Miracle-dz/UniFAR-FTUs huggingface dataset:
Cooperation Between Europe and Asia in Active Learning in Engineering Education

Worldwide, companies face a shortage of engineering and technology professionals with the right skills and competences. On one side, this is the result of a low number of candidates for those academic careers and, therefore, a low number of graduates. But, on the other side, it is also a result of the mismatch between the competences acquired in the university and those required for a professional practice. Engineering higher education is not seen by potential candidates as a motivating career, in some cases because it is seen as very hard and difficult career, also due to gender stereotypes but in most cases because potential students think that the learning methodologies in engineering courses do not fit their learning styles. It is therefore important that Engineering institutions implement new learning methodologies based on active learning processes, where the student is the center of the process. In this article we present an initiative that is currently being implemented by a network of European and Southeast Asian universities to foster the uptake of active learning in Engineering. This framework combines local laboratories designed and dedicated to active learning practices with remote collaboration through a virtual community of practice.
Multi-Port Hybrid DC Circuit Breaker for DC Distribution Network

The two-port hybrid DC circuit breaker (TP-HCB) combines the advantages of mechanical DC circuit breaker (DCCB) and solid-state DCCB, which has small loss during normal operation and fast action speed. However, the TP-HCB contains many IGBTs to withstand transient breaking voltage, therefore the total cost of TP-HCB is relatively high. In order to solve this problem, a new multi-port hybrid DC circuit breaker (MP-HCB) topology is proposed in this paper, the cost of which is much smaller than the total cost of separated TP-HCBs configured on each line connected to the DC bus. The control strategies of the MP-HCB in line fault, bus fault and fast-mechanical switch (FMS) failure are analyzed. The simulation results verify the feasibility of the proposed topology.
InP HBT technology for THz applications

InP-based electronic technologies are well suited for THz applications due to the combination of high electron velocity and breakdown field in this material system. Today's highest frequency circuits are built from InP HEMT devices, exceeding 1 THz application frequency. The InP heterojunction bipolar transistor (InP HBT) has high potential for further development in the THz frequency range through scaling and process development. A lack of circuit complexity in InP electronic circuit technology compared to CMOS can be mitigated by heterointegration. The concept of vertical integration is of particularly high interest for THz phased arrays.
Analysis and Interpretation of Global Air Quality

The mixture of solid particles and gases is air pollution. Sot, smog, mercury, plumage, dioxins, carbon dioxide etc, emissions of gas / carbon, vehicle fuels, industrial emissions could be the pollutants of air. These pollutants are the main cause for lung damage, kidneys, brain inhalation, eyes and throat irritation. If a significant amount of carbon dioxide plays a role in air pollution, it can seriously damage life. It is a greenhouse gas that allows the atmosphere to burn. This affects most people who work outside. Based on the reasons explained, air pollution must be controlled and air quality improved. However, in reality, we can not stop plying vehicles, industry and air pollution completely, but we can try to reduce emissions and therefore reduce the impact to make things better. Air pollution reached critical levels at the end of the 20th century and continues to grow even in the 21st century. Although the governments have taken several steps to reduce air pollution, a great deal still needs to be done to monitor contaminants. In this paper, we have attempted to classify the top 10 countries that emit large amounts of carbon dioxide from different sources. These include both developed and developing countries.
Malware Detection using Hybrid Autoencoder Approach for Better Security in Educational Institutions

The development of malware that continues to increase is one of the severe challenges experienced by various sectors, especially in the education sector. Educational institutions that provide open networks and connected to many devices simultaneously become an exciting testing ground for cybercriminals. Anti-virus is often used as prevention by applying signature-based detection of specific tiles contained in the database. Unfortunately, because much new malware continues to grow, the detection of the database becomes inaccurate. Therefore, automatic detection has been carried out using Autoencoder hybridized with ANN and CNN approaches. It will be developed using Python programming language with computer specification of 16GB RAM and Processor i7-7500U. Samples used are malware dataset obtained from various types of repositories such as virussign.com, the Zoo, and certain libraries from researchers. The dimensions of samples will be reconstructed using Autoencoder to generate new values that will be used as input on ANN and CNN. This research also has been developed Principal Component Analysis as a comparison architecture. Those approaches provide outstanding results in detecting malware, scilicet PCA-ANN with an accuracy of 0.985, PCACNN with an accuracy of 0.963, Autoencoder -ANN with an accuracy of 0.994, and Autoencoder -CNN with an accuracy of 0.970. Therefore, those approaches can be used as reference in increasing the need for educational institutions to improve their security from malware by detecting tiles that will be sent or read by each user.
Consumer-Led Transition: Australia's World-Leading Distributed Energy Resource Integration Efforts

