bluuebunny/crossref_metadata_2025 huggingface dataset:
Variational Bayesian inference for the probabilistic model of power load
Authors: Dong Zijian , Wang Yunpeng , Zhao Jing
Published: July 2014

It is an essential element to estimate the state of system loads in the emerging smart grid system. This study is focused on finding a distribution of power load profile through a Gaussian mixed model. The authors propose a modified variational Bayesian inference (VBI) method to set parameters of the model. Compared with other approximation techniques, such as maximum likelihood, expectation maximum (EM) algorithm, they show that the author's Bayesian approaches can solve the problem of data singularity and the problem of over‐fitting. Utilising the weights of components, their modified algorithm can dynamically remove some redundant components during iterations. The presented method in this study also reduces the computational complexity and thus improves the speed of iteration. They use practical data to examine EM algorithm, VBI algorithm and their improved VBI algorithm. The experiments verify the advantages of Bayesian inference approaches and the validity/reliability of the proposed algorithm. The performance of the algorithms is also demonstrated by the data from PJM Company.
Simulation and experiment on a flexible control method for ferroresonance
Authors: Sima Wenxia , Yang Ming , Yang Qing , Yuan Tao , Zou Mi
Published: July 2014

This study investigates the physical mechanism of ferroresonance and its control. Based on this mechanism, a flexible control method for ferroresonance is proposed, and its control mechanism is discussed. High‐frequency controllable switches are used in the control module proposed in this study, and several parameters of the control module can be adjusted according to ferroresonance types identified by the comprehensive identification system and saturation degrees of the ferroresonance. The control module is then switched into the secondary circuit of the potential transformer, and ferroresonance can be controlled. Simulation and experimentation show that ferroresonance of various types and saturation degrees can be restrained.
Effective fuzzy clustering algorithm with Bayesian model and mean template for image segmentation
Authors: Zhang Hui , Wu Qing Ming Jonathan , Zheng Yuhui , Nguyen Thanh Minh , Wang Dingcheng
Published: July 2014

Fuzzy c‐means (FCMs) with spatial constraints have been considered as an effective algorithm for image segmentation. The well‐known Gaussian mixture model (GMM) has also been regarded as a useful tool in several image segmentation applications. In this study, the authors propose a new algorithm to incorporate the merits of these two approaches and reveal some intrinsic relationships between them. In the authors model, the new objective function pays more attention on spatial constraints and adopts Gaussian distribution as the distance function. Thus, their model can degrade to the standard GMM as a special case. Our algorithm is fully free of the empirically pre‐defined parameters that are used in traditional FCM methods to balance between robustness to noise and effectiveness of preserving the image sharpness and details. Furthermore, in their algorithm, the prior probability of an image pixel is influenced by the fuzzy memberships of pixels in its immediate neighbourhood to incorporate the local spatial information and intensity information. Finally, they utilise the mean template instead of the traditional hidden Markov random field (HMRF) model for estimation of prior probability. The mean template is considered as a spatial constraint for collecting more image spatial information. Compared with HMRF, their method is simple, easy and fast to implement. The performance of their proposed algorithm, compared with state‐of‐the‐art technologies including extensions of possibilistic fuzzy c‐means (PFCM), GMM, FCM, HMRF and their hybrid models, demonstrates its improved robustness and effectiveness.
Weighting scheme for image retrieval based on bag‐of‐visual‐words
Authors: Zhu Lei , Jin Hai , Zheng Ran , Feng Xiaowen
Published: July 2014

Inspired by the success of bag‐of‐words in text retrieval, bag‐of‐visual‐words and its variants are widely used in content‐based image retrieval to describe visual content. Various weighting schemes have also been proposed to integrate different yet complementary visual‐words. However, most of these weighting schemes tend to use fixed weight for every visual‐word extracted from the query image, which may lose the discriminative information. This study presents a novel combining method which captures query‐specific weights for visual‐words in query image. The method mainly contains two stages. Firstly, in offline weight learning, the authors introduce a linear classifier to build a query‐category mapping table, and max‐margin learning to build category‐weight mapping table. Query‐category mapping table is used to map the query image to the most likely image class, and category‐weight mapping table is used to map image class to the weights of visual‐words. Secondly, in online weight mapping, the weights of visual‐words are determined efficiently by looking into the pre‐learned mapping tables. Experimental results on WANG database and Caltech 101 demonstrate that the proposed weighting scheme can effectively weight visual‐words of query image according to their discriminative information. In addition, comparative experiments demonstrate the proposed weighting scheme can obtain higher retrieval performance than other weighting schemes.
Region‐based saliency detection
Authors: Manipoonchelvi Pandivalavan , Muneeswaran Karuppiah
Published: July 2014

