BLOCKSUM, also known as KEISANBLOCK in Japanese, is a Latin square filling type puzzle, such as Sudoku. In this paper, we prove that the decision problem whether a given instance of BLOCKSUM has a solution or not is NP-complete.

Face perception and recognition have attracted more attention recently in multidisciplinary fields such as engineering, psychology, neuroscience, etc. with the advances in physical/physiological measurement and data analysis technologies. In this paper, our main interest is building computational models of human face recognition based on psychological experiments. We specially focus on modeling human face recognition characteristics of average face in the dimension of distinctiveness. Psychological experiments were carried out to measure distinctiveness of face images and their results are explained by computer analysis results of the images. Two psychological experiments, 1) Classical experiment of distinctiveness rating and, 2) Novel experiment of recognition of an average face were performed. In the later experiment, we examined on how the average face of two face images was recognized by a human in a similarity test respect to the original images which were utilized for the calculation of the average face. To explain results of the psychological experiments, eigenface spaces were constructed based on Principal Component Analysis (PCA). Significant correlation was found between human and PCA based computer recognition results. Emulation of human recognition of faces is one of the expected applications of this research.

This letter presents the ideas and methods of the winning solution* for the Kaggle Algorithmic Trading Challenge. This analysis challenge took place between 11th November 2011 and 8th January 2012, and 264 competitors submitted solutions. The objective of this competition was to develop empirical predictive models to explain stock market prices following a liquidity shock. The winning system builds upon the optimal composition of several models and a feature extraction and selection strategy. We used Random Forest as a modeling technique to train all sub-models as a function of an optimal feature set. The modeling approach can cope with highly complex data having low Maximal Information Coefficients between the dependent variable and the feature set and provides a feature ranking metric which we used in our feature selection algorithm.

Estimating a proper location of vanishing point from a single road image without any prior known camera parameters is a challenging problem due to limited information from the input image. Most edge-based methods for vanishing point detection only work well for structured roads with clear painted lines or distinct boundaries, while they usually fail in unstructured roads lacking sharply defined, smoothly curving edges. In order to overcome this limitation, texture-based methods for vanishing point detection have been widely published. Authors of these methods often calculate the texture orientation at every pixel of the road image by using directional filter banks such as Gabor wavelet filter, and seek the vanishing point by a voting scheme. A local adaptive soft voting method for obtaining the vanishing point was proposed in a previous study. Although this method is more effective and faster than prior texture-based methods, the associated computational cost is still high due to a large number of scanning pixels. On the other hand, this method leads to an estimation error in some images, in which the radius of the proposed half-disk voting region is not large enough. The goal of this paper is to reduce the computational cost and improve the performance of the algorithm. Therefore, we propose a novel local soft voting method, in which the number of scanning pixels is much reduced, and a new vanishing point candidate region is introduced to improve the estimation accuracy. The proposed method has been implemented and tested on 1000 road images which contain large variations in color, texture, lighting condition and surrounding environment. The experimental results demonstrate that this new voting method is both efficient and effective in detecting the vanishing point from a single road image and requires much less computational cost when compared to the previous voting method.

In this paper, a symbol-rate clock recovery scheme for a receiver that uses an integrating decision feedback equalizer (DFE) is proposed. The proposed clock recovery using expected received signal amplitudes as the criterion realizes minimum mean square error (MMSE) clock recovery. A receiver architecture using an integrating DFE with the proposed symbol-rate clock recovery is also proposed. The proposed clock recovery algorithm successfully recovered the clock phase in a system level simulation only with a DFE. Higher jitter tolerance than 0.26 UIPP at 10 Gb/s operation was also confirmed in the simulation with an 11 dB channel loss at 5 GHz.

In recent years, technologies and markets related to data centers have been rapidly changing and growing. Data centers are playing an important role in ICT infrastructure deployment and promise to become common platforms for almost all social infrastructures. Even though research has focused on networking technologies, various technologies are needed to develop high-performance, cost-efficient, and flexible large-scale data centers. To understand those technologies better, this paper surveys recent research and development efforts and results in accordance with a data center network taxonomy that the authors defined.

