This paper reviews architectures and topologies for column-parallel analog-to-digital converters (ADCs) used for CMOS image sensors (CISs) and discusses the performance of CISs using column-parallel ADCs based on figures-of-merit (FoM) with considering noise models which behave differently at low/middle and high pixel-rate regions. Various FoM considering different performance factors are defined. The defined FoM are applied to surveyed data on reported CISs using column-parallel ADCs which are categorized into 4 types; single slope, SAR, cyclic and delta-sigma ADCs. The FoM defined by (noise)2(power)/(pixel-rate) separately for low/middle and high pixel-rate regions well explains the frontline of the CIS' performance in all the pixel rates. Using the FoM defined by (noise)2(power)/(intrascene dynamic range)(pixel-rate), the effectiveness of recently-reported techniques for extended-dynamic-range CISs is clarified.

Internal quantum efficiency (IQE) is usually estimated from temperature dependence of photoluminescence (PL) intensity by assuming that the IQE at cryogenic temperature is unity. III-nitride samples, however, usually have large defect density, and the assumption is not necessarily valid. In 2016, we proposed a new method to estimate accurate IQE values by simultaneous PL and photo-acoustic (PA) measurements, and demonstratively evaluated the IQE values for various GaN samples. In this study, we have applied the method to InGaN quantum-well active layers and have estimated the IQE values and their excitation carrier-density dependence in the layers.

Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.

The accurate assessment of infants' pain is important for understanding their medical conditions and developing suitable treatment. Pediatric studies reported that the inadequate treatment of infants' pain might cause various neuroanatomical and psychological problems. The fact that infants can not communicate verbally motivates increasing interests to develop automatic pain assessment system that provides continuous and accurate pain assessment. In this paper, we propose a new set of pain facial activity features to describe the infants' facial expression of pain. Both dynamic facial texture feature and dynamic geometric feature are extracted from video sequences and utilized to classify facial expression of infants as pain or no pain. For the dynamic analysis of facial expression, we construct spatiotemporal domain representation for texture features and time series representation (i.e. time series of frame-level features) for geometric features. Multiple facial features are combined through both feature fusion and decision fusion schemes to evaluate their effectiveness in infants' pain assessment. Experiments are conducted on the video acquired from NICU infants, and the best accuracy of the proposed pain assessment approaches is 95.6%. Moreover, we find that although decision fusion does not perform better than that of feature fusion, the False Negative Rate of decision fusion (6.2%) is much lower than that of feature fusion (25%).

Utilizing software architecture patterns is important for reducing maintenance costs. However, maintaining code according to the constraints defined by the architecture patterns is time-consuming work. As described herein, we propose a technique to detect code fragments that are incompliant to the architecture as fine-grained architectural violations. For this technique, the dependence graph among code fragments extracted from the source code and the inference rules according to the architecture are the inputs. A set of candidate components to which a code fragment can be affiliated is attached to each node of the graph and is updated step-by-step. The inference rules express the components' responsibilities and dependency constraints. They remove candidate components of each node that do not satisfy the constraints from the current estimated state of the surrounding code fragment. If the inferred role of a code fragment does not include the component that the code fragment currently belongs to, then it is detected as a violation. We have implemented our technique for the Model-View-Controller for Web Application architecture pattern. By applying the technique to web applications implemented using Play Framework, we obtained accurate detection results. We also investigated how much does each inference rule contribute to the detection of violations.

Modeling user activities on the Web is a key problem for various Web services, such as news article recommendation and ad click prediction. In our work-in-progress paper[1], we introduced an approach that summarizes each sequence of user Web page visits using Paragraph Vector[3], considering users and URLs as paragraphs and words, respectively. The learned user representations are used among the user-related prediction tasks in common. In this paper, on the basis of analysis of our Web page visit data, we propose Backward PV-DM, which is a modified version of Paragraph Vector. We show experimental results on two ad-related data sets based on logs from Web services of Yahoo! JAPAN. Our proposed method achieved better results than those of existing vector models.

