title: Wideband Fabry–Perot Resonator Antenna With Two Layers of Dielectric Superstrates

abstract: This letter presents a new design of a Fabry–Perot resonator antenna (FPRA) with a wide gain bandwidth. A double-layered dielectric superstrate, which produces a reflection phase curve versus frequency with a positive slope, is used as a partially reflective surface (PRS) to enhance the bandwidth of the FPRA. For a physical insight, the PRS is analyzed by using the transmission line theory and Smith Chart. Experimental results demonstrate that the antenna has a 3-dB gain bandwidth over 13.5–17.5 GHz, relatively 25.8%, with a peak gain of 15 dBi. Furthermore, the gain band is overlapped well by the impedance band for the reflection coefficient ( ${ S}_{11}$ ) less than $-$ 10 dB.


title: fNIRS-EEG study of focal interictal epileptiform discharges

abstract: Summary Functional near-infrared spectroscopy (fNIRS) acquired with electroencephalography (EEG) is a relatively new non-invasive neuroimaging technique with potential for long term monitoring of the epileptic brain. Simultaneous EEG-fNIRS recording allows the spatio-temporal reconstruction of the hemodynamic response in terms of the concentration changes in oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR) associated with recorded epileptic events such as interictal epileptic discharges (IEDs) or seizures. While most previous studies investigating fNIRS in epilepsy had limitations due to restricted spatial coverage and small sample sizes, this work includes a sufficiently large number of channels to provide an extensive bilateral coverage of the surface of the brain for a sample size of 40 patients with focal epilepsies. Topographic maps of significant activations due to each IED type were generated in four different views (dorsal, frontal, left and right) and were compared with the epileptic focus previously identified by an epileptologist. After excluding 5 patients due to the absence of IEDs and 6 more with mesial temporal foci too deep for fNIRS, we report that significant HbR (respectively HbO) concentration changes corresponding to IEDs were observed in 62% (resp. 38%) of patients with neocortical epilepsies. This HbR/HbO response was most significant in the epileptic focus region among all the activations in 28%/21% of patients.


title: Accurate vertical road profile estimation using v-disparity map and dynamic programming

abstract: Detecting obstacles on the road is crucial for the advanced driver assistance systems. Obstacle detection on the road can be greatly facilitated if we have a vertical road profile. Therefore, in this paper, we present a novel method that can estimate an accurate vertical road profile of the scene from the stereo images. Unlike conventional stereo-based road profile estimation methods that heavily rely on a parametric model of the road surface, our method can obtain a road profile for an arbitrary complicated road. To this end, an energy function that includes the stereo matching fidelity and spatio-temporal smoothness of the road profile is presented, and thus the road profile is extracted by maximizing the energy function via dynamic programming. The experimental results demonstrate the effectiveness of the proposed method.


title: THE DESIGN OF THE iCub HUMANOID ROBOT

abstract: This article describes the hardware design of the iCub humanoid robot. The iCub is an open-source humanoid robotic platform designed explicitly to support research in embodied cognition. This paper covers the mechanical and electronic design of the first release of the robot. A series upgrades developed for the second version of the robot (iCub2), which are aimed at the improvement of the mechanical and sensing performance, are also described.


Modeling and Simulation of Two-Phase Interleaved Boost Converter Using Open-Source Software Scilab / Xcos


title: The practical realities of UTRA TDD and FDD co-existence and their impact on the future spectrum allocations

abstract: This paper presents some of the first published results of real UTRA TDD and FDD equipment performance in respect of co-siting. The relevant 3GPP specifications are examined in detail to see whether they guarantee co-existence and if not whether they are exceeded in practice. In conclusion, the paper shows that the necessary performance to facilitate co-existence, co-siting and indeed antenna sharing has already been achieved in practice. These results not only have implications on the coexistence discussions for new spectrum allocations for 3G, such as the IMT-2000 extension band, but also on new standards for these bands.


title: Global Optimization for Artificial Neural Networks: A Tabu Search Application

abstract: The ability of neural networks to closely approximate unknown functions to any degree of desired accuracy has generated considerable demand for neural network research in business. The attractiveness of neural network research stems from researchers' need to approximate models within the business environment without having a priori knowledge about the true underlying function. Gradient techniques, such as backpropagation, are currently the most widely used methods for neural network optimization. Since these techniques search for local solutions, they are subject to local convergence and thus can perform poorly even on simple problems when forecasting out-of-sample. Consequently, a global search algorithm is warranted. In this paper we examine tabu search (TS) as a possible alternative to the problematic backpropagation approach. A Monte Carlo study was conducted to test the appropriateness of TS as a global search technique for optimizing neural networks. Holding the neural network architecture constant, 530 independent runs were conducted for each of seven test functions, including a production function that exhibits both increasing and diminishing marginal returns and the Mackey-Glass chaotic time series. In the resulting comparison, TS derived solutions that were significantly superior to those of backpropagation solutions for in-sample, interpolation, and extrapolation test data for all seven test functions. It was also shown that fewer function evaluations were needed to find these optimal values.


title: Sepsis in European intensive care units: Results of the SOAP study*

abstract: Objective:To better define the incidence of sepsis and the characteristics of critically ill patients in European intensive care units.Design:Cohort, multiple-center, observational study.Setting:One hundred and ninety-eight intensive care units in 24 European countries.Patients:All new adult admissi


title: Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration

abstract: Data visualization is an essential component of genomic data analysis. However, the size and diversity of the data sets produced by today’s sequencing and array-based profiling methods present major challenges to visualization tools. The Integrative Genomics Viewer (IGV) is a high-performance viewer that efficiently handles large heterogeneous data sets, while providing a smooth and intuitive user experience at all levels of genome resolution. A key characteristic of IGV is its focus on the integrative nature of genomic studies, with support for both array-based and next-generation sequencing data, and the integration of clinical and phenotypic data. Although IGV is often used to view genomic data from public sources, its primary emphasis is to support researchers who wish to visualize and explore their own data sets or those from colleagues. To that end, IGV supports flexible loading of local and remote data sets, and is optimized to provide high-performance data visualization and exploration on standard desktop systems. IGV is freely available for download from http://www.broadinstitute.org/igv, under a GNU LGPL open-source license.


title: Estimation of Energy Balance Components over a Drip-Irrigated Olive Orchard Using Thermal and Multispectral Cameras Placed on a Helicopter-Based Unmanned Aerial Vehicle (UAV)

abstract: A field experiment was carried out to implement a remote sensing energy balance (RSEB) algorithm for estimating the incoming solar radiation (Rsi), net radiation (Rn), sensible heat flux (H), soil heat flux (G) and latent heat flux (LE) over a drip-irrigated olive (cv. Arbequina) orchard located in the Pencahue Valley, Maule Region, Chile (35°25′S; 71°44′W; 90 m above sea level). For this study, a helicopter-based unmanned aerial vehicle (UAV) was equipped with multispectral and infrared thermal cameras to obtain simultaneously the normalized difference vegetation index (NDVI) and surface temperature (Tsurface) at very high resolution (6 cm × 6 cm). Meteorological variables and surface energy balance components were measured at the time of the UAV overpass (near solar noon). The performance of the RSEB algorithm was evaluated using measurements of H and LE obtained from an eddy correlation system. In addition, estimated values of Rsi and Rn were compared with ground-truth measurements from a four-way net radiometer while those of G were compared with soil heat flux based on flux plates. Results indicated that RSEB algorithm estimated LE and H with errors of 7% and 5%, respectively. Values of the root mean squared error (RMSE) and mean absolute error (MAE) for LE were 50 and 43 W m−2 while those for H were 56 and 46 W m−2, respectively. Finally, the RSEB algorithm computed Rsi, Rn and G with error less than 5% and with values of RMSE and MAE less than 38 W m−2. Results demonstrated that multispectral and thermal cameras placed on an UAV could provide an excellent tool to evaluate the intra-orchard spatial variability of Rn, G, H, LE, NDVI and Tsurface over the tree canopy and soil surface between rows.


title: Computer-Suggested Facial Makeup

abstract: Finding the best makeup for a given human face is an art in its own right. Experienced makeup artists train for years to be skilled enough to propose a best-fit makeup for an individual. In this work we propose a system that automates this task. We acquired the appearance of 56 human faces, both without and with professional makeup. To this end, we use a controlled-light setup, which allows to capture detailed facial appearance information, such as diffuse reflectance, normals, subsurface-scattering, specularity, or glossiness. A 3D morphable face model is used to obtain 3D positional information and to register all faces into a common parameterization. We then define makeup to be the change of facial appearance and use the acquired database to find a mapping from the space of human facial appearance to makeup. Our main application is to use this mapping to suggest the best-fit makeup for novel faces that are not in the database. Further applications are makeup transfer, automatic rating of makeup, makeup-training, or makeup-exaggeration. As our makeup representation captures a change in reflectance and scattering, it allows us to synthesize faces with makeup in novel 3D views and novel lighting with high realism. The effectiveness of our approach is further validated in a user-study.