In this study, the authors propose an unsupervised approach to detect saliency of each pixel in an image. The proposed region‐based pixel‐wise saliency detection approach produces full resolution (same as that of the original image) saliency map and precisely locates visually prominent region/object of interest in the input image. There are two parts in the authors approach. In the first phase, they partition the input image into homogeneous regions using split‐and‐merge technique. In the second phase, they rank the regions based on its proximity to the centre of the image, visual significance, size and completeness. Based on the ranking of the regions, the significance of each pixel is computed. The proposed saliency detection approaches improves the accuracy of content‐based applications such as salient object segmentation and content aware image resizing. Experimental results show that their proposed approach qualitatively better than the state‐of‐art approaches and quantitatively comparable to ground truth information which are collected from human observers.
Query‐dependent metric learning for adaptive, content‐based image browsing and retrieval
Authors: Han Junwei , McKenna Stephen J.
Published: July 2014

Content‐based image retrieval (CBIR) systems often incorporate a relevance feedback mechanism in which retrieval is adapted based on users identifying images as relevant or irrelevant. Such relevance decisions are often assumed to be category‐based. However, forcing a user to decide upon category membership of an image, even when unfamiliar with a database and irrespective of context, is restrictive. An alternative is to obtain user feedback in the form of relative similarity judgments. The ability of a user to provide meaningful feedback depends on the interface that displays retrieved images and facilitates the feedback. Similarity‐based 2D layouts provide context and can enable more efficient visual search. Motivated by these observations, this study describes and evaluates an interactive image browsing and retrieval approach based on relative similarity feedback obtained from 2D image layouts. It incorporates online maximal‐margin learning to adapt the image similarity metric used to perform retrieval. A user starts a session by browsing a collection of images displayed in a 2D layout. He/she may choose a query image perceived to be similar to the envisioned target image. A set of images similar to the query are then returned. The user can then provide relational feedback and/or update the query image to obtain a new set of images. Algorithms for CBIR are often characterised empirically by simulating usage based on pre‐defined, fixed category labels, deeming retrieved results as relevant if they share a category label with the query. In contrast, the purpose of the system in this study is to enable browsing and retrieval without predefined categories. Therefore evaluation is performed in a target‐based setting by quantifying the efficiency with which target images are retrieved given initial queries.
Local gradient‐based illumination invariant face recognition using local phase quantisation and multi‐resolution local binary pattern fusion
Authors: Nikan Soodeh , Ahmadi Majid
Published: July 2014

A local‐based illumination insensitive face recognition algorithm is proposed which is the combination of image normalisation and illumination invariant descriptors. Illumination insensitive representation of image is obtained based on the ratio of gradient amplitude to the original image intensity and partitioned into smaller sub‐blocks. Local phase quantisation and multi‐scale local binary pattern, extract the sub‐regions characteristics. Distance measurements of local nearest neighbour classifiers are fused at the score level to find the best match and decision‐level fusion combines the results of two matching techniques. Entropy, class posterior probability and mutual information are utilised as the weights of fusion components. Simulation results on the YaleB, Extended YaleB, AR, Multi‐PIE and FRGC databases show the improved performance of the proposed algorithm under severe illumination with low computational complexity and no reconstruction or training requirement.
Towards blind detection of low‐rate spatial embedding in image steganalysis
Authors: Farhat Farshid , Ghaemmaghami Shahrokh
Published: July 2014

Steganalysis of least significant bit (LSB) embedded images in spatial domain has been investigated extensively over the past decade and most well‐known LSB steganography methods have been shown to be detectable. However, according to the latest findings in the area, two major issues of very low‐rate (VLR) embedding and content‐adaptive steganography have remained hard to resolve. The problem of VLR embedding is indeed a generic problem to any steganalyser, while the issue of adaptive embedding specifically depends on the hiding algorithm employed. The latter challenge has recently been brought up again to the area of LSB steganalysis by highly undetectable stego image steganography that offers a content‐adaptive embedding scheme for grey‐scale images. The authors new image steganalysis method suggests analysis of the relative norm of the image Clouds manipulated in an LSB embedding system. The method is a self‐dependent image analysis and is capable of operating on low‐resolution images. The proposed algorithm is applied to the image in spatial domain through image Clouding, relative auto‐decorrelation features extraction and quadratic rate estimation, as the main steps of the proposed analysis procedure. The authors then introduce and use new statistical features, Clouds‐Min‐Sum and Local‐Entropies‐Sum, which improve both the detection accuracy and the embedding rate estimation. They analytically verify the functionality of the scheme. Their simulation results show that the proposed approach outperforms some well known, powerful LSB steganalysis schemes, in terms of true and false detection rates and mean squared error.
Quantum particle swarm optimisation algorithm for feedback control of semi‐autonomous driver assistance systems
Authors: Chang Che‐Cheng , Tsai Jichiang , Pei Shi‐Jia
Published: July 2014

The development of automotive technology has become increasingly important for preventing car accidents. Hence, as a basic research of driver assistance systems, a novel control method has been proposed for steering support. In particular, the stability and limitation of such a system is investigated for the safe and comfortable drive. First, the particle swarm optimisation (PSO)‐based algorithm is used to search the optimal feedback gain under practical constraints for achieving tracking control. Moreover, to reduce the convergence time further, the PSO algorithm is combined with the technique of quantum computing. Simulation results indicate that the proposed feedback controller based on quantum PSO has the ability to provide efficient computational performance for trajectory tracking and stabilisation.
eCall minimum set of data transmission – results from a field test in Finland
Authors: Öörni Risto , Korhonen Timo O.
Published: July 2014

