Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Local Texture Features for Pedestrian Detection

Pedestrian detection is a hot issue in the field of computer vision and image processing in recent years. It has important application value in the domain of unmanned cars and driver assistance systems and so on, but there are existed many problems that need to be solved. In this paper, we present an improved texture feature MLBP (Mean of Local Binary Pattern) and the CMLBP (Color based on Mean of Local Binary Pattern) feature based on various color spaces. When the uniform LBP feature does not consider the influence of noise, the mutation of central pixel and neighborhood pixel is not taken into account and therefore the extraction processes of MLBP feature improve the calculation method of the uniform LBP, which makes the extracted feature more stable. The MLBP feature is extracted from gray images, yet color images transformed into gray images generally loss a great amount of information. In view of this point, we also propose the CMLBP feature based on multiple color spaces that is a more comprehensive description of the texture feature of images. In the INRIA pedestrian dataset, many experiments have been conducted with SVM and HIKSVM classifier, and the results manifest that the detection rates of MLBP and CMLBP are much better than the uniform LBP and the basic LBP. The combination of MLBP, CMLBP and other features has been applied to pedestrian detection, which also achieves good results.
TS-CNN: Text Steganalysis from Semantic Space Based on Convolutional Neural Network

Steganalysis has been an important research topic in cybersecurity that helps to identify covert attacks in public network. With the rapid development of natural language processing technology in the past two years, coverless steganography has been greatly developed. Previous text steganalysis methods have shown unsatisfactory results on this new steganography technique and remain an unsolved challenge. Different from all previous text steganalysis methods, in this paper, we propose a text steganalysis method(TS-CNN) based on semantic analysis, which uses convolutional neural network(CNN) to extract high-level semantic features of texts, and finds the subtle distribution differences in the semantic space before and after embedding the secret information. To train and test the proposed model, we collected and released a large text steganalysis(CT-Steg) dataset, which contains a total number of 216,000 texts with various lengths and various embedding rates. Experimental results show that the proposed model can achieve nearly 100\% precision and recall, outperforms all the previous methods. Furthermore, the proposed model can even estimate the capacity of the hidden information inside. These results strongly support that using the subtle changes in the semantic space before and after embedding the secret information to conduct text steganalysis is feasible and effective.
Guanine Vesicle Hybrid Particles for Bio-Reflector-Based Bio-Imaging

The ability to visualize biological processes in real time rather than observing them at discrete points of time holds huge applicability in understanding the incredible processes of how the human body behaves during disease progression and healing. The prospects of live cell imaging include observing changes during cell differentiation, signaling, and molecular analysis of cell cycle including targeted drug delivery. Studying cells in real time assist in recording invaluable data whose knowledge holds great importance in understanding several aspects of cell functions at both microscopic and macroscopic levels. Cell labeling using photonic crystals for live cell imaging has never been tried before. Guanine crystals (GCs) are optical nanoparticles having fulgent light reflective properties that respond rapidly and align parallel to an applied magnetic field. Our target was to fabricate a brilliant “hybrid vesicle” using guanine inside lipid vesicles. Under dark field microscopy, GC shone brilliantly, causing strong illumination of the lipid vesicles with increased motion of vesicles under magnetic exposure. We think that “hybrid vesicle” could possibly be used for real-time cell tracking in live cell bio-imaging.
High Precise Estimation of Propagation Time and Reflection Phase Shift Based on Time-Frequency Analysis on Microwave Radar

On a nondestructive inspection using the microwave radar, there are so many researches aiming metallic buried objects. On the other hand, those aiming nonmetallic ones such as a resin are very few. In this research, we propose two kind of high precise estimation methods for microwave propagation time based on the time-frequency analysis focusing on a phase shift when microwaves are reflected on surface of buried objects. In addition, we analyze observed microwaves by using proposed methods and evaluate the effectiveness of them on a propagation time estimation process. As a result, we have achieved high precise propagation time estimation results in both cases of metallic and nonmetallic buried objects. However, we have confirmed that an advanced consideration on noise reduction is necessary for higher precision of a propagation time estimation.
Scalable Key Management for Elastic Security Domains in Fog Networks

Fog computing is a promising technology that ensures sharing resources and services in the neighborhood of a network while enhancing their secrecy and availability. Indeed, sharing through the cloud raises fears when it comes to share sensitive and private data. Many studies show that users, enterprises and stakeholders are more keen to share and collaborate if that sensitive data were managed locally at the edge of the network. Therefore, Fog computing comes to alleviate those fears and allow users to manage sensitive services at the edge of the network. However, since the fog is an extension of the cloud to the edge of the networks, it brings new challenges with respect to implementing security policies relating to shared data and services among multiple consumers, especially when those consumers are dynamic. In this paper, we propose a group key management scheme that allows to manage elastic security domains where dynamic consumers share sensitive services. The elasticity of the scheme supports dynamic adaptation of security domains' size through activating or deactivating proxy services at the fog gateways in order to minimize group key management overheads (1-affects-n and encryption key translation).
A Reduced Cost Wind Energy Conversion System Based on Permanent Magnet Synchronous Generator with a Parallel Connected AC-DC Buck-Boost Converter