SYSTEMATIC EVALUATION OF E-LEARNING SYSTEMS


title: Toward Realistic Hands Gesture Interface: Keeping it Simple for Developers and Machines

abstract: Development of a rich hand-gesture-based interface is currently a tedious process, requiring expertise in computer vision and/or machine learning. We address this problem by introducing a simple language for pose and gesture description, a set of development tools for using it, and an algorithmic pipeline that recognizes it with high accuracy. The language is based on a small set of basic propositions, obtained by applying four predicate types to the fingers and to palm center: direction, relative location, finger touching and finger folding state. This enables easy development of a gesture-based interface, using coding constructs, gesture definition files or an editing GUI. The language is recognized from 3D camera input with an algorithmic pipeline composed of multiple classification/regression stages, trained on a large annotated dataset. Our experimental results indicate that the pipeline enables successful gesture recognition with a very low computational load, thus enabling a gesture-based interface on low-end processors.


title: Dosimetry of 3 CBCT devices for oral and maxillofacial radiology: CB Mercuray, NewTom 3G and i-CAT

abstract: Objectives: Cone beam computed tomography (CBCT), which provides a lower dose, lower cost alternative to conventional CT, is being used with increasing frequency in the practice of oral and maxillofacial radiology. This study provides comparative measurements of effective dose for three commercially available, large (12″) field-of-view (FOV), CBCT units: CB Mercuray, NewTom 3G and i-CAT. Methods: Thermoluminescent dosemeters (TLDs) were placed at 24 sites throughout the layers of the head and neck of a tissue-equivalent human skull RANDO phantom. Depending on availability, the 12″ FOV and smaller FOV scanning modes were used with similar phantom positioning geometry for each CBCT unit. Radiation weighted doses to individual organs were summed using 1990 (E1990) and proposed 2005 (E2005 draft) ICRP tissue weighting factors to calculate two measures of whole-body effective dose. Dose as a multiple of a representative panoramic radiography dose was also calculated. Results: For repeated runs dosimetry was ge...


title: Social Recommendation with Cross-Domain Transferable Knowledge

abstract: Recommender systems can suffer from data sparsity and cold start issues. However, social networks, which enable users to build relationships and create different types of items, present an unprecedented opportunity to alleviate these issues. In this paper, we represent a social network as a star-structured hybrid graph centered on a social domain, which connects with other item domains. With this innovative representation, useful knowledge from an auxiliary domain can be transferred through the social domain to a target domain. Various factors of item transferability, including popularity and behavioral consistency, are determined. We propose a novel Hybrid Random Walk (HRW) method, which incorporates such factors, to select transferable items in auxiliary domains, bridge cross-domain knowledge with the social domain, and accurately predict user-item links in a target domain. Extensive experiments on a real social dataset demonstrate that HRW significantly outperforms existing approaches.


title: A New Silicone Structure for uSkin—A Soft, Distributed, Digital 3-Axis Skin Sensor and Its Integration on the Humanoid Robot iCub

abstract: Tactile sensing is one important element that can enable robots to interact with an unstructured world. By having tactile perception, a robot can explore its environment by touching objects. Like human skin, a tactile sensor that can provide rich information such as distributed normal and shear forces with high density can help the robot to recognize objects. In previous work, we introduced uSkin, a soft skin with distributed 3-axis force-sensitive elements and a center-to-center distance between the 3-axis load cells of 4.7 mm for the flat version. This letter presents a new structure for the distributed soft force transducer that reduces the crosstalk between the components of the 3-axis force measurements. Three dimensionally (3-D) printing the silicone structure eased the prototype production. However, the 3-D printed material has a higher hysteresis than the previously used Ecoflex. Microcontroller boards originally developed for the skin of iCub were implemented for uSkin, increasing the readout frequency and reducing the space requirements and number of wires. The sensor was installed on iCub and successfully used for shape exploration.


title: An information retrieval model based on simple Bayesian networks

abstract: In this article a new probabilistic information retrieval (IR) model, based on Bayesian networks (BNs), is proposed. We first consider a basic model, which represents only direct relationships between the documents in the collection and the terms or keywords used to index them. Next, we study two versions of an extended model, which also represents direct relationships between documents. In either case the BNs are used to compute efficiently, by means of a new and exact propagation algorithm, the posterior probabilities of relevance of the documents in the collection given a query. The performance of the proposed retrieval models is tested through a series of experiments with several standard document collections. © 2003 Wiley Periodicals, Inc.


title: DroidScope: Seamlessly Reconstructing the OS and Dalvik Semantic Views for Dynamic Android Malware Analysis

abstract: The prevalence of mobile platforms, the large market share of Android, plus the openness of the Android Market makes it a hot target for malware attacks. Once a malware sample has been identified, it is critical to quickly reveal its malicious intent and inner workings. In this paper we present DroidScope, an Android analysis platform that continues the tradition of virtualization-based malware analysis. Unlike current desktop malware analysis platforms, DroidScope reconstructs both the OS-level and Java-level semantics simultaneously and seamlessly. To facilitate custom analysis, DroidScope exports three tiered APIs that mirror the three levels of an Android device: hardware, OS and Dalvik Virtual Machine. On top of DroidScope, we further developed several analysis tools to collect detailed native and Dalvik instruction traces, profile API-level activity, and track information leakage through both the Java and native components using taint analysis. These tools have proven to be effective in analyzing real world malware samples and incur reasonably low performance overheads.


title: A novel probabilistic feature selection method for text classification

abstract: High dimensionality of the feature space is one of the most important concerns in text classification problems due to processing time and accuracy considerations. Selection of distinctive features is therefore essential for text classification. This study proposes a novel filter based probabilistic feature selection method, namely distinguishing feature selector (DFS), for text classification. The proposed method is compared with well-known filter approaches including chi square, information gain, Gini index and deviation from Poisson distribution. The comparison is carried out for different datasets, classification algorithms, and success measures. Experimental results explicitly indicate that DFS offers a competitive performance with respect to the abovementioned approaches in terms of classification accuracy, dimension reduction rate and processing time.


title: Combining Word Embeddings and Feature Embeddings for Fine-grained Relation Extraction

abstract: Compositional embedding models build a representation for a linguistic structure based on its component word embeddings. While recent work has combined these word embeddings with hand crafted features for improved performance, it was restricted to a small number of features due to model complexity, thus limiting its applicability. We propose a new model that conjoins features and word embeddings while maintaing a small number of parameters by learning feature embeddings jointly with the parameters of a compositional model. The result is a method that can scale to more features and more labels, while avoiding overfitting. We demonstrate that our model attains state-of-the-art results on ACE and ERE fine-grained relation extraction.


title: Survival Analysis Part I: Basic concepts and first analyses

abstract: Survival analysis is a collection of statistical procedures for data analysis where the outcome variable of interest is time until an event occurs. Because of censoring–the nonobservation of the event of interest after a period of follow-up–a proportion of the survival times of interest will often be unknown. It is assumed that those patients who are censored have the same survival prospects as those who continue to be followed, that is, the censoring is uninformative. Survival data are generally described and modelled in terms of two related functions, the survivor function and the hazard function. The survivor function represents the probability that an individual survives from the time of origin to some time beyond time t. It directly describes the survival experience of a study cohort, and is usually estimated by the KM method. The logrank test may be used to test for differences between survival curves for groups, such as treatment arms. The hazard function gives the instantaneous potential of having an event at a time, given survival up to that time. It is used primarily as a diagnostic tool or for specifying a mathematical model for survival analysis. In comparing treatments or prognostic groups in terms of survival, it is often necessary to adjust for patient-related factors that could potentially affect the survival time of a patient. Failure to adjust for confounders may result in spurious effects. Multivariate survival analysis, a form of multiple regression, provides a way of doing this adjustment, and is the subject the next paper in this series.


title: Mobile Robot Navigation Based on Artificial Landmarks with Machine Vision System

abstract: The paper describes machine vision system (MVS) developed by authors, which identifies artificial landmarks on images from a video camera with pan-tilt mechanism and allows to calculate the deviation of the robot from the set course. Lines limiting robot track and tags in the form of two-dimensional barcodes were selected as artificial landmarks. Designed MVS is a hardware-software complex, which includes one camera with pan-tilt mechanism and onboard computer, which implemented the software that allows to search for artificial landmarks in the environment and to identify them at the image. Also authors developed a special software provides control of the drive wheels of the robot in order to eliminate the course deviation calculated on the basis of information about artificial landmarks. The paper shows that the proposed machine vision system for mobile robot navigation is economical, have acceptable performance and can be applied in the real-time control systems for warehouse automated guided vehicles, service robots, security robots, mobile robots operating in hostile and dangerous to human health environments. environment can be the map. The map is also can be built Navigation and positioning of mobile robots with and expanded in the process of the robot motion. machine vision systems are usually carried out with In this work authors chose the method of navigating natural or artificial landmarks. The main problem of a mobile robot with artificial landmarks using a video navigating with natural landmarks is the detection camera provides the flexibility to change the route, and comparison of the characteristics of the images undemanding to the quality of flooring, low equipment from the cameras in noisy environments, changes in light cost and ease of installation, ease of implementation of of the observed scene and the impact of other adverse the algorithm in comparison with the method of the


title: The measure of face-lift patient satisfaction: the Owsley Facelift Satisfaction Survey with a long-term follow-up study.

abstract: Background: Patient satisfaction is a major factor in determining success in aesthetic surgery. To the authors' knowledge, a long-term study measuring patient satisfaction with face-lift surgery has not been published. The authors' study was designed to measure patient satisfaction with the overall experience of a face lift and to assess the patient's level of satisfaction 10 to 15 years after surgery. Methods: Three hundred ninety-four consecutive patients were identified who had face lifts performed by the senior author g.Q.O.) between January 1, 1994, and January 1, 1999. Contact was achieved with 146 patients (37 percent), and 131 patients (90 percent) agreed to participate by completing a four-page survey. Eighty-nine patients (68 percent) returned the survey. Results: One year after face-lift surgery, 87 patients (97.8 percent) described the improvement of their facial appearance as very good or beyond expectations. After an average follow-up of 12.6 years, 61 patients (68.5 percent) rated their current degree of improvement as very good or beyond expectations, and 61 patients (68.5 percent) felt 10 or more years had been added to their youthful appearance. Thirty-four patients (31 percent) indicated disappointment in some aspect of the face lift. Conclusions: This work assesses the long-term satisfaction of face-lift patients who had a superficial musculoaponeurotic system-platysma face lift. The results suggest a high degree of satisfaction following face-lift surgery at short-term and long-term follow-up. The authors recognize that recall bias may be present when recalling the satisfaction at 1 year postoperatively. We present the survey questionnaire as a template for future research in face-lift patients. .


