Miracle-dz/UniFAR-FTUs huggingface dataset:
Generation of In-Bounds Inputs for Arrays in Memory-Unsafe Languages

This paper presents a technique to generate in-bounds inputs for arrays used in memory-unsafe programming languages, such as C and C++. We show that most memory indexation found in actual C programs follows patterns that are easy to analyze statically. Based on this observation, we show how symbolic range analysis can be used to establish contracts between the arguments of a function and the arrays used within that function. To demonstrate the effectiveness of our ideas, we use them to implement Griffin-TG, a tool to stress-test C programs whose source code might be partially available. We show how Griffin-TG improves Aprof, a well-known algorithmic profiling tool, and we show how it lets us enrich PolyBench with a large set of new inputs.
A Double-Layer Highly Efficient and Wideband Transmitarray Antenna

A double-layer highly efficient and wideband transmitarray antenna is presented. The transmitarray element is composed of four metal vias and two crosspatches with two stubs. The metal vias penetrate the entire substrate and arrange symmetrically. The crosspatches are printed on both sides of the dielectric substrate. The metal vias are introduced to enhance the coupling strength. The stubs are added to ensure a sufficient phase shift range. The achievable transmission magnitude is greater than −2 dB, and the phase shift range exceeds 360° within the whole band. A transmitarray antenna using the proposed element was designed, manufactured, and measured. The simulation and measurement results are in good agreement. The measured maximum gain is 29.2 dBi at 18 GHz with the 51.4% aperture efficiency. The experimental results show that the proposed antenna has a 1-dB gain bandwidth of 9% (17.2–18.8 GHz). The proposed double-layer transmittarray antenna realizes the low-profile characteristic, simplifies the design complexity, and solves the problems of the mass and the cost.
Metasurface Synthesis With Arbitrary Incident Angles Using Planar Electric Impedance Surfaces

Metasurfaces are devices to manipulate electromagnetic wave propagations. Conventionally, nonplanar structures, e.g., metallic loops, are used to fabricate metasurfaces, which is complicated at high frequency regimes. In this paper, we propose a metasurface synthesis method using only planar electric impedance surfaces, which are not only easy to fabricate even at very high frequencies, but also have big freedom to control electromagnetic wave propagations. Without loss of generality, the proposed method has taken into account the tensor form of the constituent planar electric surface impedance, as well as arbitrary incident angles. The proposed method is general so as to have a wide application scope. It has been validated by numerical simulations, and has been applied to design a reflectionless polarization converter working under oblique incidence as an application demonstration.
Design Analysis of Integrated Passive Device-Based Balun Devices With High Selectivity for Mobile Application

This paper presents highly selective, low-loss, and miniaturized balun devices fabricated using the integrated passive device (IPD) technique for the GSM band (900/1800 MHz) and the WiFi band (2400 MHz) in mobile applications. Balun devices were fabricated on a gallium arsenide (GaAs) substrate using the IPD fabrication process to reduce the overall size ( $0.05 \lambda _{\mathrm {g}} \times 0.036\lambda _{\mathrm {g}}$ at 900 MHz). Each device is the combination of lattice lumped structure with a low-pass filter and a high-pass filter configuration. This structural formation of lumped elements helps to reduce the phase mismatch error in the balun devices. For all the balun devices, the measured results indicated a minimum amplitude imbalance (<0.47 dB) and low phase imbalance (180 ± 2.6°). Mathematically calculated, calculated after considering parasitic effects, simulated and measured results exhibited a good correlation. The return loss is below 18 dB and insertion loss is below 0.25 dB for the entire fabricated devices. A balun device with a center frequency of 900 MHz has given the best results amongst all fabricated devices.
Generating Photographic Faces From the Sketch Guided by Attribute Using GAN

