Query: Higher mode SIW excitation technology and its array application

Relevant passages:
A single-layer SIW slot array antenna with TE20 mode <=SEP=> The idea of using higher order modes is demonstrated by an SIW slot array antenna with a TE20 mode to realize boresight radiation. In order to excite the TE20 mode, an SIW hybrid coupler and a compact SIW 90° phase shifter are designed to offer the two out-of-phase outputs with identical amplitude. Besides, a CPW-SIW transition is adopted for measurement. The SIW slot array antenna with the TE20 mode is designed at X-band in a single-layer PCB. The measured bandwidth is 5.5% (9.72–10.27 GHz). The measured total efficiency is 80% at 10 GHz. Compared to a conventional SIW slot array just with a power divider, using the TE20 mode provides the merits of not only reducing the number of vias but also relaxing fabrication limit and tolerance which could be the fabrication bottleneck at high frequencies.

Low-Cost Wideband and High-Gain Slotted Cavity Antenna Using High-Order Modes for Millimeter-Wave Application <=SEP=> A novel single-fed low-cost wideband and high-gain slotted cavity antenna based on substrate integrated waveguide (SIW) technology using high-order cavity modes is demonstrated in this paper. High-order resonant modes (TE130, TE310, TE330) inside the cavity are simply excited by a coaxial probe which is located at the center of the antenna. Energy is coupled out of the cavity by a 3 × 3 slot array etched on the top surface of the cavity. Two antennas with different polarizations are designed and tested. Measured results show that the linearly polarized prototype achieves an impedance bandwidth (|S11| <; -10 dB) of > 26% (28 to 36.6 GHz), and a 1-dB gain bandwidth of 14.1% (30.3 to 34.9 GHz). In addition, a measured maximum gain of 13.8 dBi and radiation efficiency of 92% are obtained. To generate circularly polarized radiation, a rotated dipole array is placed in front of the proposed linearly polarized antenna. Measured results show that the circularly polarized antenna exhibits a common bandwidth (10-dB return loss bandwidth, 3-dB axial ratio bandwidth, and 1-dB gain bandwidth) of 11%.

Wideband Excitation Technology of ${\rm TE}_{20}$ Mode Substrate Integrated Waveguide (SIW) and Its Applications <=SEP=> The higher order mode substrate integrated waveguide (SIW) has advantages in the applications, which are: simplifying the structure with reduced fabrication cost and enhancing the stability of performance by relaxed fabrication tolerance. In this paper, two wideband TE20 mode excitation structures are presented and investigated for the SIW. A slot along the mid line in the longitudinal direction of the SIW is employed to convert the electromagnetic field pattern between slotline and the TE20 mode SIW. The second structure is based on the slot aperture coupling and can realize wideband direct transition between the TE20 mode SIW and microstrip line. Both transitions have a simple and compact structure, as well as broadband characteristics. The wideband transition performance is demonstrated in this paper. As application examples of the transitions, two broadband substrate integrated baluns are presented and fabricated based on the TE20 mode excitation structures and TE20 mode characteristics. The 180 ° out-of-phase and equal magnitude of the balun outputs in a wide frequency range can be achieved inherently. The balun based on the slotline excitation has a fractional bandwidth of 50.2%, from 7.3 to 12.2 GHz, with measured return loss, amplitude imbalance, and phase imbalance better than 10 and 0.45 dB and 3.8 °. The balun based on the aperture coupling excitation shows a fractional bandwidth of 50.3%, from 7 to 11.7 GHz, with measured return loss, insertion loss, amplitude imbalance, and phase imbalance better than 10, 1, and 0.27 dB and 2.4 °, respectively. Both baluns not only show good performance, but also demonstrate the existence of the TE20 mode in the SIW.

