Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Power Flow Solution Paradigm for Well and Ill-Conditioned Cases

This paper develops a novel four-stage power flow solver for ill-conditioned systems. Although the developed solver could be considered efficient, it is not competitive with the Newton-Raphson method in well-conditioned cases. With the aim of being fully competitive in a wide range of cases and scenarios, the developed algorithm is integrated within a novel efficient solution paradigm. As a result, a robust and efficient solution framework, competitive in both well and ill-conditioned cases, is obtained. The new proposals are tested in various well and ill-conditioned cases from 30-, to 13,659-buses. Results obtained with the developed solvers are promising.
Study on Pressure Variation Characteristics of Cable Accessories Interface under Temperature Cycling

Interfacial pressure is one of the key factors that determine the insulation strength of cable accessories. However, the cable accessories will relax due to the temperature cycling during operation. Therefore, it is worth to study the change regulation of the interfacial pressure of the cable accessories with the temperature. In this study, an interfacial pressure acquisition device is designed by the built-in pressure sensor. The interfacial pressure of 10 kV cold shrinkable cable joint is measured by the device at 25°C and 130 °C respectively. Meanwhile, the joint thickness and inner diameter is recorded to compare the changes of joint geometry before and after aging. Then, the cable joint is built by the finite element simulation software, and the simulation results are compared with the measured data to verify the validity of the data. With the increase of the temperature cycle time, the interfacial pressure of the cable joint at room temperature decreased by 15.9%, while the interfacial pressure at high temperature increased by 11%. Experimental results proved that after the temperature cycle of the cable joint, the geometric dimensions of the cable joint changes, and the stress relaxation increases. When the cable joint work at high temperatures, the interfacial pressure of the cable accessories increases, while the cable accessories work at room temperature, the interfacial pressure decreases, resulting in a decrease in the electric field strength of the cable accessories.
Performance Analysis of Machine Learning Algorithms for Disease Prediction

With the recent technological advances in microelectronics, wireless communication, machine learning (ML), and decision-making process, Wireless Body Area Network (WBAN) has become the most promising technology. As we all know that we are in global pandemic due to Covid-19 situation now, hence, there is a demand occurring in health care services and continuous monitoring. Moreover, prediction of abnormalities at an early stage will be crucial for a person in diagnosis. Hence, in this paper we have developed and compared the performance of three machine learning algorithms such as Decision Tree Classifier (DTC), K-Nearest Neighbor (KNN), and Random Forest (RF). Each algorithm is tested with datasets of 100, 200, 500 & 1000 users respectively. Further, threshold values have been identified by consulting with doctors for accurate disease prediction based on the vital signals collected by various sensors. The three algorithms used are based on supervised learning, where the output is predicted based on the training of the developed classifier. From the results, it is observed that the accuracy in disease prediction using RF is 0.99 & outperformed when compared with state of the art for datasets of 1000 users.
Modeling and Analysis of A Feedforward Current Based Active Common-Mode EMI Filter For Modular Multilevel Converters

Modular Multilevel Converter (MMC) is becoming more and more popular in High Voltage Direct Current (HVDC) system recently since it can achieve high efficiency power conversion. However, numerous switching devices in MMC system generate severe Electromagnetic Interference (EMI) during its operation. Common-Mode (CM) EMI is generated by the high frequency fluctuation of voltage on the power devices and the parasitic capacitance in the system which may threaten the reliable operation of the system. EMI filters are commonly used for EMI suppression. To suppress the DC side CM EMI in MMC system, this paper proposed a feedforward current based active EMI filter. A 5-level MMC simulation platform is built in MATLAB/SIMULINK. The feasibility of this method is verified by simulation results and the CM EMI reduction could approach 20dB within several MHz with the proposed active EMI filter.
Mobile User Trajectory Tracking for IRS Enabled Wireless Networks

