Miracle-dz/UniFAR-FTUs huggingface dataset:
In Search of Airworthy Trailing-Edge Noise Reduction Means

The EC co-financed project OPENAIR aims at a further development of both innovative and established aircraft noise reduction technologies. Among these activities an innovative two-component trailing-edge (TE) design, applicable at a slat TE, was evaluated through generic tests in DLR's Acoustic Wind-Tunnel Braunschweig(AWB). The proposed design combines a supporting frame structure (a coarse metal mesh or rib structure) with a thin, hydraulically smooth cover material (a fine metal mesh, micro-perforated sheet metal or cloth material) which are both permeable to the flow. The result is a mainly hollow, flow-transparent TE region. Variants of this concept were parametrically tested versus a solid reference TE at a 0.4-m chord generic airfoil. Material selection was based on airwor- thiness considerations. Detailed flow/acoustic resistance measurements were performed to characterise the used materials. TE noise was measured by a directional microphone system. The tested TE modifications achieve a broadband noise reduction of up to 4 dB, de-pendent of the configuration. However, the noise reduction effect diminishes with growing angle-of attack. This adverse behavior as well as geometrical dependences will have to be further studied prior to large scale testing. Pressure distribution measurements reveal a non-measurable to small effect of the TE modifications on the airfoil's suction peak. Basic noise scaling laws for transposition of the results to full-scale applications are suggested.
Malay Tweets: Discovering Mental Health Situation during COVID-19 Pandemic in Malaysia

During the unprecedented of COVID-19 pandemic, numbers of research had been conducted on mental health in social media worldwide. Past research has shown interest in Twitter sentiment analysis by using keywords, geographical area, and range of ages. Up to the authors’ analysis, there is no research conducted on mental health using keyword in the case of Malaysia. A Malay Tweet dataset was built for analysing mental health tweets during the first Movement Control Order period using unique keywords. Machine learning algorithms namely, Naïve Bayes classifier and Support Vector Machine were used to predict the sentiment of tweets. The classifiers were evaluated using 10-fold cross-validation, accuracy, precision, and F1-score. The data then visualized in charts and WordCloud. The results shows that Support Vector Machine performed better than Naïve Bayes classifier for both test set and 10-fold cross-validation in terms of performances in n-gram TF-IDF. The visualized data could provide insights to the authority pertaining the mental health issues, in which it relates to local news and situations during the periods.
Optimum Load-Frequency Continuous Control with Unknown Deterministic Power Demand

Since the incremental power demand in a power system is not always apriori known, direct application of the optimum linear- state regulator to load-frequency control is not possible. Furthermore, load-frequency control generally requires the use of an integral type control operation to meet the system operating specifications. This requirement is introduced into the formulation of the optimum load- frequency control problem presented in this paper.
Multilevel simulation-based co-design of next generation HPC microprocessors

This paper demonstrates the combined use of three simulation tools in support of a co-design methodology for an HPC-focused System-on-a-Chip (SoC) design. The simulation tools make different trade-offs between simulation speed, accuracy and model abstraction level, and are shown to be complementary. We apply the MUSA trace-based simulator for the initial sizing of vector register length, system-level cache (SLC) size and memory bandwidth. It has proven to be very efficient at pruning the design space, as its models enable sufficient accuracy without having to resort to highly detailed simulations. Then we apply gem5, a cycle-accurate micro-architecture simulator, for a more refined analysis of the performance potential of our reference SoC architecture, with models able to capture detailed hardware behavior at the cost of simulation speed. Furthermore, we study the network-on-chip (NoC) topology and IP placements using both gem5 for representative small- to medium-scale configurations and SESAM/VPSim, a transaction-level emulator for larger scale systems with good simulation speed and sufficient architectural details. Overall, we consider several system design concerns, such as processor subsystem sizing and NoC settings. We apply the selected simulation tools, focusing on different levels of abstraction, to study several configurations with various design concerns and evaluate them to guide architectural design and optimization decisions. Performance analysis is carried out with a number of representative benchmarks. The obtained numerical results provide guidance and hints to designers regarding SIMD instruction width, SLC sizing, memory bandwidth as well as the best placement of memory controllers and NoC form factor. Thus, we provide critical insights for efficient design of future HPC microprocessors.
Comparison of DI and JI lateral IGBTs

High voltage DI LIGBTs using the RESURF principle have been fabricated in thin silicon layers. Their electrical characteristics are compared to JI-LIGBTs simultaneously fabricated in silicon epi-layers. Three LIGBT structures were examined, namely, the conventional LIGBT, the collector-shorted LIGBT, and the hybrid Schottky LIGBT. The forward voltage drop of all three structures in DI was found to be slightly higher than that of the corresponding structure in JI. However, the DI devices were observed to be faster by an order of magnitude than JI. In addition, a shorter turn-on pulse has been found to decrease the turn-off time for both DI and JI devices.
The effect of offset voltage on the kick-out pulses used in the nose-to-nose sampler impulse response characterization method