60-GHz Circularly Polarized U-Slot Patch Antenna Array on LTCC <=SEP=> This communication presents a 60-GHz wideband circularly polarized (CP) U-slot patch antenna array of 4 × 4 elements on low temperature cofired ceramic (LTCC). A CP U-slot patch antenna is used as the array element to enhance the impedance bandwidth and a stripline sequential rotation feeding scheme is applied to achieve wide axial ratio (AR) bandwidth. Meanwhile, a grounded coplanar waveguide (GCPW) to stripline transition is designed for probe station measurement. The fabricated antenna array has a dimension of 14 ×16 × 1.1 mm3 . The simulated and measured impedance bandwidths, AR bandwidths, and radiation patterns are investigated and compared. Measured results show that the proposed antenna array has a wide impedance bandwidth from 50.5 GHz to 67 GHz for |S11| <; -10 dB, and a wide AR bandwidth from 54 GHz to 65.5 GHz for AR <; 3 dB. In addition, it exhibits a peak gain of 16 dBi and a beam-shaped pattern with 3-dB beam width of 20°. Moreover, its AR keeps below 3 dB within the 3-dB beam width.

Integrated transition of coplanar to rectangular waveguides <=SEP=> Usual transitions between planar circuit and rectangular waveguide make use of 3-D complex mounting structures. Such an integration requires costly high precision mechanical alignment, In this paper, a new planar platform is developed in which a coplanar waveguide (CPW) and a rectangular waveguide are fully integrated on the same substrate, and they are interconnected via a simple transition. They can be built with a standard PCB process. Our experiments at 28 GHz show that an effective bandwidth of 7% at 15 dB return loss can easily be achieved. The CPW-to-waveguide transition allows for a complete integration of waveguide components on substrate with active components such as MMIC.

TagAssist: Automatic Tag Suggestion for Blog Posts <=SEP=> In this paper, we describe a system called TagAssist that provides tag suggestions for new blog posts by utilizing existing tagged posts. The system is able to increase the quality of suggested tags by performing lossless compression over existing tag data. In addition, the system employs a set of metrics to evaluate the quality of a potential tag suggestion. Coupled with the ability for users to manually add tags, TagAssist can ease the burden of tagging and increase the utility of retrieval and browsing systems built on top of tagging data.

Storytelling by the StoryCake visualization <=SEP=> On the issue of how to explore the complex relationships of entities in a story, Storyline visualization has proven to be a useful approach. The traditional Storyline visualization technology only applies to a linear continuous story and has the limitation of reflecting the development of the plots in a story. In this paper, we propose a hierarchical plot visualization method called StoryCake to improve this problem. First, according to the story elements, inter-sessions are divided into groups, whereby the layout of the entities will be optimized in individual groups. Then, the hierarchical relationships of entities in polar coordinates can be confirmed. Finally, we use several skills, e.g., interaction, labels and a fan-shaped visualization view, to enable people better understand how story evolves and track the hierarchical relationship more conveniently. Experimental results show that the proposed hierarchical plot visualization method in polar coordinates can reveal discontinuous events and nonlinear stories. The results also show that our algorithm presents the narrative structure and development of the story.

The self to other model of empathy: Providing a new framework for understanding empathy impairments in psychopathy, autism, and alexithymia <=SEP=> Despite increasing empirical and theoretical work on empathy, particularly on the content of empathic representations, there is a relative lack of consensus regarding the information processing necessary for empathy to occur. Here we attempt to delineate a mechanistic cognitive model of empathy in order to provide a framework within which neuroimaging work on empathy can be located, and which may be used in order to understand various disorders characterised by atypical levels of empathy. To this end data from individuals with psychopathy, autism, and alexithymia inform the model, and the model is used to provide a unifying framework for any empathy impairments seen in these disorders. The model adopts a developmental framework and tries to address the four difficult questions of empathy: How do we know what another is feeling? What is the role of theory of mind in empathy? How does the state of another cause a corresponding state in the self? How do we represent another's emotion once emotional contagion has taken place?

