the Camellia cipher and other circuits and also sucessfully retrieves its secret key on the SASEBO-GII board, which is a side-channel attack standard evaluation board.

Reduced-reference (RR) image quality assessment (IQA) algorithm aims to automatically evaluate the distorted image quality with partial reference data. The goal of RR IQA metric is to achieve higher quality prediction accuracy using less reference information. In this paper, we introduce a new RR IQA metric by quantifying the difference of discrete cosine transform (DCT) entropy features between the reference and distorted images. Neurophysiological evidences indicate that the human visual system presents different sensitivities to different frequency bands. Moreover, distortions on different bands result in individual quality degradations. Therefore, we suggest to calculate the information degradation on each band separately for quality assessment. The information degradations are firstly measured by the entropy difference of reorganized DCT coefficients. Then, the entropy differences on all bands are pooled to obtain the quality score. Experimental results on LIVE, CSIQ, TID2008, Toyama and IVC databases show that the proposed method performs highly consistent with human perception with limited reference data (8 values).

Microwave ultra-wideband (UWB) radar systems are advantageous for their high-range resolution and ability to penetrate dielectric objects. Internal imaging of dielectric objects by UWB radar is a promising nondestructive method of testing aging roads and bridges and a noninvasive technique for human body examination. For these applications, we have already developed an accurate internal imaging approach based on the range points migration (RPM) method, combined with a method that efficiently estimates the dielectric constant. Although this approach accurately extracts the internal boundary, it is applicable only to highly conductive targets immersed in homogeneous dielectric media. It is not suitable for multi-layered dielectric structures such as human tissues or concrete objects. To remedy this limitation, we here propose a novel dielectric constant and boundary extraction method for double-layered materials. This new approach, which simply extends the Envelope method to boundary extraction of the inner layer, is evaluated in finite difference time domain (FDTD)-based simulations and laboratory experiments, assuming a double-layered concrete cylinder. These tests demonstrate that our proposed method accurately and simultaneously estimates the dielectric constants of both media and the layer boundaries.

Wireless local area networks (LANs) based on the IEEE802.11 standard usually use carrier sense multiple access with collision avoidance (CSMA/CA) for media access control. However, in CSMA/CA, if the number of wireless terminals increases, the back-off time derived by the initial contention window (CW) tends to conflict among wireless terminals. Consequently, a data frame collision often occurs, which sometimes causes the degradation of the total throughput in the transport layer protocols. In this study, to improve the total throughput, we propose a new media access control method, SP-MAC, which is based on the synchronization phenomena of coupled oscillators. Moreover, this study shows that SP-MAC drastically decreases the data frame collision probability and improves the total throughput when compared with the original CSMA/CA method.

In this study, we propose and fabricate an oscillator array composed of three resonant-tunneling-diode terahertz oscillators integrated with slot-coupled patch antennas, and which does not require a Si lens. We measure the radiation pattern for single and arrayed oscillator, and calculate the output power using the integration of the pattern. The output power of a single oscillator was found to be ～15 µW. However, using an array configuration, almost combined output power of ～55 µW was obtained.

Many public cloud datacenters have adopted the Edge-Overlay model which supports virtual switch-based network virtualization using IP tunneling. However, software-implemented virtual switches can cause performance degradation because the packet processing load can concentrate on a particular CPU core. As a result, such load concentration decreases and destabilizes the performance of virtual networks. Although multi-queue functions like Receive Side Scaling (RSS) can distribute the load onto multiple CPU cores, they still have performance problems such as IRQ core collision between priority flows as well as competitive resource use between host and guest machines for received packet processing. In this paper, we propose Virtual Switch Extension (VSE) that adaptively determines CPU core assignment for SoftIRQ to prevent performance degradation. VSE supports two types of SoftIRQ core selection mechanisms, on-the-fly or predetermined. In the on-the-fly mode, VSE selects a SoftIRQ core based on current CPU load to exploit low-loaded CPU resources. In the predetermined mode, SoftIRQ cores are assigned in advance to differentiate the performance of priority flows. This paper describes a basic architecture and implementation of VSE and how VSE assigns a SoftIRQ cores. Moreover, we evaluate fundamental throughput of various CPU assignment models in the predetermined mode. Finally, we evaluate the performance of a priority VM in two VM usecases, the client-usecase which is receive-oriented and the router-usecase which performs bi-directional communications. In the client-usecase, the throughput of the priority VM was improved by 31% compared with RSS when the priority VM had one dedicated core. In the router-usecase, the throughput was improved by 29% when three dedicated cores were provided for the VM.

Nonnegative matrix factorization (NMF) is an unsupervised technique to represent nonnegative data as linear combinations of nonnegative bases, which has shown impressive performance for source separation. However, its source separation performance degrades when one signal can also be described well with the bases for the interfering source signals. In this paper, we propose a discriminative NMF (DNMF) algorithm which exploits the reconstruction error for the interfering signals as well as the target signal based on target bases. The objective function for training the bases is constructed so as to yield high reconstruction error for the interfering source signals while guaranteeing low reconstruction error for the target source signals. Experiments show that the proposed method outperformed the standard NMF and another DNMF method in terms of both the perceptual evaluation of speech quality score and signal-to-distortion ratio in various noisy environments.

This letter presents a method for active noise cancelation (ANC) for headphone application. The method improves the performance of ANC by deriving a flexible independent component analysis (ICA) algorithm in a hybrid structure combining feedforward and feedback configurations with correlation-based wind detection. The effectiveness of the method is demonstrated through simulation.