In this paper, we consider an intelligent reflecting surface (IRS) enabled mobile network, where a fixed access point (AP) communicates with a mobile user (MU) via the aid of an IRS. We assume that the MU moves from one elementary square to another following a Markov random walk within a grid, and propose a maximum a posteriori (MAP) criterion to track the movement of the MU by leveraging the line-of-sight component of the IRS-MU link. Since it is infeasible to derive an explicit expression for the average probability of estimation error (APEE) for the proposed MAP criterion, we derive a closed-form upper bound for the APEE, which is used as the cost function to optimize the phase shifts of the IRS units. Considering the unit modulus constraints incurred by the IRS units, a manifold optimization (MO) method is firstly employed to gain a favorable solution to the formulated optimization problem, followed by a low-complexity codebook based solution to circumvent the high computational cost of the MO method. Our numerical results demonstrate the superior performance of the proposed IRS phase shift designs over the benchmark method.
Design of Wideband Linearly Polarized 3-Bit Transmit-Array Antenna With Polarization Rotation Unit Cell

The millimeter-wave (mm-wave) band is expected to be the optimal solution for future wireless communication systems as it provides a wide bandwidth, which enhancing data transmission rate. Therefore, high-directive antennas, principal elements for mm-wave wireless communications, are used at the mm-wave band as they can overcome the negative effect of high path losses. A transmit-array antenna (TA) operates at the mm-wave band (around 28 GHz) with high aperture efficiency, high gain, wide bandwidth, and low-profile TA surface has been designed. Basically, the aperture efficiency of the TA depends on the unit cell (UC) characteristics, and feed antenna radiation pattern. Therefore, the UC elements designed based on capacitive differential feeding and true time delay techniques, as a result the designed UC has a wide bandwidth with a stable broadside radiation pattern, high cross-polarization discrimination and a full phase range (0–360°) and a maximum element loss of 0.5 dB. Moreover, the designed UC rotates the polarization of linearly polarized electromagnetic (EM) wave to its orthogonal direction with high efficiency, a polarization conversion ratio higher than 0.9 is achieved within the operating frequency band. The used techniques to design the proposed UC have a significant effect on TA antenna performance, in terms of gain and bandwidth. The TA antenna surface and the feeding antenna have been designed and fabricated. The maximum gain is 31.15 dBi. The 1 dB gain bandwidth is 12.7% while the 3 dB gain bandwidth is 21% around 28 GHz. The aperture efficiency is better than 50% and the cross-polarization level is less than −37 dB, on the frequency range from 25 to 31.5 GHz.
CoSMoS: Cooperative Sky-Ground Mobile Edge Computing System

In this correspondence, we study a tethered unmanned aerial vehicle (TUAV)-assisted mobile edge computing (MEC) system, in which tasks of several ground mobile users (MUs) are served by ground edge cloud (GEC) with superior computing capability and poor communication links and TUAV-mounted cloudlet with lower computing capability and better communication links. We aim to minimize weighted-sum system delay of MUs by jointly optimizing TUAV position, time slot allocation, and task splitting ratio. We first decompose the optimization problem into three subproblems, and then to solve non-convex subproblem related to TUAV position, we reformulate it by the first-order Taylor series approximation and apply the successive convex approximation (SCA) method. Then, we tackle the overall problem by applying the alternative optimization algorithm. Numerical results verify that our proposed cooperative sky-ground mobile edge computing system (CoSMoS) algorithm can achieve a better performance than other benchmark schemes.
Recent Security Trends in Internet of Things: A Comprehensive Survey

The Internet of Things (IoT) aims to transform everyday physical objects into an interconnected ecosystem with digital data accessible anywhere and anytime. “Things” in IoT are embedded with sensing, processing, and actuating capabilities and cooperate in providing smart and innovative services autonomously. The rapid spread of IoT services arises different security vulnerabilities that need to be carefully addressed. Several emerging and promising technologies and techniques are introduced to improve the security of IoT. This paper aims to provide an up-to-date vision of the current research topics related to IoT security. Initially, we introduce common elements and protocols of IoT to demystify the origins of threats in IoT. Then, we propose a taxonomy of IoT attacks and analyze the security vulnerabilities of IoT at different layers. Subsequently, we provide a comparison of recent security schemes based on emerging solutions including fog computing, edge computing, software-defined networking (SDN), blockchain, lightweight cryptography, homomorphic and searchable encryption, and machine learning. Finally, security challenges are discussed and future directions are highlighted for future interested researchers.
The Impact of the Collective Members’ Independence on the Prediction Accuracy

