Miracle-dz/UniFAR-FTUs huggingface dataset:
A Practical Black-Box Attack on Source Code Authorship Identification Classifiers

Existing researches have recently shown that adversarial stylometry of source code can confuse source code authorship identification (SCAI) models, which may threaten the security of related applications such as programmer attribution, software forensics, etc. In this work, we propose source code authorship disguise (SCAD) to automatically hide programmers’ identities from authorship identification, which is more practical than the previous work that requires to known the output probabilities or internal details of the target SCAI model. Specifically, SCAD trains a substitute model and develops a set of semantically equivalent transformations, based on which the original code is modified towards a disguised style with small manipulations in lexical features and syntactic features. When evaluated under totally black-box settings, on a real-world dataset consisting of 1,600 programmers, SCAD induces state-of-the-art SCAI models to cause above 30% misclassification rates. The efficiency and utility-preserving properties of SCAD are also demonstrated with multiple metrics. Furthermore, our work can serve as a guideline for developing more robust identification methods in the future.
A Core-Stateless L4S Scheduler for P4-enabled hardware switches with emulated HQoS

Novel Internet applications often require low latency and high throughput at the same time, posing challenges to access aggregation networks (AAN). Low-Latency Low-Loss Scalable- Throughput (L4S) Internet service and related schedulers have been proposed to meet these requirements and also allow the coexistence of Classic and L4S flows in the same system. AANs generally apply Hierarchical QoS (HQoS) to enforce fairness among their subscribers. It allows subscribers to utilize their fair share as they desire, and it also protects traffic of various subscribers from each other. The traffic management engines of available P4-programmable hardware switches do not support complex HQoS and L4S scheduling. In this demo paper, we show how a recent core-stateless L4S Active Queue Management (AQM) proposal called VDQ-CSAQM can be implemented in P4, and executed in high-speed programmable hardware switches. We also show how a cloud-rendered gaming service benefits from the low latency and HQoS provided by our VDQ-CSAQM.
A Multi-Sensor Subspace-Based Clustering Algorithm Using RGB and Hyperspectral Data

In this work, we introduce a multi-sensor subspace-based clustering algorithm that benefits from fine spectral-resolution hyperspectral images (HSIs) and fine spatial-resolution RGB images. In order to extract spatial information, a hidden Markov random field (HMRF) is employed on the fine spatial-resolution RGB image, whereas, spectral information is derived from an HSI using an advanced sparse subspace clustering algorithm. The proposed algorithm is validated on two real geological data sets. The experimental results in this study show that the proposed algorithm outperforms the state-of-the-art clustering algorithms in terms of clustering accuracy.
A Wearable Graphene Strain Gauge Sensor with Haptic Feedback for Silent Communications

Silent communication devices are necessary in situations when audio voice signals cannot be relied upon. This could be due to physical voice impairments of the sender, or being in an environment in which sound cannot be transferred reliably or securely. A wearable ultrasensitive strain sensor worn on the throat may be able to detect small muscle movements and vibrations which can be mapped to the intended phonations. Feedback can then passed back to the wearer to inform if the speech has been correctly predicted. In this paper we propose a wearable patch which can be used for silent communications and demonstrate a proof-of-concept graphene-based strain gauge sensor which, combined with machine learning algorithms, can record and decode non-audio signals. The sensor detects small throat movements when someone speaks, or attempts to speak, as changes in the resistance of the device. These are passed to machine learning algorithms which makes predictions on what is being said. A dataset of 15 unique words and four movements, each with ten repetitions from two participants, was developed and used for the training of the machine learning algorithms. The results demonstrate the ability for such sensors to be able to predict spoken words. We produced a prediction accuracy rate of 51% on the word dataset and 82% on the movements dataset. We further explore haptic forms of feedback which can be incorporated into a smart wearable patch. This provides an initial demonstration of a wearable silent communications device.
Serious Games for seniors: Learning safe behaviors on the web : Position paper

In a modern society, seniors want to be a part of the digital world and the research in progress seeks to present whether through Serious Games can help their learning process and understanding of cybersecurity when online browsing, namely, deciding which actions to make when facing an eminent threat. this position paper aims to presents a new research on how Serious Games can help seniors to become more aware in the cybersecurity theme and how to be more careful when search the web. In this research the methodology apply is the Action Research, by identifying the problem –lack of knowledge that seniors have on the online threats and promoting an action –the Serious Game played to teach and motivate the senior to become safer online.
A Single User Millimeter Wave Massive MIMO System using Defected Ground Structure and Metasurface Antenna Arrays