The amplitude and bandwidth of kick-out pulses used in the nose-to-nose sampler impulse response characterization method were measured as a function of offset voltage. The amplitude is almost linear for offset voltages from -500 mV to 500 mV except for values from about -50 mV to 50 mV. Slight changes in bandwidth were observed for offset voltages from -250 mV to 250 mV with significant bandwidth loss observed for offset voltages outside this range.
Influence Prediction on Social Media Network through Contents and Interaction Behaviors using Attention-based Knowledge Graph

This paper presents a model for predicting the influence of information in social media networks. Given the content, the proposed model aims to approximate the influence of one user on another by learning from both user's interaction behaviors and the vast amount of content created on the network and combining with the state-of-the-art graph convolutional and attention-based methods. We compare the performance of the proposed approach with other popular methods on one dataset, manually collected from Facebook and including the real-world interactions and contents produced by users. The experimental results show that our approach could bypass other techniques with competitive results and have more scalability for applying in real-world applications, especially in influencer and content marketing campaigns.
A Bio-Inspired Strategy for Robotic Fish Swimming in Unsteday Flows

Fish can swim swiftly in complicated flow environments, which conceives inspirations for man-made underwater vehicles. The paper concentrates on some bio-inspired strategies to enable robotic fish better adaptability within changing environments. An adaptive neural method corresponding to environment is proposed and developed with a pair of coupled neural oscillators. A parameters forecasting algorithm is also designed. On the other hand, a notional four joints robotic fish is designed to validate the effectiveness of the model. Simulation results show that the proposed algorithms predict the altering kinematics parameters exactly and improved model can depict the fishs adaptable behaviors. Therefore the effectiveness is further validated for potential applications into robotic fish.
Identifying Audio-Visual Familiarity Effects on Emotion via Directed Functional Connectivity

Some studies have reported that audiovisual stimuli have a significant influence on generating human emotions. In this paper, we propose to adopt directed functional connectivity to identify how emotions, in terms of high valence (HV) and low valence (LV), are affected by familiar/unfamiliar music videos. The current study applied Directed Transfer Function (DTF) to estimate connectivity between each pair of channels, followed by theoretical graph analysis (e.g., degree and strength). Our results showed that watching familiar/unfamiliar musical videos had a significant impact on emotions. First, HV showed greater functional connectivity during familiar conditions, while LV revealed stronger functional connectivity for unfamiliar tasks within the alpha and beta bands. Second, in the beta band during unfamiliar conditions, increased outflows of LV were identified at the right central, and enhanced inflows at the left frontal.
Determinants of Stated and Revealed Mental Map Quality: An Empirical Study

This paper presents the results of an empirical study into the role of travel behaviour and socio-demographic factors as determinants of mental map quality. Several interesting findings are reported. In line with previous research, conducted in quite different urban contexts, the study finds that travelling by means of active modes, requiring active navigation of the traveller, leads to higher quality mental maps. Strong effects are found for both the car and bicycle modes (relative to the more passive bus-mode). Furthermore, there appears to be a rather strong correspondence between the stated (or: perceived) and revealed (or: actual) quality of people's mental maps. This correspondence is particularly strong among women and non-residents of the study area.
Driver behaviour when using an integrated advisory warning display for advanced driver assistance systems

With the increasing amount of safety features that are being introduced in our vehicles, research on warning design has suggested that advisory warning information may benefit driving performance. This simulator driving study compared driver's performance using an integrated advisory advanced driver assistance system (ADAS) display based on ecological interface design (EID) combined with critical warnings to three ADAS with warnings of a critical character only. Results show that drivers drove with safer distances to vehicles in front when they received combined advisory/critical warnings compared to critical warnings only. Further, participants maintained better lane positioning during both the critical and combined ADAS conditions compared to baseline driving. In addition, participants found the combined warnings made them more aware of the traffic situation than when driving with critical warnings only and that the display helped them notice potential dangers in the traffic environment. These results suggest that providing drivers with advisory ADAS information can be a good complement to the critical warnings found in vehicles today and that a combination of these warnings, if correctly designed, may benefit both driver performance and driver acceptance.
Poster: Private Internet: A Global End-to-End Service Model

The public Internet is a network of autonomously owned and operated networks. Outdated peering policies and lack of end-to-end performance guarantees are causing its ossification which have led large cloud and content providers to build their own global private backbone infrastructures. As much as these private backbones help eliminate public transit for content hosted across their networks, content hosted elsewhere is still carried over the public Internet. In this poster, we propose a model where these private backbone operators collaborate with the access-networks of content providers and consumers to implement end-to-end network services with better performance characteristics than the public Internet. We call the resulting end-to-end service domain as a "Private Internet".
The importance of raising e-safety awareness amongst children