European in‐vehicle emergency call system eCall aims to save lives and mitigate consequences of road accidents. eCall minimum set of data (MSD) which contains information on the accident vehicle is transmitted in the beginning of the call in the voice channel opened between in‐vehicle system and public safety answering point. The main objectives of the study are to analyse the successfulness of eCall MSD transmission in Finnish fixed‐line and GSM networks and to provide information on factors which contribute to the success rate of MSD transmission. The results of the Wilcoxon rank sum test indicated that the signal strength has no major impact on the success or failure of the MSD transmission when the mobile network signal strength measured by IVS is between −80 and −40 dBm. The analysed data included 12 failed MSD transmission attempts and 214 initiated MSDs in total. However, the test results also indicated that the MSD success rate can still be very different in different real‐life physical mobile and fixed‐line locations.
Model‐based approach for estimating energy used by traffic flows on motorways with ITS
Authors: Bottero Marco , Chiara Bruno Dalla , Deflorio Francesco , Franco Gino , Spessa Ezio
Published: July 2014

Monitoring traffic flows on road infrastructures has increasingly become a more common practice. Diverse types of sensors and devices to count and classify vehicles have been tested and installed on European roads in recent years, contributing to the growing availability of several databases. Moreover, methodologies to assess energy consumption for transport and the consequent emissions require several data sets, which are not always available. Consequently, it is an interesting endeavour to investigate an approach that can model energy dissipation, beginning from simple mechanical rules and traffic monitoring data and related parameters. The presence of ITS can have a positive influence on traffic flows. Beginning with this assumption, this study presents different scenarios based on actual and simulated data to estimate energy used in vehicular flow and how the energy consumed can change when the vehicular flow changes due to the influence of an ITS application. The approach presented in this study accounts to use both a mechanical model, providing a simple evaluation of energy consumption, and a traffic micro‐simulation approach; both cases begin from the measurement of classical traffic flow parameters.
Detection of potholes in autonomous vehicle
Authors: Bharadwaj Sundra Murthy Sachin , Varaprasad Golla
Published: July 2014

Pothole avoidance may be considered similar to other obstacle avoidance, except that the potholes are depressions rather than extrusions from a surface. This study discusses a solution for detection of potholes in the path of an autonomous vehicle operating in an unstructured environment. Here, a vision approach is used since the simulated potholes are significantly different from the background surface. Furthermore, using this approach, pothole can only be detected in case of uniform lighting conditions. The solution to the problem is developed in a systematic manner. Initially, a specific camera and frame grabber are chosen, then camera is mounted on top of the autonomous vehicle and the images will be acquired. Then, a software solution is designed using MATLAB. The method is tested under real‐time conditions and results demonstrate its reasonable efficiency.
Modified mu‐zero resonator for efficient wireless power transfer
Authors: Park Jae‐Hyun , Park Byung‐Chul , Ryu Young‐Ho , Park Eun‐Seok , Lee Jeong‐Hae
Published: July 2014

A mu‐zero resonator with an effective zero permeability is presented for efficient wireless power transfer (WPT) using resonant inductive coupling (RIC). An N‐cell mu‐zero resonator is modified to maintain a fixed size and resonance frequencies that are important design factors of WPT using RIC because they are related to the magnetic coupling coefficient and Q‐factor. The resonator has many resonant modes with the extraordinary phenomena of metamaterials such as an infinite wavelength wave and backward‐wave propagation. An analysis of the resonant modes and a design of the N‐cell mu‐zero resonator is performed by theory and full‐wave simulation based on a dispersion diagram and magnetic field distribution. The power transfer efficiencies of one‐cell and two‐cell mu‐zero resonators are simulated and measured. To optimise the transfer efficiency of the WPT system using the mu‐zero resonance (MZR) mode, which supports stronger coupling than the other modes, an equivalent circuit of mu‐zero resonator is analysed for a high Q‐factor. The theoretical, simulated, and measured results of a one‐cell resonator with optimum values confirm that an efficient WPT system can be successfully designed by the MZR mode.
Compact multiple‐input–multiple‐output antenna using quasi‐self‐complementary antenna structures for ultrawideband applications
Authors: Liu Li , Cheung Sing Wai , Yuk Tung Ip
Published: July 2014

A compact multiple‐input–multiple‐output (MIMO) antenna with a very small size of only 21 × 38 mm2 is proposed for ultra‐wideband (UWB) applications. It consists of two quasi‐self‐complementary antenna (QSCA) elements with an inverted T‐shaped common ground plane. The QSCA elements are the mirror images of each other, having a half‐circular conductor patch on one side of the substrate and a slot with the complement of the half‐circular shape on the other side. To reduce mutual coupling between the two QSCA elements, two rectangular slots are cut symmetrically on the ground plane between the two elements. Simulation and measurement are used to study the performance of the MIMO antenna in terms of reflection coefficient, isolation between the two ports, radiation pattern, realised gain, efficiency and envelope correlation coefficient. The results show that the MIMO antenna has a bandwidth from 3.1 GHz to more than 10.6 GHz with a mutual coupling of less than −15 dB and a correlation of less than 0.1, respectively, making it a good candidate for portable UWB applications.
Improved algorithm of retrieving oceanic surface wind speed based on a stratified media model at high sea states
Authors: Tian Jiasheng , Liu Qiaoyun , Pan Wan , Shi Jian
Published: July 2014