title: ShuffleDog: Characterizing and Adapting User-Perceived Latency of Android Apps

abstract: Numerous complains have been made by Android users who severely suffer from the sluggish response when interacting with their devices. However, very few studies have been conducted to understand the user-perceived latency or mitigate the UI-lagging problem. In this paper, we conduct the first systematic measurement study to quantify the user-perceived latency using typical interaction-intensive Android apps in running with and without background workloads. We reveal the insufficiency of Android system in ensuring the performance of foreground apps and therefore design a new system to address the insufficiency accordingly. We develop a lightweight tracker to accurately identify all delay-critical threads that contribute to the slow response of user interactions. We then build a resource manager that can efficiently schedule various system resources including CPU, I/O, and GPU, for optimizing the performance of these threads. We implement the proposed system on commercial smartphones and conduct comprehensive experiments to evaluate our implementation. Evaluation results show that our system is able to significantly reduce the user-perceived latency of foreground apps in running with aggressive background workloads, up to 10x, while incurring negligible system overhead of less than 3.1 percent CPU and 7 MB memory.


title: Balanced Two-Stage Residual Networks for Image Super-Resolution

abstract: In this paper, balanced two-stage residual networks (BTSRN) are proposed for single image super-resolution. The deep residual design with constrained depth achieves the optimal balance between the accuracy and the speed for super-resolving images. The experiments show that the balanced two-stage structure, together with our lightweight two-layer PConv residual block design, achieves very promising results when considering both accuracy and speed. We evaluated our models on the New Trends in Image Restoration and Enhancement workshop and challenge on image super-resolution (NTIRE SR 2017). Our final model with only 10 residual blocks ranked among the best ones in terms of not only accuracy (6th among 20 final teams) but also speed (2nd among top 6 teams in terms of accuracy). The source code both for training and evaluation is available in https://github.com/ychfan/sr_ntire2017.


title: Unipolar switched bidirectional bridgeless power factor correction boost rectifier with adaptive dual current mode control

abstract: This paper proposes an application of adaptive dual current mode control (ADCMC) on bidirectional bridgeless power factor correction (BBPFC) boost rectifier with unipolar switching. The given simulation results confirm the benefits of the proposed control strategy of the BBPFC converter, primarily regarding the maintaining of the sine waveform of the average inductor current.


title: Accurate Pulmonary Nodule Detection in Computed Tomography Images Using Deep Convolutional Neural Networks

abstract: Early detection of pulmonary cancer is the most promising way to enhance a patient’s chance for survival. Accurate pulmonary nodule detection in computed tomography (CT) images is a crucial step in diagnosing pulmonary cancer. In this paper, inspired by the successful use of deep convolutional neural networks (DCNNs) in natural image recognition, we propose a novel pulmonary nodule detection approach based on DCNNs. We first introduce a deconvolutional structure to Faster Region-based Convolutional Neural Network (Faster R-CNN) for candidate detection on axial slices. Then, a three-dimensional DCNN is presented for the subsequent false positive reduction. Experimental results of the LUng Nodule Analysis 2016 (LUNA16) Challenge demonstrate the superior detection performance of the proposed approach on nodule detection (average FROC-score of 0.893, ranking the 1st place over all submitted results), which outperforms the best result on the leaderboard of the LUNA16 Challenge (average FROC-score of 0.864).


title: Ex utero intrapartum technique

abstract: Upper airway obstruction of a neonate constitutes an emergency. The ex utero intrapartum technique (EXIT) is a procedure for safely managing airway obstruction at birth, in which placental support is maintained until the airway is evaluated and secured. The anaesthetist is involved in preventing uterine contractions that impair oxygenation of the foetus and cause placental separation, in providing foetal anaesthesia to help airway manipulations, in maintaining foetal pattern of circulation, in preventing and treating maternal hypotension and in resuscitating the neonate. General anaesthesia with high concentration of inhalational agents is preferred as it provides surgical tocolysis and foetal anaesthesia. Additional uterine relaxation may be obtained using tocolytic drugs like nitroglycerin or β-adrenergic agonists. During EXIT the foetus is delivered only as far as the shoulders or thorax leaving the cord entirely in utero to maximize the duration of placental support and to minimize heat and water loss. In this position foetal airway is examined and secured, which may involve tracheal intubation, bronchoscopy or tracheostomy. The umbilical cord is divided and the neonate is completely delivered only after the airway has been secured. With EXIT, a potential life-threatening emergency at birth can be managed like an elective procedure that can improve the prognosis for foetuses with airway obstruction.


title: Introduction To Genetic Algorithms

abstract: The book contains basic concepts, several applications of Genetic Algorithms and solved Genetic Problems using MATLAB software and C/C++. The salient features of the book include - detailed explanation of Genetic Algorithm concepts, - numerous Genetic Algorithm Optimization Problems, - study on various types of Genetic Algorithms, - implementation of Optimization problem using C and C++, - simulated solutions for Genetic Algorithm problems using MATLAB 7.0, - brief description on the basics of Genetic Programming, - application case studies on Genetic Algorithm on emerging fields.


title: Secure cloud storage using AES encryption

abstract: In cloud computing distributed resources are shared via network in open environment. Hence user can easily access their data from anywhere. At the same time there exist privacy and security issues due to many reasons. First one is dramatic development in network technologies. Another is increased demand for computing resources, which make many organizations to outsource their data storage. So there is a need for secure cloud storage service in public cloud environment where the provider is not a trusted one. This paper addresses different data security and privacy protection issues in a cloud computing environment and proposes a method for providing different security services like authentication, authorization and confidentiality along with monitoring in delay. 128 bit Advanced Encryption Standard (AES) is used for increase data security and confidentiality. In this proposed approach data is encrypted using AES and then uploaded on a cloud. The proposed model uses Short Message Service (SMS) alert mechanism for avoiding unauthorized access to user data.


title: Continuous blood pressure measurement by using the pulse transit time: comparison to a cuff-based method

abstract: Pulse transit time (PTT) and pulse wave velocity (PWV), respectively, were shown to have a correlation with systolic blood pressure (SBP) and have been reported to be suitable for indirect BP measurements. The aim of this study was to create a function between SBP and PWV, and to test its reliability for the determination of absolute SBP using a non-linear algorithm and a one-point calibration. 63 volunteers performed exercise to induce rises in BP. Arterial PTT was measured between the R-spike of the ECG and the plethysmographic curve of finger pulse-oximetry. The reference BP was measured using a cuff-based sphygmomanometric aneroid device. Data from 13 of the 63 volunteers served for the detection of the PWV-BP relationship. The created non-linear function was used to calculate BP values after individual correction for the BP offset in a group of 50 volunteers. Individual correlation coefficients for SBP measured by PTT (SBP(PTT)) and by cuff (SBP(CUFF)) varied between r = 0.69 and r = 0.99. Taking all data together, we found r = 0.83 (276 measurements in 50 volunteers). In the Bland-Altman plot, the limits of agreement were [Formula: see text]± 19.8 mmHg. In conclusion, comparing SBP values using the PTT-based method and those measured by cuff resulted in a significant correlation. However, the Bland-Altman plot shows relevant differences between both methods, which are partly due to greater variability of the SBP(PTT) measurement during intensified exercise. Results suggest that PTT can be used for measuring absolute SBP when performing an individual correction for the offset of the BP-PWV relation.


title: Occupational Therapy Alone Has Looked Upon Occupation: Future Applications of Occupational Science to Pediatric Occupational Therapy.

abstract: Occupational therapy has been an invisible profession, largely because the public has had difficulty grasping the concept of occupation. The emergence of occupational science has the potential of improving this situation. Occupational science is firmly rooted in the founding ideas of occupational therapy. In the future, the nature of human occupation will be illuminated by the development of a basic theory of occupational science. Occupational science, through research and theory development, will guide the practice of occupational therapy. Applications of occupational science to the practice of pediatric occupational therapy are presented. Ultimately, occupational science will prepare pediatric occupational therapists to better meet the needs of parents and their children.


title: The space of cross sections of a bundle

abstract: Let B be a nondiscrete compactum, Y a separable complete metrizable ANR with no isolated point and p: X -B a locally trivial bundle with fiber Y admitting a section. It is proved that the space r(X) of all cross sections of p: X -B is an 12-manifold. 0. Introduction. Through the paper, spaces are separable metrizable and maps are continuous. Let p: X -* B be a locally trivial bundle with fiber Y, that is, each point b E B has a neighborhood U and a homeomorphism p: U x Y -, p-1 (U) such that p'p = ru, the projection to U. A map s: B -* X is called a cross section of p: X -* B provided ps = id. The space of all cross sections of p: X -* B with compact-open topology is denoted by 17(X). Then 17(X) is a closed subspace of the space C(B, X) of all maps from B into X. If B is compact and d is a compatible metric for X, the topology of 17(X) (and C(B, X)) is induced by the sup-metric d(f, g) = sup{d(f (b), g(b)) I b E B}. A manifold modeled on Hilbert space 12 is called an 12-manifold. In this note, we prove the following MAIN THEOREM. Let B be a nondiscrete compactum, Y a complete metrizable ANR with no isolated point and p: X B a locally trivial bundle with fiber Y admitting a section. Then 17(X) is an 12-manifold. For the trivial bundle 7rB: B x Y -* B, the space F(B x Y) can be regarded as the space C(B, Y). Thus the space C(B, Y) is an 12-manifold if B is a nondiscrete compactum and Y is a complete-metrizable ANR with no isolated point. This is a generalization of Eells-Geoghegan-Torunczyk's result [E, Ge, To1]. The author would like to thank Doug Curtis for helpful comments. 1. Preliminaries. Our proof is based on the following: TORU?NCZYK'S CHARACTERIZATION THEOREM FOR 12-MANIFOLDS [TO2] (CF. [To3]). A complete-metrizable ANR X is an 12-manifold if and only if X has the discrete approximation property, that is, for each map f: eDnEN I' X of the free union of n-cells (n E N) into X and each map E: X -+ (0, 1) there is a Received by the editors February 27, 1987 and, in revised form, April 22, 1987. Presented to the Mathematical Society of Japan, April 2, 1988. 1980 Mathematics Subject Classification. Primary 58D15, 57N20, 55F10.