From a sketch image or text description, generating a semantic and photographic face image has always been an extremely important issue in computer vision. Sketch images generally contain only simple profile information but not the detail of the face. Therefore, it is difficult to generate facial attributes accurately. In this paper, we treat the sketch to face the problem as a face hallucination reconstruction problem. In order to solve this problem, we propose an image translation network by exploiting attributes with the generated adversarial network. And it can significantly contribute to the authenticity of the generated face by supplementing sketch image with the additional facial attribute feature. The generator network is composed of a feature extracting network and downsampling–upsampling network, both networks use skip-connection to reduce the number of layers without affecting network performance. The discriminator network is designed to examine whether the generated faces contain the desired attributes or not. In the underlying feature extraction phase, our network is different from most attribute-embedded networks, we fuse the sketch images and attributes perceptually. We set the network sub-Branch A and B, which receive a sketch image and attribute vector in order to extract low-level profile information and high-level semantic features. Compared with the state-of-the-art methods of image translation, the performance of the proposed network is excellent.
Yb-Doped Aluminophosphosilicate Triple-Clad Laser Fiber With High Efficiency and Excellent Laser Stability

We fully demonstrated an ytterbium (Yb) doped triple-clad laser fiber with intense pump absorption, high efficiency, and laser stability. P<sup>5+</sup>/Al<sup>3+</sup> molar ratio in the central region of fiber core was specially designed to be ∼1.08 for compensating P<sub>2</sub>O<sub>5</sub> evaporation, while the ratio in the outer region was set as ∼0.92 for obtaining a flattened refractive index profile. Applying a two-stage deposition process, one-time collapse technique, low-temperature multi-times sintering, and suitable flow of pure POCl<sub>3</sub> during sintering and collapsing process were instrumental in decreasing and offsetting element evaporation. Measured in an all-fiber master oscillator power amplifier configuration, the 7-m-long fiber obtained 1.39 kW near-single-mode laser output at 1079.6 nm with a slope efficiency of 85.2% and a beam quality <italic>M</italic><sup>2</sup> of 1.36. Output laser spectrum with no sign of nonlinear-related peaks and a narrow 3-dB-bandwidth of ∼0.33 nm was obtained. The fiber-based laser setup was kept at the maximum power for 1 h with power degradation less than 0.21%. The results demonstrated Yb-doped aluminophosphosilicate triple-clad fiber is a highly competitive candidate for commercial high-power laser and high-power narrow-linewidth fiber laser.
Joint Event Extraction Based on Hierarchical Event Schemas From FrameNet

Event extraction is useful for many practical applications, such as news summarization and information retrieval. However, the popular automatic context extraction (ACE) event extraction program only defines very limited and coarse event schemas, which may not be suitable for practical applications. FrameNet is a linguistic corpus that defines complete semantic frames and frame-to-frame relations. As frames in FrameNet share highly similar structures with event schemas in ACE and many frames actually express events, we propose to redefine the event schemas based on FrameNet. Specifically, we extract frames expressing event information from FrameNet and leverage the frame-to-frame relations to build a hierarchy of event schemas that are more fine-grained and have much wider coverage than ACE. Based on the new event schemas, we propose a joint event extraction approach that leverages the hierarchical structure of event schemas and frame-to-frame relations in FrameNet. The extensive experiments have verified the advantages of our hierarchical event schemas and the effectiveness of our event extraction model. We further apply the results of our event extraction model on news summarization. The results show that the summarization approach based on our event extraction model achieves significant better performance than several state-of-the-art summarization approaches, which also demonstrates that the hierarchical event schemas and event extraction model are promising to be used in the practical applications.
A Novel Bidirectional Solid-State Circuit Breaker for DC Microgrid