This paper presents a variable speed Wind Energy Conversion System (WECS) using a back-to-back converter. The current drawn from the generator is sinusoidal with unity power factor where the introduced buck-boost converter is operating in the discontinuous conduction mode. A three-phase Permanent Magnet Synchronous Generator (PMSG) is connected to three parallel single phase ac-dc cascaded buck-boost converters, to minimize the voltage stress over the converter's switches. For optimal operation, Maximum Power Point Tracking (MPPT) is used to regulate the speed and currents of the PMSG by controlling the duty-ratio of the proposed ac-dc buck-boost converters. Moreover, a Low Voltage Ride-Through (LVRT) strategy is integrated with the proposed scheme. PSCAD/EMTDC simulation results are provided to assess the steady state and dynamic performance of the proposed WECS under different operating conditions.
Distributed Robust Resource Allocation with Convex-Concave Uncertain Objective Functions

This paper investigates the distributed robust resource allocation problem where the objective function is a convex-concave function with uncertain parameters. To guarantee the robustness, we investigate the worst-case scenario, which results in finding the saddle point of the objective function with the resource constraint satisfied. We deal with this problem by adopting a continuous-time distributed projected algorithm. A numerical example is presented to illustrate the effectiveness of the proposed algorithm.
Performance Evaluation of Scheduling Schemes for D2D Communications

We address the performance of a system where D2D communications add up to standard cellular traffic in future 5G networks. D2D resources are taken from the Uplink spectrum and, in this framework, two scheduling schemes are envisaged: the first one consists in two independent schedulers working on separate subsets of the Uplink channel, respectively dedicated to Uplink cellular communications and to D2D communications; the second one is a joint scheduler making use of the whole Uplink channel. In both schemes, all communications are scheduled, which in particular avoids the intra-cell interference issue. We propose multi-class Processor Sharing queueing models which account for realistic cellular radio conditions and provide traffic performance in terms of the average throughput for the different classes of flows. From the considered numerical scenarios, we conclude that the joint Uplink scheduling scheme provides better performance and allows D2D users to make an efficient use of their higher potential capacity, due to the device proximity. The corresponding throughput is also shown to be significantly higher than that perceived without any dedicated D2D link.
Loss Reduction Optimization for Heat Capacity Improvement in Interior Permanent Magnet Synchronous Machine

In this paper, the optimization for the reduction of copper loss, iron loss, and permanent magnet (PM) eddy current loss considering harmonics is carried out to improve thermal performance. The effect in terms of thermal performance is confirmed through thermal analysis using a lumped-parameter thermal network (LPTN). First, the optimal shape is determined using an automatic optimization method that combines the explorative particle swarm optimization algorithm and finite element analysis. Then, the iron loss and PM eddy current loss considering carrier harmonics are recalculated by inputting the actual pulsewidth modulation current. Finally, an LPTN-based thermal analysis is performed with the calculated loss as the input. In particular, the thermal parameter is confirmed through an experimental method to validate the accuracy of the thermal analysis. The advantages over the conventional motor are clarified.
JFML: A Java Library to Design Fuzzy Logic Systems According to the IEEE Std 1855-2016

Fuzzy logic systems are useful for solving problems in many application fields. However, these systems are usually stored in specific formats and researchers need to rewrite them to use in new problems. Recently, the IEEE Computational Intelligence Society has sponsored the publication of the IEEE Standard 1855-2016 to provide a unified and well-defined representation of fuzzy systems for problems of classification, regression, and control. The main aim of this standard is to facilitate the exchange of fuzzy systems across different programming systems in order to avoid the need to rewrite available pieces of code or to develop new software tools to replicate functionalities that are already provided by other software. In order to make the standard operative and useful for the research community, this paper presents JFML, an open source Java library that offers a complete implementation of the new IEEE standard and capability to import/export fuzzy systems in accordance with other standards and software. Moreover, the new library has associated a Website with complementary material, documentation, and examples in order to facilitate its use. In this paper, we present three case studies that illustrate the potential of JFML and the advantages of exchanging fuzzy systems among available software.
Magnon-Dragged Magnetoresistance and Spin Seebeck Effect in YIG/IrMn Thin Films