The impedance expansion method (IEM), which has been previously proposed by the authors, is a circuit-modeling technique for electrically-very-small devices. This paper provides a new idea on the principle of undesired radiation in wireless power transfer systems by employing IEM. In particular, it is shown that the undesired radiation is due to equivalent infinitesimal dipoles and loops of the currents on the coils.

We target the estimation of antenna patterns of distributed array antenna (DAA) systems for satellite communications. Measuring DAA patterns is very difficult because of the large antenna separations involved, more than several tens of wavelengths. Our goal is to elucidate the accuracy of the DAA pattern estimation method whose inputs are actual antenna pattern data and array factors by evaluating their similarity to actually measured DAA radiation patterns. Experiments on two Ku band parabolic antennas show that their patterns can be accurately estimated even if we change the conditions such as frequency, antenna arrangement and polarization. Evaluations reveal that the method has high estimation accuracy since its errors are better than 1dB. We conclude the method is useful for the accurate estimation of DAA patterns.

In this paper, we propose a method of salient object detection based on distributed seeds and a co-propagation of seed information. Salient object detection is a technique which estimates important objects for human by calculating saliency values of pixels. Previous salient object detection methods often produce incorrect saliency values near salient objects in the case of images which have some objects, called the leakage of saliencies. Therefore, a method based on a co-propagation, the scale invariant feature transform, the high dimensional color transform, and machine learning is proposed to reduce the leakage. Firstly, the proposed method estimates regions clearly located in salient objects and the background, which are called as seeds and resultant seeds, are distributed over images. Next, the saliency information of seeds is simultaneously propagated, which is then referred as a co-propagation. The proposed method can reduce the leakage caused because of the above methods when the co-propagation of each information collide with each other near the boundary. Experiments show that the proposed method significantly outperforms the state-of-the-art methods in mean absolute error and F-measure, which perceptually reduces the leakage.

Automatic detection of heart cycle abnormalities in a long duration of ECG data is a crucial technique for diagnosing an early stage of heart diseases. Concretely, Paroxysmal stage of Atrial Fibrillation rhythms (ParAF) must be discriminated from Normal Sinus rhythms (NS). The both of waveforms in ECG data are very similar, and thus it is difficult to completely detect the Paroxysmal stage of Atrial Fibrillation rhythms. Previous studies have tried to solve this issue and some of them achieved the discrimination with a high degree of accuracy. However, the accuracies of them do not reach 100%. In addition, no research has achieved it in a long duration, e.g. 12 hours, of ECG data. In this study, a new mechanism to tackle with these issues is proposed: “Door-to-Door” algorithm is introduced to accurately and quickly detect significant peaks of heart cycle in 12 hours of ECG data and to discriminate obvious ParAF rhythms from NS rhythms. In addition, a quantitative method using Artificial Neural Network (ANN), which discriminates unobvious ParAF rhythms from NS rhythms, is investigated. As the result of Door-to-Door algorithm performance evaluation, it was revealed that Door-to-Door algorithm achieves the accuracy of 100% in detecting the significant peaks of heart cycle in 17 NS ECG data. In addition, it was verified that ANN-based method achieves the accuracy of 100% in discriminating the Paroxysmal stage of 15 Atrial Fibrillation data from 17 NS data. Furthermore, it was confirmed that the computational time to perform the proposed mechanism is less than the half of the previous study. From these achievements, it is concluded that the proposed mechanism can practically be used to diagnose early stage of heart diseases.

This paper derives highly accurate and effective closed-form formulas for the average upper bound on the pairwise error probability (PEP) of the multi-carrier index keying orthogonal frequency division multiplexing (MCIK-OFDM) system with low-complexity detection (i.e., greedy detection) in two-wave with diffuse power (TWDP) fading channels. To be specific, we utilize an exact moment generating function (MGF) of the signal-to-noise ratio (SNR) under TWDP fading to guarantee highly precise investigations of error probability performance; existing formulas for average PEP employ the approximate probability density function (PDF) of the SNR for TWDP fading, thereby inducing inherent approximation error. Moreover, some special cases of TWDP fading are also considered. To quantitatively reveal the achievable modulation gain and diversity order, we further derive asymptotic formulas for the upper bound on the average PEP. The obtained asymptotic expressions can be used to rapidly estimate the achievable error performance of MCIK-OFDM with the greedy detection over TWDP fading in high SNR regimes.