Rectification of QR-code images using the parametric cylindrical surface model <=SEP=> In recent years, QR codes have found a wide range of applications in business and industry. Moreover, their popularity and function are still growing (fast). Therefore, the processing of the images of QR codes is an important task. In this paper, we try to solve a problem encountered in QR decoding when the QR code is printed near the binding edge inside a book or on the surface of a cylindrical container. When a picture is taken on such a QR code, the picture is no longer in a rectangular shape, which is supposedly the “right” shape that any QR code should take, due to warping from the image capturing mechanism by the camera. We refer to such warping as cylinder-to-screen (C2S) warping. This warping translates into serious distortion of the original QR-code image (also referred to as QR image, for short) and thus causes failure in its decoding. In this paper, a mathematical model called the parametric cylindrical surface model (PCSM) is proposed. Then, based on it, a scheme is proposed to rectify C2S-warped QR images. Experiments show that the proposed scheme is effective, in the sense that many failed QR decodings become successful after the rectification.

Image Segmentation Techniques Overview <=SEP=> The technology of image segmentation is widely used in medical image processing, face recognition pedestrian detection, etc. The current image segmentation techniques include region-based segmentation, edge detection segmentation, segmentation based on clustering, segmentation based on weakly-supervised learning in CNN, etc. This paper analyzes and summarizes these algorithms of image segmentation, and compares the advantages and disadvantages of different algorithms. Finally, we make a prediction of the development trend of image segmentation with the combination of these algorithms.

Biometrics from Brain Electrical Activity: A Machine Learning Approach <=SEP=> The potential of brain electrical activity generated as a response to a visual stimulus is examined in the context of the identification of individuals. Specifically, a framework for the visual evoked potential (VEP)-based biometrics is established, whereby energy features of the gamma band within VEP signals were of particular interest. A rigorous analysis is conducted which unifies and extends results from our previous studies, in particular, with respect to 1) increased bandwidth, 2) spatial averaging, 3) more robust power spectrum features, and 4) improved classification accuracy. Simulation results on a large group of subject support the analysis

EARTh: An Environmental Application Reference Thesaurus in the Linked Open Data cloud <=SEP=> The paper aims at providing a description of EARTh, the Environmental Application Reference Thesaurus. It represents a general-purpose thesaurus for the environment, which has been published as a SKOS dataset in the Linked Open Data cloud. It promises to become a core tool for indexing and discovery environmental resources by refining and extending GEMET, which is considered the de facto standard when speaking of general-purpose thesaurus for the environment in Europe, besides it has been interlinked to popular LOD datasets as AGROVOC, EUROVOC, DBPEDIA and UMTHES. The paper illustrates the main characteristics of EARTh as a guide to its usage. It clarifies (i) the methodology adopted to define the EARTh content; (ii) the design and technological choices made when publishing EARTh as Linked Data; (iii) the information pertaining to its access and maintenance. Descriptions of EARTh applications and future relevance are highlighted. CNR-IIA-EKOLab Environmental Knowledge Organization Laboratory, Area della Ricerca di Roma 1, Via Salaria Km 29,300 C.P. 10,I-00016 Monterotondo stazione RM, {difranco, vds, plini} @iia.cnr.it

Nurse Managers’ Emotional Intelligence and Effective Leadership: A Review of the Current Evidence <=SEP=> Background
Emotional Intelligence has made a significant contribution to effective leadership, becoming one of the key characteristics of leaders.Objective: The aim of the present study was to review qualitative and quantitative studies concerning Emotional Intelligence of nurse leaders and the evidence-based composition of their results.


Method
A search was performed in the electronic databases (Pubmed, Scopus and CINAHL) for articles, which were published in the period 2000-2017 in English or Greek. Eleven studies met the inclusion criteria, of which 10 were quantitative and one was qualitative.


Results
The results suggested that Emotional Intelligence is a useful tool for nurse leaders and contributes decisively to the achievement of effective management in healthcare.


Conclusion
It is necessary for nurses to improve their social and emotional skills because of the particular nature of the nursing profession, which places the healthy or weak person at its center.