DC microgrid has attracted more and more attention due to its unique characteristics, but the development of a dc microgrid is also facing some challenges, such as interruption and isolation of short-circuit fault currents. Therefore, the dc circuit breaker plays an important role in ensuring the normal work of a dc microgrid. In this paper, a novel bidirectional dc solid-state circuit breaker is proposed to realize the bidirectional flow of energy, which ensures the higher operating efficiency of the dc microgrid. Compared with other solid-state circuit breakers, the proposed novel topology has simpler structure, common ground, and fewer components. First, this paper makes a detailed analysis of the different working stages of the circuit when the fault occurs in combination with simulation results of the circuit topology. Then, the standard of selecting the components through the calculation and analysis of the circuit is given in this paper. Finally, the performance of the novel bidirectional solid-state circuit breaker is verified by experiments.
Face Depth Estimation With Conditional Generative Adversarial Networks

Depth map estimation and 3-D reconstruction from a single or a few face images is an important research field in computer vision. Many approaches have been proposed and developed over the last decade. However, issues like robustness are still to be resolved through additional research. With the advent of the GPU computational methods, convolutional neural networks are being applied to many computer vision problems. Later, conditional generative adversarial networks (CGAN) have attracted attention for its easy adaptation for many picture-to-picture problems. CGANs have been applied for a wide variety of tasks, such as background masking, segmentation, medical image processing, and superresolution. In this work, we developed a GAN-based method for depth map estimation from any given single face image. Many variants of GANs have been tested for the depth estimation task for this work. We conclude that conditional Wasserstein GAN structure offers the most robust approach. We have also compared the method with other two state-of-the-art methods based on deep learning and traditional approaches and experimentally shown that the proposed method offers great opportunities for estimation of face depth maps from face images.
Ultrawideband (UWB) Technology For Smart Cities IoT Applications

Ultrawideband (UWB) technology provides relatively high throughput at short distances by utilizing low-power pulse transmission as a coexisting radio service in the C/X-band portion of the electromagnetic spectrum. This paper aims at validating the suitability of UWB technology for emerging Internet of Things (IoT) applications. The expectation in the industry is that e-health applications that entail Body Area Networks, Smart City applications dealing with autonomous vehicles and precise location, Positive Train Control in the context of rail transportation, and other near field communications will become prevalent in the near future. This review article provides a description of UWB technology in the IoT environment, as well assessing its technical limitations.
Arbitrary Power-Division Branch-Line Hybrids for High-Performance, Wideband, and Selective Harmonic Suppressions From  $2f_{0}$

A branch-line hybrid (BH) topology is suggested, consisting of four equal lengths of transmission-line sections (TLs) with two different characteristic impedances and four identical L-sections with each a TL and an open stub. The topology can provide three distinct properties; lower characteristic impedances of TLs, longer electrical paths for the scattering parameters, and additional transmission zeros, enabling high performance of harmonic suppressions from <inline-formula> <tex-math notation="LaTeX">$2f_{0}$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$f_{0}$ </tex-math></inline-formula> is a design frequency, wideband and selective harmonic suppressions. A compact equivalent circuit of a TL is suggested for harmonic suppression BH which can be applied for all possible power-division ratios. As a proof-of-concept demonstration, two prototypes for the power-division ratios of 0 and 6 dB are tested and measured. The measured frequency responses are in a good agreement with the predicted ones, given fabrication errors.
A Family of Blocked Proportionate Hybrid Error Criterion Algorithms

A family of blocked proportionate normalized least mean mixed-norm (BPNLMMN) algorithms using hybrid error criterion are devised and investigated for estimating block-sparse channels that are always considered in networks and satellite echo channels. The derived BPNLMMN algorithms are realized by considering two different errors in the least mean algorithm and incorporating hybrid-norm constraints into the constructed cost function to fully use the prior cluster-sparse information in the systems to be estimated. We carefully derive the BPNLMMN algorithms and provide a completed analysis of the BPNLMMN algorithms for cluster channel estimations. The obtained results from various simulations illustrate that the BPNLMMN algorithms provide superior performance under various inputs and perform better than existing least mean mixed-norm algorithms.
A survey on graduates’ curriculum-based knowledge gaps in software testing