In this paper, we propose a boundary-aware superpixel segmentation method, which could quickly and exactly extract superpixel with a non-iteration framework. The basic idea is to construct a minimum spanning tree (MST) based on structure edge to measure the local similarity among pixels, and then label each pixel as the index with shortest path seeds. Intuitively, we first construct MST on the original pixels with boundary feature to calculate the similarity of adjacent pixels. Then the geodesic distance between pixels can be exactly obtained based on two-round tree recursions. We determinate pixel label as the shortest path seed index. Experimental results on BSD500 segmentation benchmark demonstrate the proposed method obtains best performance compared with seven state-of-the-art methods. Especially for the low density situation, our method can obtain the boundary-aware oversegmentation region.

This paper proposes route advertisement policies (RAP) and an inbound traffic engineering (ITE) technique for a multihomed autonomous system (AS) employing the Border Gateway Protocol (BGP) and provider aggregatable (PA) addressing. The proposed RAP avail the advantage of address aggregation benefit of PA addressing. If multiple address spaces are allocated to each of the ASes that are multihomed to multiple upstream ASes, reduction of the forwarding information base (FIB) and quick convergence are achieved. However, multihoming based on PA addressing raises two issues. First, more specific address information is hidden due to address aggregation. Second, multiple allocated address spaces per AS does not provide the capability of ITE. To cope with these two limitations, we propose i) RAP to ensure connectivity among ASes with fewer routes installed in the FIB of each top-tier AS, and ii) an ITE technique to control inbound routes into multihomed ASes. Our ITE technique does not increase the RIB and FIB sizes in the Internet core. We implement the proposed RAP in an emulation environment with BGP using the Quagga software suite and our developed Hierarchical Automatic Number Allocation (HANA) protocols. We use HANA as a tool to automatically allocate hierarchical PA addresses to ASes. We confirm that with our proposed policies the FIB and RIB (routing information base) sizes in tier-1 ASes do not change with the increase of tier-3 ASes, and the number of BGP update messages exchanged is reduced by up to 69.9% from that achieved with conventional BGP RAP. We also confirmed that our proposed ITE technique, based on selective prefix advertisement, can indeed control inbound traffic into a multihomed AS employing PA addressing.

This paper discusses the effect of pre-grouping on vector classification based on the self-organizing map (SOM). The SOM is an unsupervised learning neural network, and is used to form clusters of vectors using its topology preserving nature. The use of SOMs for practical applications, however, may pose difficulties in achieving high recognition accuracy. For example, in image recognition, the accuracy is degraded due to the variation of lighting conditions. This paper considers the effect of pre-grouping of feature vectors on such types of applications. The proposed pre-grouping functionality is also based on the SOM and introduced into a new parallel configuration of the previously proposed SOM-Hebb classifers. The overall system is implemented and applied to position identification from images obtained in indoor and outdoor settings. The system first performs the grouping of images according to the rough representation of the brightness profile of images, and then assigns each SOM-Hebb classifier in the parallel configuration to one of the groups. Recognition parameters of each classifier are tuned for the vectors belonging to its group. Comparison between the recognition systems with and without the grouping shows that the grouping can improve recognition accuracy.