ProgTest: An environment for the submission and evaluation of programming assignments based on testing activities <=SEP=> Programming foundations is not an easy subject to be taught — many students have difficulties understanding the abstract concepts of programming and have a wrong view about the programming activity. In order to address these problems, experiences have suggested the integrated teaching of programming concepts and software testing in introductory CS courses. Shortly, the idea is that testing can contribute to enhance the students' capabilities of understanding and analysis. However, such perspective requires tools to provide an adequate feedback to evaluate the students' performance concerning programming and testing activities. In this paper we describe ProgTest — a web-based tool for the submission and automatic evaluation of practical programming assignments based on testing activities. Results from a preliminary validation of ProgTest are also presented. Such results provide evidences on the practical use of ProgTest as a supporting mechanism for the integrated teaching of programming foundations and software testing.

Building a HighLevel Dataflow System on top of MapReduce: The Pig Experience <=SEP=> Increasingly, organizations capture, transform and analyze enormous data sets. Prominent examples include internet companies and e-science. The Map-Reduce scalable dataflow paradigm has become popular for these applications. Its simple, explicit dataflow programming model is favored by some over the traditional high-level declarative approach: SQL. On the other hand, the extreme simplicity of MapReduce leads to much low-level hacking to deal with the many-step, branching dataflows that arise in practice. Moreover, users must repeatedly code standard operations such as join by hand. These practices waste time, introduce bugs, harm readability, and impede optimizations. Pig is a high-level dataflow system that aims at a sweet spot between SQL and Map-Reduce. Pig offers SQL-style high-level data manipulation constructs, which can be assembled in an explicit dataflow and interleaved with custom Mapand Reduce-style functions or executables. Pig programs are compiled into sequences of Map-Reduce jobs, and executed in the Hadoop Map-Reduce environment. Both Pig and Hadoop are open-source projects administered by the Apache Software Foundation. This paper describes the challenges we faced in developing Pig, and reports performance comparisons between Pig execution and raw Map-Reduce execution.

Matroids and the greedy algorithm <=SEP=> (0) Many discrete programming algorithms are being proposed. One thing most of them have in common is that they do not work very well. Solving problems that are a priori finite, astronomically finite, is preferably a matter of finding algorithms that are s o m e h o w better than finite. These considerations prompt looking for good algorithms and trying to understand how and why at least a few combinatorial problems have them. (1) Let H be a finite (for convenience) set of real-valued vectors , x = [xj] , ] ~ E. Often all the members of H will be integer-valued; often they will all be {0, 1}-valued. The index-set, E, is any finite set of elements. Let c = [cj], ] ~ E, be any real vector on E, called the objective or weighting of E. The problem of finding a member o f H which maximizes (or minimizes) cx = iN cjx/, j ~ E, we call a loco problem or loco programming. "Loco" stands for "linear-objective combinatorial". (2) In order for a loco problem to be a completely defined problem, the way H is given must of course be specified. There are various ways to describe implicitly very large sets H so tha t it is relatively easy to determine whether or not any particular vector is a member of H. One well-known:way is in linear programming, where H is the set of extreme points of the solution-set of a given finite system, L, of linear equations and <_ type linear inequalities in the variables xj (briefly, a

Bitcoin Network Measurements for Simulation Validation and Parameterization <=SEP=> Bitcoin is gaining increasing popularity nowadays, even though the crypto-currencies field has plenty of digital currencies that have emerged before the adoption of Bitcoin idea. Bitcoin is a decentralized digital currency which relies on set of miners to maintain a distributed public ledger and peer-to-peer network to broadcast transactions. In this paper, we analyse how transaction validation is achieved by the transaction propagation round trip and how transaction dissemination throughout the network can lead to inconsistencies in the view of the current transactions ledger by different nodes. We then measure the transaction propagation delay in the real Bitcoin network and how it is affected by the number of nodes and network topology. This measurement enables a precise validation of any simulation model of the Bitcoin network. Large-scale measurements of the real Bitcoin network are performed in this paper. This will provide an opportunity to parameterise any model of the Bitcoin