In this study, we designed a single user millimeter wave massive MIMO system using the defected ground structure and metasurface square patch antenna array in the transmitter and receiver. Since power reduction is a key factor for the 5G technology, hybrid precoding is implemented to enhance the power performance of the millimeter-wave large-scale antenna systems with a minimum spectral efficiency loss compared with the fully digital baseband precoders. Hence, Barzilai-Borwein (BB) based alternating minimization algorithm is applied to compute the hybrid precoders and simulation results are illustrated for different setups to compare the proposed system with the competing methods in the literature. Simulation results are supported by additional performance parameters and demonstrate that the BB algorithm would be a strong candidate for hybrid precoding. The transmitting and receiving antenna arrays are designed using novel defected ground structure and metasurface patch antenna to achieve antenna miniaturization and reduced mutual coupling in array elements. The proposed single element antenna with a compact size operates at 28 GHz with a bandwidth of 3.1 GHz and gain of about 6.28 dB. Antenna arrays are optimized iteratively to achieve high isolation between antennas to avoid the degradation in antenna radiation properties.
Performance Analysis of Wideband Circularly Polarized Pyramidal Horn Antenna with Binomial Polarizer Manufactured by 3D Printing Technology

This paper proposes development and performance analysis of wideband pyramidal horn antenna equipped with binomial polarizer to produce circularly polarized waves. The proposed antenna which is designed and optimized to operate at the X-band frequency is intended to be used for circularly polarized synthetic aperture radar (CP-SAR) application. The optimized antenna design is fabricated using 3D printing technology for fast, low cost and light weight which is very suitable for small platform of CP-SAR sensor. The performance of manufactured antenna has demonstrated the fractional impedance bandwidth of 26% for S11 below –10dB, the axial-ratio bandwidth of 6.2% below 3dB, and the gain achievement up to 12dBic at the desired working frequency.
Leaf Segmentation Algorithm Based on Improved U-shaped Network under Complex Background

In order to segment leaf image under complex background and improve the accuracy of leaf image segmentation, an image segmentation method based on improved U-shaped network is proposed. Based on the Pytorch deep learning framework, the U-shaped network model FPN is improved, the model adopts the encoder-decoder structure, ResNet50 is used as the trunk network, the encoder receives the image input, the feature extraction is accomplished by convolution, and the decoder uses the bilinear interpolation to complete the image reconstruction and outputs the segmentation results. In order to integrate the underlying position features and high-level semantic features better, the feature fusion module is introduced in the decoder. The experimental results show that the model has a significant effect in plant leaf segmentation, and the technical index is better than most traditional image segmentation algorithms.
Predicting the Survival of Heart Failure Patients in Unbalanced Data Sets

Heart failure is a serious, cardiovascular condition that affects the lives of millions of people. Early diagnosis of this disease is extremely important in the treatment of the disease. Survival analysis of sick individuals gives us information for early diagnosis and treatment. Survival analysis of heart failure patients was performed within the scope of the study. Using the Correlation Matrix and Random Forest methods, the most relevant characteristics to death status were determined as serum creatinine, ejection fraction and age. Patient follow-up time was ignored because it was not known when performing the survival analysis. Resampling methods were applied due to the uneven class distribution in the data set. It has been shown in experimental studies that when data cleaning is applied together with resampling, the prediction success is higher. It was determined that eliminating the class imbalance in the data set increased the success of the classifier. While the oversampling method showed a better success on the Random Forest algorithm with %84.51, the undersampling method showed a higher success on the Extra Trees algorithm with %84.58.
Thermal Analysis and Design of a 30kW EV Wireless Charger with Liquid-Cooled Shell for Magnetic Coupler and Integrated Power Converter

The thermal performance affects the reliability and safety of the inductive power transfer system. This paper studies the thermal design method of wireless chargers for the electric vehicle. The thermal resistance of materials is calculated, and the thermal networks of heating components are established. Then power losses are applied to the nodes in the form of heat sources. The calculated hotspot temperatures are close to those obtained by the finite element method in comparison. A prototype of a 30kW onboard wireless charger with a liquid-cooled shell is set up, and the steady-state temperature error of less than 10% proves the effectiveness of the thermal design scheme. This paper expands the application of the thermal network method in the field of the liquid-cooled onboard receiver of wireless chargers.
Development of Fault Diagnosis Model for Sucker Rod Pump Using Motor Power Curve

