Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining Fix Patterns with Context Information for Automatic Program Repair

Template-based automatic program repair (APR) using pre-defined fix patterns for generating patches is common in APR literature and is implemented in many APR tools. As the existing APR tools can fix only a limited number of bugs, automatic mining fix patterns from human-written fixes is an appropriate approach to expand the fix pattern set at low cost. On the other hand, a large number of fix patterns do not ensure that a template-based APR tool will become more effective if the buggy context describing the condition for choosing a fix pattern to generate fixes for a buggy code is too generic. Because the state-of-the-art fix patterns just provide a generic code context for matching a fix pattern, the number of matched patterns and therefore the number of generated patches is exceptionally large. Therefore, we mine human-written fixes automatically to not only extract new fix patterns but also clarify the buggy contexts of the bug fix instances forming each fix pattern. Different from the previous works, we propose to use test execution information, such as exception types and execution paths, in addition to code contexts, as the buggy contexts of the fix patterns. For mining strategy, we choose an agglomerative hierarchical clustering algorithm with our custom distance metric to group the bug fix instances that make the same or similar changes into the same cluster. The evaluation result on the bug set of two APR benchmarks Defects4J and Bears reveals that the fix patterns extracted from the clusters containing at least two similar bug fix instances are matched with most of the state-of-the-art fix patterns. Moreover, 11 new fix patterns are found. The buggy contexts, including the code context and the test execution information, of all bug fix instances forming each fix pattern are also clarified. Our fix patterns with the new buggy context information are expected to help the template-based APR tools generate and verify patches more effectively.
Nearby Unsafe Driving Detection

Unsafe driving has evolved into a public safety crisis. More than half of fatal crashes are due to distracted and aggressive driving. Modern cars have systems to monitor and notify drivers when erratic driving is detected. However, such systems do not help when other nearby vehicles drive unsafely. In this paper, we focus on this use case. We propose a nearby erratic driving detection method in which the ego vehicle observes its surroundings and identifies anomalous driving. We develop and test the proposed method through simulation. Then, we check the feasibility of the proposed method in field trials with multiple test vehicles. Evaluation results show that the proposed method can detect erratic driving on average 4 seconds before the risk of collision becomes maximum with 70% accuracy.
A Low Loss Self-Packaged Power Divider Using Right-Angled Isosceles Triangular Patch Based on the SISL Platform

This paper proposes a low-loss power divider using the right-angled isosceles triangular patch (RITP) based on the substrate integrated suspended line (SISL) platform. By adjusting the length of slots on the patch to control the resonant frequencies of different TM modes, the required operating frequency band and input return loss are obtained. The measured return loss is better than 15 dB from 6.05 to 6.77 GHz. The measured phase imbalance is less than 1° from 6.26 to 6.56 GHz. The self-packaged SISL RITP power divider is embedded into SISL cavities and has a very low insertion loss. From 6.12 to 6.76 GHz, the measured insertion loss is better than 0.31 dB, which is much smaller than previous works.
Policy2Graph: A Structure-aware Perspective on Constructing Policy Knowledge Graph for Smart Governance

The social governance empowered by AI are energetically promoted in many countries with one emerging technology, namely policy knowledge graph. Normally, a classical knowledge graph that encodes the data into Resource Description Framework (RDF) triples could fit most cases. However, a large number of imperative sentences in policy discourses make it difficult to extract the key elements: entities. Thus, using words such as entities and concepts as nodes are impractical in this work. In this paper, we shed light on a high-level abstraction of the policy discourse that can explicitly reflect rich semantic and structural information (Policy2Graph). Specifically, the utterance-level semantic nodes and syntactic dependency methods are employed to represent the detailed contents of the policies. In addition, the implicit outline of policy is generalized to connect the semantic nodes. In this way, each policy discourse is constructed into a small-scale knowledge graph. Furthermore, to fusion them into a large-scale knowledge graph, similar nodes in different policy knowledge graphs could be associated through the semantic similarity, considering the weight of each feature in the dependency relationship of syntactic dependency policy trees. We have demonstrated Policy2Graph on the rural innovation and entrepreneurship policies released by the Chinese government over the past eight years. Results have validated the effectiveness of our approach.
Automatic Extrinsic Calibration of Thermal Camera and LiDAR for Vehicle Sensor Setups

LiDAR is one of the most used sensors in many areas like robotics, self-driving cars, and advanced driving assistance systems due to providing an accurate point cloud of the surroundings. However, to cope with challenges in perceiving the environment around a vehicle, LiDAR data is often combined with data from other sensors. Thermal cameras can provide complementary information that can be beneficial, especially for detecting pedestrians and seeing at nighttime and in fog, dust, etc. In this paper, we propose an algorithm for the extrinsic calibration of a thermal camera and a LiDAR sensor in a vehicle. First, one or more thermal image-point cloud pairs of our designed calibration target are collected. Then line and plane equations of the target’s edges and plane in both data modalities are found. Finally, the algorithm uses lines and plane correspondences to cross-calibrate the sensors. The proposed method obtains good results with one or more poses. We also show that it works well with sparse LiDAR data. Several experiments are presented to illustrate the effectiveness of the method.
Improving security in the operation of nuclear power plants using Defence in Depth principle