We report the magnon-dragged magnetoresistance and spin Seebeck effect simultaneously in lateral yttrium iron garnet (YIG)/Ir<sub>20</sub>Mn<sub>80</sub> thin films, which are detected as <inline-formula> <tex-math notation="LaTeX">$R_{{\text {drag}}}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$R_{{\text {SSE}}}$ </tex-math></inline-formula>, respectively, namely, the nonlocal inverse spin Hall voltages quantified by the injected current. According to their different dependences on applied current, <inline-formula> <tex-math notation="LaTeX">$R_{{\text {drag}}}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$R_{{\text {SSE}}}$ </tex-math></inline-formula> can be separated as the antisymmetric and symmetric part of the nonlocal signals. By a simple magnon diffusion model, the diffusion length of electrically generated magnons is calculated which is comparable to the values reported in YIG/Pt structures. The low magnetic field and the temperature dependences of <inline-formula> <tex-math notation="LaTeX">$R_{{\text {drag}}}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$R_{{\text {SSE}}}$ </tex-math></inline-formula> are found to be different, indicating that the origin and transport properties of magnons associated with these two effects are distinct.
Correlated System Noise Error Tracking Filter Design for a Sharply Maneuvering Ground Target

This paper is about the design of a correlated system noise error tracking filter for a sharply maneuvering off-road ground target. A high process noise Unscented Kalman Filter based two-model Interacting Multiple Model filter is designed to match the evasive target conditions. In addition to uncertainties in the system dynamics, the terrain profile is assumed to be part of the input noise to the system. The overall noises in position and velocity are taken to be correlated and assumed to be generated by a linear shaping filter. The Kalman filter for the discrete white noise acceleration model and the unscented Kalman filter for the highly nonlinear horizontal coordinated turn model with unknown turn rates are designed. The simulated results show good filter performance with low mean square errors of target position and velocity. The filter also shows good stability with nondivergent error dynamics. The computational challenge of the designed filter is observed at the maneuver entry and exit but despite severe target maneuvers, the filter is able to maintain its tracks.
A Text Mining Approach for Evaluating Event Credibility on Twitter

Users on social media platforms tend to readily believe the contents of posts related to the events. However, some of these events might be fake or incredible. The spread of such events takes the form of rumors that have the potential for affecting negatively the individuals and society. To this end, in this paper we develop a text mining approach for automatic evaluation of events on social networks. We consider Twitter as a case study. Given a set of popular Twitter events along with different credibility ratings assigned manually by human annotators (i.e., crowdsourcing), we study the problem of automatically assessing the credibility of such events. The conducted experiment in this paper using events extracted from the CREDBANK dataset; a corpus of tweets annotated with human credibility judgements shows that our approach is promising. It achieves an automatic credibility assessment of events of 82.86% with Decision Tree (DT) classifier.
A mixed-longitudinal study of children’s growth, motor development and cognition. Design, methods and baseline results on sex-differences

Abstract Background: There is a renewed interest in longitudinal studies which link children’s growth, motor and cognition development. This is important for both educational outcomes and identification of children who are at risk. Aim: To identify cross-sectional sex-differences. Subjects and methods: In total, 1166 Portuguese children, aged 4–11 years, were recruited into the Growth, Motor Development and Cognition Study (GMDC-Vouzela study). Measures included: anthropometry, gestational development, motor coordination, cognitive performance, laterality, physical fitness, metabolic syndrome risk, lifestyle characteristics and environmental exposures. Analysis of covariance was used to compare outcomes between boys and girls, adjusting for chronological age. Results: Most variables did not show significant differences between the sexes (p > 0.05). However, girls had more body fat mass than boys (p < 0.05) and boys were significantly heavier at birth (p < 0.05); furthermore, boys outperformed girls in a hopping high coordination test (p < 0.001) and were more physically fit (p < 0.05). Conclusions: Baseline results from the GMDC-Vouzela study indicate the dynamic relationships between children's biological and environmental characteristics. They also highlight lifestyle traits that will most likely effect subsequent growth, motor and cognitive development.
Empowering lower limbs exoskeletons: state-of-the-art

SUMMARY Given the advanced breakthroughs in the field of supportive robotic technologies, interest in the integration of the human body and a robot into a single system has rapidly increased. The aim of this work is to provide an overview of empowering lower limbs exoskeletons. Along with lower exoskeleton limbs, their unique design concepts, operator–exoskeleton interactions and control strategies are described. Although many problems have been solved in recent development, many challenges remain. Especially in the context of infantry soldiers, fire fighters and rescuers, the challenges of empowering exoskeletons are discussed, and improvements are outlined and described. This study is not only a summary of the current state, but also points to weaknesses of empowering lower limbs exoskeletons and outlines possible improvements.
Countertransference Management and Effective Psychotherapy: Meta-Analytic Findings

