Miracle-dz/UniFAR-FTUs huggingface dataset:
A Reflexive and Automated Approach to Syntactic Pattern Matching in Code Transformations

Empowering software engineers often requires to let them write code transformations. However existing automated or tool-supported approaches force developers to have a detailed knowledge of the internal representation of the underlying tool. While this knowledge is time consuming to master, the syntax of the language, on the other hand, is already well known to developers and can serve as a strong foundation for pattern matching. Pattern languages with metavariables (that is variables holding abstract syntax subtrees once the pattern has been matched) have been used to help programmers define program transformations at the language syntax level. The question raised is then the engineering cost of metavariable support. Our contribution is to show that, with a GLR parser, such patterns with metavariables can be supported by using a form of runtime reflexivity on the parser internal structures. This approach allows one to directly implement such patterns on any parser generated by a parser generation framework, without asking the pattern writer to learn the AST structure and node types. As a use case for that approach we describe the implementation built on top of the SmaCC (Smalltalk Compiler Compiler) GLR parser generator framework. This approach has been used in production for source code transformations on a large scale. We will express perspectives to adapt this approach to other types of parsing technologies.
Biologi og idræt - et funktionelt kompetenceudviklende tværfagligt samarbejde?

I naturfagssamarbejdet om faelles faglige fokusomrader er der biologifaglige indholdsomrader der er vanskelige at integrere i samarbejdet med de to andre naturfag i overbygningen. I naervaerende artikel beskrives hvordan disse omrader i tvaerfagligt samarbejde med idraet kan daekkes ind og vaere med til at udvikle bade elevernes naturfaglige og idraetsfaglige kompetencer. Igennem to projektperioder arbejdede elever fra fire folkeskoler tvaerfagligt og undersogelsesbaseret med faellesfaglige problemstillinger for biologi og idraet. Ved hjaelp af observationer og interviews blev det belyst hvilke fordele der var i forhold til elevernes kompetenceudvikling i de to fag, og ligeledes hvilke udfordringer der er ved at arbejde undersogelsesbaseret og tvaerfagligt i de to fag.
Minimization of Circularly Polarized Patch Antenna Using Metasurface

A low-profile, broadband, circularly polarized (CP) patch antenna is presented. It consists of a driven patch using a loop feeding structure with the purpose of producing the CP radiation. The driven patch is surrounded by eight parasitic patches to broadening the antenna bandwidth. A metasurface, which is a periodic array composed of 10 × 10 square metallic plates, is inserted into between the patches and the ground plane in order to minimize the antenna size. The optimized antenna, with dimensions of 100 mm × 100 mm × 4 mm (0.7λo × 0.7λo × 0.028λo at 2.1 GHz) achieves an impedance matching bandwidth of 27.3% (1.9 – 2.5 GHz), a CP radiation bandwidth of 11.76% (2.00 – 2.27 GHz), the peak gain of 6.9 dBic, and a radiation efficiency of 76%.
Design and Application of Erbium-Doped Photonic Crystal Fiber for Superfluorescent Fiber Source

A kind of erbium-doped photonic crystal fiber (EDPCF) designed for superfluorescent fiber source is reported. The proposed EDPCF is composed of an erbium-doped core and a cladding with seven rings of air holes arranged in a circular structure. The full-vector finite-element model of the EDPCF has been established and the relevant characteristics have been demonstrated via simulations. Using anisotropic perfectly matched layer as an absorbing boundary condition, the confinement loss 5.27×10−12dB/m has been calculated, which is far below the level of 0.01dB/km. Furthermore, the splice losses between the EDPCF and the two types step-index fibers have been estimated and it implies that the design fulfills low splice loss conditions theoretically. The designed EDPCF had been fabricated successfully. The experiment had been carried out to evaluate the splice losses between the EDPCF and the common single mode fibers. It is turned out that using manual aligning mode of the fiber fusion splicer can obtain lower splice loss than using automatic aligning mode for PCF splice. The EDPCF has already been applied in the superfluorescent light source as the gain medium.
An Approach for Image Encryption / Decryption Based on Quaternion Fourier Transform