title: Is vaginal mucosal graft the excellent substitute material for urethral reconstruction in female-to-male transsexuals?

abstract: PURPOSE ::: Construction of a neourethra is always considered to be a difficult part in phalloplasty, especially for the female-to-male (FTM) transsexual patients. We report our experience with prefabricated pars pendulans urethrae using vaginal mucosal graft for phalloplasty in FTM transsexuals. ::: ::: ::: MATERIALS AND METHODS ::: We retrospectively reviewed notes on the 22 FTM patients treated with pedicled-flap phalloplasty with prefabricated pars pendulans urethrae using vaginal mucosal graft between January 2008 and December 2012. Surgical outcome, urological function, and complications were recorded. Histological difference between normal mucosa and skin, and pathological changes of vaginal mucosal graft were also observed. ::: ::: ::: RESULTS ::: All the reconstructive penis survived, and patients could void in a standing position finally at a median follow-up of 25.4 ± 6.0 months. Urethral fistula and urethral stricture rates were 31.8 % (7/22 patients) and 4.5 % (1/22 patients), respectively. The occurrence of the urethral stricture was remarkably low compared with previous reports. Our histological results also showed a pronounced similarity between vaginal and buccal mucosa. Morphologically, they resembled urethral epithelium more closely than the forearm skin. Following the free transfer, the vaginal mucosal graft also showed a good revascularization and the inflammatory reaction and the extent of fibrosis of the mucosa decreased to the normal level after a 6-month prefabrication. ::: ::: ::: CONCLUSION ::: With prefabrication of vaginal mucosal graft, we reconstruct a competent phallic neourethra in these FTM transsexuals. According to its histological similarities and source character, the vaginal mucosa is the excellent substitute material for promising urethral reconstruction in FTM transsexuals.


title: A CMOS Transceiver for a Multistandard 13.56-MHz RFID Reader SoC

abstract: A CMOS transceiver for a multistandard 13.56-MHz radio-frequency identification reader system-on-a-chip (SoC) is designed and fabricated. The SoC consists of an RF/analog part for modulation/demodulation and a digital part for controlling the transceiver functionality. Prior to designing the integrated circuit, pre-experiments using discrete components and commercial tags are performed. With the results, overall functions and specifications are determined. For supporting multistandard, several blocks are designed with digital controls according to the standards. In the transmitter, a digitally controlled amplitude modulator for various modulation indexes and a power control circuit are adopted. In the receiver, a variable gain amplifier and a level-controllable comparator, which are also controlled digitally according to the standard, are introduced. The full transceiver SoC is implemented in the Chartered 0.18-?m CMOS technology. The measurement results of the implemented chip indicate that the designed transceiver operates in a multistandard mode.


title: Electronic Control of a Motorcycle Suspension for Preload Self-Adjustment

abstract: This paper describes the application of electronics to the control of the rear suspension of a motorcycle. The aim of the system is to make the suspension work around its optimal operating point, so that the safety and comfort of the vehicle can be improved. In fact, variations of the load carried by the vehicle determine a change of the suspension spring compression that moves the operating point away from the optimal value. Spring compression can also be changed by varying the suspension preload. The electronic system described here reveals load changes and automatically adjusts the motorcycle suspension preload in order to compensate the load variation and keep the suspension to its optimal operating point. The system is based on a linear position sensor that monitors the actual stroke of the suspension and a microcontroller that executes the control algorithm and drives the preload actuator. Road tests carried out on a motor scooter equipped with the system show its correct functionality and demonstrate the achievement of a better operation of the suspension with simple hardware and cost affordable for the two-wheel market.


title: All-Copper Flip Chip Interconnects by Pressureless and Low Temperature Nanoparticle Sintering

abstract: Flip chip interconnects purely made out of Cu, so-called all-Cu interconnects, have the potential to overcome the present current capacity limit of state-of-the-art solder based interconnects, while meeting the demand for ever decreasing interconnect pitches. Parasitic effects in solder based interconnects, caused by interdiffusion of various metals, are mitigated in all-Cu interconnects. In this work, all-Cu interconnects were formed by the use of low temperature and pressureless sintering of Cu nanoparticles. Thereby, a Cu paste material was applied between the Cu pillars of a silicon chip and the Cu pads on a silicon substrate by a dip transfer method. The electrical and mechanical properties of sintered Cu were characterized on films of the same Cu pastes. The porous films resulted in 4.4 times higher electrical resistivity and one order of magnitude reduced mechanical stiffness and tensile strength compared to bulk Cu. All-Cu interconnects with a diameter of 30 µm and a pitch of 100 µm were formed with an optimized Cu particle distribution and sintering procedure. Resistances down to 1.7 ± 0.5 mO were measured for these all-Cu interconnects which is comparable to solder based benchmark interconnects. However, the porosity of the sintered Cu interconnect results in lower shear strength compared to the solder benchmark.


title: Integration of 2D CMUT arrays with front-end electronics for volumetric ultrasound imaging

abstract: For three-dimensional (3D) ultrasound imaging, connecting elements of a two-dimensional (2D) transducer array to the imaging system's front-end electronics is a challenge because of the large number of array elements and the small element size. To compactly connect the transducer array with electronics, we flip-chip bond a 2D 16 times 16-element capacitive micromachined ultrasonic transducer (CMUT) array to a custom-designed integrated circuit (IC). Through-wafer interconnects are used to connect the CMUT elements on the top side of the array with flip-chip bond pads on the back side. The IC provides a 25-V pulser and a transimpedance preamplifier to each element of the array. For each of three characterized devices, the element yield is excellent (99 to 100% of the elements are functional). Center frequencies range from 2.6 MHz to 5.1 MHz. For pulse-echo operation, the average -6-dB fractional bandwidth is as high as 125%. Transmit pressures normalized to the face of the transducer are as high as 339 kPa and input-referred receiver noise is typically 1.2 to 2.1 rnPa/ radicHz. The flip-chip bonded devices were used to acquire 3D synthetic aperture images of a wire-target phantom. Combining the transducer array and IC, as shown in this paper, allows for better utilization of large arrays, improves receive sensitivity, and may lead to new imaging techniques that depend on transducer arrays that are closely coupled to IC electronics.


title: Event Representations for Automated Story Generation with Deep Neural Nets

abstract: Automated story generation is the problem of automatically selecting a sequence of events, actions, or words that can be told as a story. We seek to develop a system that can generate stories by learning everything it needs to know from textual story corpora. To date, recurrent neural networks that learn language models at character, word, or sentence levels have had little success generating coherent stories. We explore the question of event representations that provide a mid-level of abstraction between words and sentences in order to retain the semantic information of the original data while minimizing event sparsity. We present a technique for preprocessing textual story data into event sequences. We then present a technique for automated story generation whereby we decompose the problem into the generation of successive events (event2event) and the generation of natural language sentences from events (event2sentence). We give empirical results comparing different event representations and their effects on event successor generation and the translation of events to natural language.


title: Disruption in the Inhibitory Architecture of the Cell Minicolumn: Implications for Autisim

abstract: The modular arrangement of the neocortex is based on the cell minicolumn: a self-contained ecosystem of neurons and their afferent, efferent, and interneuronal connections. The authors' preliminary studies indicate that minicolumns in the brains of autistic patients are narrower, with an altered internal organization. More specifically, their minicolumns reveal less peripheral neuropil space and increased spacing among their constituent cells. The peripheral neuropil space of the minicolumn is the conduit, among other things, for inhibitory local circuit projections. A defect in these GABAergic fibers may correlate with the increased prevalence of seizures among autistic patients. This article expands on our initial findings by arguing for the specificity of GABAergic inhibition in the neocortex as being focused around its mini- and macrocolumnar organization. The authors conclude that GABAergic interneurons are vital to proper minicolumnar differentiation and signal processing (e.g., filtering capacity of the neocortex), thus providing a putative correlate to autistic symptomatology.


title: The Demographics of Mail Search and their Application to Query Suggestion

abstract: Web mail search is an emerging topic, which has not been the object of as many studies as traditional Web search. In particular, little is known about the characteristics of mail searchers and of the queries they issue. We study here the characteristics of Web mail searchers, and explore how demographic signals such as location, age, gender, and inferred income, influence their search behavior. We try to understand for instance, whether women exhibit different mail search patterns than men, or whether senior people formulate more precise queries than younger people. We compare our results, obtained from the analysis of a Yahoo Web mail search query log, to similar work conducted in Web and Twitter search. In addition, we demonstrate the value of the user's personal query log, as well as of the global query log and of the demographic signals, in a key search task: dynamic query auto-completion. We discuss how going beyond users' personal query logs (their search history) significantly improves the quality of suggestions, in spite of the fact that a user's mailbox is perceived as being highly personal. In particular, we note the striking value of demographic features for queries relating to companies/organizations, thus verifying our assumption that query completion benefits from leveraging queries issued by ``people like me". We believe that demographics and other such global features can be leveraged in other mail applications, and hope that this work is a first step in this direction.


