Deterioration of sewer pipes is one of very important problems in Japan. Sewer inspections have been carried out mainly by visual check or wired remote robots with a camera. However, such inspection schemes involve high labor and/or monetary cost. Sewer inspection with boat-type video cameras or unwired robots takes a long time to check the result of the inspection because video data are obtained after the equipment is retrieved from the pipe. To realize low cost, safe and quick inspection of sewer pipes, we have proposed a sewer inspection system using drifting wireless sensor nodes. Water, soil, and the narrow space in the pipe make the long-range and high throughput wireless radio communication difficult. Therefore, we have to identify suitable radio frequency and antenna configuration based on wireless communication characteristics in sewer pipes. If the frequency is higher, the Fresnel zone, the needed space for the line of sight is small, but the path loss in free space is large. On the other hand, if the frequency is lower, the size of the Fresnel zone is large, but the path loss in free space is small. We conducted wireless communication experiments using 920MHz, 2.4GHz, and 5GHz band off-the-shelf devices in an experimental underground pipe. The measurement results show that the wireless communication range of 5GHz (IEEE 802.11a) is over 8m in a 200mm-diameter pipe and is longer than 920MHz (ARIB STD-T108), 2.4GHz (IEEE 802.11g, IEEE 802.15.4) band at their maximum transmission power. In addition, we confirmed that devices that use IEEE 802.11a and 54Mbps bit rate can transmit about 43MB data while they are in the communication range of an AP and drift at 1m/s in a 200mm-diameter pipe, and it is bigger than one of devices that use other bit rate.

We propose an edge-preserving multiscale image decomposition method using filters for non-equispaced signals. It is inspired by the domain transform, which is a high-speed edge-preserving smoothing method, and it can be used in many image processing applications. One of the disadvantages of the domain transform is sensitivity to noise. Even though the proposed method is based on non-equispaced filters similar to the domain transform, it is robust to noise since it employs a multiscale decomposition. It uses the Laplacian pyramid scheme to decompose an input signal into the piecewise-smooth components and detail components. We design the filters by using an optimization based on edge-preserving smoothing with a conversion of signal distances and filters taking into account the distances between signal intervals. In addition, we also propose construction methods of filters for non-equispaced signals by using arbitrary continuous filters or graph spectral filters in order that various filters can be accommodated by the proposed method. As expected, we find that, similar to state-of-the-art edge-preserving smoothing techniques, including the domain transform, our approach can be used in many applications. We evaluated its effectiveness in edge-preserving smoothing of noise-free and noisy images, detail enhancement, pencil drawing, and stylization.

In this paper, an infinite-horizon team-optimal incentive Stackelberg strategy is investigated for a class of stochastic linear systems with many non-cooperative leaders and one follower. An incentive structure is adopted which allows for the leader's team-optimal Nash solution. It is shown that the incentive strategy set can be obtained by solving the cross-coupled stochastic algebraic Riccati equations (CCSAREs). In order to demonstrate the effectiveness of the proposed strategy, a numerical example is solved.

Finding software vulnerabilities in source code before the program gets deployed is crucial to ensure the software quality. Existing source code auditing tools for vulnerability detection generate too many false positives, and only limited types of vulnerability can be detected automatically. In this paper, we propose an extendable mechanism to reveal vulnerabilities in source code with low false positives by specifying security requirements and detecting requirement violations of the potential vulnerable sinks. The experimental results show that the proposed mechanism can detect vulnerabilities with zero false positives and indicate the extendability of the mechanism to cover more types of vulnerabilities.

In this paper, we consider filter-and-forward relay beamforming using orthogonal frequency-division multiplexing (OFDM) in the presence of inter-block interference (IBI). We propose a filter design method based on a constrained max-min problem, which aims to suppress IBI and also avoid deep nulls in the frequency domain. It is shown that IBI can be suppressed completely owing to the employment of beamforming with multiple relays or multiple receive antennas at each relay when perfect channel state information (CSI) is available. In addition, we modify the proposed method to cover the case where only the partial CSI for relay-receiver channels is available. Numerical simulation results show that the proposed method significantly improves the performance as the number of relays and antennas increases due to spatial diversity, and the modified method can make use of the channel correlation to improve the performance.

With the appearance of large OLED panels, the OLED TV industry has experienced significant growth. However, this technology is still in the early stages of commercialization, and some technical challenges remain to be overcome. During the development phase of a product, power consumption is one of the most important considerations. To reduce power consumption in OLED displays, we propose a method based on just-noticeable difference (JND). JND refers to the minimum visibility threshold when visual content is altered and results from physiological and psychophysical phenomena in the human visual system (HVS). A JND model suitable for OLED displays is derived from numerous experiments with OLED displays. With the use of JND, it is possible to reduce power consumption while minimizing perceptual image quality degradation.