This research full paper presents a study on graduates’ knowledge gaps in software testing according to industry needs. Several studies indicate that students graduate from computing programs with a knowledge gap in software testing. In this sense, we aimed to investigate in details this broader testing gap, by considering gaps in the level of testing topics. We conducted a survey with Brazilian practitioners in order to collect data (N=90). For each testing topic, knowledge gaps were calculated as the difference between what respondents’ learned/practiced in undergraduate courses and what they actually applied in industry after graduating. Results provide evidence on points that could be improved in software testing education. Firstly, for all testing topics there was a negative gap on practice activities. This means that students could benefit from more testing assignments throughout the curriculum. Regarding gaps in concepts, some testing topics presented negative gaps (such as test in web applications) and others positive (such as test in aspect oriented software and mutation analysis). Therefore, results suggest that it is possible to counterbalance them in order to reduce the existing gaps. We also present respondents’ opinions about their experience in software testing education and industry practices.
Compensation of Environmental Influences on Sensorized-Forceps for Practical Surgical Tasks

For more secure and delicate robotic surgery, force sensing ability is essential but it has still not been used in actual robot surgery. This is because the environmental factors that occur during actual operation affect the sensor and the sensor cannot give reliable force information. In this letter, we aim to develop reliable sensorized-forceps that can be used in practical surgical tasks by compensating environmental influences. The environmental factors affecting the sensor were analyzed. Humidity, temperature, and high voltage were considered as main factors. At first, to compensate the humidity influences, the humidity sensing capability was integrated in the sensorized-forceps and humidity compensation algorithm is applied. Second, to eliminate the temperature-sensitive element, ac shield is applied to the signal processing board. Finally, for cutting off electric conduction, entire surface of forceps is covered by an oxide layer. To verify the proposed solutions, revised sensorized-forceps are installed in surgical robot platform and ex vivo experiments with electro-cautery task were conducted.
Identification of a Novel Pool of Extracellular Pro-myostatin in Skeletal Muscle*

Myostatin, a transforming growth factor-β superfamily ligand, negatively regulates skeletal muscle growth. Generation of the mature signaling peptide requires cleavage of pro-myostatin by a proprotein convertase, which is thought to occur constitutively in the Golgi apparatus. In serum, mature myostatin is found in an inactive, non-covalent complex with its prodomain. We find that in skeletal muscle, unlike serum, myostatin is present extracellularly as uncleaved pro-myostatin. In cultured cells, co-expression of pro-myostatin and latent transforming growth factor-β-binding protein-3 (LTBP-3) sequesters pro-myostatin in the extracellular matrix, and secreted pro-myostatin can be cleaved extracellularly by the proprotein convertase furin. Co-expression of LTBP-3 with myostatin reduces phosphorylation of Smad2, and ectopic expression of LTBP-3 in mature mouse skeletal muscle increases fiber area, consistent with reduction of myostatin activity. We propose that extracellular pro-myostatin constitutes the major pool of latent myostatin in muscle. Post-secretion activation of this pool by furin family proprotein convertases may therefore represent a major control point for activation of myostatin in skeletal muscle.
Quarter-Wave Balun Fed Vivaldi Antenna Pair for V2X Communication Measurement

A dual-polarized Vivaldi antenna pair has been designed for use in a vehicle-to-anything (V2X) measurement facility. The operating bandwidth is from 560 MHz to 7.7 GHz (173% fractional bandwidth), covering all the existing V2X communication frequencies. The ultrawideband (UWB) property was achieved by integrating quarter-wave baluns at the feeding point of two orthogonally crossed Vivaldi antennas. The measured port isolation between the two antennas is better than −28 dB. The cross-polarization discrimination of better than 17.2 dB and antenna gain of up to 9.2 dB have also been realized across the whole bandwidth. Three of the designed antennas were mounted on a vehicle testing facility and were used to measure the radiation patterns of a roof-top shark antenna under four different V2X scenarios. That is, vehicle-to-pedestrian, vehicle-to-vehicle, and vehicle-to-infrastructure and vehicle-to-network. The results have also been presented in this communication.
A Versatile Triangular Patch Array for Wideband Frequency Alteration With Concurrent Circular Polarization and Pattern Reconfigurability