title: Incremental Division of Very Large Point Clouds for Scalable 3D Surface Reconstruction

abstract: The recent progress in Structure from Motion and Multi-View Stereo as well as the always rising number of high resolution images lead to ever larger 3D point clouds. Unfortunately, due to the large amount of memory and processing power needed, there are no suitable means for manipulating these massive amounts of data as a whole, such as fusion by 3D surface reconstruction methods. In this paper we, therefore, present an algorithm for division of very large 3D point clouds into smaller subsets allowing for a parallel 3D reconstruction of many suitably small parts. Within our space division algorithm, octrees are built representing the divided space. To limit the maximum size of the underlying data structure, we present an incremental extension of the algorithm which renders a division of billions of 3D points possible and speeds up the processing on multi-core systems. As the proposed space division does not guarantee a density-based decomposition, we show the limitations of kd-trees as an alternative data structure. Space division is especially important for volumetric 3D reconstruction, as the latter has a high memory requirement. To this end, we finally discuss the adaptability of the space division to existing surface reconstruction methods to achieve scalable 3D reconstruction and show examples on existing and novel datasets which demonstrate the potential of the incremental space division algorithm.


title: Entity-centric topic-oriented opinion summarization in twitter

abstract: Microblogging services, such as Twitter, have become popular channels for people to express their opinions towards a broad range of topics. Twitter generates a huge volume of instant messages (i.e. tweets) carrying users' sentiments and attitudes every minute, which both necessitates automatic opinion summarization and poses great challenges to the summarization system. In this paper, we study the problem of opinion summarization for entities, such as celebrities and brands, in Twitter. We propose an entity-centric topic-based opinion summarization framework, which aims to produce opinion summaries in accordance with topics and remarkably emphasizing the insight behind the opinions. To this end, we first mine topics from #hashtags, the human-annotated semantic tags in tweets. We integrate the #hashtags as weakly supervised information into topic modeling algorithms to obtain better interpretation and representation for calculating the similarity among them, and adopt Affinity Propagation algorithm to group #hashtags into coherent topics. Subsequently, we use templates generalized from paraphrasing to identify tweets with deep insights, which reveal reasons, express demands or reflect viewpoints. Afterwards, we develop a target (i.e. entity) dependent sentiment classification approach to identifying the opinion towards a given target (i.e. entity) of tweets. Finally, the opinion summary is generated through integrating information from dimensions of topic, opinion and insight, as well as other factors (e.g. topic relevancy, redundancy and language styles) in an unified optimization framework. We conduct extensive experiments on a real-life data set to evaluate the performance of individual opinion summarization modules as well as the quality of the produced summary. The promising experiment results show the effectiveness of the proposed framework and algorithms.


Female-biased Parental Investment and Growth Performance among the Mukogodo


title: SLS at SemEval-2016 Task 3: Neural-based Approaches for Ranking in Community Question Answering

abstract: Community question answering platforms need to automatically rank answers and questions with respect to a given question. In this paper, we present the approaches for the Answer Selection and Question Retrieval tasks of SemEval-2016 (task 3). We develop a bag-of-vectors approach with various vectorand text-based features, and different neural network approaches including CNNs and LSTMs to capture the semantic similarity between questions and answers for ranking purpose. Our evaluation demonstrates that our approaches significantly outperform the baselines.


title: Agglomerative Information Bottleneck

abstract: We introduce a novel distributional clustering algorithm that maximizes the mutual information per cluster between data and given categories. This algorithm can be considered as a bottom up hard version of the recently introduced "Information Bottleneck Method". The algorithm is compared with the top-down soft version of the information bottleneck method and a relationship between the hard and soft results is established. We demonstrate the algorithm on the 20 Newsgroups data set. For a subset of two news-groups we achieve compression by 3 orders of magnitudes loosing only 10% of the original mutual information.


title: Why Amazon Chose TLA +

abstract: Since 2011, engineers at Amazon have been using TLA+ to help solve difficult design problems in critical systems. This paper describes the reasons why we chose TLA+ instead of other methods, and areas in which we would welcome further progress.


title: 3D trajectory recovery for tracking multiple objects and trajectory guided recognition of actions

abstract: A mechanism is proposed that integrates low-level (image processing), mid-level (recursive 3D trajectory estimation), and high level (action recognition) processes. It is assumed that the system observes multiple moving objects via a single, uncalibrated video camera. A novel extended Kalman filter formulation is used in estimating the relative 3D motion trajectories up to a scale factor. The recursive estimation process provides a prediction and error measure that is exploited in higher-level stages of action recognition. Conversely, higher-level mechanisms provide feedback that allows the system to reliable segment and maintain the tracking of moving objects before, during, and after occlusion. The 3D trajectory, occlusion, and segmentation information are utilized in extracting stabilized views of the moving object. Trajectory-guided recognition (TGR) is proposed as a new and efficient method for adaptive classification of action. The TGR approach is demonstrated using "motion history images" that are then recognized via a mixture of Gaussian classifier. The system was tested in recognizing various dynamic human outdoor activities; e.g., running, walking, roller blading, and cycling. Experiments with synthetic data sets are used to evaluate stability of the trajectory estimator with respect to noise.


title: Applicability of one-stage partial nitritation and anammox in MBBR for anaerobically pre-treated municipal wastewater

abstract: Energy consumption of municipal wastewater treatment plants can be reduced by the anaerobic pre-treatment of the main wastewater stream. After this pre-treatment, nitrogen can potentially be removed by partial nitritation and anammox (PN/A). Currently, the application of PN/A is limited to nitrogen-rich streams (>500 mg L(-1)) and temperatures 25-35 °C. But, anaerobically pretreated municipal wastewater is characterized by much lower nitrogen concentrations (20-100 mg L(-1)) and lower temperatures (10-25 °C). We operated PN/A under similar conditions: total ammonium nitrogen concentration 50 mg L(-1) and lab temperature (22 °C). PN/A was operated for 342 days in a 4 L moving bed biofilm reactor (MBBR). At 0.4 mg O2 L(-1), nitrogen removal rate 33 g N m(-3) day(-1) and 80 % total nitrogen removal efficiency was achieved. The capacity of the reactor was limited by low AOB activity. We observed significant anammox activity (40 g N m(-3) day(-1)) even at 12 °C, improving the applicability of PN/A for municipal wastewater treatment.


title: Dealing with time-series data in Predictive Maintenance problems

abstract: In this paper an approach to deal with Predictive Maintenance (PdM) problems with time-series data is discussed. PdM is a important approach to tackle maintenance and it is gaining an increasing attention in advanced manufacturing to minimize scrap materials, downtime, and associated costs. PdM approaches are generally based on Machine Learning tools that require the availability of historical process and maintenance data. Given the exponential growth in data logging in modern equipment, time series dataset are increasingly available in PdM applications. To exploit time series data for PdM, a functional learning methodology, namely Supervised Aggregative Feature Extraction (SAFE), is here employed on a semiconductor manufacturing maintenance problem.


title: Satellite Image Segmentation and Classification

abstract: Keywords: classification ; feature extraction ; LTS5 ; satellite Reference EPFL-STUDENT-87073 Record created on 2006-06-14, modified on 2017-05-10


title: A Rapid Pattern-Recognition Method for Driving Types Using Clustering-Based Support Vector Machines

abstract: A rapid pattern-recognition approach to characterize driver's curve-negotiating behavior is proposed. To shorten the recognition time and improve the recognition of driving styles, a k-means clustering-based support vector machine (kMC-SVM) method is developed and used for classifying drivers into two types: aggressive and moderate. First, vehicle speed and throttle opening are treated as the feature parameters to reflect the driving styles. Second, to discriminate driver curve-negotiating behaviors and reduce the number of support vectors, the k-means clustering method is used to extract and gather the two types of driving data and shorten the recognition time. Then, based on the clustering results, a support vector machine approach is utilized to generate the hyperplane for judging and predicting to which types the human driver are subject. Lastly, to verify the validity of the kMC-SVM method, a cross-validation experiment is designed and conducted. The research results show that the kMC-SVM is an effective method to classify driving styles with a short time, compared with SVM method.


title: Geometric Data Analysis Based on Manifold Learning with Applications for Image Understanding

abstract: Nowadays, pattern recognition, computer vision, signal processing and medical image analysis, require the managing of large amount of multidimensional image databases, possibly sampled from nonlinear manifolds. The complex tasks involved in the analysis of such massive data lead to a strong demand for nonlinear methods for dimensionality reduction to achieve efficient representation for information extraction. In this avenue, manifold learning has been applied to embed nonlinear image data in lower dimensional spaces for subsequent analysis. The result allows a geometric interpretation of image spaces with relevant consequences for data topology, computation of image similarity, discriminant analysis/classification tasks and, more recently, for deep learning issues. In this paper, we firstly review Riemannian manifolds that compose the mathematical background in this field. Such background offers the support to set up a data model that embeds usual linear subspace learning and discriminant analysis results in local structures built from samples drawn from some unknown distribution. Afterwards, we discuss topological issues in data preparation for manifold learning algorithms as well as the determination of manifold dimension. Then, we survey dimensionality reduction techniques with particular attention to Riemannian manifold learning. Besides, we discuss the application of concepts in discrete and polyhedral geometry for synthesis and data clustering over the recovered Riemannian manifold with emphasis in face images in the computational experiments. Next, we discuss promising perspectives of manifold learning and related topics for image analysis, classification and relationships with deep learning methods. Specifically, we discuss the application of foliation theory, discriminant analysis and kernel methods in curved spaces. Besides, we take differential geometry in manifolds as a paradigm to discuss deep generative models and metric learning algorithms.


