RAID has been widely deployed in disk array storage systems to manage both performance and reliability simultaneously. RAID conducts two performance-critical operations during disk failures known as degraded reads/writes and recovery process. Before the recovery process is complete, reads and writes are degraded because data is reconstructed using data redundancy. The performance of degraded reads/writes is critical in order to meet stipulations in customer service level agreements (SLAs), and the recovery process affects the reliability of a storage system considerably. Both operations require fast data reconstruction. Among the erasure codes for fast reconstruction, Local Reconstruction Codes (LRC) are known to offer the best (or optimal) trade-off between storage overhead, fault tolerance, and the number of disks involved in reconstruction. Originally, LRC was designed for fast reconstruction in distributed cloud storage systems, in which network traffic is a major bottleneck during reconstruction. Thus, LRC focuses on reducing the number of disks involved in data reconstruction, which reduces network traffic. However, we observe that when LRC is applied to primary array storage systems, a major bottleneck in reconstruction results from uneven disk utilization. In other words, underutilized disks can no longer receive I/O requests as a result of the bottleneck of overloaded disks. Uneven disk utilization in LRC is due to its dedicated group partitioning policy to achieve the Maximally Recoverable property. In this paper, we present Distributed Reconstruction Codes (DRC) that support fast reconstruction in primary array storage systems. DRC is designed with group shuffling policy to solve the problem of uneven disk utilization. Experiments on real-world workloads show that DRC using global parity rotation (DRC-G) improves degraded performance by as much as 72% compared to RAID-6 and by as much as 35% compared to LRC under the same reliability. In addition, our study shows that DRC-G reduces the recovery process completion time by as much as 52% compared to LRC.

We prepared alumina passivation films for p-type silicon substrates by sol-gel wet process mainly using aluminum isopropoxide (Al(O-i-Pr)3) as a precursor material. The precursor solution was spin-coated onto p-type silicon substrates and then calcined for 1 hour in air. Minority carrier lifetime of the passivated wafers was evaluated for different calcination temperature conditions. We also compared the passivation quality of the alumina passivation films using different alumina precursor, aluminum acetylacetonate (Al(acac)3). Obtained effective minority carrier lifetime indicated that the lifetime is strongly depends on the calcination temperature. The substrate calcined below 400°C shows relatively short lifetime below 100 µsec. On the other hand, the substrate calcined around 500°C to 600°C indicates lifetime from 250 to 300 µsec. Calcination temperature dependence of the lifetime for the samples using Al(O-i-Pr)3 precursors shows almost the same as that using Al(acac)3.

Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique, suitable for measurement during motor learning. However, effects of contamination by systemic artifacts derived from the scalp layer on learning-related fNIRS signals remain unclear. Here we used fNIRS to measure activity of sensorimotor regions while participants performed a visuomotor task. The comparison of results using a general linear model with and without systemic artifact removal shows that systemic artifact removal can improve detection of learning-related activity in sensorimotor regions, suggesting the importance of removal of systemic artifacts on learning-related cerebral activity.

The sparse representation models have been widely applied in image super-resolution. The certain optimization problem is supposed and can be solved by the iterative shrinkage algorithm. During iteration, the update of dictionaries and similar patches is necessary to obtain prior knowledge to better solve such ill-conditioned problem as image super-resolution. However, both the processes of iteration and update often spend a lot of time, which will be a bottleneck in practice. To solve it, in this paper, we present the concept of image quality difference based on generalized Gaussian distribution feature which has the same trend with the variation of Peak Signal to Noise Ratio (PSNR), and we update dictionaries or similar patches from the termination strategy according to the adaptive threshold of the image quality difference. Based on this point, we present two sparse representation algorithms for image super-resolution, one achieves the further improvement in image quality and the other decreases running time on the basis of image quality assurance. Experimental results also show that our quantitative results on several test datasets are in line with exceptions.