The image encryption or the secure image pro-cessing is an art of handling the image to provide protection from those image information theft or damage. It is necessary to maintain security for images such as medical, military, etc. So far many research work have been developed in the field of image information security and prevention. However the achieved level of security is not satisfactory, thus still this field is in research to find a better solution for the image data security and prevention. In this sense, this research is targeted to develop a better strategy for the image data prevention and security enhancement. There are many cryptography technique is available in the technical world, however this work adapted quaternion based approach for the image data security. Qua-ternion is a kind of number notation, it is the combination of both scalar and vector. Quaternion rotation is the concept applied in the image encryption for the security purpose. In the existing works authors have applied the Quaternion rotation based encryption of medical image and color images. In order to further enhance the performance of encryption, in this work the Quaternion Fourier Transform is applied. The Fourier transform based Quaternion rotation improves the performance in both security and computation. The proposed system is implemented using the working platform of MATLAB, and the performance is compared with the conventional quaternion technique. The proposed system provided better performance based on the comparative analysis with respect to correlation coefficient, avalanche effect, computational speed, normalized correlation and histogram.
Generation of Non-Minimum Phase Response of Electromagnetic Systems Using Amplitude only Data

The objective of this paper is to illustrate how to generate the nonminimum phase response of an electromagnetic system from amplitude only data. It is important to note that the phase reconstruction from amplitude only data yields a nonunique solution as a linear phase term can be added to the system response without distorting its amplitude response since the linear phase term only adds a delay.
Whole-Body Electromyostimulation Improves Performance-Related Parameters in Runners

The aim of this study was to study the effects of a 6-session (one per week) WB-EMS training intervention on maximum oxygen uptake, aerobic and gas exchange thresholds, running economy, and muscular power in male recreational runners. Twelve men were randomized into WB-EMS intervention (n = 6; 27.0 ± 7.5 years; 70.1 ± 11.1 kg; 1.75 ± 0.5 m) or control (n = 6; 27.0 ± 6.1 years; 73.6 ± 3.4 kg; 1.77 ± 0.3 m). The WB-EMS group reduced the running training frequency to one per week and followed one WB-EMS training session per week during 6 weeks. Participants in the control group maintained their usual running endurance training. Each participant completed four assessments: physiological parameters [(i) VO2max, aerobic and gas exchange threshold values, and (ii) running economy at two intensities], muscular power (vertical jump), and anthropometric parameters both at baseline and after the intervention. Participants in the WB-EMS group improved VO2max, aerobic and gas exchange threshold values, running economy, and vertical jump (p < 0.05) compared to the control group. There, WB-EMS seems to be an effective training methodology leading to improvements in performance during endurance training volume reduction in male recreational runners.
On the Residual of Mirror Descent Search and Scalability via Dimensionality Reduction

In the the specific class of black-box optimization algorithms to find the optimal probabilistic distribution of some expected utility in reinforcement learning, higher dimensional decision variables cause the increase of cost and the slowing down of the learning speed. We clarified that the variance of the sampling probability distribution affects both for the cost and the learning speed. Especially, there exists the trade-0ff between the cost and the learning speed. In this paper, we propose two trick to improve both of the learning speed and the cost. First trick is to employ the small variance sampling distribution for improving the cost; it causes slower convergence as a side effect. As the second trick, we employed the dimensionality reduction of the decision variable for improving the learning speed. We evaluated the effects of these tricks with 2D-arm reaching task.
AIDGenS: An Automatic Image Description System Using Residual Neural Network