Decision making is one of the most frequently performed processes nowadays. Our future or other people’s future may depend on the decision we make, therefore we try to take it as good as possible. The rapid development of technology facilitates it for us, as we are able to store, process and analyse more and more data. However, the power of human knowledge extended by experience and intuition still overperforms computer systems in solving such problems. The power of the combined knowledge of a group of people is known as a collective intelligence. In this paper, an analysis of one of the properties describing the consensus is presented, id est the influence between its members. The work is based on graph theory and a multi-agent system approach to formalise the problem. The new measures describing the collective and the accuracy of the final prediction were proposed. Experimental evaluations, based on the developed environment, followed by the statistical analysis of the obtained results allowed to observed four relationships between the considered measures describing the collective and the accuracy of collective prediction. The independence of the collective members plays a crucial role in the decision-making, therefore it should be carefully considered when selecting people for the collective, especially the large ones.
Photoelectrochemical Hydrogen Generation in Coral-like TiO2 Photoanode

The coral-like TiO2 nanoparticles were synthesized on the transparent FTO conductive substrate and their photovoltaic properties investigated under illumination. Coral-like TiO2 photoanodes were synthesized using a hydrothermal method and annealed at 450 ˚C to obtain better crystallinity. Annealed coral-like TiO2 show a photocurrent enhancement of ~50% compared to pristine coral-like TiO2 without annealing using 1M Na2SO4 as electrolyte at potential of 0 V.
Impact Phenomena of Metallic Microparticles under Breakdown Voltages in Vacuum Interrupters

This paper studies the impact phenomena of the metallic microparticles with the vacuum gap in the range of 10–50 mm under different breakdown voltages in vacuum interrupters. The results show that for the vacuum gap 10–40 mm, the average impact velocities of the microparticles increase linearly with the increase of the vacuum gap, and the impact could damage the cathode surface, which would cause irregularities and give high local field enhancement, finally it may lead to vacuum breakdown. For the vacuum gap 40–50 mm, the average impact velocities of the microparticles are thought to enter the saturation region and remain nearly constant. The impact could cause more metal vapor, which may lead to developing gradually into the vacuum breakdown. Furthermore, the materials with the higher yield stress will cause more obvious fractures and broken phenomena on the edge of the craters, which would have an influence on the vacuum breakdown.
WIDE: Physical-Level CTC via Digital Emulation

Cross-Technology Communication (CTC) is an emerging technique that enables direct communication across different wireless technologies. Recent works achieve physical-level CTC by emulating the standard time-domain waveform of the receiver. This method faces the challenges of inherent unreliability due to the imperfect emulation. Different from analog emulation, we propose a novel concept named digital emulation, which stems from the following insight: The receiver relies on phase shift rather than the phase itself to decode signals. Instead of emulating the original time-domain waveform, the sender emulates the phase shift associated with the desired signals. Clearly there are multiple different phase sequences that correspond to the same signs of phase shifts. Digital emulation has flexibility in setting the phase values in the emulated signals, which is effective in reducing emulation errors and enhancing the reliability of CTC. The key point of digital emulation is generic and applicable to a set of CTCs, where the transmitter has a wider bandwidth for emulation and the receiver decoding is based on the phase shift. In this paper, we implement our proposal as WIDE, a physical-level CTC via digital emulation from WiFi to ZigBee. We conduct extensive experiments to evaluate the performance of WIDE. The results show that WIDE significantly improves the Packet Reception Ratio (PRR) from 41.7% to 86.2%, which is $2\times $ of WEBee’s, an existing representative physical-level CTC.
Synthesis of Poly(N-vinylcaprolactam)-Based Microgels by Precipitation Polymerization: Process Modeling and Experimental Validation