Consider the effect of spray droplets and foams on the radar altimeter, an improved algorithm of retrieving oceanic surface wind speed is proposed in this study. Firstly, a four‐layer medium model is established in order to simulate accurately the air–sea interface. Secondly, the microwave reflectivity of the established model is computed at 13.5 GHz. The computed results show that the effect of spray droplets and foams plays an important role in the reflectivity of the air–sea surface and causes it to decline from 0.6 to 0.23. Thirdly, the computed results are applied to retrieve the sea surface wind speed and an improved algorithm of retrieving wind speed is proposed. At low wind speeds, the improved algorithm is in good agreements with those reported results, and at high wind speeds is also in good agreements with some empirical algorithms presented by Brown, Young and so on. Finally, the improved algorithm can improve the sea surface wind speed retrieval more effectively and also is closer to the actual situation of the sea surface than those algorithms based on the three‐layer medium model.
Study and analysis of a novel Runge–Kutta high‐order finite‐difference time‐domain method
Authors: Zhu Min , Cao Qunsheng , Zhao Lei
Published: July 2014

In this study, a novel high‐order finite‐difference time‐domain (HO‐FDTD) method, Runge–Kutta (RK)‐HO‐FDTD, is proposed. The RK‐HO‐FDTD method employs the strong stability preserving RK algorithm to substitute time derivates and the Taylor series to replace spatial derivates. The characteristics of the stability, dispersion and convergence are studied. The proposed new method presents a better numerical dispersion and a faster convergence rate both in time and space domain. Compared with the HO‐FDTD method, if the mesh size is fixed, it is found that the computational memory of the RK‐HO‐FDTD method is more than two times of the HO‐FDTD method for the same mesh size; but if keeping the same accuracy, the computational cost of the RK‐HO‐FDTD is the controllable times that of the HO‐FDTD method. And compared with the HO‐FDTD and RK‐MRTD methods, the new scheme presents more accuracy and great potential in electromagnetic problems.
Fundamental modulation strategy with selective harmonic elimination for multilevel inverters
Authors: Lou Huibo , Mao Chengxiong , Wang Dan , Lu Jiming , Wang Libing
Published: July 2014

This study presents a novel fundamental modulation strategy with selective harmonic elimination (SHE) for multilevel inverters. Compared with conventional schemes, more kinds of stepped waveforms can be adaptively synthesised and it is more possible to obtain the optimal solutions for the SHE problem, especially at low‐modulation indices. The control purpose, SHE and fundamental voltage control, for a cascaded 11‐level inverter is formulated as multi‐objective optimisation problem which is solved by using shuffled frog leaping algorithm in this study. The theoretical and experimental results are presented to confirm the validity of the proposed modulation scheme.
Subproportion control of double input buck converter for fuel cell/battery hybrid power supply system
Authors: Xian Liang , Wang Gucheng , Wang Youyi
Published: July 2014

Characterised with more integrated topology, simpler manipulations, less component count, and comparative higher efficiency, multiple‐input converters (MICs) become an attractive candidate in renewable energy hybrid systems (REHSs). To seamlessly and smoothly transit from one operating mode to another is one of the critical issues that the energy management strategy should concern about. Normally, the mode transition (MT) design is usually required for the auxiliary circuits and components, which runs opposite to the MIC's intrinsic advantages and may cause potential problems for the system's reliability and stability. The subproportion control (SPC) approach presented in this study combines two operating modes into a sole control algorithm module without any hardware assistance. The so‐called subproportion (SP) term is an additional control variable served as a certain proportion of the voltage‐regulation duty cycle, dv. The product of SP and dv composes the duty cycle for current limitation of the first power source, beyond which, a seamless and smooth MT can be automatically and spontaneously implemented. The small‐signal modelling for the three most‐commonly‐used topologies in the MIC family showed SPC's universal applicability. It was employed onto a 1 kW double‐input‐buck‐converter‐based fuel cells/battery REHS prototype for the verification of its control performance and auto‐MT capability.
Family of single‐switch soft‐switching pulse‐width modulation DC–DC converters with reduced switch stress
Authors: Khalilian Mojtaba , Adib Ehsan , Farzanehfard Hosein
Published: July 2014

In this study, a new family of pulse width modulation DC–DC converters is introduced. The proposed converters have one switch that turns on at zero current switching condition and turns off at zero voltage switching condition. The proposed auxiliary circuit can be used instead of converter switch in any non‐isolated and isolated DC–DC converter. The buck converter from this converter family is analysed and its operating modes are discussed. The design considerations are presented and a prototype is realised. The experimental results confirm the validity of theoretical analysis.
Design and implementation of a high‐frequency LC‐based half‐bridge resonant converter for dielectric barrier discharge ozone generator
Authors: Amjad Muhammad , Salam Zainal
Published: July 2014