Process variation causes significant fluctuations in the timing performance of analog circuits, which causes a fraction of circuits to fail specifications. By testing the delay-performance, we can recognize the failed circuits during production testing. In this paper, we have proposed a low overhead and process tolerant delay evaluation circuit for built-in self test (BIST) function for analog differential circuits. This circuit contains a delay generation cell, an input differential signal generation cell, a delay matching cell, a sample-hold circuit, and a comparator. This circuit was implemented with 0.18 µm CMOS process. Simulation results over process variation, devices mismatch and layout parasitics, but without silicon measurement, show that the accuracy in delay detection is within 5 ps. A case study was done over a feed-forward equalizer (FFE). A typical use of this circuit is testing the delay of various FIR (Finite Impulse Response) filters.

We have fabricated printed active antenna for flexible information tag which have a loop antenna combined with step-edge vertical channel organic field-effect transistor (SVC-OFET). Fabrication using printing process, characterization of SVC-OFETs, and performances of active antenna elements are discussed in detail.

REMUS-II (REconfigurable MUltimedia System 2) is a coarse-grained dynamically reconfigurable computing system for multimedia and communication baseband processing. This paper proposes a real-time H.264 baseline profile encoder on REMUS-II. First, we propose an overall mapping flow for mapping algorithms onto the platform of REMUS-II system and then illustrate it by implementing the H.264 encoder. Second, parallel and pipelining techniques are considered for fully exploiting the abundant computing resources of REMUS-II, thus increasing total computing throughput and solving high computational complexity of H.264 encoder. Besides, some data-reuse schemes are also used to increase data-reuse ratio and therefore reduce the required data bandwidth. Third, we propose a scheduling scheme to manage run-time reconfiguration of the system. The scheduling is also responsible for synchronizing the data communication between tasks and handling conflict between hardware resources. Experimental results prove that the REMUS-MB (REMUS-II version for mobile applications) system can perform a real-time H.264/AVC baseline profile encoder. The encoder can encode CIF@30 fps video sequences with two reference frames and maximum search range of [-16,15]. The implementation, thereby, can be applied to handheld devices targeted at mobile multimedia applications. The platform of REMUS-MB system is designed and synthesized by using TSMC 65 nm low power technology. The die size of REMUS-MB is 13.97 mm2. REMUS-MB consumes, on average, about 100 mW while working at 166 MHz. To my knowledge, in the literature this is the first implementation of H.264 encoding algorithm on a coarse-grained dynamically reconfigurable computing system.

This paper describes Path-Moose, a scalable tree-based shortest path bridging protocol. Both ARP-Path and Path-Moose protocols belong to a new category of bridges that we name All-path, because all paths of the network are explored simultaneously with a broadcast frame distributed over all network links to find a path or set a multicast tree. Path-Moose employs the ARP-based low latency routing mechanism of the ARP-Path protocol on a bridge basis instead of a per-single-host basis. This increases scalability by reducing forwarding table entries at core bridges by a factor of fifteen times for big data center networks and achieves a faster reconfiguration by an approximate factor of ten. Reconfiguration time is significantly shorter than ARP-Path (zero in many cases) because, due to the sharing of network paths by the hosts connected to same edge bridges, when a host needs the path it has already been recovered by another user of the path. Evaluation through simulations shows protocol correctness and confirms the theoretical evaluation results.