Stereoscopic vision technology is applied in a wide range of fields, from 3D movies to medical care. Stereoscopic vision makes it possible to observe images in parallax between both eyes. However, parallax images cannot be used all the time due to a situation called “occlusion”, in which an object is hidden in the depths by another object. In this case, different images are projected on the right and left retina. Here, we propose a psychology experiment to elucidate the function of parvocellular cells in the LGN of the visual cortex of the brain using occlusion perception. As a new psychology experiment to clarify whether parvocellular cells in the LGN of the visual cortex, said to process chromatic and luminance information, can detect a disagreement between the retinal images produced by each eye, we measured convergence eye movement when gazing at the rim of a column under occlusion using an equiluminance random dot pattern. When eye movement prevented the disagreement of the retinal images caused by occlusion, we thought that convergence eye movement to move both eyes in front of the rim or divergence eye movement to move them behind the rim would occur. In other words, we thought that we could clarify whether there was parvocellular system process agreement or disagreement between the right and left retinal images under equiluminance. Therefore, we examined whether a system to detect disagreement between the retinal images exists in the brain when gazing at the rim of a column onto which an equiluminance random dot texture was mapped. Results suggested that the mechanism to avoid disagreement between the retinal images of the eyes caused by occlusion occurs in the parvocellular cells, which mainly process color information, as well as in the magnocellular cells, which process binocular disparity.

In this research, we propose an effective stability analysis method to impacting systems with periodically moving borders (periodic borders). First, we describe an n-dimensional impacting system with periodic borders. Subsequently, we present an algorithm based on a stability analysis method using the monodromy matrix for calculating stability of the waveform. This approach requires the state-transition matrix be related to the impact phenomenon, which is known as the saltation matrix. In an earlier study, the expression for the saltation matrix was derived assuming a static border (fixed border). In this research, we derive an expression for the saltation matrix for a periodic border. We confirm the performance of the proposed method, which is also applicable to systems with fixed borders, by applying it to an impacting system with a periodic border. Using this approach, we analyze the bifurcation of an impacting system with a periodic border by computing the evolution of the stable and unstable periodic waveform. We demonstrate a discontinuous change of the periodic points, which occurs when a periodic point collides with a border, in the one-parameter bifurcation diagram.

In this letter, we present a new expression of ergodic capacity for two-wave with diffuse power (TWDP) fading channels. The derived formula is relatively concise and consists of well-known functions even in infinite series form. Especially, the truncated approximate expression and asymptotic formula are also presented, which enable us to obtain useful and physical insights on the effect of TWDP fading on the ergodic capacity for various fading conditions.

An accurate but energy-efficient estimation of a position is important as the number of mobile computing systems grow rapidly. A challenge is to develop a highly accurate but energy efficient estimation method. A particle filter is a key algorithm to estimate and track the position of an object which exhibits non-linear movement behavior. However, it requires high usage of computation resources and energy. In this paper, we propose a scheme which can dynamically adjust the number of particles according to the accuracy of the reference signal for positioning and reduce the energy consumption by 37% on Cortex A7.

In this paper, a compact controlled reception pattern antenna (CRPA) array based on a mu-zero resonance (MZR) antenna is proposed for a global positioning system (GPS). The MZR antenna can be minimized by designing structure based in mu-negative (MNG) transmission line. The MNG transmission line can be implemented by a gap structure for the series capacitance and a shorting via for a short-ended boundary condition. The CRPA array, which operates in L1 (1.57542GHz) and L2 (1.2276GHz) bands, is designed as a cylinder with a diameter and a height of 127mm (5 inches) and 20mm, respectively, and is composed of seven radiating elements. To design the compact CRPA array with high performance attributes such as an impedance matching (VSWR) value of less than 2, an isolation between array elements (<-12dB), an axial ratio (<5dB), and a circular polarization (CP) gain (>-1dBic: L1 band and >-3dBic: L2 band), we employ two orthogonal MZR antennas, a superstrate, and chip couplers. The performances of the CRPA antenna are verified and compared by an analytic analysis, a full-wave simulation, and measurements.

We have previously introduced the static dependency pair method that proves termination by analyzing the static recursive structure of various extensions of term rewriting systems for handling higher-order functions. The key is to succeed with the formalization of recursive structures based on the notion of strong computability, which is introduced for the termination of typed λ-calculi. To bring the static dependency pair method close to existing functional programs, we also extend the method to term rewriting models in which functional abstractions with patterns are permitted. Since the static dependency pair method is not sound in general, we formulate a class; namely, accessibility, in which the method works well. The static dependency pair method is a very natural reasoning; therefore, our extension differs only slightly from previous results. On the other hand, a soundness proof is dramatically difficult.