title: Spotting Fake News: A Social Argumentation Framework for Scrutinizing Alternative Facts

abstract: The proliferation of fake news in today's digital world has moved beyond a specific election cycle and now commands headlines globally. In this paper, we propose countering the spread of fake news on social networks by leveraging these crowds to instead help verify alternative facts. We present a prototype social argumentation framework to verify the validity of proposed alternative facts to help curb the propagation of fake news. We utilize fundamental argumentation ideas in a graph-theoretic framework that also incorporates semantic web and linked data principles. The argumentation structure is crowdsourced and mediated by expert moderators in a virtual community.


title: TBD: Benchmarking and Analyzing Deep Neural Network Training

abstract: The recent popularity of deep neural networks (DNNs) has generated a lot of research interest in performing DNN-related computation efficiently. However, the primary focus is usually very narrow and limited to (i) inference -- i.e. how to efficiently execute already trained models and (ii) image classification networks as the primary benchmark for evaluation. Our primary goal in this work is to break this myopic view by (i) proposing a new benchmark for DNN training, called TBD (TBD is short for Training Benchmark for DNNs), that uses a representative set of DNN models that cover a wide range of machine learning applications: image classification, machine translation, speech recognition, object detection, adversarial networks, reinforcement learning, and (ii) by performing an extensive performance analysis of training these different applications on three major deep learning frameworks (TensorFlow, MXNet, CNTK) across different hardware configurations (single-GPU, multi-GPU, and multi-machine). TBD currently covers six major application domains and eight different state-of-the-art models. We present a new toolchain for performance analysis for these models that combines the targeted usage of existing performance analysis tools, careful selection of new and existing metrics and methodologies to analyze the results, and utilization of domain specific characteristics of DNN training. We also build a new set of tools for memory profiling in all three major frameworks; much needed tools that can finally shed some light on precisely how much memory is consumed by different data structures (weights, activations, gradients, workspace) in DNN training. By using our tools and methodologies, we make several important observations and recommendations on where the future research and optimization of DNN training should be focused.


title: A 0.15 V Input Energy Harvesting Charge Pump With Dynamic Body Biasing and Adaptive Dead-Time for Efficiency Improvement

abstract: A charge pump using 0.13- $\mu$ m CMOS process for low-voltage energy harvesting is presented. A low-power adaptive dead-time (AD) circuit is used which automatically optimizes the dead-time according to the input voltage. A negative charge pump is also utilized for high efficiency at low input voltages $(V_{IN})$ . The AD circuit improves efficiency by 17% at $V_{IN}$ of 0.2 V compared to the fixed dead time circuit as well as enables the charge pump to work at $V_{IN}$ down to 0.15 V. Dynamic body bias (DBB) and switch-conductance enhancement techniques are applied to a unit stage of the three-stage charge pump. The reverse current flowing through the cross-coupled NMOS switches is prevented and the current transfer is also maximized. Together with the AD circuit and the DBB technique, the maximum output current was improved by 240% as compared to the conventional charge pump design using only the forward body bias.


title: Reporting Experiments in Software Engineering

abstract: Background: One major problem for integrating study results into a common body of knowledge is the heterogeneity of reporting styles: (1) It is difficult to locate relevant information and (2) important information is often missing. Objective: A checklist for reporting results from controlled experiments is expected to support a systematic, standardized presentation of empirical research, thus improving reporting in order to support readers in (1) finding the information they are looking for, (2) understanding how an experiment is conducted, and (3) assessing the validity of its results. Method: The checklist for reporting is based on (1) a survey of the most prominent published proposals for reporting guidelines in software engineering and (2) an iterative development incorporating feedback from members of the research community. Result: This paper presents a unification of a set of guidelines for reporting experiments in software engineering. Limitation: The checklist has not been evaluated broadly, yet. Conclusion: The resulting checklist provides detailed guidance on the expected content of the sections and subsections for reporting a specific type of empirical studies, i.e., experiments (controlled experiments and quasi-experiments).


title: MISO: Mutual Information Loss with Stochastic Style Representations for Multimodal Image-to-Image Translation

abstract: Unpaired multimodal image-to-image translation is a task of translating a given image in a source domain into diverse images in the target domain, overcoming the limitation of one-to-one mapping. Existing multimodal translation models are mainly based on the disentangled representations with an image reconstruction loss. We propose two approaches to improve multimodal translation quality. First, we use a content representation from the source domain conditioned on a style representation from the target domain. Second, rather than using a typical image reconstruction loss, we design MILO (Mutual Information LOss), a new stochastically-defined loss function based on information theory. This loss function directly reflects the interpretation of latent variables as a random variable. We show that our proposed model Mutual Information with StOchastic Style Representation(MISO) achieves state-of-the-art performance through extensive experiments on various real-world datasets.


title: On Information Technology Competencies for Collaborative Organizational Structures

abstract: There is an uptake of organizations involvement in collaborative organizational structures (COS). As the nature and level of information technology (IT) investment in COS will be similar, the COS IT competencies will leverage the IT investments to create the collaborative rent generating potential of the COS, which would then improve the business value of the COS members. Consistent with the resource-centric views of the firm, we suggest that the COS members need to contribute their managed IT competencies to their COS, whose synergies would create COS IT competencies. We suggest three key IT competencies for COS; proactive top management decision synergy, collaborative and agile IT infrastructure, and cross-functional tactical management synergy. Using survey data, we find evidence of a positive association between these COS IT competencies and the collaborative rent generating potential of the COS. We also find a positive association between the collaborative rent generating potential of the COS and the business value of the COS members. The results suggest that developing COS IT competencies add value to a COS and its members. This study provides guidance for organizations looking to leverage their involvement in a COS.


title: A 2.45-GHz planar array antenna with harmonic suppression for wireless power transmission applications

abstract: A wireless power transmission array antenna with harmonic suppression, which eliminates the need for a harmonic filter circuit in the rectenna circuit, is designed. The second and third harmonics are suppressed to less than −10 dB using the stub on the antenna patch and the slot on the ground plane. The proposed antenna, which is compact, economical, and efficient, can be applied in 2.45-GHz rectenna and active integrated antenna applications.


Linking Collaboration Processes and Outcomes: Foundations for Advancing Empirical Theory


title: FutureRank: Ranking Scientific Articles by Predicting their Future PageRank

abstract: The dynamic nature of citation networks makes the task of ranking scientific articles hard. Citation networks are continually evolving because articles obtain new citations every day. For ranking scientific articles, we can define the popularity or prestige of a paper based on the number of past citations at the user query time; however, we argue that what is most useful is the expected future references. We define a new measure, FutureRank, which is the expected future PageRank score based on citations that will be obtained in the future. In addition to making use of the citation network, FutureRank uses the authorship network and the publication time of the article in order to predict future citations. Our experiments compare FutureRank with existing approaches, and show that FutureRank is accurate and useful for finding and ranking publications.


Extracting paraphrase patterns from bilingual parallel corpora


title: BodyAvatar: creating freeform 3D avatars using first-person body gestures

abstract: BodyAvatar is a Kinect-based interactive system that allows users without professional skills to create freeform 3D avatars using body gestures. Unlike existing gesture-based 3D modeling tools, BodyAvatar centers around a first-person "you're the avatar" metaphor, where the user treats their own body as a physical proxy of the virtual avatar. Based on an intuitive body-centric mapping, the user performs gestures to their own body as if wanting to modify it, which in turn results in corresponding modifications to the avatar. BodyAvatar provides an intuitive, immersive, and playful creation experience for the user. We present a formative study that leads to the design of BodyAvatar, the system's interactions and underlying algorithms, and results from initial user trials.


title: Planning with Abstract Markov Decision Processes

abstract: Robots acting in human-scale environments must plan under uncertainty in large state–action spaces and face constantly changing reward functions as requirements and goals change. Planning under uncertainty in large state–action spaces requires hierarchical abstraction for efficient computation. We introduce a new hierarchical planning framework called Abstract Markov Decision Processes (AMDPs) that can plan in a fraction of the time needed for complex decision making in ordinary MDPs. AMDPs provide abstract states, actions, and transition dynamics in multiple layers above a base-level “flat” MDP. AMDPs decompose problems into a series of subtasks with both local reward and local transition functions used to create policies for subtasks. The resulting hierarchical planning method is independently optimal at each level of abstraction, and is recursively optimal when the local reward and transition functions are correct. We present empirical results showing significantly improved planning speed, while maintaining solution quality, in the Taxi domain and in a mobile-manipulation robotics problem. Furthermore, our approach allows specification of a decision-making model for a mobile-manipulation problem on a Turtlebot, spanning from low-level control actions operating on continuous variables all the way up through high-level object manipulation tasks.


title: Purely functional lazy non-deterministic programming

abstract: Functional logic programming and probabilistic programming have demonstrated the broad benefits of combining laziness (non-strict evaluation with sharing of the results) with non-determinism. Yet these benefits are seldom enjoyed in functional programming, because the existing features for non-strictness, sharing, and non-determinism in functional languages are tricky to combine. We present a practical way to write purely functional lazy non-deterministic programs that are efficient and perspicuous. We achieve this goal by embedding the programs into existing languages (such as Haskell, SML, and OCaml) with high-quality implementations, by making choices lazily and representing data with non-deterministic components, by working with custom monadic data types and search strategies, and by providing equational laws for the programmer to reason about their code.


title: What is the role of protein aggregation in neurodegeneration?

abstract: Neurodegenerative diseases typically involve deposits of inclusion bodies that contain abnormal aggregated proteins. Therefore, it has been suggested that protein aggregation is pathogenic. However, several lines of evidence indicate that inclusion bodies are not the main cause of toxicity, and probably represent a cellular protective response. Aggregation is a complex multi-step process of protein conformational change and accretion. The early species in this process might be most toxic, perhaps through the exposure of buried moieties such as main chain NH and CO groups that could serve as hydrogen bond donors or acceptors in abnormal interactions with other cellular proteins. This model implies that the pathogenesis of diverse neurodegenerative diseases arises by common mechanisms, and might yield common therapeutic targets.