Given a graph G = (V,E) together with a nonnegative integer requirement on vertices r:V Z+, the annotated edge dominating set problem is to find a minimum set M ⊆ E such that, each edge in E - M is adjacent to some edge in M, and M contains at least r(v) edges incident on each vertex v ∈ V. The annotated edge dominating set problem is a natural extension of the classical edge dominating set problem, in which the requirement on vertices is zero. The edge dominating set problem is an important graph problem and has been extensively studied. It is well known that the problem is NP-hard, even when the graph is restricted to a planar or bipartite graph with maximum degree 3. In this paper, we show that the annotated edge dominating set problem in graphs with maximum degree 3 can be solved in O*(1.2721n) time and polynomial space, where n is the number of vertices in the graph. We also show that there is an O*(2.2306k)-time polynomial-space algorithm to decide whether a graph with maximum degree 3 has an annotated edge dominating set of size k or not.

In this paper, we consider a problem of simultaneously optimizing a sequence of graphs and a route which exhaustively visits the vertices from each pair of successive graphs in the sequence. This type of problem arises from repetitive routing of grasp-and-delivery robots used in the production of printed circuit boards. The problem is formulated as follows. We are given a metric graph G*=(V*,E*), a set of m+1 disjoint subsets Ci ⊆ V* of vertices with |Ci|=n, i=0,1,...,m, and a starting vertex s ∈ C0. We seek to find a sequence π=(Ci1, Ci2, ..., Cim) of the subsets of vertices and a shortest walk P which visits all (m+1)n vertices in G* in such a way that after starting from s, the walk alternately visits the vertices in Cik-1 and Cik, for k=1,2,...,m (i0=0). Thus, P is a walk with m(2n-1) edges obtained by concatenating m alternating Hamiltonian paths between Cik-1 and Cik, k=1,2,...,m. In this paper, we show that an approximate sequence of subsets of vertices and an approximate walk with at most three times the optimal route length can be found in polynomial time.

Magnetospinography (MSG) is one of the most promising techniques to detect the nerve activity of spinal cords thanks to its noninvasiveness and high spatial/temporal resolutions. Multichannel superconducting quantum interference device (SQUID) MSG measurement systems optimized for supine subjects have been developed previously and employed in clinical applications in hospitals. Magnetic source analyses of MSG data based on spatial filter techniques reveal the transition of reconstructed current distributions adjacent to the spinal cord. The propagation of the neural signals was noninvasively visualized. The MSG measurements provide significant diagnostic information such as irregularities in the transitions of the reconstructed current distribution and/or considerable decreases in the current intensity at the lesion. Such functional imaging of the spinal cord in addition to conventional neurologic examinations and morphological imaging will be fairly effective in presurgical lesion localizations of the spinal cord.

We report enhanced photocurrent properties of dye/Au-loaded titanium dioxide (TiO2) films on Au gratings. Au-loaded TiO2 nanopowders were first synthesized by a modified sol-gel method and then prepared by the impregnation method. We also fabricated dye-sensitized solar cells, which were composed of Au grating/Au-TiO2/TMPyP-SCC LbL (20 bilayers)/electrolyte/ITO substrates. Short-circuit photo-current measurements showed that Au-loaded TiO2 with grating-coupled surface plasmon excitation can enhance the short-circuit photocurrentof the fabricated cells.

This paper describes mobile backhaul optical access network designs for future cellular systems, in particular, for those systems that exploit coordinated multipoints (CoMP) transmission/reception techniques. Wavelength-division-multiplexing passive optical networks (WDM-PON) are primarily considered and two proposals to enhance mobile backhaul capability of WDM-PONs for CoMP are presented. One is physical X2 links that support dedicated low latency and high capacity data exchange between base stations (BSs). The other is multicasting in WDM-PONs. It effectively reduces data/control transmission time from central node to multiple BSs joining CoMP. Evaluation results verify that the proposed X2 links and the multicasting enable more BSs to join CoMP by enhancing the mobile backhaul capability, which results in improved service quality for users.