All the existing sender-based message logging (SBML) protocols share a well-known limitation that they cannot tolerate concurrent failures. In this paper, we analyze the cause for this limitation in a unicast network environment, and present an enhanced SBML protocol to overcome this shortcoming while preserving the strengths of SBML. When the processes on different nodes execute a distributed application together in a broadcast network, this new protocol replicates the log information of each message to volatile storages of other processes within the same broadcast network. It may reduce the communication overhead for the log replication by taking advantage of the broadcast nature of the network. Simulation results show our protocol performs better than the traditional one modified to tolerate concurrent failures in terms of failure-free execution time regardless of distributed application communication pattern.

This paper deals with the diffraction of a monochromatic plane wave by a periodic grating. We discuss a problem how to obtain a numerical diffraction efficiency (NDE) satisfying the reciprocity theorem for diffraction efficiencies, because diffraction efficiencies are the subject of the diffraction theories. First, this paper introduces a new formula that decomposes an NDE into two components: the even component and the odd one. The former satisfies the reciprocity theorem for diffraction efficiencies, but the latter does not. Therefore, the even component of an NDE becomes an answer to our problem. On the other hand, the odd component of an NDE represents an unwanted error. Using such the decomposition formula, we then obtain another new formula that decomposes the conventional energy error into two components. One is the energy error made by even components of NDE's. The other is the energy error constructed by unwanted odd ones and it may be used as a reciprocity criterion of a numerical solution. This decomposition formula shows a drawback of the conventional energy balance. The total energy error is newly introduced as a more strict condition for a desirable solution. We point out theoretically that the reciprocal wave solution, an approximate solution satisfying the reciprocity for wave fields, gives another solution to our problem. Numerical examples are given for the diffraction of a TM plane wave by a very rough periodic surface with perfect conductivity. In the case of a numerical solution by the image integral equation of the second kind, we found that the energy error is much reduced by use of the even component of an NDE as an approximate diffraction efficiency or by use of a reciprocal wave solution.

Packages are re-usable components for faster and effective software maintenance. To promote the re-use in object-oriented systems and maintenance tasks easier, packages should be organized to depict compact design. Therefore, understanding and assessing package organization is primordial for maintenance tasks like Re-usability and Changeability. We believe that additional investigations of prevalent basic design principles such as defined by R.C. Martin are required to explore different aspects of package organization. In this study, we propose package-organization framework based on reachable components that measures re-usability index. Package re-usability index measures common effect of change taking place over dependent elements of a package in an object-oriented design paradigm. A detailed quality assessment on different versions of open source software systems is presented which evaluates capability of the proposed package re-usability index and other traditional package-level metrics to predict fault-proneness in software. The experimental study shows that proposed index captures different aspects of package-design which can be practically integrated with best practices of software development. Furthermore, the results provide insights on organization of feasible software design to counter potential faults appearing due to complex package dependencies.

We fabricated silicon solar cells with spin-coated sol-gel alumina passivation layers on the rear side. Spin-coated alumina passivation films have moderate passivation quality and are inferior to atomic layer deposited passivation films. However, low-cost and low temperature process of the sol-gel deposition is still beneficial for the cells using commercially available Cz silicon wafers. Thus, we consider an applicability of the spin-coated alumina passivation layer for rear side passivation. Dependence of cell efficiency on contact spacing and contact diameter of a rear electrode was investigated by both experiments and numerical calculation. The experimental results indicated that conversion efficiency of the cell is enhanced from 9.1% to 11.1% by optimizing an aperture ratio and contact spacing of the rear passivation layers. Numerical calculation indicated that small contact diameter with low aperture ratio of a rear passivation layer is preferable to achieve good cell performance in our experimental condition. We confirmed the effectivity of the spin-coated alumina passivation films for rear surface passivation of the low-cost silicon solar cells.

We propose a framework to perform auto-radiometric calibration in photometric stereo methods to estimate surface orientations of an object from a sequence of images taken using a radiometrically uncalibrated camera under varying illumination conditions. Our proposed framework allows the simultaneous estimation of surface normals and radiometric responses, and as a result can avoid cumbersome and time-consuming radiometric calibration. The key idea of our framework is to use the consistency between the irradiance values converted from pixel values by using the inverse response function and those computed from the surface normals. Consequently, a linear optimization problem is formulated to estimate the surface normals and the response function simultaneously. Finally, experiments on both synthetic and real images demonstrate that our framework enables photometric stereo methods to accurately estimate surface normals even when the images are captured using cameras with unknown and nonlinear response functions.