Haptic jamming: A deformable geometry, variable stiffness tactile display using pneumatics and particle jamming <=SEP=> Many controllable tactile displays present the user with either variable mechanical properties or adjustable surface geometries, but controlling both simultaneously is challenging due to electromechanical complexity and the size/weight constraints of haptic applications. This paper discusses the design, manufacturing, control, and preliminary evaluation of a novel haptic display that achieves both variable stiffness and deformable geometry via air pressure and a technique called particle jamming. The surface of the device consists of a flat, deformable layer of hollow silicone cells filled with coffee grounds. It selectively solidifies in different regions when the air is vacuumed out of individual cells, jamming the coffee particles together. The silicone layer is clamped over a chamber with regulated air pressure. Different sequences of air pressure and vacuum level adjustment allow regions of the surface to display a small rigid lump, a large soft plane, and various other combinations of lump size and stiffness. Experimental data from individual cells show that surface stiffness increases with vacuum level and the elliptical shape of the cells become increasingly spherical with increased chamber pressure.

Design of a Dual-Band High-Gain Antenna Array for WLAN and WiMAX Base Station <=SEP=> A dual-band 3 ×2 antenna array with high gain is presented in this letter. A dual-band folded dipole antenna is utilized as the antenna array element. A broadband symmetric feed network is designed to maintain each array element with the identical current magnitude and phase. The antenna array has a low profile of 12 mm (about 0.1λL; λL is the wavelength in free space at the lowest operating frequency). Dual bands 2.3 ~ 2.56 and 3 ~ 4.2 GHz for return loss (RL) being higher than 10 dB can be obtained in simulation, while two 10-dB RL bands 2.31 ~ 2.51 and 3.1 ~ 4.15 GHz in measurement cover the wireless local area network (WLAN, 2.4 ~ 2.48 GHz) and Worldwide Interoperability for Microwave Access (WiMAX, 3.3 ~ 3.8 GHz). The measured results also show that this planar antenna array has a high gain 14.3 ~ 15.1 dBi (2.31 ~ 2.51 GHz), 16.2 ~ 17.3 dBi ( 3.1 ~ 4.15 GHz) in + z-direction and a low cross-polarization level <; - 26 dB.

Short Group Signatures <=SEP=> We construct a short group signature scheme. Signatures in our scheme are approximately the size of a standard RSA signature with the same security. Security of our group signature is based on the Strong Diffie-Hellman assumption and a new assumption in bilinear groups called the Decision Linear assumption. We prove security of our system, in the random oracle model, using a variant of the security definition for group signatures recently given by Bellare, Micciancio, and Warinschi.

Systematic review of the research evidence examining the effectiveness of interventions using a sensory integrative approach for children. <=SEP=> Twenty-seven studies were systematically reviewed to identify, evaluate, and synthesize the research literature on the effectiveness of sensory integration (SI) intervention on the ability of children with difficulty processing and integrating sensory information to engage in desired occupations and to apply these findings to occupational therapy practice. Results suggest the SI approach may result in positive outcomes in sensorimotor skills and motor planning; socialization, attention, and behavioral regulation; reading-related skills; participation in active play; and achievement of individualized goals. Gross motor skills, self-esteem, and reading gains may be sustained from 3 mo to 2 yr. Findings may be limited by Type II error because of small sample sizes, variable intervention dosage, lack of fidelity to intervention, and selection of outcomes that may not be meaningful to clients and families or may not change with amount of treatment provided. Replication of findings with methodologically and theoretically sound studies is needed to support current findings.

Speed measurement algorithm for low speed permanent magnet synchronous motor based on overlapped measurement regions <=SEP=> In order to improve the speed measurement performance of low speed PMSM drives equipped with absolute optical encoders, this paper proposes a speed measurement method based on overlapped measurement regions. The proposed method replaces the long measurement region of the conventional backward differentiation method with several short ones which are overlapped at most regions. In one speed measurement process, the results obtained from the short regions are averaged to improve precision. Then the relationship between precision, time delay and region length, overlap times, are analyzed using expectation and variance as performance index. Based on the analysis, an optimal design method of the measurement region is derived. Experimental researches are carried out on a low speed permanent magnet synchronous motor equipped with a 13 bit absolute encoder. The results prove the validity and effectiveness of the proposed method.