title: Demonstration of RF and Microwave Passive Circuits Through 3-D Printing and Selective Metalization

abstract: The ultimate goal of this paper is to print radio frequency (RF) and microwave structures using a 3-D platform and to pattern metal films on nonplanar structures. To overcome substrate losses, air core substrates that can readily be printed are utilized. To meet the challenge of patterning conductive layers on complex or nonplanar printed structures, two novel self-aligning patterning processes are demonstrated. One is a simple damascene-like process, and the other is a lift-off process using a 3-D printed lift-off mask layer. A range of microwave and RF circuits are designed and demonstrated between 1 and 8 GHz utilizing these processes. Designs are created and simulated using Keysight Advanced Design System and ANSYS High Frequency Structure Simulator. Circuit designs include a simple microstrip transmission line (T-line), coupled-line bandpass filter, circular ring resonator, T-line resonator, resonant cavity structure, and patch antenna. A commercially available 3-D printer and metal sputtering system are used to realize the designs. Both simulated and measured results of these structures are presented.


title: Extraction of Syntactic Translation Models from Parallel Data using Syntax from Source and Target Languages

abstract: We propose a generic rule induction framework that is informed by syntax from both sides of a parsed parallel corpus, as sets of structural, boundary and labeling related constraints. Factoring syntax in this manner empowers our framework to work with independent annotations coming from multiple resources and not necessarily a single syntactic structure. We then explore the issue of lexical coverage of translation models learned in different scenarios using syntax from one side vs. both sides. We specifically look at how the non-isomorphic nature of parse trees for the two languages affects coverage. We propose a novel technique for restructuring targetside parse trees, that generates alternate isomorphic target trees that preserve the syntactic boundaries of constituents that were aligned in the original parse trees. We also show that combining rules extracted by restructuring syntactic trees on both sides produces significantly better translation models. The improved precision and coverage of our syntax tables particularly fill in for the lack of lexical coverage in Syntax based Machine Translation approaches.


title: Continuous Delivery Practices in a Large Financial Organization

abstract: Continuous Delivery is an agile software development practice in which developers frequently integrate changes into the main development line and produce releases of their software. An automated Continuous Integration infrastructure builds and tests these changes. Claimed advantages of CD include early discovery of (integration) errors, reduced cycle time, and better adoption of coding standards and guidelines. This paper reports on a study in which we surveyed 152 developers of a large financial organization (ING Nederland), and investigated how they adopt a Continuous Integration and delivery pipeline during their development activities. In our study, we focus on topics related to managing technical debt, as well as test automation practices. The survey results shed light on the adoption of some agile methods in practice, and sometimes confirm, while in other cases, confute common wisdom and results obtained in other studies. For example, we found that refactoring tends to be performed together with other development activities, technical debt is almost always "self-admitted", developers timely document source code, and assure the quality of their product through extensive automated testing, with a third of respondents dedicating more than 50% of their time to do testing activities.


title: Better external memory suffix array construction

abstract: Suffix arrays are a simple and powerful data structure for text processing that can be used for full text indexes, data compression, and many other applications, in particular, in bioinformatics. However, so far, it has appeared prohibitive to build suffix arrays for huge inputs that do not fit into main memory. This paper presents design, analysis, implementation, and experimental evaluation of several new and improved algorithms for suffix array construction. The algorithms are asymptotically optimal in the worst case or on average. Our implementation can construct suffix arrays for inputs of up to 4-GB in hours on a low-cost machine. As a tool of possible independent interest, we present a systematic way to design, analyze, and implement pipelined algorithms.


title: Strategies of human mating

abstract: Modern humans have inherited the mating strategies that led to the success of their ancestors. These strategies include long-term mating, short-term mating, extra-pair mating, mate poaching, and mate guarding. This article presents empirical evidence supporting evolution-based hypotheses about the complexities of these mating strategies. Since men and women historically confronted different adaptive problems in the mating domain, the sexes differ profoundly in evolved strategic solutions. These differences include possessing different mate preferences, different desires for short-term mating, and differences in the triggers that evoke sexual jealousy. The study of human mating is one of the “success stories” of evolutionary psychology. Strategies of Human Mating No adaptive domain is more central to reproduction than mating. Those in our evolutionary past who failed to mate failed to become ancestors. Modern humans are all descendants of a long and unbroken line of ancestors who succeeded in the complex tasks involved required to mate successfully. As their descendants, modern humans have inherited the adaptations that led to the success of their ancestors. Successful mating requires solutions of a number of difficult adaptive problems. These including selecting a fertile mate, out-competing same-sex rivals in attracting a mate, fending off mate poachers (those who try to lure one’s mate away), preventing the mate from leaving, and engaging in all of the necessarily sexual and social behaviors required for successful conception to take place. As a consequence of the number and complexity of mating problems humans have recurrently faced over the long expanse of human evolutionary history, it is


title: Common-Duty-Ratio Control of Input-Parallel Output-Parallel (IPOP) Connected DC–DC Converter Modules With Automatic Sharing of Currents

abstract: Input-parallel output-parallel (IPOP) connected converter systems allow the use of low-power converter modules for high-power applications, with interleaving control scheme resulting in smaller filter size, better dynamic performance, and higher power density. In this paper, a new IPOP converter system is proposed, which consists of multiple dual-active half-bridge (DAHB) dc-dc converter modules. Moreover, by applying a common-duty-ratio control scheme, without a dedicated current-sharing controller, the automatic sharing of input currents or load currents is achieved in the IPOP converter even in the presence of substantial differences of 10% in various module parameters. The current-sharing performance of the proposed control method is analyzed using both a small-signal model and a steady-state dc model of the IPOP system. It is concluded that the equal sharing of currents among modules can be achieved by reducing the mismatches in various module parameters, which is achievable in practice. The current-sharing performance of the IPOP converter is also verified by Saber simulation and a 400-W experimental prototype consisting of two DAHB modules. The common-duty-ratio control method can be extended to any IPOP system that consists of three or more converter modules, including traditional dual-active bridge dc-dc converters, which have a characteristic of current source.


title: Design and implementation of an augmented reality system using gaze interaction

abstract: In this paper, we discuss an interactive optical see-through head-mounted device (HMD) which makes use of a user's gaze for an augmented reality (AR) interface. In particular, we propose a method to employ a user's half-blink information for more efficient interaction. Since the interaction is achieved using a user's gaze and half-blinks, the proposed system can create a more efficient computing environment. In addition, the proposed system can be quite helpful to those who have difficulties in using their hands for conventional interaction methods. The experimental results present the robustness and efficiency of the proposed system.


title: Malignant tumours of the foot and ankle

abstract: Most of tumours of the foot are tumour-like (synovial cyst, foreign body reactions and epidermal inclusion cyst) or benign conditions (tenosynovial giant cells tumours, planta fibromatosis). Malign...


title: Doctors’ attitudes and beliefs regarding acute low back pain management: A systematic review

abstract: The aim of this systematic review was to determine the attitudes and beliefs of doctors to acute low back pain, and the factors that influence these. The review comprised three phases: a methodological assessment of databases (Medline, EMBASE, Psychinfo, BIOSIS, CINAHL, and the Cochrane Central Register of Controlled Trials) identified potential papers; these were screened for inclusion criteria by two independent reviewers, the extraction of data and the rating of internal validity and strength of the evidence, using valid and reliable scales from accepted papers. Themes were then identified from the accepted literature. The search generated a total of 15 papers of both qualitative (n = 3) and quantitative (n = 12) methodologies. Themes that emerged included doctors’ attitudes and beliefs, and four factors that influenced attitudes and beliefs: doctors’ specialty, demographic factors, personal beliefs and education. There was consistent evidence that doctors’ specialty impacted their attitudes and beliefs: lack of consensus regarding the natural history of LBP, around treatment options, and issues regarding work. There was inconsistent evidence that demographic factors (age) and level of education impacted doctors’ attitudes and beliefs. Strategies to address/ modify these attitudes and beliefs are required, as in some cases they are at odds with guideline recommendations. Long term, these changes in these areas have the potential to maximise patient-care, and reduce costs to health services. 2008 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.


title: Android Cache Taxonomy and Forensic Process

abstract: Android is one of the most popular and widely used mobile operating systems and one of the most actively researched products in the field of mobile forensics. However, analysis of Android caches has been, to date, an understudied research topic, which limits its potential use in forensic investigations. Due to the diversity of cache formats on Android, we propose a cache taxonomy based on app usage. Using this taxonomy as a base, a systematic process, known as the Android Cache Forensic Process, is proposed to forensically classify, extract and analyze Android caches. Various cache formats utilized by 11 popular Android apps are analyzed. As part of this analysis, a number of cache formats are decoded and several cache formats commonly used by Android apps are documented from a forensic perspective. Based on our technical findings, an Android Cache Viewer prototype was also developed. This prototype is able to decode a number of Android cache formats and display the contents in an accessible manner.


title: Alan Turing and the Mathematical Objection

abstract: This paper concerns Alan Turing's ideas about machines, mathematical methods of proof, and intelligence. By the late 1930s, Kurt Godel and other logicians, including Turing himself, had shown that no finite set of rules could be used to generate all true mathematical statements. Yet according to Turing, there was no upper bound to the number of mathematical truths provable by intelligent human beings, for they could invent new rules and methods of proof. So, the output of a human mathematician, for Turing, was not a computable sequence (i.e., one that could be generated by a Turing machine). Since computers only contained a finite number of instructions (or programs), one might argue, they could not reproduce human intelligence. Turing called this the ``mathematical objection'' to his view that machines can think. Logico-mathematical reasons, stemming from his own work, helped to convince Turing that it should be possible to reproduce human intelligence, and eventually compete with it, by developing the appropriate kind of digital computer. He felt it should be possible to program a computer so that it could learn or discover new rules, overcoming the limitations imposed by the incompleteness and undecidability results in the same way that human mathematicians presumably do.