Visually impaired people can't see the world through their eyes. The description of photos is an interesting thing to help visually impaired people to understand their surroundings. AIDGenS is an automatic image description system for visually impaired people. This system contains two components: I2T system and T2S system. I2T is an image to text translation framework, and other is text to speech converter. I2T is implemented using the residual neural network and bidirectional LSTM. T2S is implemented using pyttsx package. The I2T system is evaluated on standard benchmark dataset Flickr8k using BLEU and ROUGE scores. AIDGenS is an efficient system for visually struggling people.
Real-Time Ear Detection Based On Embedded Systems

Ear detection is the first step of ear recognition. This paper proposes a real-time ear detection system based on embedded systems. An improved YOLO network is proposed for ear detection. With the same network depth, the width of the improved yolov2-tiny network in YOLO has been reduced to a quarter of the conventional network. By introducing batch processing and reducing the regularization coefficient of the improved yolov2-tiny network, the detection accuracy has been improved and the detection time has been reduced. The proposed model is more applicable for embedded implementation. On Nvidia Jetson tx2 real-time detection of the ear has been realized. The image is captured by an external camera and the ear will be marked when the ear appears in the image. On Nvidia Jetson tx2, the real-time detection frame rate is 30 frames per second which can meet the real-application requirements.
DeFatigue: Online Non-Intrusive Fatigue Detection by a Robot Co-Worker

A robot as a companion or co-worker is not an emerging concept anymore, but a reality. However, one of the major barriers to this realization is the seamless interaction with the robots that includes both explicit and implicit interaction. In this work, we assume a use-case where a human and a robot together carry a heavy object in a co-habitat (home or workplace/factory). Two human beings while doing such a work understands each other without explicit (vocal) interaction. To realize such behavior, the robot must understand the fatigue state of the human co-worker to enable seamless work experience and ensure safety. In this article, we present DeFatigue, a non-intrusive fatigue state detection mechanism. We assume that the robot's hand is equipped with a force sensor. Based on the change of force from the human side while carrying the object, DeFatigue is able to determine the fatigue state without instrumenting the human being with an additional sensor (internally or externally). Moreover, it detects the fatigues state on-the-fly (online) as well as it does not require any (user-specific) training. Based on our experiments with 18 test subjects, fatigue state detection by DeFatigue overlaps with the ground truth for 85.18% of the cases whereas it deviates 4.09 s (on average) for the remaining cases.
Design of High Efficiency Broadband Continuous Class-F Power Amplifier Using Real Frequency Technique With Finite Transmission Zero

In this paper, a new methodology using a distributed ladder structure with finite transmission zero at finite frequencies is proposed for designing a broadband high-efficiency continuous Class-F (CCF) power amplifier (PA). The approach of realizing finite transmission zeros in Richard domain using Real Frequency Technique is first presented. By applying the proposed approach, the characteristics of the driving point impedance (DPI) of the proposed structure can be deduced and obtained in theory. Furthermore, the synthesis methods in Richard domain are extended to synthesize the DPI of the proposed structure. Four types of distributed elements are investigated to synthesize the DPI of the proposed structure. This proposed structure can improve the performance of the CCF PA when the bandwidth approaches an octave as the finite transmission zero can be used to control the second harmonic impedance of the lower frequency which is near the upper frequency of the operation band. To verify the validity of the proposed method, a broadband high-efficiency CCF PA working from 1.15 to 2.2 GHz is designed. Experimental results show that the fabricated PA achieves 11.3–13.7 dB power gain and 40.5–43.2 dBm output power in the operation band. And the PA has also achieved a high-efficiency characteristic of 70%–83% drain efficiency (DE) over the whole operation bandwidth.
Quantification of DNA double‐strand breaks using Geant4‐DNA