A real time diagnostic system development for detecting sucker rod pump working conditions is current demand for most oil producers because of significant expenses related to costs of labor and consequent damages when a fault is not identified timely. In this paper the main objective is to develop a fault diagnostic model that helps to solve the existing diagnostic problems in sucker rod pump installations. The main source of data which relays on the use of unreliable sensors is the main cause to the existing difficulties. However, motor power curve is reliable source and has a potential to improve the efficiency of sucker rod pump diagnosis. In this research, sucker rod pump simulating model generates motor power curves considering the influences of possible scenarios in the subsurface on the subsurface boundary condition. The generated motor power curves are used to train support vector machine (SVM) and for testing. The results of the simulation indicate satisfactory performance of SVMs in solving the diagnostic problem of sucker rod pumps.
2.4/5-GHz dual-band vertically/horizontally dual-polar ized omnidirectional antennas for WLAN base station

This paper proposed a novel antenna configuration to achieve 2.4/5 GHz-dual-band WLAN base station antennas with vertically/horizontally dual-polarized omnidirectional radiation pattern in the horizontal plane. The proposed antenna provides a VSWR of 2 in the 2.4-2.5 and 4.9-6-GHz bands and satisfies all the bands required for the IEEE 802.11n standard. Good omnidirectional radiation patterns are achieved such that the averages of the deviation levels, gain, and XPDs for the radiation patterns in the horizontal plane over both bands for the vertically and horizontally polarized antennas are approximately 2.7 dB, -0.8 dBi, and 14 dB, and 5.5 dB, 0.3 dBi, and 10 dB, respectively.
Robot Behavior-Based User Authentication for Motion-Controlled Robotic Systems

Motion-controlled robotic systems would become more and more popular in the future since they allow humans to easily control robots to carry out various tasks. However, current authentication methods rely on static credentials, such as passwords, fingerprints, and faces, which are independent of the robot control. Thus, they cannot guarantee that a robot is always under the control of its enrolled user. In this paper, we build a motion-controlled robotic arm system and show that a robotic arm’s motion inherits much of its user’s behavioral information in interactive control scenarios. Based on that, we propose a novel user authentication approach to verify the robotic arm user. In particular, we log the angle readings of the robotic arm’s joints to reconstruct the 3D movement trajectory of its end effector. We then develop a learning-based algorithm to identify the user. Extensive experiments show that our system achieves 95% accuracy to verify users while preventing various impersonation attacks.
Temperature Dependent Relaxation Behavior of Pressureless and Pressure Assisted Sintered Silver

In this study we investigate the creep properties of pressureless and pressure assisted sintered silver. Based on density analysis and tensile strength, the relaxation behavior of the series was observed at room temperature, at 130°C and at 200°C. A material model for mechanical properties of porous metals was derived from experimentally established time dependent material response under tensile load.
The Impact of Economic Policy Uncertainty on China’s Regional Economy and Its Dynamic Effects —A theoretical analysis based on TVP-FAVAR

Through a review of prior literature, we can conclude that average consumption in developed regions is generally lower than less developed regions and the economic policy uncertainty (EPU) has differently negative effects on China’s investment, consumption, price levels, and output in the short term. This paper intends to divide further China’s provinces and cities into consumption-led areas, moderate areas, and investment-led areas. Then this paper adopts the time-varying parameter factor-augmented vector autoregression (TVP-FAVAR) model to conduct a theoretical analysis of macroeconomic response under China’s economic policy uncertainty. Using the transmission mechanism of interest rate channel, credit channel, and exchange rate channel, we predict that the increase in policy uncertainty will have a more significant negative impact on regions with a low proportion of consumption, manifested in a higher degree of decline in consumption, investment, and output. However, the price level is significantly consistent across regions. As for the nonlinear issue, as China’s economic environment changes, major economic indicators in various regions have shown obvious time-varying characteristics.
Real-Time Driver’s Monitoring Mobile Application through Head Pose, Drowsiness and Angry Detection

The current driver's monitoring system requires a set-up that includes the usage of a variety of camera equipment behind the steering wheel. It is highly impractical in a real-world environment as the set-up might cause annoyance or inconvenience to the driver. This project proposes a framework of using mobile devices and cloud services to monitor the driver's head pose, detect angry expression and drowsiness, and alerting them with audio feedback. With the help of a phone camera functionality, the driver’s facial expression data can be collected then further analyzed via image processing under the Microsoft Azure platform. A working mobile app is developed, and it can detect the head pose, angry emotion, and drowsy drivers by monitoring their facial expressions. Whenever an angry or drowsy face is detected, pop-up alert messages and audio feedback will be given to the driver. The benefit of this mobile app is it can remind drivers to drive calmly and safely until drivers manage to handle their emotions where anger or drowsy is no longer detected. The performance of the mobile app in classifying anger emotion is achieved at 96.66% while the performance to detect driver’s drowsiness is 82.2%. On average, the head pose detection success rate across the six scenarios presented is 85.67%.
LiCamPos : An Indoor Positioning System using Light to Camera Communication