In this paper, we propose a fast Maximal Empty Rectangle (MER) enumeration algorithm for online task placement on reconfigurable Field-Programmable Gate Arrays (FPGAs). On the assumption that each task utilizes rectangle-shaped resources, the proposed algorithm can manage the free space on FPGAs by an MER list. When assigning or removing a task, a series of MERs are selected and cut into segments according to the task and its assignment location. By processing these segments, the MER list can be updated quickly with low memory consumption. Under the proof of the upper limit of the number of the MERs on the FPGA, we analyze both the time and space complexity of the proposed algorithm. The efficiency of the proposed algorithm is verified by experiments.

In this paper, we will present analysis on the fault erasure BP decoders based on the density evolution. In the fault BP decoder, the messages exchanged in a BP process are stochastically corrupted due to unreliable logic gates and flip-flops; i.e., we assume circuit components with transient faults. We derived a set of the density evolution equations for the fault erasure BP processes. Our density evolution analysis reveals the asymptotic behaviors of the estimation error probability of the fault erasure BP decoders. In contrast to the fault free cases, it is observed that the error probabilities of the fault erasure BP decoder converge to positive values, and that there exists a discontinuity in an error curve corresponding to the fault BP threshold. It is also shown that an message encoding technique provides higher fault BP thresholds than those of the original decoders at the cost of increased circuit size.

Faster-than-Nyquist (FTN) signaling is investigated for quasi-static flat fading massive multiple-input multiple-output (MIMO) systems. In FTN signaling, pulse trains are sent at a symbol rate higher than the Nyquist rate to increase the transmission rate. As a result, inter-symbol interference occurs inevitably for flat fading channels. This paper assesses the information-theoretically achievable rate of MIMO FTN signaling based on the optimum joint equalization and multiuser detection. The replica method developed in statistical physics is used to evaluate the achievable rate in the large-system limit, where the dimensions of input and output signals tend to infinity at the same rate. An analytical expression of the achievable rate is derived for general modulation schemes in the large-system limit. It is shown that FTN signaling does not improve the channel capacity of massive MIMO systems, and that FTN signaling with quadrature phase-shift keying achieves the channel capacity for all signal-to-noise ratios as the symbol period tends to zero.

The main contribution of this paper is a non-trivial expression, that is called dual expression, of the posterior values for non-adaptive group testing problems. The dual expression is useful for exact bitwise MAP estimation. We assume a simplest non-adaptive group testing scenario including N-objects with binary status and M-tests. If a group contains one or more positive object, the test result for the group is assumed to be one; otherwise, the test result becomes zero. Our inference problem is to evaluate the posterior probabilities of the objects from the observation of M-test results and the prior probabilities for objects. The derivation of the dual expression of posterior values can be naturally described based on a holographic transformation to the normal factor graph (NFG) representing the inference problem. In order to handle OR constraints in the NFG, we introduce a novel holographic transformation that converts an OR function to a function similar to an EQUAL function.

The three dimensional (3D) reconstruction of a medical image sequence can provide intuitive morphologies of a target and help doctors to make more reliable diagnosis and give a proper treatment plan. This paper aims to reconstruct the surface of a renal corpuscle from the microscope renal biopsy image sequence. First, the contours of renal corpuscle in all slices are extracted automatically by using a context-based segmentation method with a coarse registration. Then, a new coevolutionary-based strategy is proposed to realize a fine registration. Finally, a Gauss-Seidel iteration method is introduced to achieve a non-rigid registration. Benefiting from the registrations, a smooth surface of the target can be reconstructed easily. Experimental results prove that the proposed method can effectively register the contours and give an acceptable surface for medical doctors.