To achieve overall business goals, GQM+Strategies is one approach that aligns business goals at each level of an organization to strategies and assesses the achievement of goals. Strategies are based on rationales (contexts and assumptions). Because extracting all rationales is an important process in the GQM+Strategies approach, we propose the Context-Assumption-Matrix (CAM), which refines the GQM+Strategies model by extracting rationales based on analyzing the relationships between stakeholders, and the process of using GQM+Strategies with CAM effectively. To demonstrate the effectiveness of the CAM and the defined process, we conducted three experiments involving students majoring in information sciences at two different Japanese universities. Moreover, we applied the GQM+Strategies approach with CAM to the Recruit Sumai Company in Japan. The results reveal that compared to GQM+Strategies alone, GQM+Strategies with CAM can extract rationales of the same quality more efficiently and exhaustively.

A compact multiple-input multiple-output (MIMO) dielectric resonator antenna (DRA) was proposed and studied. The DRA consists of three antenna ports. The antennas operate at 2.4GHz, where one of the antenna ports was placed at the center and resonates in the monopole mode, and the two other ports were located at the sides and resonate in the TEy111 mode. Both simulation and measurements were carried out, and reasonably good agreement was obtained. In addition, a study for miniaturization with different permittivities for the DRA and a comparison of the throughput with the reference antennas of a commercial wireless LAN router were performed. Our proposed MIMO DRA gave similar performance as that of the reference antennas but was more compact in size.

NoSQL systems have become vital components to deliver big data services due to their high horizontal scalability. However, existing NoSQL systems rely on experienced administrators to configure and tune the wide range of configurable parameters for optimized performance. In this work, we present a configuration management framework for NoSQL systems, called xConfig. With xConfig, its users can first identify performance sensitive parameters and capture the tuned parameters for different workloads as configuration policies. Next, based on tuned policies, xConfig can be implemented as the corresponding configuration optimiaztion system for the specific NoSQL system. Also it can be used to analyze the range of configurable parameters that may impact the runtime performance of NoSQL systems. We implement a prototype called HConfig based on HBase, and the parameter tuning strategies for HConfig can generate tuned policies and enable HBase to run much more efficiently on both individual worker node and entire cluster. The massive writing oriented evaluation results show that HBase under write-intensive policies outperforms both the default configuration and some existing configurations while offering significantly higher throughput.

In the early phases of the system development process, stakeholders exchange ideas and describe requirements in natural language. Requirements described in natural language tend to be vague and include logical inconsistencies, whereas logical consistency is the key to raising the quality and lowering the cost of system development. Hence, it is important to find logical inconsistencies in the whole requirements at this early stage. In verification and validation of the requirements, there are techniques to derive logical formulas from natural language requirements and evaluate their inconsistencies automatically. Users manually chunk the requirements by paragraphs. However, paragraphs do not always represent logical chunks. There can be only one logical chunk over some paragraphs on the other hand some logical chunks in one paragraph. In this paper, we present a practical approach to detecting logical inconsistencies by clustering technique in natural language requirements. Software requirements specifications (SRSs) are the target document type. We use k-means clustering to cluster chunks of requirements and develop semantic role labeling rules to derive “conditions” and “actions” as semantic roles from the requirements by using natural language processing. We also construct an abstraction grammar to transform the conditions and actions into logical formulas. By evaluating the logical formulas with input data patterns, we can find logical inconsistencies. We implemented our approach and conducted experiments on three case studies of requirements written in natural English. The results indicate that our approach can find logical inconsistencies.

In this letter, a method of wideband direction of arrival (DOA) estimation based on co-prime arrays with sub-Nyquist sampling is proposed. Previous works have employed co-prime arrays for wideband DOA estimation, which can increase the degrees of freedom (DOFs) in the spatial domain. However, they are all based on Nyquist sampling. Different from existing methods, we incorporate a sub-Nyquist sampling scheme called multicoset sampling for DOA estimation to relax hardware condition. Simulation results show the correctness and effectiveness.

In this paper, we propose a method for color error diffusion based on the Neugebauer model for color halftone printing. The Neugebauer model expresses an arbitrary color as a trilinear interpolation of basic colors. The proposed method quantizes the color of each pixel to a basic color which minimizes an accumulated quantization error, and the quantization error is diffused to the ratios of basic colors in subsequent pixels. Experimental results show that the proposed method outperforms conventional color error diffusion methods including separable method in terms of eye model-based mean squared error.

In a scenario-based software development, a lot of scenarios should be described in order to clarify the whole behaviors of the target software. By reusing scenarios of similar software systems, it becomes more efficient to newly describe scenarios of the target software. A differential scenario includes the difference between sequences of events of the two scenarios and the difference between nouns in the scenarios. If the nouns of the two scenarios are commonly used in the two scenarios, we regard the two scenarios specify the same or similar system. If the sequences of the events of the two scenarios are corresponding each other, we regard behavior of the two scenarios are similar. In this paper, we derive differential information including different words and events from two scenarios. Then, we propose a method of scenario retrieval using differential information between two scenarios. This method enables to detect similar scenarios for a given scenario. The proposed retrieval method and a prototype system for creating and visualizing differential scenario will be illustrated with examples.