Due to the limitations of the Global Positioning System to track or locate ultra-small resolutions, Indoor Positioning System(IPS) came into existence. IPS is used to provide useful indoor location-based information. Mostly Radio Frequency (RF) based system is used to achieve IPS. However, alternatives to RF are getting popular due to the debatable health risks of RF. In this paper, a light-based camera communication technique for IPS is proposed and evaluated. The proposed method uses a light aperture to encode location beacon information and is decoded using image processing techniques on the user’s mobile phone. An On-Off Keying (OOK) modulation technique is employed to encode and broadcast beacon information, and software-based custom modified mobile camera parameters are used for position estimation. A phenomenon called the "Rolling Shutter" effect is used to extract useful information from the beacon. During experimentation, it was observed that the number of observable rolling shutter stripes is inversely proportional to the distance between the beacon and the receiver, and it is directly proportional to the frequency of OOK. It was also observed that the stripe’s width is independent of the distance between beacon and receiver. Finally, an android application is built to show location-relevant messages/ads based on the identified beacon.
Effect of Soap, Methanol, and Water on Glycerol Particle Size in Biodiesel Purification

For use as a transportation fuel, biodiesel must meet certain quality standards (e.g., ASTM D6751 and EN 14214). Free dispersed particles of glycerol are among the important impurities in biodiesel that should be removed. The use of membrane separation technology to remove glycerol particles from fatty acid methyl ester (FAME) has been demonstrated to be an effective biodiesel purification method. The presence of large glycerol particles promotes its separation from FAME. The effect of water, methanol, soap, and glycerol on the size of suspended particles in FAME was studied using a three-level Box−Behnken experimental design technique. The statistical analysis revealed the significant effect of water and glycerol on increasing particle size while methanol and soap served to reduce the particle size. Experimental verification using a polyacrylonitrile (PAN) membrane at a temperature of 25 °C was completed. The addition of small amounts of water was found to improve the removal of glycerol from FAME, and a.
MMC-Based High Gain Solid-State Transformers for Energy Storage Applications

This paper examines modular high-gain isolated DC/DC converter topologies for energy storage systems (ESS). The structure and operation of the topologies discussed resemble modular multilevel converter (MMC) and dual-active-bridge (DAB), in that regulated bidirectional power flow is realized with traditional circuit building blocks by applying classic phase shift control. The operation of two topologies is presented. Both can realize a high voltage step-down ratio from a medium-voltage (MV) bus to a medium frequency (MF) transformer primary winding so that reduced winding insulation is achieved to shrink the transformer size. These two topologies are compared in terms of their step-down ratios, frequency multiplication factors, switching and conduction losses, submodule (SM) capacitance, and transformer area products. Preliminary experimental results are presented to verify the key features of both topologies using 3.3-kV silicon carbide (SiC) devices (Generation-2 engineering samples from GeneSiC).
Millimeter-Wave Wideband Waveguide Power Divider With Improved Isolation Between Output Ports

We present a novel compact wideband waveguide T-junction power divider, especially suited for millimeter-wave and THz frequencies. It incorporates substrate-based elements into a waveguide structure to provide the output port's isolation and matching. The internal port is introduced at the apex of the T-junction formed as an E-probe on a substrate. This facilitates efficient coupling of the reflected energy from the output port to a novel thin-film-based resistive termination integrated with the E-probe onto the same substrate and fabricated by means of thin-film technology. A power divider was designed, simulated, and fabricated for the frequency band 150–220 GHz to experimentally verify the theoretical and simulated performance. The results showed excellent agreement between the simulations and measurements with the devices demonstrating a remarkable return loss of 20 dB for both the input and output ports for a three-port device with equal split and isolation better than 17 dB between the output ports. Furthermore, the measured insertion loss is less than 0.3 dB and the amplitude and phase imbalance are 0.15 dB and 0°, respectively. Moreover, the divider's remarkable tolerance to the dimensions and sheet resistance of the resistive material of the built-in absorbing load makes the device a very practical component for millimeter-wave and THz systems, in particular radio-astronomy receivers.
A Review on Application of Knowledge Graph in Cybersecurity

With the development of information technology and the increasing complexity cyber environment, the volume of data involved in cybersecurity is also increasing rapidly and the risks of cybersecurity are also increased. There is an urgent need to find correlation and attack patterns from fragmented and massive multi-source heterogeneous cyberspace related data. The construction of cyberspace security knowledge graph can build massive fragmented multi-source heterogeneous data into one module and conduct fine-grained deep association analysis. To provide further master the cyberspace security situation and auxiliary decision-making. In this paper, we summarizes the development of knowledge graph related technology and the application of knowledge graph in cyberspace.