Multi-task low-rank affinity pursuit for image segmentation <=SEP=> This paper investigates how to boost region-based image segmentation by pursuing a new solution to fuse multiple types of image features. A collaborative image segmentation framework, called multi-task low-rank affinity pursuit, is presented for such a purpose. Given an image described with multiple types of features, we aim at inferring a unified affinity matrix that implicitly encodes the segmentation of the image. This is achieved by seeking the sparsity-consistent low-rank affinities from the joint decompositions of multiple feature matrices into pairs of sparse and low-rank matrices, the latter of which is expressed as the production of the image feature matrix and its corresponding image affinity matrix. The inference process is formulated as a constrained nuclear norm and ℓ2;1-norm minimization problem, which is convex and can be solved efficiently with the Augmented Lagrange Multiplier method. Compared to previous methods, which are usually based on a single type of features, the proposed method seamlessly integrates multiple types of features to jointly produce the affinity matrix within a single inference step, and produces more accurate and reliable segmentation results. Experiments on the MSRC dataset and Berkeley segmentation dataset well validate the superiority of using multiple features over single feature and also the superiority of our method over conventional methods for feature fusion. Moreover, our method is shown to be very competitive while comparing to other state-of-the-art methods.

Sensors and systems for fruit detection and localization: A review <=SEP=> This paper reviews the research and development of machine vision systems for fruit detection and localization for robotic harvesting and/or crop-load estimation of specialty tree crops including apples, pears, and citrus. Variable lighting condition, occlusions, and clustering are some of the important issues needed to be addressed for accurate detection and localization of fruit in orchard environment. To address these issues, various techniques have been investigated using different types of sensors and their combinations as well as with different image processing techniques. This paper summarizes various techniques and their advantages and disadvantages in detecting fruit in plant or tree canopies. The paper also summarizes the sensors and systems developed and used by researchers to localize fruit as well as the potential and limitations of those systems. Finally, major challenges for the successful application of machine vision system for robotic fruit harvesting and crop-load estimation, and potential future directions for research and development are discussed. 2015 Elsevier B.V. All rights reserved.

Change impact analysis for Natural Language requirements: An NLP approach <=SEP=> Requirements are subject to frequent changes as a way to ensure that they reflect the current best understanding of a system, and to respond to factors such as new and evolving needs. Changing one requirement in a requirements specification may warrant further changes to the specification, so that the overall correctness and consistency of the specification can be maintained. A manual analysis of how a change to one requirement impacts other requirements is time-consuming and presents a challenge for large requirements specifications. We propose an approach based on Natural Language Processing (NLP) for analyzing the impact of change in Natural Language (NL) requirements. Our focus on NL requirements is motivated by the prevalent use of these requirements, particularly in industry. Our approach automatically detects and takes into account the phrasal structure of requirements statements. We argue about the importance of capturing the conditions under which change should propagate to enable more accurate change impact analysis. We propose a quantitative measure for calculating how likely a requirements statement is to be impacted by a change under given conditions. We conduct an evaluation of our approach by applying it to 14 change scenarios from two industrial case studies.

Privacy-Preserving Multiple Linear Regression of Vertically Partitioned Real Medical Datasets <=SEP=> This paper studies the feasibility of privacy-preservingdata mining in epidemiological study. As for the data-miningalgorithm, we focus to a linear multiple regression thatcan be used to identify the most significant factorsamong many possible variables, such as the historyof many diseases. We try to identify the linear model to estimate a lengthof hospital stay from distributed dataset related tothe patient and the disease information. In this paper, we have done experiment usingthe real medical dataset related to stroke andattempt to apply multiple regression with sixpredictors of age, sex, the medical scales, e.g., Japan Coma Scale, and the modified Rankin Scale. Our contributions of this paper include(1) to propose a practical privacy-preserving protocols for linear multiple regressionwith vertically partitioned datasets, and(2) to show the feasibility of the proposed system usingthe real medical dataset distributed into two parties, the hospital who knows the technical details of diseasesduring the patients are in the hospital, and the local government who knows the residence even afterthe patients left hospital. (3) to show the accuracy and the performance of thePPDM system which allows us to estimate the expectedprocessing time with arbitrary number of predictors.