The Internet is being used by different age generations. More people are becoming involved in online activities than in the past, regardless of their age. However, when comparing different age groups, it can be concluded that the younger generation has shown a higher percentage of utilization regarding online activities. Today, most mobile phones, game consoles and even various television sets can access the Internet. Parents should understand that when buying children mobile phones, they are giving them the worldwide access at their fingertips. Mobile phones with their various capabilities can be utilized for almost anything nowadays. Using mobile phones, the Internet can be accessed substantially anytime and anywhere. Therefore, it could be seen as being more powerful than a computer. The Internet provides numerous opportunities, however users should also be aware of the associated risks. Children may not always be aware of the risks involved, and they may not have the necessary skills to keep themselves safe online. Therefore, they are not necessarily concerned about the personal information they share on social networking sites, like Facebook. A recent survey conducted at the Nelson Mandela Metropolitan University (NMMU) involving three primary and three secondary schools, in the Nelson Mandela Bay area, found that a total of 90 percent of 1594 students use social networking sites. Facebook and MXit were the preferred choice above all others. According to literature it has been found that Facebook is the second-most visited website in South Africa, with Google being number one. The objective of this paper is to convey the trends in electronic use amongst school children, the concerns and risks will also be identified. The results of the survey, done at NMMU, have established that there is a lack of formal education regarding e-Safety in Southern African schools. This shows that children should be made more aware of the dangers associated with the Internet and how to keep themselves safe online. Many parents are unaware of these dangers and they do not necessarily know how to educate their children in this regard. Therefore, this paper proposes the implementation of an extensive educational programme that can stimulate e-Safety awareness in various Southern African schools. Not only to educate the children, but the teachers and parents as well. The researchers will argue to why such an implementation will be beneficial. Keywords: Internet, Risks, Social Networking, Awareness, Education, e-Safety
Vietnamese Fake News Detection Based on Hybrid Transfer Learning Model and TF-IDF

There are a lot of studies about fake news detection on English social networks. However, Vietnamese fake news detection on social networks still limit. In this paper, we propose a new approach for Vietnamese Fake News Detection on Social Network Sites using a pre-train language model PhoBERT combine with Term Frequency - Inverse Document Frequency (TF-IDF) for word embedding and Convolutional Neural Network (CNN) for features extracting. Our proposed model is trained and evaluated on the dataset of Reliable Intelligence Identification on Vietnamese SNSs (ReINTEL) shared task. We process text data into two scenarios: raw data and processed data to elucidate the hypothesis of pre-processing data on social networks. In addition, we use the different extra features to improve the efficiency of model. We compare our proposed model with the baseline methods. The proposed model achieved outstanding results with 0.9538 AUC score on raw data.
The integration of UAVs to the C-ITS Stack

In this paper, we conceptualise and propose integrating UAVs with Intelligent Transportation Systems (ITS) based on using the Cooperative-ITS (C-ITS) framework. We start by discussing the state of the art and pinpointing some of the reasons for integration and the applications that the envisaged integration would enable. Next, we recall the critical aspects of the state of the art C-ITS connectivity and discuss how seamless integration of UAVs into C-ITS can be achieved. Notably, we show that encapsulation of UAVs in C-ITS does not imply significant changes for the currently existing mechanisms and data formats. Finally, we discuss some of the open research challenges related to the integration and operation of the integrated systems and pinpoint some mechanisms which can help to address these.
Near single-crystal electrical properties of polycrystalline HgI/sub 2/ produced by physical vapor deposition

Polycrystalline films of HgI/sub 2/ Prepared by Physical Vapor Deposition (PVD) exhibited electrical charge transport properties similar to those of single crystals. Transient charge transport (TCT) measurements were used to evaluate their electrical properties. The mobility /spl mu/, trapping time /spl tau/, and surface recombination velocity s of electrons or holes were determined by analyses of transient voltages developed across the sample in response to a drift of the corresponding charge carriers created by alpha particle absorption near one of the electrodes. Typical electron-, and hole mobilities were /spl mu//sub n/ = 88 cm/sup 2//V/spl middot/s and /spl mu//sub p/ = 4.1 cm/sup 2//V/spl middot/s, respectively; Trapping times were /spl tau//sub n/ >/spl tilde/16 /spl mu/s and /spl tau//sub p/ </spl tilde/ 3.5 /spl mu/s, and surface recombination velocities s/sub n/ /spl cong/ 1.4/spl times/10/sup 5/ cm/s and s/sub p/ /spl cong/ 3.7/spl times/10/sup 3/ cm/s. All parameters depend to a large extent on the material deposition technology. The effect of carriers being first generated in near-surface traps and then gradually released is observed.
Initial Development IoT-Based of Heart Sound Segmentation and Diagnosis System