The successful application of poly(N-vinylcaprolactam)-based microgels requires a profound understanding of their synthesis. For this purpose, a validated process model for the microgels synthesis by precipitation copolymerization with the cross-linker N,N′-methylenebis(acrylamide) is formulated. Unknown reaction rate constants, reaction enthalpies, and partition coefficients are obtained by quantum mechanical calculations. The remaining parameter values are estimated from reaction calorimetry and Raman spectroscopy measurements of experiments with different monomer/cross-linker compositions. Because of high cross-propagation reaction rate constants, simulations predict a fast incorporation of the cross-linker. This agrees with reaction calorimetry measurements. Furthermore, the gel phase is predicted as the major reaction locus. The model is utilized for a prediction of the internal particle structure regarding its cross-link distribution. The highly cross-linked core reported in the literature correspon.
Combined use of probiotics and other active ingredients in broiler production during free antibiotic period-an update review

Sugiharto, S. (2021). Combined use of probiotics and other active ingredients in broiler production during free antibiotic period an update review. Bulg. J. Agric. Sci., 27 (4), 667–676 Probiotics has gaining a great attention from broiler producers during the post-antibiotic era. The application of such bioactive substance is actually expected to safely substitute the use of antibiotic growth promoters in broiler production. Yet, their efficacy as in-feed antibiotic substitute for broiler chickens is erratic. The combined use of probiotics and other active compounds, such as prebiotics, phytobiotics, enzymes and organic acids, is subjected to improve the potential of probiotic in promoting the growth and wellbeing of broiler chickens. The synergistic or complementary effect between probiotics and other active ingredient would be greatly beneficial for the production and health of broilers more than either supplement administrated on its own. This review aimed to update the use of probiotics simultaneously with other active compounds in broiler production. The possible synergistic effect between probiotics and its counterpart on broiler production is also investigated in this present review. Overall, some studies reported that the combined administration of probiotics and other active ingredients resulted in synergistic or complementary effects, while other studies pointed out no mutual supportive effect between probiotics and its counterpart on broiler production.
A Similarity Score Model for Aspect Category Detection

Aspect-based Sentiment Analysis (ABSA) aims to extract significant aspects of an item or product from reviews and predict the sentiment of each aspect. Previous similarity methods tend to extract aspect categories at the word level by combining Language Models (LM) in their models. A drawback for the LM model is its dependence on a large amount of labelled data for a specific domain to function well. This work proposes a mechanism to address labelled data dependency by a one-step approach experimenting to decide the best combinatory architectures of recurrent-based LM and the best semantic similarity measures for fostering a new aspect category detection model. The proposed model addresses drawbacks of previous aspect category detection models in an implicit manner. The datasets of this study, S1 and S2, are from standard SemEval online competition. The proposed model outperforms the previous baseline models in terms of the F1-score of aspect category detection. This study finds more relevant aspect categories by creating a more stable and robust model. The F1 score of our best model for aspect category detection is 79.03% in the restaurant domain for the S1 dataset. In dataset S2, the F1score is 72.65% in the laptop domain and 75.11% in the
Oppression in the “Happy” Multicultural Land in Zadie Smith’s White Teeth