We realize homogenous luminance of the directional backlight for the time-division multiplexing autostereoscopic display using a convex lens array with the elemental lenses whose phase of placement in each row differs from one another. The validity of the proposed optical design is confirmed by a prototype system.

An Al-N system optical absorption layer has been developed, to be used for Al-based metal mesh electrodes on touch screen panels. The triple-layered electrode effectively suppresses the optical reflection in both visible light and the blue color region and exhibits excellent wet etching property that accommodates micro-fabrication. Due to its high noise immunity and contact sensitivity originating from its low electrical resistivity, the proposed metal mesh electrodes are useful for touch-sensitive panels in the next generation ultra-high-resolution displays.

With the growth of cloud-based services, cloud data centers are experiencing large growth. A key component in a cloud data center is the network technology deployed. In particular, Ethernet technology, commonly deployed in cloud data centers, is already envisioned for 10 Tbps Ethernet. In this paper, we study and analyze the makespan, workload execution times, and virtual machine migrations as the network speed increases. In particular, we consider homogeneous and heterogeneous data centers, virtual machine scheduling algorithms, and workload scheduling algorithms. Results obtained from our study indicate that the increase in a network's speed reduces makespan and workloads execution times, while aiding in the increase of the number of virtual machine migrations. We further observed that the number of migrations' behaviors in relation to the speed of the networks also depends on the employed virtual machines scheduling algorithm.

Router virtualization is becoming more common as a method that uses network (NW) equipment effectively and robustly similar to server virtualization. Edge routers, which are gateways of core NWs, should be virtualized because they have many functions and resources just as servers do. To virtualize edge routers, a metro NW, which is a wide area layer-2 NW connecting each user's residential gateway to edge routers, must trace dynamic edge router re-allocation by changing the route of each Ethernet flow. Therefore, we propose a scalable centralized control architecture of a virtual layer-2 switch on a metro NW to trace virtual router re-allocation and use metro NW equipment effectively. The proposed scalable control architecture improves the centralized route control performance by processing in parallel on a flow-by-flow basis taking into account route information even in the worst case where edge routers fail. In addition, the architecture can equalize the load among parallel processes dynamically by using two proposed load re-allocation methods to increase the route control performance stably while minimizing the amount of resources for the control. We evaluate the scalability of the proposed architecture through theoretical analysis and experiments on a prototype and show that the proposed architecture increases the number of flows accommodated in a metro NW. Moreover, we evaluate the load re-allocation methods through simulation and show that they can evenly distribute the load among parallel processes. Finally, we show that the proposed architecture can be applied to not only large-scale metro NWs but also to data center NWs, which have recently become an important type of large-scale layer-2 NW.

In this paper, we propose a novel Autonomous Decentralized Control (ADC) scheme for indirectly controlling a system performance variable of large-scale and wide-area networks. In a large-scale and wide-area network, since it is impractical for any one node to gather full information of the entire network, network control must be realized by inter-node collaboration using information local to each node. Several critical network problems (e.g., resource allocation) are often formulated by a system performance variable that is an amount to quantify system state. We solve such problems by designing an autonomous node action that indirectly controls, via the Markov Chain Monte Carlo method, the probability distribution of a system performance variable by using only local information. Analyses based on statistical mechanics confirm the effectiveness of the proposed node action. Moreover, the proposal is used to implement traffic-aware virtual machine placement control with load balancing in a data center network. Simulations confirm that it can control the system performance variable and is robust against system fluctuations. A comparison against a centralized control scheme verifies the superiority of the proposal.

A low-complexity time-frequency multiplex estimator and low-complexity equalizer transceiver design are proposed to combat the problems of RF impairment associated with zero-IF transceiver of multi-carrier systems. Moreover, the proposed preambles can estimate the transmitter (TX) in-phase and quadrature-phase (IQ) imbalance, carrier frequency offset (CFO), and channel impulse response parameters. The proposed system has two parts. First, all parameters of the impairments are estimated by the designed time-frequency multiplex estimator. Second, the estimated parameters are used to compensate the above problems and detect the transmitted signal with low complexity. Simulation results confirm that the proposed estimator performs reliably with respect to IQ imbalance, CFO, and multipath fading channel effects.

Middle-level parts have attracted great attention in the computer vision community, acting as discriminative elements for objects. In this paper we propose an unsupervised approach to mine discriminative parts for object detection. This work features three aspects. First, we introduce an unsupervised, exemplar-based training process for part detection. We generate initial parts by selective search and then train part detectors by exemplar SVM. Second, a part selection model based on consistency and distinctiveness is constructed to select effective parts from the candidate pool. Third, we combine discriminative part mining with the deformable part model (DPM) for object detection. The proposed method is evaluated on the PASCAL VOC2007 and VOC2010 datasets. The experimental results demons-trate the effectiveness of our method for object detection.

This paper analyzes the impact of directional antennas in improving the transmission capacity, defined as the maximum allowable spatial node density of successful transmissions multiplied by their data rate with a given outage constraint, in wireless networks. We consider the case where the gain Gm for the mainlobe of beamwidth can scale at an arbitrarily large rate. Under the beamwidth scaling model, the transmission capacity is analyzed for all path-loss attenuation regimes for the following two network configurations. In dense networks, in which the spatial node density increases with the antenna gain Gm, the transmission capacity scales as Gm4/α, where α denotes the path-loss exponent. On the other hand, in extended networks of fixed node density, the transmission capacity scales logarithmically in Gm. For comparison, we also show an ideal antenna model where there is no sidelobe beam. In addition, computer simulations are performed, which show trends consistent with our analytical behaviors. Our analysis sheds light on a new understanding of the fundamental limit of outage-constrained ad hoc networks operating in the directional mode.