Phonocardiogram (PCG) signal is a heart sound recording that represents first (S1) and second (S2) heart sounds which physically defined as the closure of mitral and tricuspid valves, and the closure of semilunar valves, respectively. Since the assessment of PCG signal that acquired from stethoscope is essential to be conducted for heart disease early diagnosis, numbers of work have been put into effort including computing aided methods such as classification of PCG signal abnormality, and predictive system of heart condition. This work however, proposed to develop a PCG signal acquisition device that able to segment the signal thus diagnose the heart condition within two parties: user and healthcare professionals. Initially, a heart sound sensor was used to collect the PCG signals that controlled by an Arduino Uno microcontroller. Fast Fourier transform and power spectral density were applied on the signals to find the frequency range of the normal and pathological PCG. It was found that pathological PCG signals produced higher frequency than that of the normal PCG signals. Furthermore, detection of the S1 and S2 peak location in both normal and pathological PCG signals convinced the significant difference with the presence of murmur. Apart from the detection of S1 and S2 peak’s location, power spectrum of the PCG signals were stored in Amazon Web Services (AWS) as cloud system which able to be accessed by authorized person. Hence, these outcomes have possibility to contribute to e-health system in sequence for better lifestyle.
Goal Assignment in Leader-Following Formation Control of Second-Order Multi-Agent Systems

In this paper, the goal assignment problem of second-order multi-agent systems is considered in the leader-following formation control framework. The goals of followers, which are defined as their relative positions with respect to the leader corresponding to a predefined target shape, are assumed to be interchangeable. During the operation of the multi -agent systems, the goals of a pair of followers are exchanged locally if an assignment condition is satisfied. Compared with the existing goal assignment studies utilizing the position information, the main feature of this paper is to derive a velocity-based assignment condition to deal with the assignment problem of second-order multi-agent systems. Based on the proposed goal assignment algorithm, it is verified that the transient leader-following formation control performance is improved in the sense of Lyapunov. Simulation results are presented to demonstrate the effectiveness of our theoretical results.
Efficiently Vehicle Route Planning based on Metaheuristic Algorithm in 5G

Navigation is an important function when we want to travel or reach a new place. Although the navigation can lead the people to go to the destination, the user always hopes that it can fast to achieve the site. However, the situation on the road is unpredictable, so that the vehicle routes need to adjust in real-time. Fortunately, the concept with mobile edge computing (MEC) and vehicle to anything (V2X) in the fifth-generation wireless network (5G), that can help us to achieve the goal. In this paper, we take the achieved destination time of vehicle, vehicle route, and retransmission times for network package into account for the multi-objective optimization (MOO) problem in 5G. Then, we through the Efficiently Vehicle Route Planning based on simulated annealing algorithm (EVRPSA) to find the best vehicle route. The simulation results show using our method can planning the vehicle route efficiently.
A Meta-Model for Test Case Reduction by Reducing Cyclomatic Complexity in Regression Testing

There is a rapid expansion in software and web applications. Software may have different components and a particular component of a software may have specific functionality. We perform software testing to check the functionality of different software aspects by designing different test cases. Software testing is difficult to perform, which mostly is conducted in inappropriate way. While performing white box testing of a software components, we face difficulties as it is very time consuming due to the high cyclomatic complexity. This paper will help reduce cyclomatic complexity i.e., with focus on developing a metamodel for reducing cyclomatic complexity of software under test and ways to reduce test cases in white box testing by reducing conditionality.
Design and fabrication of passive wireless sensor array system using composite coding resonant SAW transducer

This paper presents a novel composite SAW (surface acoustic wave) passive wireless sensor system involving a resonator and a delay line. While the interrogational signal is a sinusoidal burst, the response is a delayed and damped oscillation. The frequency and the delay time of response are related to the measurand and the coding of the sensor element, respectively. The composite sensor consists of a SAW resonator and a delay line. It combines the advantages of these two devices and can be used as elements of multiple sensors for longer distance passive wireless measurements. As the wireless sensing response is weak and transient, in order to get the response with the maximum signal-to-noise ratio, the interrogational frequency is designed to be adjustable according to the result of frequency estimation. As a result, an optimal sensing result is achieved. In the transceiver set-up, the software DDS (direct digital synthesis) source with a rather high resolution is implemented to track the passive wireless sensor. An isolated switch is set in transmitter to depress the correlation leakage noise after switching off the wireless RF (radio frequency) interrogation signal. In this paper, the characteristics of the response, the working procedure of the signal processing, sensor temperature test results and the system error analyses are elaborated. A prototype instrument is built. Experimental results show the effectiveness of the instrumentation and the advantages of the composite sensor system.