Purpose This study aims to standardize the simulation procedure in measuring DNA double‐strand breaks (DSBs), by using advanced Monte Carlo toolkits, and newly introduced experimental methods for DNA DSB measurement. Methods For the experimental quantification of DNA DSB, an innovative DNA dosimeter was used to produce experimental data. GATE in combination with Geant4‐DNA toolkit were exploited to simulate the experimental environment. The PDB4DNA example of Geant4‐DNA was upgraded and investigated. Parameters of the simulation such energy threshold (ET) for a strand break and base pair threshold (BPT) for a DSB were evaluated, depending on the dose. Results Simulations resulted to minimum differentiation in comparison to experimental data for ET = 19 ± 1 eV and BPT = 10 bp, and high differentiation for ET<17.5 eV or ET>22.5 eV and BPT = 10 bp. There was also small differentiation for ET = 17.5 eV and BPT = 6 bp. Uncertainty has been kept lower than 3%. Conclusions This study includes first results on the quantification of DNA double‐strand breaks. The energy spectrum of a LINAC was simulated and used for the first time to irradiate DNA molecules. Simulation outcome was validated on experimental data that were produced by a prototype DNA dosimeter.
A Study of Interdependence of Patron's Characteristics and IRCTC E-Surfing Through Chi-Square Test Analysis

IRCTC is a common platform to book tickets and other commodities for travelling through Indian railways. Numbers of tickets are booked each day through the IRCTC portal by person with different characteristics. This study brings out the interdependence of patron's unique characteristics like age, gender, education level, family income and his/her frequency of visit at the portal. The chi-square test is performed for the 155 analyzed users to validate the null and valid hypotheses. The responses of the users were collected through 5 pointer questionnaires in form of online Google docs. Finally, age and education qualification of the user were verified to be the key demographic factor to influence the frequency of visit.
An Interpretable Generative Model for Handwritten Digit Image Synthesis

An interpretable generative model for handwritten digits synthesis is proposed in this work. Modern image generative models, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), are trained by backpropagation (BP). The training process is complex and the underlying mechanism is difficult to explain. We propose an interpretable multi-stage PCA method to achieve the same goal and use handwritten digit images synthesis as an illustrative example. First, we derive principal-component-analysis-based (PCA-based) transform kernels at each stage based on the covariance of its inputs. This results in a sequence of transforms that convert input images of correlated pixels to spectral vectors of uncorrelated components. In other words, it is a whitening process. Then, we can synthesize an image based on random vectors and multi-stage transform kernels through a coloring process. The generative model is a feedforward (FF) design since no BP is used in model parameter determination. Its design complexity is significantly lower, and the whole design process is explainable. Finally, we design an FF generative model using the MNIST dataset, compare synthesis results with those obtained by state-of-the-art GAN and VAE methods, and show that the proposed generative model achieves comparable performance.
Analytical Framework of Hybrid Beamforming in Multi-Cell Millimeter-Wave Systems

Multi-cell wireless systems usually encounter both intra-cell and inter-cell interference, which can be mitigated via coordinated multipoint (CoMP) transmission. Previous works on multi-cell analysis in the microwave band generally consider fully digital beamforming, requiring a complete radio-frequency chain behind each antenna. This is practically infeasible for millimeter-wave (mmWave) systems where large amounts of antennas are necessary to provide sufficient gain and to enable transmission/reception of multiple streams to/from a user. This paper provides a general methodology to analytically compute the expected per-cell spectral efficiency of an mmWave multi-cell single-stream system using phase-shifter-based analog beamforming and regularized zero-forcing digital beamforming. Four analog–digital hybrid beamforming techniques for multi-cell multi-stream mmWave communication are proposed, assuming that base stations in different cells can share channel state information to cooperatively transmit signals to their home-cell users. Spectral efficiency of the proposed hybrid beamforming approaches is investigated and compared using two channel models suitable for fifth-generation cellular systems, namely the 3rd Generation Partnership Project model and the NYUSIM model. Numerical results show that the benefits of base station coordination (as compared with the non-CoMP case) are governed by the underlying propagation model, and the aggregate interference levels proportional to the cell radius and number of users per cell. We show that in sparse channels, non-CoMP approaches exceed CoMP (coordinated beamforming) performance.
Exploring the effects of cosolutes and crowding on the volumetric and kinetic profile of the conformational dynamics of a poly dA loop DNA hairpin: a single-molecule FRET study