This study describes the design and implementation of a high‐frequency resonant converter based on the transformerless half‐bridge inverter topology. The transformer can be omitted because the voltage gain of the ‘LC’ tank circuit (without transformer) is sufficiently high to overcome the initiation voltage and to maintain steady ozone yield. Another important contribution of the work is the increase in operating frequencies, that is, up to 95 kHz. This increase has two main benefits: (i) smaller resonant component values (which lead to a smaller size of converter) and (ii) lower initiation voltage. To validate the theory, the high‐frequency power converter is designed and tested on a dielectric barrier discharge chamber. It is shown that ozone yield is improved and the ozone formation starts at lower chamber voltages. The experimental and simulation results are found to be in close agreement and hence to validate the design procedures.
Isolated step‐up converter based on flyback converter and charge pumps
Authors: Hwu Kuo‐Ing , Jiang Wen‐Zhuang
Published: July 2014

In this study, a single switch isolated step‐up converter is presented, which is derived from the traditional flyback converter and charge pump concept. The proposed converter possesses an output inductor, so the output current is non‐pulsating. Moreover, there are several advantages of the proposed converter over the traditional flyback converter, such as higher voltage conversion ratio with only additional four passive elements, and smaller voltage and current ripples, except the same switch voltage stress. In this study, some experimental results are provided to verify the effectiveness of the proposed converter.
Modelling and analysis of modular multilevel converter for solar photovoltaic applications to improve power quality
Authors: Alexander Albert , Thathan Manigandan
Published: July 2014

The design of control circuit for a solar fed cascaded multilevel inverter to reduce the number of semiconductor switches is presented in this study. The design includes ‘binary’, ‘trinary’ and ‘modified multilevel connection’ (MMC)‐based topologies suitable for varying input sources from solar photovoltaic's (PV). In binary mode, output voltage levels are obtained where Ns is the number of individual inverters. This is achieved by digital logic functions which includes counters, flip‐flops and logic gates. In trinary mode, 3Ns levels are achieved by corresponding look‐up table. MMC intends design in both control and power circuits to provide corresponding output voltage levels by appropriate switching sequences. Hence to obtain a 15‐level inverter, the conventional method requires 28 switches and in binary mode 12 switches are needed. In trinary mode with the same 12 switches, 27 levels can be obtained whereas in MMC only 7 switches are employed to achieve 15 levels. The advantage of these three designs is in the reduction of total harmonic distortion by increasing the levels. Simulations are carried out in MATLAB/Simulink and comparisons were made. All the three topologies are experimentally investigated for a 3 kWp solar PV plant and power quality indices were measured.
Fuzzy c‐means‐based intelligent tracking algorithm for an underwater manoeuvring target
Authors: Son Hyun Seung , Park Jin Bae , Joo Young Hoon
Published: July 2014

The effort to detect a target conflicts with the covertness in anti‐submarine warfare. The underwater detection rate is extremely low and sound waves are the only detection method unlike the airborne operational environment. The data of an underwater target based on noise levels are more difficult to interpret when the acceleration inputs are included. Hence, the authors propose a complementary algorithm for the tracking problem in an active sonar system. The bearing‐range data of the target yield the measurement residuals, and the residuals are used as inputs to the clustering method. The clustering method estimates the acceleration and the noise level. The estimates aid in positional compensation and enhance the tracking performance. The fuzzy c‐means clustering is utilised for the clustering and maintains the filter sustainable. Finally, some examples are provided to show the effectiveness of the proposed method.
Stability analysis of inertial navigation system‐aided phase‐lock‐loop via an integral quadratic constraint approach
Authors: Fu Li , Wang Lingling , Hu Jianghai , Liu Xiaohong
Published: July 2014

To satisfy the increasingly challenging specifications in terms of accuracy and availability of the positioning and velocity solution, especially in scenarios where reliable and robust navigation is needed, a novel inertial navigation system (INS) aiding Doppler estimator based on the extend Kalman filter was present. Via integral quadratic constraints approach, the absolute stability conditions of the global positioning system carrier tracking loop aided by INS aiding Doppler estimator are derived in order to ensure reliable and robust navigation performance for practical engineering application. The performance of the third‐order carrier tracking loop aided by the proposed INS aiding Doppler estimator was evaluated in the high dynamic flight trajectory and low carrier‐to‐noise ratio scenarios. It is shown that INS aiding Doppler estimator can increase the receiver's robustness in high dynamics when the proposed absolute stability conditions are satisfied.
Maximum‐likelihood‐based approach for single‐pass synthetic aperture radar tomography over urban areas
Authors: Schmitt Michael , Stilla Uwe
Published: July 2014