title: Using Smart Homes to Detect and Analyze Health Events

abstract: Smart homes offer an unprecedented opportunity to unobtrusively monitor human behavior in everyday environments and to determine whether relationships exist between behavior and health changes. Behavior change detection (BCD) can be used to identify changes that accompany health events, which can potentially save lives.


title: Independent domination in graphs: A survey and recent results

abstract: Abstract A set S of vertices in a graph G is an independent dominating set of G if S is an independent set and every vertex not in S is adjacent to a vertex in S . In this paper, we offer a survey of selected recent results on independent domination in graphs.


title: Bayesian Depth-from-Defocus with Shading Constraints

abstract: We present a method that enhances the performance of depth-from-defocus (DFD) through the use of shading information. DFD suffers from important limitations—namely coarse shape reconstruction and poor accuracy on textureless surfaces—that can be overcome with the help of shading. We integrate both forms of data within a Bayesian framework that capitalizes on their relative strengths. Shading data, however, is challenging to accurately recover from surfaces that contain texture. To address this issue, we propose an iterative technique that utilizes depth information to improve shading estimation, which in turn is used to elevate depth estimation in the presence of textures. The shading estimation can be performed in general scenes with unknown illumination using an approximate estimate of scene lighting. With this approach, we demonstrate improvements over existing DFD techniques, as well as effective shape reconstruction of textureless surfaces.


Fracture Mechanics Analysis of Cracked Plate Repaired by Composite Patch


title: Sensitivity analysis and explanations for robust query evaluation in probabilistic databases

abstract: Probabilistic database systems have successfully established themselves as a tool for managing uncertain data. However, much of the research in this area has focused on efficient query evaluation and has largely ignored two key issues that commonly arise in uncertain data management: First, how to provide explanations for query results, e.g., Why is this tuple in my result? or Why does this output tuple have such high probability?. Second, the problem of determining the sensitive input tuples for the given query, e.g., users are interested to know the input tuples that can substantially alter the output, when their probabilities are modified (since they may be unsure about the input probability values). Existing systems provide the lineage/provenance of each of the output tuples in addition to the output probabilities, which is a boolean formula indicating the dependence of the output tuple on the input tuples. However, lineage does not immediately provide a quantitative relationship and it is not informative when we have multiple output tuples. In this paper, we propose a unified framework that can handle both the issues mentioned above to facilitate robust query processing. We formally define the notions of influence and explanations and provide algorithms to determine the top-l influential set of variables and the top-l set of explanations for a variety of queries, including conjunctive queries, probabilistic threshold queries, top-k queries and aggregation queries. Further, our framework naturally enables highly efficient incremental evaluation when input probabilities are modified (e.g., if uncertainty is resolved). Our preliminary experimental results demonstrate the benefits of our framework for performing robust query processing over probabilistic databases.


title: CSLabel: An Approach for Labelling Mobile App Reviews

abstract: Mobile apps (applications) have become a popular form of software, and the app reviews by users have become an important feedback resource. Users may raise some issues in their reviews when they use apps, such as a functional bug, a network lag, or a request for a feature. Understanding these issues can help developers to focus on users’ concerns, and help users to evaluate similar apps for download or purchase. However, we do not know which types of issues are raised in a review. Moreover, the amount of user reviews is huge and the nature of the reviews’ text is unstructured and informal. In this paper, we analyze 3 902 user reviews from 11 mobile apps in a Chinese app store — 360 Mobile Assistant, and uncover 17 issue types. Then, we propose an approach CSLabel that can label user reviews based on the raised issue types. CSLabel uses a cost-sensitive learning method to mitigate the effects of the imbalanced data, and optimizes the setting of the support vector machine (SVM) classifier’s kernel function. Results show that CSLabel can correctly label reviews with the precision of 66.5%, the recall of 69.8%, and the F1 measure of 69.8%. In comparison with the state-of-the-art approach, CSLabel improves the precision by 14%, the recall by 30%, the F1 measure by 22%. Finally, we apply our approach to two real scenarios: 1) we provide an overview of 1 076 786 user reviews from 1 100 apps in the 360 Mobile Assistant and 2) we find that some issue types have a negative correlation with users’ evaluation of apps.


title: Computed tomography pulmonary angiography using high-pitch dual-source scanner technology

abstract: OBJECTIVES ::: To compare use of ultra-fast high-pitch dual-source free-breathing computed tomography pulmonary angiogram (CTPA) with conventional standard-pitch single-source breath-hold CTPA. Methods: This retrospective comparative study was conducted in Radiology Department at King Fahad Military Medical Complex Dhahran, Saudi Arabia from July 2016 to December 2017. Patients (N=130) were divided into 2 groups, each having 65 consecutive patients; Group-1 (single-source CT) and Group-2 (dual-source CT). Previously treated pulmonary embolism cases, pregnant patients and those with incomplete data were excluded. Image quality was subjectively assessed by 2 readers for adequacy of contrast opacification and pulmonary vessel outline, and presence of artifacts (breathing motion, cardiac pulsation, and contrast related). Scan acquisition times and radiation doses were also compared. Chi-square and t-test were used to determine association. Results: Improved image quality (optimal studies without artifacts 91%) was seen in Group-2 compared to Group-1 (optimal studies without artifacts 75.4%). Also, reduced scan time (1-2 sec.) and radiation dose (mean dose length product (DLP)-248 mGy-cm) were observed in Group-2 compared to Group-1 (scan time- 6.5 sec, mean DLP-375). Results were found significant (p less than 0.05). Conclusion: High-pitch dual-source CT with free-breathing yields better image quality, reduces image acquisition time and radiation doses.


title: Autoantibodies in inflammatory arthritis

abstract: Rheumatoid arthritis (RA) is a systemic chronic inflammatory disease characterized by extensive synovitis resulting in erosions of articular cartilage and marginal bone with joint destruction. The lack of immunological tolerance in RA represents the first step toward the development of autoimmunity. Susceptible individuals, under the influence of environmental factors, such as tobacco smoke, and silica exposure, develop autoimmune phenomena that result in the presence of autoantibodies. HLA and non-HLA haplotypes play a major role in determining the development of specific autoantibodies differentiating anti-citrullinated antibodies (ACPA)-positive and negative RA patients. Rheumatoid factor (RF) and ACPA are the serological markers for RA, and during the preclinical immunological phase, autoantibody titers increase with a progressive spread of ACPA antigens repertoire. The presence of ACPA represents an independent risk factor for developing RA in patients with undifferentiated arthritis or arthralgia. Moreover, anti-CarP antibodies have been identified in patients with RA as well as in individuals before the onset of clinical symptoms of RA. Several autoantibodies mainly targeting post-translational modified proteins have been investigated as possible biomarkers to improve the early diagnosis, prognosis and response to therapy in RA patients. Psoriatic arthritis (PsA) is distinguished from RA by infrequent positivity for RF and ACPA, together with other distinctive clinical features. Actually, specific autoantibodies have not been described. Recently, anti-CarP antibodies have been reported in sera from PsA patients with active disease. Further investigations on autoantibodies showing high specificity and sensibility as well as relevant correlation with disease severity, progression, and response to therapy are awaited in inflammatory arthritides.


title: A Planar Reconfigurable Aperture With Lens and Reflectarray Modes of Operation

abstract: This paper presents the design and experimental characterization of a planar 6 × 6 fully reconfigurable array operating at 5.7 GHz, capable of functioning both as a reconfigurable array lens and a reconfigurable reflectarray. First, the design of the array element, which consists of two varactor diode-loaded patches coupled by a varactor diode-loaded slot, is reviewed. Next, the design and fabrication of a planar array is described, and the varactor biasing scheme is discussed in detail. Experimental results demonstrating 2-D beamforming are presented, where a broadside directivity of 20.8 dBi and a beam-scanning range of 50° by 50° is achieved for the lens mode. The ability of the array to also function as a reflectarray is also demonstrated, achieving a directivity of 19.4 dBi at broadside and a beam-scanning range of 60° by 30°. Not only is this array able to demonstrate full 2-D beamforming, it is also low-cost and easy to fabricate, making it very attractive for applications where high-gain beam-scanning is needed.


title: Heart failure patients with a lower educational level and better cognitive status benefit most from a self-management group programme

abstract: Objective: The Chronic Disease Self-Management Programme (CDSMP)was recently evaluated among patients with congestive heart failure (CHF) in a randomized controlled trial (n = 317) with twelve months of follow-up after the start of the programme. That trial demonstrated short-term improvements in cardiac-specific quality of life. The current study assessed which of the patients participating in this trial benefited most from the CDSMP with respect to cardiac-specific quality of life. Methods: Subgroup analyses were conducted using mixed-effects linear regression models to assess the relationship between patient characteristics and the effects of the CDSMP on cardiac-specific quality of life. Results: In the short term, patients with better cognitive status benefited more from the CDSMP than their poorer functioning counterparts. In addition, lower educated patients benefited more from the CDSMP than their higher educated counterparts during total follow-up. Conclusion: Subgroup effects were found for cognitive status and educational level. Future research should be performed to validate current findings and further explore the conditions under which CHF patients may benefit more from the programme. Practice implications: These results indicate that lower educated patients, in particular, should be encouraged to participate in the CDSMP. In addition, healthcare practitioners are recommended to take into account potential cognitive impairments of patients.