This paper presents a study on the impact of using Defence-in-Depth principle to improve security in operation of the nuclear power plants. The simulation results showed that the use of characteristics to ensure the layers of Defence in Depth, such as redundancy, in the design of the Auxiliary Power Supply System, increased the reliability of the system by up to 26.7%. The results suggest that the Defence in Depth principle is effective in improving the security and reliability of power plant systems and equipment. This study provides a framework for future evaluations of other Defence in Depth characteristics on the reliability of power plants systems and equipment.
Data-driven Predictive Connected Cruise Control

In this paper, we propose a data-driven predictive controller for connected automated vehicles (CAVs) traveling in mixed traffic consisting of both connected and non-connected vehicles. We assume a low penetration of connectivity, with only one connected vehicle in the downstream traffic. A model predictive controller is designed to integrate multiple specifications, including safety and energy efficiency, while accounting for the time delay in the longitudinal dynamics of the vehicle. A data-driven prediction method based on the behavioral theory of linear systems is proposed to model the relationship between the speeds of the distant connected vehicle and the vehicle immediately in front of the CAV. The proposed method is evaluated using real traffic data and demonstrates improved prediction accuracy and energy efficiency compared to model-based prediction methods.
Dynamical circulation regimes in planetary (and exo-planetary) atmospheres

In this thesis, we study the effect of diurnally- and seasonally-varying forcing on the global circulation of planetary atmospheres explored within a large parameter space. This work focusses on studying the spacial and spectral energy budgets across a large range of planetary parameters as well as the momentum transfer as a response to diurnal and seasonal effects. We simulate planetary atmospheres using PUMA-GT, a simple GCM co-developed for this work, that is forced by a semi-grey two-band radiative-convective scheme, dissipated by Rayleigh friction and allows for temporally varying insolation. Our parameter regime includes the variation of the planetary rotation rate, frictional timescale in the boundary layer, the thermal inertia of the surface and the atmosphere, as well as the short-wave optical thickness. We calculate the energy transfer in Martian atmosphere to have a reference case of an atmosphere that is subject to very strong seasonal and diurnal variation. For this we present the first Lorenz energy budget calculated from reanalysis data of a non-Earth planet. A comparison between Martian and Earth atmosphere reveals a fundamentally different behaviour of the barotropic conversion term in the global mean. A significant impact of the thermal tide can be discerned in the generation of eddy kinetic energy, especially during global dust storms. Our study of seasonal variation reaffirms previous work that the equatorial super-rotating jet in the slow-rotating regime is arrested for strong seasonal variation. We find a novel explanation as to why the Titan atmosphere is able to maintain super-rotation despite strong surface seasonality; for non-zero short-wave absorption in the atmosphere the mechanism that hinders equatorial super-rotation is weakened. Diurnally-varying forcing can significantly enhance the equatorial super-rotation in cases with non-zero short-wave absorption. In our simulations this enhancement is maintained by a convergence of vertical momentum flux at the equator. Efforts to identify the atmospheric waves involved in this enhancement point towards thermally-excited gravity waves.
Compact Hybrid Filter based on HMSIFW and SICL Technology with Wide-Stopband Suppression

A bandpass filter (BPF) based on the hybrid substrate integrated coaxial line (SICL) and half mode substrate integrated folded waveguide (HMSIFW) is proposed in this paper. Two SICL resonators are etched between the two HMSIFW cavities. Four transmission poles are generated in the passband. To achieve better frequency selectivity, cross-coupling is introduced between two HMSIFW cavities, which generates two transmission zeros close to the passband. Meanwhile, the coupling between SICL and HMSIFW cavities is designed to constitute a coupling-null structure, which can achieve the suppression of higher mode transmission. Based on the application of SCIL and HMSIFW, a bandpass filter operated at 4 GHz with low loss, high-quality factor, and compact size is designed, simulated, fabricated, and measured for verification.
Building an autonomous boat: a multidisciplinary design engineering approach