Synthetic aperture radar (SAR) tomography (TomoSAR) is one of the key techniques in remote sensing for a sophisticated, three‐dimensional (3D) analysis of complex scenes such as forests or urban areas. During recent years, much progress has been made in order to deal with unfavourable data conditions and to further enhance the achievable resolutions. Since TomoSAR has essentially be seen as a spectral estimation problem in the context of array signal processing, most of the methods investigated until now rely on a relatively large tomographic aperture and a relatively high number of receiving antennas in order to be able to separately reconstruct scatterers below the Rayleigh resolution limit. In contrast to that, this study proposes a maximum‐likelihood‐based approach for tomographic SAR inversion, which provides a better height resolution than conventional array signal processing approaches even if the number of antennas or the overall baseline size is limited. The algorithm is tested on real multi‐baseline SAR data acquired over an urban area by an airborne single‐pass four‐antenna system operating in the millimetre‐wave domain. First results show the feasibility of the method both with respect to 3D scatterer reconstruction and 3D SAR focusing.
Two‐stage channel calibration technique for multichannel synthetic aperture radar‐ground moving target indication systems
Authors: Chen Zhao‐Yan , Wang Tong
Published: July 2014

Multichannel synthetic aperture radar (SAR) provides a powerful means for ground moving target indication (GMTI) purpose. The channels are often mismatched because of various kinds of errors. However, perfectly calibrated channels are always needed to perform an effective GMTI. In this study, the authors present a two‐stage channel calibration technique to compensate the channel errors. The authors find that the channel errors can be classified into two categories, that is, the so called convolutional and multiplicative errors. The convolutional errors are more suitable to be compensated in two‐dimensional (2‐D) frequency domain, whereas the multiplicative errors should be compensated in image domain. The authors show that the convolutional errors can be effectively compensated by a Stage 1 calibration filter, in which the conventional 2‐D frequency domain calibration methods can be employed. To compensate the multiplicative errors, the authors introduce a median filter as a Stage 2 calibration filter in the image domain. The proposed two‐stage technique is tested with real SAR data obtained from terribly mismatched channels and is found to work well.
Automatic static contact angle algorithm for blurry drop images and its application in hydrophobicity measurement for insulating materials
Authors: Xu Zhiniu
Published: July 2014

To improve the accuracy of the static contact angle evaluation for the blurry drop images, a large number of water drop images are numerically generated or acquired by the contact angle instrument/digital camera. Based on these images, the applicability of the circle Hough transformation and circle fitting algorithms is systematically investigated and compared. The results reveal that the least‐squares circle fitting algorithm is particularly suitable for the clear drop images, such as the images acquired by the contact angle instrument. The circle Hough transformation is particularly suitable for the blurry drop images, such as the images acquired by the digital camera. The influence of the contact angle on the contact angle error by the circle Hough transformation is investigated. The critical contact angle values corresponding to various water drop volumes are given, which can be used to improve the accuracy of the static contact angle measurement for the blurry drop images. A modified Hough transformation based on the critical contact angle is proposed. The modified Hough transformation is verified by the static contact angle measurements of different insulating materials. The study proposes a comparatively effective algorithm for automatic and accurate static contact angle measurement of the blurry drop images.
Regulation of signal transduction by spatial parameters: a case in NF–κ B oscillation
Authors: Ichikawa Kazuhisa , Ohshima Daisuke , Sagara Hiroshi
Published: July 2014

NF‐k B is a transcription factor regulating expression of more than 500 genes, and its dysfunction leads to the autoimmune and inflammatory diseases. In malignant cancer cells, NF‐k B is constitutively activated. Thus the elucidation of mechanisms for NF‐k B regulation is important for the establishment of therapeutic treatment caused by incorrect NF‐k B responses. Cytoplasmic NF‐k B translocates to the nucleus by the application of extracellular stimuli such as cytokines. Nuclear NF‐k B is known to oscillate with the cycle of 1.5–4.5 h, and it is thought that the oscillation pattern regulates the expression profiles of genes. In this review, first we briefly describe regulation mechanisms of NF‐k B. Next, published computational simulations on the oscillation of NF‐k B are summarised. There are at least 60 reports on the computational simulation and analysis of NF‐k B oscillation. Third, the importance of a ‘space’ for the regulation of oscillation pattern of NF‐k B is discussed, showing altered oscillation pattern by the change in spatial parameters such as diffusion coefficient, nuclear to cytoplasmic volume ratio (N/C ratio), and transport through nuclear membrane. Finally, simulations in a true intracellular space (TiCS), which is an intracellular 3D space reconstructed in a computer with organelles such as nucleus and mitochondria are discussed.
Prediction of hot spots in protein interfaces using extreme learning machines with the information of spatial neighbour residues
Authors: Wang Lin , Zhang Wenjuan , Gao Qiang , Xiong Congcong
Published: July 2014