This paper focuses on the design with experimental verification of a circular polarization (CP) and pattern reconfigurable triangular patch array simultaneously operating at various tunable frequencies. The resonant frequency of the antenna can be altered from 1.97 to 2.54 GHz (25.3% tunable bandwidth) by varying the capacitance values from 4.27 to 1.15 pF of the six varactors fixed between the annular slots on the three triangular patches. A wideband phase shifting network with switching capability is also designed which facilitates the antenna to operate it in both types of CP and pattern reconfigurable modes at each frequency. The antenna is tested in receiving mode and it shows a maximum realized gain of 3.1 dBc when operated in any of the CP mode and 1.45 dB for pattern reconfigurability mode. It has a very wideband axial ratio (AR) value (<3 dB) at each reconfigured frequency and also covers the entire frequency agility bandwidth. Investigation confirms that the antenna produces circularly polarized radiation pattern with minimum AR beamwidth of 24° at all frequency bands for both types of CP radiation. It is also observed that the antenna pattern can be rotated at 120° angle in the complete azimuth plane with a wide 3 dB beamwidth of ±45° at its operating frequencies. The multifaceted reconfiguring ability of the antenna enables it to serve many futuristic communication system requirements such as supporting multiple radios and maintaining signal quality in diverse climatic conditions.
Optimal Trajectory Planning of a Six DOF Parallel Stewart Manipulator

this article introduces a nonlinear dynamic optimization procedure for trajectory planning of a spatial parallel Stewart-Gough manipulator. The planning process is composed of minimizing the energy consumption of actuators and accuracy error in end-effector positioning subject to the kinematic and dynamic constraints. A numerical solving procedure based on finite element method is being used as the optimization tool. The dynamics of this manipulator are obtained by virtue of Lagrange’s method and results has been obtained by developing a program in MATLAB software to simulate Stewart-Gough manipulator and design an optimal path using collocation method.
A Design of Bandwidth-Enhanced Cavity-Backed Slot Filtenna Using Resonance Windows

A class of bandwidth-enhanced full-metal cavity-backed slot filtenna is proposed in this communication. The design is constructed by three resonators. They are two resonance windows and one resonance cavity. As a consequence of that, three resonance modes are achieved using a single cavity. By using this resonance window, the 10 dB frequency bandwidth of the proposed cavity antenna has wide fractional bandwidth (FBW) of 20%. To the authors’ best knowledge, the proposed filtenna achieves the widest FBW among those published full-metal cavity-backed slot filtennas. Moreover, a fifth-order filtenna is also designed to further broaden the 10 dB FBW to 24%. Finally, an antenna prototype was fabricated and tested for experimental verification of the proposed design methodology. Good agreement between the measurement and simulation shows the feasibility of the proposed wideband full-metal filtenna using a resonance window approach.
Fully Automated Annotation With Noise-Masked Visual Markers for Deep-Learning-Based Object Detection

Automated factories use deep-learning-based vision systems to accurately detect various products. However, training such vision systems requires manual annotation of a significant amount of data to optimize the large number of parameters of the deep convolutional neural networks. Such manual annotation is very time-consuming and laborious. To reduce this burden, we propose a fully automated annotation approach without any manual intervention. To do this, we associate one visual marker with one object and capture them in the same image. However, if an image showing the marker is used for training, normally, the neural network learns the marker as a feature of the object. By hiding the marker with a noise mask, we succeeded in reducing this erroneous learning. Experiments verified the effectiveness of the proposed method in comparison with manual annotation, in terms of both the time needed to collect training data and the resulting detection accuracy of the vision system. The time required for data collection was reduced from 16.1 to 1.87 h. The accuracy of the vision system trained with the proposed method was 87.3%, which is higher than the accuracy of a vision system trained with the manual method.