In this article, we review the history and definition of countertransference, as well as empirical research on countertransference, its management, and the relation of both with psychotherapy outcome. Three meta-analyses are presented, as well as studies that illustrate findings from the meta-analyses. The first meta-analysis indicated that countertransference reactions are related inversely and modestly to psychotherapy outcomes (r = −.16, p = .02, 95% CI [−.30, −.03], d = −0.33, k = 14 studies, N = 973). A second meta-analysis supported the notion that countertransference management factors attenuate countertransference reactions (r = −.27, p = .001, 95% CI [−.43, −.10], d = −0.55, k = 13 studies, N = 1,065). The final meta-analysis revealed that successful countertransference management is related to better therapy outcomes (r = .39, p < .001, 95% CI [.17, .60], d = 0.84, k = 9 studies, N = 392 participants). In all meta-analyses, there was significant heterogeneity across studies. We conclude by summarizing the limitations of the research base and highlighting the therapeutic practices predicated on research.
Fault Diagnosis of Bounded Petri Nets Using Path Marking Graphs

This paper proposes a fault diagnosis method based on the path information of a bounded Petri net model. It relies on the notions of two graphs called path marking graph and modified path marking graph, which characterize different sets of paths and markings consistent with an observed sequence, and a set of unobservable transitions whose firing will enable the sequence. The fault diagnosis method can be applied to a bounded Petri net model with unobservable and acyclic subnets. Moreover, the process of using these two particular graphs to calculate the possibilities of fault behaviors can be taken off-line, which is the most burdensome part for a bounded Petri net model, but also can reduce the memory cost. Finally, this method is verified through a production line example. The main contribution of this paper is to dig out the path information of a bounded Petri net, and to map it into different categories. By analyzing the inherent structure information of Petri net, the presented algorithm can diagnose faults without traversing all the system states.
Attitudes to ageing and their relationship with quality of life in older adults in Turkey

With the increase in life expectancy, it has become necessary to expand our knowledge of how older individuals perceive their own ageing and how ageing affects their quality of life. The aim of the study was to determine older adults’ attitudes towards ageing and the relationship between attitudes and quality of life among community‐dwelling older adults in Turkey.
A Novel Two-Element Linear Array for DSRC Band

This paper proposed the design of a novel microstrip patch antenna and a two element array. The proposed antenna is linearly polarized and is designed to operate in the Dedicated Short-Range Communications band (DSRC IEEE 802.11p) with the center frequency $(f_{r})$ of 5.9 GHz using Rogers RT 5880 lossy $(\epsilon_{r}=2.2)$ as substrate. The proposed antenna carries low profile, conformity and also exhibits better gain performance. The design is obtained by etching squares and rectangles on the patch symmetrically. The design of feed network for the two element array is obtained based on the implementation of the Wilkinson power divider. Single element antenna and the array maintains a gain of 7.15 dB and 9.61 dB respectively.
An Open-Label Study Evaluating the Performance of the Dose Indicator in a Metered Dose Inhaler Delivering Glycopyrrolate and Formoterol Fumarate in Patients with Moderate-to-Very Severe Chronic Obstructive Pulmonary Disease

Abstract Background: GFF MDI is a glycopyrrolate/formoterol fumarate fixed-dose combination metered dose inhaler formulated using co-suspension delivery technology. This open-label, single-arm multicenter study (NCT02268396) evaluated the accuracy, reliability, and functionality of the GFF MDI AeroCount® dose indicator when used by patients with chronic obstructive pulmonary disease (COPD). Patients and Methods: The study enrolled subjects (40–80 years of age) with an established clinical history (≥6 months) of COPD, who completed an electronic diary twice daily to record study-drug administration time, the number of actuations used, and pre- and post-dose dose indicator readings. The primary endpoint was the percentage of devices for which the number of subject-reported actuations was consistent (±20 actuations) with the dose indicator-based actuation count (equal to 130 minus the dose indicator reading) at the end of the treatment period (4 weeks). Safety was monitored throughout the study. Results: A total of 138 subjects with moderate-to-very severe COPD (50.7% male; mean [standard deviation (SD)] age 62.1 [8.3] years) were enrolled and treated. Subject-reported actuation count and dose indicator-based actuation counts were consistent for 96.4% (132/137) of devices at the end of the treatment period (4 weeks) in the intent-to-treat (ITT) population and for all devices in the per-protocol (PP) population. The mean (SD) dose indicator-based actuation and subject-reported actuation counts in the ITT population (n = 137) were 113.4 (18.9) and 117.0 (19.0), respectively, with a mean (SD) difference of 3.6 (7.9). The mean (SD) dose indicator-based actuation and subject-reported actuation counts in the PP population (n = 112) were 116.8 (8.7) and 119.7 (8.1), respectively. There were no unexpected safety findings. Conclusions: This study supported the accuracy, reliability, and utility of the dose indicator integrated into the GFF MDI device when used by patients with COPD.