The identification of hot spots, a small subset of protein interfaces that accounts for the majority of binding free energy, is becoming increasingly important for the research on protein–protein interaction and drug design. For each interface residue or target residue to be predicted, the authors extract hybrid features which incorporate a wide range of information of the target residue and its spatial neighbor residues, that is, the nearest contact residue in the other face (mirror‐contact residue) and the nearest contact residue in the same face (intra‐contact residue). Here, feature selection is performed using random forests to avoid over‐fitting. Thereafter, the extreme learning machine is employed to effectively integrate these hybrid features for predicting hot spots in protein interfaces. By the 5‐fold cross validation in the training set, their method can achieve accuracy (ACC) of 82.1% and Matthew's correlation coefficient (MCC) of 0.459, and outperforms some alternative machine learning methods in the comparison study. Furthermore, their method achieves ACC of 76.8% and MCC of 0.401 in the independent test set, and is more effective than the major existing hot spot predictors. Their prediction method offers a powerful tool for uncovering candidate residues in the studies of alanine scanning mutagenesis for functional protein interaction sites.
Properties of sparse penalties on inferring gene regulatory networks from time‐course gene expression data
Authors: Liu Li‐Zhi , Wu Fang‐Xiang , Zhang Wen‐Jun
Published: July 2014

Genes regulate each other and form a gene regulatory network (GRN) to realise biological functions. Elucidating GRN from experimental data remains a challenging problem in systems biology. Numerous techniques have been developed and sparse linear regression methods become a promising approach to infer accurate GRNs. However, most linear methods are either based on steady‐state gene expression data or their statistical properties are not analysed. Here, two sparse penalties, adaptive least absolute shrinkage and selection operator and smoothly clipped absolute deviation, are proposed to infer GRNs from time‐course gene expression data based on an auto‐regressive model and their Oracle properties are proved under mild conditions. The effectiveness of those methods is demonstrated by applications to in silico and real biological data.
Frequency response and bandwidth analysis of multi‐layer graphene nanoribbon and multi‐walled carbon nanotube interconnects
Authors: Majumder Manoj Kumar , Kukkam Narasimha Reddy , Kaushik Brajesh Kumar
Published: July 2014

This reported research analyses and compares the bandwidth and absolute frequency response of a multi‐layer graphene nanoribbon (MLGNR) and a multi‐walled carbon nanotube (MWCNT) at local, semi‐global and global interconnect lengths. The transfer function of the driver‐interconnect‐load system is obtained by representing the interconnect line with an equivalent single conductor model of either a MLGNR or a MWCNT. Using absolute frequency response, it is observed that the bandwidth of the MLGNR is higher by almost ten times and four times in comparison to the MWCNT for local and global interconnect lengths, respectively.
In-situ wave resource assessment near Taveuni, Fiji Islands
Authors: Kaushal Reddy Sandeep , Rafiuddin Ahmed M.
Published: July 2014

A lack of field data, visible dominant wave activity in the northern division of Fiji Islands particularly off the southern coast of Taveuni, and increasing cost of nonrenewable energy sources coupled with associated harmful effects to the environment have led to initial wave energy resource assessment. The present work involved twelve months of on-site wave measurements commencing July 2012. The measured data were compared with a 30 yr hindcast WW3 model data from a joint project between the Bureau of Metrology, Australia (BoM) and The Pacific Australia Climate Change Science and Adaption Planning. The model was used to relate to the site characteristic in terms of significant wave-height and period in representation of Fiji's overall wave climate and at the same time validating the model with site measurements. The swell and wind wave components together with its prevailing direction was studied in detail. The calculated average power output was 12 kW/m for an average wave-height of 1 m while a peak wave-height of 3.75 m yielded power output of 24 kW/m. Comparison of the wave climate was also made with in situ wave assessment that was performed off the southern coast of Kadavu in 1994. In addition, two offshore wave energy converters' performance data (power matrix) were used to estimate the expected power generation based on the average sea states to briefly examine the site's potential with current technology. The summer and winter variation in wave power was calculated and wave power statistics such as percentile occurrence were also discussed. The results of the present study provide sufficient evidence of the potential of wave energy on site for future feasibility studies and subsequent power extraction.
Pyrolysis of Suncheon-Bay wild reed over zeolite catalysts
Authors: Park Young-Kwon , Yoo Myung Lang , Jin Sung Ho , Jung Sang-Chul , Park Sang-Sook , Park Sung Hoon
Published: July 2014