Generalized Haar Filter based Deep Networks for Real-Time Object Detection in Traffic Scene <=SEP=> Vision-based object detection is one of the fundamental functions in numerous traffic scene applications such as self-driving vehicle systems and advance driver assistance systems (ADAS). However, it is also a challenging task due to the diversity of traffic scene and the storage, power and computing source limitations of the platforms for traffic scene applications. This paper presents a generalized Haar filter based deep network which is suitable for the object detection tasks in traffic scene. In this approach, we first decompose a object detection task into several easier local regression tasks. Then, we handle the local regression tasks by using several tiny deep networks which simultaneously output the bounding boxes, categories and confidence scores of detected objects. To reduce the consumption of storage and computing resources, the weights of the deep networks are constrained to the form of generalized Haar filter in training phase. Additionally, we introduce the strategy of sparse windows generation to improve the efficiency of the algorithm. Finally, we perform several experiments to validate the performance of our proposed approach. Experimental results demonstrate that the proposed approach is both efficient and effective in traffic scene compared with the state-of-the-art.

Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition <=SEP=> Brain electrical activity recorded via electroencephalogram (EEG) is the most convenient means for brain-computer interface (BCI), and is notoriously noisy. The information of interest is located in well defined frequency bands, and a number of standard frequency estimation algorithms have been used for feature extraction. To deal with data nonstationarity, low signal-to-noise ratio, and closely spaced frequency bands of interest, we investigate the effectiveness of recently introduced multivariate extensions of empirical mode decomposition (MEMD) in motor imagery BCI. We show that direct multichannel processing via MEMD allows for enhanced localization of the frequency information in EEG, and, in particular, its noise-assisted mode of operation (NA-MEMD) provides a highly localized time-frequency representation. Comparative analysis with other state of the art methods on both synthetic benchmark examples and a well established BCI motor imagery dataset support the analysis.

Source Code Metrics for Programmable Logic Controller (PLC) Ladder Diagram (LD) Visual Programming Language <=SEP=> The IEC 611131-3, an open international standard for Programmable Logic Controllers (PLC) defines several domain specific languages for industrial and process automation. Domain specific languages have several features, programming constructs and notations which are different than general purpose languages and hence the traditional source code metrics for general purpose programming languages cannot be directly applied to domain specific languages for writing control programs in the area of industrial automation. We propose source code level metrics to measure size, vocabulary, cognitive complexity and testing complexity of a visual Programmable Logic Controller (PLC) programming language. We present metrics for Ladder Diagram (LD) programming language which is one of the five languages defined in the IEC 61131-3 standard. The proposed metric is based on factors like number of distinct operators and operands, total number of operators and operands, number of rungs, weights of different basic control structures, structure of the program and control flow. We apply Weyukur's property to validate the metrics and evaluate the number of properties satisfied by the proposed metric.

Accelerometer-based tilt estimation of a rigid body with only rotational degrees of freedom <=SEP=> An estimation algorithm is developed for determining pitch and roll angles (tilt) of a rigid body fixed at a pivot point using multiple accelerometers. The estimate is independent of the rigid body dynamics; the method is applicable both in static conditions and for any dynamic motion of the body. No dynamic model is required for the estimator; only the mounting positions of the sensors need to be known. The proposed estimator is the optimal linear estimate in a least-squares sense if knowledge of the system dynamics is not used. The estimate may be used as a basis for further filtering and fusion techniques, such as sensor fusion with rate gyro data. The estimation algorithm is applied to the problem of state estimation for the Balancing Cube, a rigid structure that can actively balance on its corners. Experimental results are provided.