This paper describes the work completed for the design and development of a prototype autonomous boat (or autonomous surface vessel). The goal of the boat was to compete in a number of races, which were part of the International Aegean Ro-Boat Races, sailing completely autonomously, that is using onboard data sensors and processing, so as to navigate safely, without any input from shore. It outlines the path to development from initial concept and requirements, to detailed design of the physical and software systems, complete to the first sea trials. We describe how the boat performs the entire Sense-Think-Act paradigm on board, at sea, while using occupancy grids to safely navigate and avoid collisions. The boat perceives its surroundings through a collection of low-cost sensors (such as cameras, LIDAR, etc) that are used to map the environment. Following this, path and trajectory planning algorithms, navigate the boat safely and free of collisions towards its destination. Overall this work demonstrates the potential of using open source software and off the shelf components to build a cost effective autonomous vessel with advanced capabilities. Although the design purpose and requirements of this boat were very specific, the basic design of the boat can be adapted to different needs, environments and applications. The system has been extensively tested in various environments, including open water testing, and the results demonstrate its capacity to navigate safely and efficiently.
Two-step Random Access with Collision Resolution Queueing for Cellular IoT networks

Recently, 2-step random access (RA) has been a preferred scheme through which an IoT device transmits data in cellular Internet of Things (IoT) networks for Machine-Type Communications (MTC). In contrast to 4-way handshake that was originally needed before data transmission, in 2-step RA the signalling is reduced and there is no need of connection establishment for data transmission. Overall, the latter approach reduces also latency. In this work, collision resolution queueing (CRQ) algorithm is employed in 2-step RA scheme in order to manage preamble collisions. Simulation results reveal improvement on system performance when a large number of IoT devices exist in the network, or the offered load is high.
Deep Learning Sparse Array Design Considering Binary Switching and Missing Coarray Lags

Sparse array reconfigurability via fast switching is pivotal to a realizable perception-action cycle of cognition in dynamic radio frequency (RF) environments. In this paper, we propose a deep learning (DL) sparse array design method using binary switching per RF chain for optimum beamforming that maximizes the signal-to-interference-and-noise ratio (MaxSINR). We consider two binary switching strategies and design the arrays to incorporate missing spatial data correlation values. Through design examples, we demonstrate that the DL method can effectively learn the optimum sparse arrays for MaxSINR in the presence of a missing correlation lag.
Row-Segmented Sparse-Dense Matrix Matrix Multiplication on GPUs

SpMM (Sparse-Dense Matrix Matrix Multiplication) is the key computing core in many machine learning, big data analysis, and neural network applications. Although SpMM has received more attention in recent years, it is still a challenge to effectively improve the performance of SpMM. For example, existing work has largely given little consideration to improving performance by optimizing memory accesses. To alleviate the problems, we propose a matrix partition method, then, a SpMM algorithm is customized to match the partition, which makes full use of the architecture of GPU, and it easily improves the parallelism to achieve the best performance by adjusting parameters. Furthermore, we present two optimized algorithms for memory access, named rsSpMM and rrSpMM, which not only combine the advantages of the above algorithms, but also greatly exploit the advantage of different memory spaces of GPU. Experimental results on NVIDIA Tesla T4 demonstrate that the proposed algorithms in this paper has a significant improvement over the previous state-of-the-art cuSPARSE libraries, and preferably delivers 4. 6x, 8.9x, and 10. 1x improvements, respectively.
t-PSI: Efficient Multi-party Private Set Intersection with Threshold

Multi-party privacy set intersection (MPSI) enables multiple parties to compute the intersection of their datasets without leaking data privacy. Among existing MPSI protocols, e.g., KMPRT-based protocols, oblivious evaluation of programmable pseudo-random function (OPPRF) or oblivious pseudo-random function (OPRF) is typically used to generate pseudo random numbers, requiring frequent online interactions. To mitigate such communication overheads, we propose the threshold Privacy Set Intersection (t-PSI) protocol for multi-party, leveraging the Shamir Secret Sharing (SSS) protocol and the masking construction mechanism. We propose two types of masking construction mechanisms: Polynomial and Garbled Bloom-filter. To the best of our knowledge, this is the first Secret Sharing-based MPSI protocol. With the significant reduction of inter-party communication, the t-PSI protocol is highly scalable and can handle datasets ranging from 26 to 220. Further, with built-in fault tolerance, t-PSI works even if some parties went offline during protocol execution. As shown in the experiments, for five parties with datasets of 220 items each, the proposed t-PSI takes only 63 seconds, outperforming the state-of-the-art in [1].
1.26–2-GHz Miniaturized Tunable Bandpass Filter with Constant Absolute Bandwidth and Wide Stopband Using Two-Path Electrical Complementary Coupling