Congestion inherently occurs on the Internet due to traffic concentration on certain nodes or links of networks. The traffic concentration is caused by inefficient use of topological information of networks in existing routing protocols, which reduces to inefficient mapping between traffic demands and network resources. Actually, the route with minimum cost, i.e., number of hops, selected as a transmission route by existing routing protocols would pass through specific nodes with common topological characteristics that could contribute to a large improvement in minimizing the cost. However, this would result in traffic concentration on such specific nodes. Therefore, we propose a measure of the distance between two nodes that is suitable for reducing traffic concentration on specific nodes. To consider the topological characteristics of the congestion points of networks, we define node-to-node distance by using a generalized norm, p-norm, of a vector of which elements are degrees of intermediate nodes of the route. Simulation results show that both the maximum Stress Centrality (SC) and the coefficient of variation of the SC are minimized in some network topologies by selecting transmission routes based on the proposed measure of node-to-node distance.

Automatic vessel tortuosity measures are crucial for many applications related to retinal diseases such as those due to retinopathy of prematurity (ROP), hypertension, stroke, diabetes and cardiovascular diseases. An automatic evaluation and quantification of retinal vascular tortuosity would help in the early detection of such retinopathies and other systemic diseases. In this paper, we propose a novel tortuosity index based on principal component analysis. The index is compared with three existant indices using simulated curves and real retinal images to demonstrate that it is a valid indicator of tortuosity. The proposed index satisfies all the tortuosity properties such as invariance to translation, rotation and scaling and also the modulation properties. It is capable of differentiating the tortuosity of structures that visually appear to be different in tortuosity and shapes. The proposed index can automatically classify the image as tortuous or non tortuous. For an optimal set of training parameters, the prediction accuracy is as high as 82.94% and 86.6% on 45 retinal images at segment level and image level, respectively. The test results are verified against the judgement of two expert Ophthalmologists. The proposed index is marked by its inherent simplicity and computational attractiveness, and produces the expected estimate, irrespective of the segmentation approach. Examples and experimental results demonstrate the fitness and effectiveness of the proposed technique for both simulated curves and retinal images.

Multihoming is widely used by Internet service providers (ISPs) to obtain improved performance and reliability when connecting to the Internet. Recently, the use of overlay routing for network application traffic is rapidly increasing. As a source of both routing oscillation and cost increases, overlay routing is known to bring challenges to ISPs. In this paper, we study the interaction between overlay routing and a multihomed ISP's routing strategy with a Nash game model, and propose a routing strategy for the multihomed ISP to alleviate the negative impact of overlay traffic. We prove that with the proposed routing strategy, the network routing game can always converge to a stable state, and the ISP can reduce costs to a relatively low level. From numerical simulations, we show the efficiency and convergence resulting from the proposed routing strategy. We also discuss the conditions under which the multihomed ISP can realize minimum cost by the proposed strategy.

We propose a novel technique for the estimation of device-parameters suitable for postfabrication performance compensation and adaptive delay testing, which are effective means to improve the yield and reliability of LSIs. The proposed technique is based on Bayes' theorem, in which the device-parameters of a chip, such as the threshold voltage of transistors, are estimated by current signatures obtained in a regular IDDQ testing framework. Neither additional circuit implementation nor additional measurement is required for the purpose of parameter estimation. Numerical experiments demonstrate that the proposed technique can achieve 10-mV accuracy in threshold voltage estimations.

Overlay routing is an application-level routing mechanism on overlay networks. Previous researches have revealed that the overlay routing can improve user-perceived performance. However, it may also generate traffic unintended by ISPs, incurring additional monetary cost. In addition, since ISPs and end users have their own objectives respectively regarding traffic routing, overlay routing must be operated considering both standpoints. In the present paper, we propose a method to reduce inter-ISP transit costs caused by overlay routing from the both standpoints of ISPs and end users. To determine the relationships among ASes, which are required for ISP cost-aware routing, we construct a method to estimate a transit cost of overlay-routed paths from end-to-end network performance values. Utilizing the metric, we propose a novel method that controls overlay routing from the both standpoints of ISPs and end users. Through extensive evaluations using measurement results from the actual network environments, we confirm that the advantage of the proposed method whereby we can reduce the transit cost in the overlay routing and can control the overlay routing according to the objectives of both ISPs and end users.