The catalytic fast pyrolysis of wild reed was carried out over HZSM-5 zeolite catalysts with two different SiO2/Al2O3 ratios, 23 and 280. The effects of the pyrolysis temperature and catalyst on the bio-oil yield were examined using a laboratory-scale batch-type quartz reactor for the pyrolysis experiments over the temperature range, 440–560 °C. The highest bio-oil yield was obtained between 520 °C and 560 °C depending on the catalytic conditions. The bio-oil yields obtained from catalytic pyrolysis were generally lower than those obtained from non-catalytic pyrolysis because of the cracking of large-molecular-mass products into gaseous species. Further experiments were carried out using the pyrolysis-gas chromatography/mass spectrometry at 550 °C for the in-situ analysis of the species distribution of the product bio-oil. Regardless of the use of catalyst, oxygenates were the most abundant products from the pyrolysis of wild reed, followed by phenolics. The fraction of total oxygenates was reduced considerably when pyrolysis was carried over HZSM-5(23). Unlike the other oxygenate species, the production of furans was promoted by catalytic reforming. Furans produced during the pyrolysis process were apparently converted to aromatics upon the catalytic reforming over HZSM-5(23) owing to its large number of strong Brønsted acid sites. Large-molecular-mass oxygen-containing phenolics were converted by catalytic reforming to small-molecular-mass oxygen-free phenolics and aromatics via cracking, dehydration, and deoxygenation. The catalytic effect of HZSM-5(280) was much smaller than that of HZSM-5(23) in every respect owing to its small number of Brønsted acid sites. Another significant change made by catalytic reforming was the increase in the fraction of aromatics. In particular, when pyrolysis was performed over HZSM-5(23), the fraction of aromatics was 14%, whereas they were not produced from non-catalytic pyrolysis.
Aeroacoustic analysis of a wind turbine airfoil and blade on icing state condition
Authors: Hwang Byeongho , Kim Taehyung , Lee Seunghoon , Lee Soogab
Published: July 2014

An influences of iced airfoils on aerodynamic and aeroacoustic properties were studied to predict of the wind turbine noise on icing state. In order to validate the aerodynamic performance, the experimental results and iced airfoils, which were studied by Jasinski et al. [“Wind turbine performance under icing state conditions,” AIAA Paper No. 97-0977, 1997], were used. Ice accretions on the two S809 wind turbine airfoils were predicted using the NASA LEWICE code. For analysis of boundary layer properties, the computational fluid dynamics was used when the Reynolds number is 1 × 106. To validate aerodynamic performances, lift coefficients were compared to the experimental result. The aeroacoustic analysis is estimated by summating the Turbulent inflow (TI) noise and the airfoil self-noise. The airfoil self-noise is obtained using aerodynamics data such as a boundary layer thickness. Semi-empirical method proposed by Brooks et al. [Airfoil Self-Noise and Prediction (NASA reference publication 1218, 1989)] was used. The TI noise is a dominant noise source because of a complicated shape of leading edge on the iced airfoil. For considering leading edge shapes, therefore, TI noise modeling proposed by Moriarty et al. [“Recent improvement of a semi-empirical aeroacoustic prediction code for wind turbines,” AIAA Paper 2004–3041, 2004; “Prediction of turbulent inflow and trailing-edge noise for wind turbines,” AIAA Paper 2005–2881, 2005] was used. As a result, lift coefficients of the iced airfoils matched well experimental data by Jasinski et al. The sound pressure level was increased 2–4 dB from the clean airfoils. The analysis of wind turbine blades on icing state was conducted using the same method. The NREL Phase VI rotor was used as the baseline. Ice accretions on the two wind turbine blades were predicted using the LEWICE code. The overall sound pressure level was increased up to 2.6 dB from the clean wind turbine blade.
Light output function and assembly of the time-of-flight enhanced diagnostics neutron spectrometer plastic scintillators for background reduction by double kinematic selection at EAST
Authors: Peng X. Y. , Chen Z. J. , Zhang X. , Hu Z. M. , Du T. F. , Cui Z. Q. , Xie X. F. , Ge L. J. , Yuan X. , Gorini G. , Nocente M. , Tardocchi M. , Hu L. Q. , Zhong G. Q. , Lin S. Y. , Wan B. N. , Li X. Q. , Zhang G. H. , Chen J. X. , Fan T. S.
Published: July 2014

The 2.5 MeV neutron spectrometer TOFED (Time-Of-Flight Enhanced Diagnostics) has been constructed to perform advanced neutron emission spectroscopy diagnosis of deuterium plasmas on EAST. The instrument has a double-ring structure which, in combination with pulse shape digitization, allows for a dual kinematic selection in the time-of-flight/recoil proton energy (tof/Ep) space, thus improving the spectrometer capability to resolve fast ion signatures in the neutron spectrum, in principle up to a factor ≈100. The identification and separation of features from the energetic ions in the neutron spectrum depends on the detailed knowledge of the instrument response function, both in terms of the light output function of the scintillators and the effect of undesired multiple neutron scatterings in the instrument. This work presents the determination of the light output function of the TOFED plastic scintillator detectors and their geometrical assembly. Results from dedicated experiments with γ-ray sources and quasi-monoenergetic neutron beams are presented. Implications on the instrument capability to perform background suppression based on double kinematic selection are discussed.
Carbon charge exchange analysis in the ITER-like wall environment
Authors: Menmuir S. , Giroud C. , Biewer T. M. , Coffey I. H. , Delabie E. , Hawkes N. C. , Sertoli M. ,   JET EFDA Contributors
Published: July 2014

Charge exchange spectroscopy has long been a key diagnostic tool for fusion plasmas and is well developed in devices with Carbon Plasma-Facing Components. Operation with the ITER-like wall at JET has resulted in changes to the spectrum in the region of the Carbon charge exchange line at 529.06 nm and demonstrates the need to revise the core charge exchange analysis for this line. An investigation has been made of this spectral region in different plasma conditions and the revised description of the spectral lines to be included in the analysis is presented.