With being pushed into sub-16nm regime, advanced technology nodes printing in optical micro-lithography relies heavily on aggressive Optical Proximity Correction (OPC) in the foreseeable future. Although acceptable pattern fidelity is utilized under process variations, mask design time and mask manufacturability form crucial parameters whose tackling in the OPC recipe is highly demanded by the industry. In this paper, we propose an intensity based OPC algorithm to find a highly manufacturable mask solution for a target pattern with acceptable pattern fidelity under process variations within a short computation time. This is achieved through utilizing a fast intensity estimation model in which intensity is numerically correlated with local mask density and kernel type to estimate the intensity in a short time and with acceptable estimation accuracy. This estimated intensity is used to guide feature shifting, alignment, and concatenation following linearly interpolated variational intensity error model to achieve high mask manufacturability with preserving acceptable pattern fidelity under process variations. Experimental results show the effectiveness of our proposed algorithm on the public benchmarks.

Cross correlation is a general way to estimate time delay of arrival (TDOA), with a computational complexity of O(n log n) using fast Fourier transform. However, since only one spike is required for time delay estimation, complexity can be further reduced. Guided by Chinese Remainder Theorem (CRT), this paper presents a new approach called Co-prime Aliased Sparse FFT (CASFFT) in O(n1-1/d log n) multiplications and O(mn) additions, where m is smooth factor and d is stage number. By adjusting these parameters, it can achieve a balance between runtime and noise robustness. Furthermore, it has clear advantage in parallelism and runtime for a large range of signal-to-noise ratio (SNR) conditions. The accuracy and feasibility of this algorithm is analyzed in theory and verified by experiment.

Wireless channel emulators are used for the performance evaluation of wireless systems when actual wireless environment test is infeasible. The main contribution of this paper is the design of a MU-MIMO channel emulator capable of sending channel feedback automatically to the access point from the generated channel coefficients after the programmable time duration. This function is used for MU beamforming features of IEEE 802.11ac. The second contribution is the low complexity design of MIMO channel emulator with a single path implementation for all MIMO channel taps. A single path design allows all elements of the MIMO channel matrix to use only one Gaussian noise generator, Doppler filter, spatial correlation channel and Rician fading emulator to minimize the hardware complexity. In addition, single path implementation allows the addition of the feedback channel output with only a few additional non-sequential elements which would otherwise double in a parallel implementation. To demonstrate the functionality of our MU-MIMO channel emulator, we present actual hardware emulator results of MU-BF receive signal constellation on oscilloscope.

To resist algebraic and fast algebraic attacks, Boolean functions used in stream ciphers should have optimal algebraic immunity and good fast algebraic immunity. One challenge of cryptographic Boolean functions is to determine their ability to resist fast algebraic attacks, which can be measured by their fast algebraic immunities. In this letter, we determine the exact values of fast algebraic immunity of the majority function of 2m and 2m+1 variables. This is the first time that the exact values of the fast algebraic immunity of an infinite class of symmetric Boolean functions with optimal algebraic immunity are determined.

In this letter, we propose a novel discriminative representation for patterned fabric defect inspection when only limited negative samples are available. Fisher criterion is introduced into the loss function of deep learning, which can guide the learning direction of deep networks and make the extracted features more discriminating. A deep neural network constructed from the encoder part of trained autoencoders is utilized to classify each pixel in the images into defective or defectless categories, using as context a patch centered on the pixel. Sequentially the confidence map is processed by median filtering and binary thresholding, and then the defect areas are located. Experimental results demonstrate that our method achieves state-of-the-art performance on the benchmark fabric images.

Many important problems in communication networks, transportation networks, and logistics networks are solved by the minimization of cost functions. In general, these can be complex optimization problems involving many variables. However, physicists noted that in a network, a node variable (such as the amount of resources of the nodes) is connected to a set of link variables (such as the flow connecting the node), and similarly each link variable is connected to a number of (usually two) node variables. This enables one to break the problem into local components, often arriving at distributive algorithms to solve the problems. Compared with centralized algorithms, distributed algorithms have the advantages of lower computational complexity, and lower communication overhead. Since they have a faster response to local changes of the environment, they are especially useful for networks with evolving conditions. This review will cover message-passing algorithms in applications such as resource allocation, transportation networks, facility location, traffic routing, and stability of power grids.