Quadriphase sequences with good correlation properties are required in higher order digital modulation schemes, e.g., for timing measurements, channel estimation or synchronization. In this letter, based on interleaving technique and pairs of mismatched binary sequences with perfect cross-correlation function (PCCF), two new methods for constructing quadriphase sequences with mismatched filtering which exist for even length N ≡ 2(mod4) are presented. The resultant perfect mismatched quadriphase sequences have high energy efficiencies. Compared with the existing methods, the new methods have flexible parameters and can give cyclically distinct perfect mismatched quadriphase sequences.

In this letter, standard particle swarm optimization (PSO) with the center-symmetric trimmed correlation matrix and the orthogonal projection technique is firstly presented for blind carrier frequency offset estimation under interleaved orthogonal frequency division multiple access (OFDMA) uplink systems. It doesn't require eigenvalue decomposition and only needs a single OFDMA data block. Second, this letter also presents adaptive multiple inertia weights with Newton method to speed up the convergence of standard PSO iteration process. Meanwhile, the advantage of inherent interleaved OFDMA signal structure also is exploited to conquer the problems of local optimization and the effect of ambiguous peaks for the proposed approaches. Finally, several simulation results are provided for illustration and comparison.

With the rapid development of Internet of things (IoT), Radio Frequency Identification (RFID) has become one of the most significant information technologies in the 21st century. However, more and more privacy threats and security flaws have been emerging in various vital RFID systems. Traditional RFID systems only focus attention on foundational implementation, which lacks privacy protection and effective identity authentication. To solve the privacy protection problem this paper proposes a privacy protection method with a Privacy Enhancement Model for RFID (PEM4RFID). PEM4RFID utilizes a “2+2” identity authentication mechanism, which includes a Two-Factor Authentication Protocol (TFAP) based on “two-way authentication”. Our TFAP employs “hardware information + AES-ECC encryption”, while the ”“two-way authentication” is based on improved Combined Public Key (CPK). Case study shows that our proposed PEM4RFID has characteristics of untraceability and nonrepeatability of instructions, which realizes a good trade-off between privacy and security in RFID systems.

Forming Business Continuity Planning (BCP) is recognized as a significant counter-measure against future large-scale disasters by private enterprises after the 2011 Great East Japan Earthquake more than before. Based on a questionnaire survey, this paper reports business recovery conditions of private enterprises in Miyagi Prefecture affected by the disaster. Analyzing the results of questionnaire, it suggests some important points: (1) estimation of long-term internal/external factors that influence business continuity, (2) development of concrete pre-disaster framework, (3) multi-media-based advertising strategy, and (4) re-allocation of resources.

We present a hard-wired central patter generator (CPG) hardware network that reproduces the periodic oscillations of the typical gaits, namely, walk, trot, and bound. Notably, the three gaits are generated by a single parameter, i.e., the battery voltage EMLR, which acts like a signal from the midbrain's locomotor region. One CPG is composed of two types of hardware neuron models, reproducing neuronal bursting and beating (action potentials), and three types of hardware synapse models: a gap junction, excitatory and inhibitory synapses. When four hardware CPG models were coupled into a Z4 symmetry network in a previous study [22], two neuronal oscillation patterns corresponding to four-legged animal gaits (walk and bound) were generated by manipulating a single control parameter. However, no more than two neuronal oscillation patterns have been stably observed on a hard-wired four-CPG hardware network. In the current study, we indicate that three neuronal oscillation patterns (walk, trot, and bound) can be generated by manipulating a single control parameter on a hard-wired eight-CPG (Z4 × Z2 symmetry) hardware network.

Based on a ternary perfect sequence and a binary orthogonal matrix, the Z-periodic complementary sequence (ZPCS) sets over the 8-QAM+ constellation are constructed. The resultant sequences can be used in multi-carriers code division multiple access (MC-CDMA) systems to remove interference and increase the transmission rate. The proposed construction provides flexible choice for parameters so as to meet different requirements in the application. A construction of shift sequence sets is proposed and the number of 8-QAM ZPCS sets is extended by changing the parameters of shift sequences. As a result, more users can be accommodated in the system.

In the current IoT (Internet of Things) environment, more and more Things: devices, objects, sensors, and everyday items not usually considered computers, are connected to the Internet, and these Things affect and change our social life and economic activities. By using IoTs, service providers can collect and store personal information in the real world, and such providers can gain access to detailed behaviors of the user. Although service providers offer users new services and numerous benefits using their detailed information, most users have concerns about the privacy and security of their personal data. Thus, service providers need to take countermeasures to eliminate those concerns. To help eliminate those concerns, first we conduct a survey regarding users' privacy and security concerns about IoT services, and then we analyze data collected from the survey using structural equation modeling (SEM). Analysis of the results provide answers to issues of privacy and security concerns to service providers and their users. And we also analyze the effectiveness and effects of personal information management and protection functions in IoT services.