Abstract We investigated the volumetric and kinetic profile of the conformational landscape of a poly dA loop DNA hairpin (Hp) in the presence of salts, osmolytes and crowding media, mimicking the intracellular milieu, using single-molecule FRET methodology. Pressure modulation was applied to explore the volumetric and hydrational characteristics of the free-energy landscape of the DNA Hp, but also because pressure is a stress factor many organisms have to cope with, e.g. in the deep sea where pressures even up to the kbar level are encountered. Urea and pressure synergistically destabilize the closed conformation of the DNA Hp due to a lower molar partial volume in the unfolded state. Conversely, multivalent salts, trimethylamine-N-oxide and Ficoll strongly populate the closed state and counteract deteriorating effects of pressure. Complementary smFRET measurements under immobilized conditions at ambient pressure allowed us to dissect the equilibrium data in terms of folding and unfolding rate constants of the conformational transitions, leading to a deeper understanding of the stabilization mechanisms of the cosolutes. Our results show that the free-energy landscape of the DNA Hp is a rugged one, which is markedly affected by the ionic strength of the solution, by preferential interaction and exclusion of cosolvents as well as by pressure.
Analysis of Different IoT Protocols for Heterogeneous Devices and Cloud Platform

Till today researchers and innovative developing corporations are putting a continuous effort to bring IoT into day to day life. As for defining protocols there is no common agreement over a unified IoT architecture and standards. Internet as the backbone of the communication, Internet of Things is establishing a smart interaction between people and surrounding objects. In the field of application domains cloud plays a crucial component of IoT by providing valuable application specific services for leveraging specific and suitable IoT based services nowadays the market has a no. of emerging IoT cloud providers. The currently used framework by cloud IoT platforms do not fulfill IoT technologies requirements. Existing technologies are being employed by the developers to build IoT meanwhile to optimize communications in IoT, researchers are working on adapting existing protocols. In this paper we present an overview and comprehensive research over cloud platforms as well as protocols required to connect end-user applications to things and internet. We have proposed a cloud framework for heterogeneous protocol and support. We have also discussed about the suitability of proposed framework for IoT by considering the qualitative parameters like reliability, security and energy consumption.
Research on Community Detection Algorithm for Complex Networks with Multi-Attribute Nodes

The study of complex network has attracted more and more attention from researchers, and community detection has gradually become one of the most significant directions. The majority of existing community detection algorithms regard the connections between nodes as single relationship, which are not fully satisfied with the practical needs. This paper described complex networks with multi-attribute nodes and proposed a community detection algorithm (CDMAN). The algorithm represented a node's information in real world as a set of node's attributes in networks, then the properties and structural similarity of nodes were employed to take further partition. Experimental results on real datasets demonstrate that the algorithm (CDMAN) outperforms the traditional structure algorithm (LPA) and is proved to be more feasible and promising.
Interactive mapping of nonindigenous species in the Laurentian Great Lakes

Nonindigenous species pose significant risks to the health and integrity of ecosystems around the world. Tracking and communicating the spread of these species has been of interest to ecologists and environmental managers for many years, particularly in the bi-national Laurentian Great Lakes of North America. In this paper, we introduce the Great Lakes Aquatic Nonindigenous Species Information System (GLANSIS) Map Explorer. The Map Explorer provides access to records of documented nonindigenous species and their spatial distributions. Users may view the distributions of well-known nonindigenous species (such as zebra mussels) as well as perform custom queries. Additional map layers allow users to compare the distribution of nonindigenous species to environmental conditions. This tool serves to communicate knowledge to diverse stakeholder groups and to enable further in-depth research on nonindigenous species.