In this paper, a miniaturized third-order tunable bandpass filter (BPF) with constant absolute bandwidth (ABW) and wide stopband is proposed. By using two-path electrical complementary coupling, the coupling coefficients almost match the ideal curve for constant ABW in wide tuning range. Then, a tiny bandwidth variation and simple tuning operation are obtained. Wide stopband is achieved from the slow-wave effect of patch-loaded transmission line. Besides, multilayer structure is used to implement couplings at different layers for independent coupling control. Based on the mechanisms above, a third-order tunable BPF covering the range from 1.26 to 2.00 GHz is designed and fabricated. The measured 3-dB bandwidth is 278±5 MHz with the insertion loss of 2.42–3.05 dB, showing a good passband performance with constant ABW. Besides, the stopband is up to 10 GHz with a rejection level more than 20 dB. The proposed tunable BPF exhibits a miniaturized size (i.e., 0.0054 $\lambda _g^2$, where λg is the microstrip guided wavelength at 1.26 GHz).
Wettability of electrodeposited copper films and correlation with morphology and surface chemistry

In this study, different forms of copper films were electrodeposited (ED) on silicon wafer, copper and brass foils. The effect of monocrystalline Si(111) surface cleaning method and electrodeposition conditions and regimes (frequency in the pulsating current (PC) regime, an addition of additives in electrolyte for the constant galvanostatic (DC) regime, and thickness) on surface morphology and wettability of copper films was investigated. Optical microscopy equipped with high-resolution camera, scanning electron microscopy (SEM) and an atomic force microscopy (AFM) were used for thin film characterization and to evaluate wettability of copper films. The sessile drop method was used for the measurement of water contact angle. According to the obtained results, choice of electrolyte used in ED greatly affects wettability of copper films. It was also shown that copper films electrodeposited from basic sulfate electrolyte with varying current regimes frequencies, thicknesses, and cathode types have opposite trends between roughness parameter values and the water contact angle value. Structural-morphological changes of a film or bulk solid surface are key parameters in determining wettability properties and the analysis of the wetting angle oscillations, but not the only one.
Performance of Mixed Shadowed Ricean/TWDP Relayed Assisted Link

In this paper, we consider the inclusion of Low-Earth-Orbit (LEO) satellites in the terrestrial mobile network. We study the transmission of information from a LEO satellite to a mobile terminal on the surface of the Earth. Signal transmission is performed with help of a relay on Earth that applies a decode-and-forward (DF) strategy. For the channel from the satellite to the relay, a channel model is used that includes multipath propagation, where there are one dominant and many non-dominant components, where both the dominant and non-dominant components are under the influence of the shadowing effect. After decoding in the relay and amplification, the signal is further transmitted in the millimeter range to the mobile terminal. A numerical procedure for calculating the outage probability is developed, and then an analysis of the influence of the parameters of both channels on the outage probability is performed.
IRS-Aided Sectorized Base Station Design and 3D Coverage Performance Analysis

Intelligent reflecting surface (IRS) is regarded as a revolutionary paradigm that can reconfigure the wireless propagation environment for enhancing the desired signal and/or weakening the interference, and thus improving the quality of service (QoS) for communication systems. In this paper, we propose an IRS-aided sectorized BS design where the IRS is mounted in front of a transmitter (TX) and reflects/reconfigures signal towards the desired user equipment (UE). Unlike prior works that address link-level analysis/optimization of IRS-aided systems, we focus on the system-level three-dimensional (3D) coverage performance in both single-/multiple-cell scenarios. To this end, a distance/angle-dependent 3D channel model is considered for UEs in the 3D space, as well as the non-isotropic TX beam pattern and IRS element radiation pattern (ERP), both of which affect the average channel power as well as the multi-path fading statistics. Based on the above, a general formula of received signal power in our design is obtained, along with derived power scaling laws and upper/lower bounds on the mean signal/interference power under IRS passive beamforming or random scattering. Numerical results validate our analysis and demonstrate that our proposed design outperforms the benchmark schemes with fixed BS antenna patterns or active 3D beamforming. In particular, for aerial UEs that suffer from strong inter-cell interference, the IRS-aided BS design provides much better QoS in terms of the ergodic throughput performance compared with benchmarks, thanks to the IRS-inherent double pathloss effect that helps weaken the interference.
Design of Highly-Efficient Dual-Band GaN HEMT Power Amplifier With Dual-Class E/F−1 Operation

A novel methodology for designing high-efficiency dual-band (DB) power amplifier (PA) with a packaged transistor is presented in this paper. Specifically, a transmission lines-implemented load network is deployed to exhibit a composite operation with class E mode for low frequency and inverse class F (class F−1) mode for high frequency, which can overcome the difficulty of DB harmonic manipulation in class F−1 mode and efficiency degradation at high frequency in class E mode. A Cree transistor and two widely-spaced frequencies of 1.4 GHz and 3.5 GHz are selected for verification. The measured results show that saturation drain efficiency (DE) is 79.3% and 70.2%, corresponding to peak power added efficiency (PAE) of 77.4% and 62.9%, output power of 38.2 dBm and 37 dBm, and gain of 14.2 dB and 9 dB at 1.37 GHz and 3.48 GHz, respectively.