Zadie Smith’s White Teeth (2000) is a complex and paradoxical work since it presents a portrayal of England in the late twentieth century employing characters from various racial and religious groups. The novel focuses on the relationships between three families: the Bangladeshi and Muslim Iqbals, the English-Jamaican Joneses, and the Jewish-British Chalfens. It depicts a multicultural society, yet it also reflects on the oppression experienced by certain characters, who are marginalized due to their differences from mainstream society. This raises the question whether Smith’s novel celebrates or criticizes the discourse of multiculturalism. This study considers the novel’s attitude towards multiculturalism through the representation of oppression. It aims to explore the theme of oppression with regard to the issues of race, religion, gender, and sexual orientation because these intertwined categories determine an individual’s sense of self and the social relations between different groups. In light of Tariq Modood’s conception of multiculturalism, which underlines the importance of some principles, such as the recognition of the other, positive difference, equality, and a more inclusive version of national identity, this study argues that the novel does not seem optimistic in its treatment of multiculturalism because various kinds of oppression, such as racial discrimination, violence, stigmatization, and indifference, haunt the lives of the marginalized or disempowered characters and trigger counter-attacks from the oppressed group. While impeding the other’s integration into society, this situation also poses a threat to the social order. This reveals that a multicultural society, which embraces all differences and cherishes this diversity, is a dream difficult to be realized in England as portrayed in the novel.
IDENTIFICATION AND ASSESSMENT OF A NONLINEAR DYNAMIC ACTUATOR MODEL FOR GUST LOAD ALLEVIATION IN A WIND TUNNEL EXPERIMENT

The actuator dynamics of an active load alleviation system for a low speed wind tunnel model is investigated. For the design of the control law a model, consisting of aerodynamics, structural dynamics and actuator dynamics is required. While methods for modeling of aerodynamics and structural dynamics exist, an equivalent model for the actuator must be determined experimentally. A nonlinear actuator model is derived and its parameters are identified. The impact of nonlinearities on the control performance is quantified in simulations.
Ray-traced Shell Traversal of Tetrahedral Meshes for Direct Volume Visualization

A well-known method for rendering unstructured volumetric data is tetrahedral marching (tet marching), where rays are marched through a series of tetrahedral elements. Rowever, existing tet marching techniques do not easily generalize to rays with arbitrary origin and direction required for advanced shading effects or non-convex meshes. Additionally, the memory footprint of these methods may exceed GPU memory limits. Interactive performance and high image quality are opposing goals. Our approach significantly lowers the burden to render unstructured datasets with high image fidelity while maintaining real-time and interactive performance even for large datasets. To this end, we leverage hardware-accelerated ray tracing to find entry and exit faces for a given ray into a volume and utilize a compact mesh representation to enable the efficient marching of arbitrary rays, thus allowing for advanced shading effects that ultimately yields more convincing and grounded images. Our approach is also robust, supporting both convex and non-convex unstructured meshes. We show that our method achieves interactive rates even with moderately-sized datasets while secondary effects are applied.
“Don’t discuss”: Investigating Semantic and Argumentative Features for Supervised Propagandist Message Detection and Classification

One of the mechanisms through which disinformation is spreading online, in particular through social media, is by employing propaganda techniques. These include specific rhetorical and psychological strategies, ranging from leveraging on emotions to exploiting logical fallacies. In this paper, our goal is to push forward research on propaganda detection based on text analysis, given the crucial role these methods may play to address this main societal issue. More precisely, we propose a supervised approach to classify textual snippets both as propaganda messages and according to the precise applied propaganda technique, as well as a detailed linguistic analysis of the features characterising propaganda information in text (e.g., semantic, sentiment and argumentation features). Extensive experiments conducted on two available propagandist resources (i.e., NLP4IF’19 and SemEval’20-Task 11 datasets) show that the proposed approach, leveraging different language models and the investigated linguistic features, achieves very promising results on propaganda classification, both at sentence- and at fragment-level.
Reproducing: Parameterized Explainer for Graph Neural Network

1. The PGExplainer is able to correctly identify the ground-truth motif responsible for node and graph classifica4 tion of a given GNN. 5 2. The PGExplainer is able to achieve a maximum AUC of 0.987 for node classification and a maximum AUC of 6 0.926 for graph classification, both with a standard deviation that is a maximum of 0.021. 7 3. The PGExplainer is able to generate explanations for the given node classification tasks in 24 milliseconds or 8 less, and graph classification tasks in 80 milliseconds or less. 9