It's a sunny spring DAY in South Australia. A light breeze is cooling the coastal state capital of Adelaide as approximately 260,000 distributed solar photovoltaic (D-PV) systems on residential and business rooftops generate electricity, setting a new state record for the lowest minimum electrical demand for the third time this season. All looks peaceful throughout the suburbs. D-PVs form an irregular yet persistent patchwork across one-third of the houses in the state. Most consumers are going about their day without a glance at the D-PV panels on these roofs. However, the mild temperature and bountiful sunshine lead the D-PV generation to climb, causing the voltage to creep higher and power to flow in reverse across large swathes of the distribution network. Some D-PVs are tripping off, unbeknownst to their owners and the local network operator.
Imaging as a non-intrusive tool in quantifying the dynamics of liquid sheets

Non-intrusive techniques of flow measurement have gathered attention in quantifying the dynamics of liquid sheets over a long period of time. Among those, imaging and further post processing to extract useful information of motion of sheets have been extensively used. The current study is an experimental analysis of a planar liquid sheet using two non-intrusive imaging techniques – Manual tracking (M.T) and Feature Correlation Velocimetry (FCV). The advantages of using the cross correlation of successive images over manual tracking have been detailed. The study shows that even though the results obtained from manual tracking are prone to errors, but still the method can be considered as a sufficient tool in giving an estimate of the sheet velocity.
Smart Energy Meter and Digital Billing System for Bangladesh

Digitalization is very important in all sector of a developing country. A digital smart energy meter can reduce the harassment of a consumer and effort of vendors over the traditional physical energy meter reading and billing process. This paper presents a very effective solution for this problem with a smart energy meter and digital billing system. This energy meter can measure the real-time consumed energy and store this data into an SD card. For determining the consumed energy different electrical parameters such as AC voltage, the current, phase angle is measured against real-time. It can be implemented in both the prepaid and postpaid billing system. The proposed energy meter has a 20*4 LCD for understating the consumed energy or remaining energy to consumers. A GSM modem is integrated with the system that allows the vendor to inquire about consumed energy and making digital billing without errors. The main power passes through a relay to the consumer. The vendor can cut off or on the consumer's power supply by triggering relay via SMS. By implementing this smart energy meter, the vendor can ensure the proper use of energy. That will be a huge improvement on the national power grid. This smart energy meter is developed by using low-cost components that are available at the local market.
ZnO Nanorod FET Biosensors With Enhanced Sensing Performance: Design Issues for Rational Geometry Selection

ZnO nanorod field effect transistor (FET) biosensors enable ultrasensitive, rapid and label free detection of biomolecules. However, the fabrication of these nanorods without any design guideline results in poor signal to noise ratio, limiting their commercial deployment. The various forces operating within the spacing of the nanorods may prevent complete penetration of the liquid for large aspect ratios and hence mere enhancement of the geometric surface area may not yield the optimum output which indicates the intricacies involved in the design of such sensors. The present work consistently models the analyte and the device regions of the sensor by transforming the understanding of the transduction mechanism of biomolecule capture in nanowire FETs into nanorod FET structure and integrating the spacing dependent liquid penetration depth along with the various temporal fluctuations of the sensor to enhance the signal to noise ratio (SNR) and lower the molecule detection limit(MDL). Simulation results, verified experimentally for prostate specific antigen (PSA) shows that the optimal geometry does not correspond to the maximum surface area. Instead it is dependent on the developed surface potentials after receptor immobilization and ligand capture which vary non-monotonically with nanorod radius due to nonlinear dependence of buffer penetration for high aspect ratios. This approach has significantly increased the SNR leading to reliable quantification of PSA in human serum with MDL reduced by almost three orders of magnitude in comparison to recent reports. In summary, this work brings the ZnO nanorod sensors a step closer towards practical application for early diagnosis.
Reversible Data Hiding in Encrypted Images Based on Reversible Integer Transformation and Quadtree-Based Partition

This paper presents an improved secure reversible data hiding scheme in encrypted images based on integer transformation, which does not need using a data hider key to protect the embedded secret data. We first segment the original image into blocks of various sizes based on the quadtree-based image partition. For each block, we reserve <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> least significant bits (LSBs) of each pixel as embedding room based on the reversible integer transformation. In order to improve the security of the image encryption, we pad the <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>LSBs of each pixel using the corresponding (8-<inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>) most significant bits (MSBs) information after the transformation, which protects the security of the encryption key. Then, we encrypt the transformed image with a standard stream cipher. After the image encryption, the data hider embeds the secret data in the <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula>LSBs of the encrypted images through an exclusive or operation. On the receiving side, the receiver can extract the secret data after the image decryption and recover the original image without loss of quality. The security analysis shows that the proposed scheme improves the security weakness of the scheme directly using adaptive integer transformation. The experimental results show that the proposed method achieves a higher embedding ratio compared with several relevant methods.
Design Theory of a Parallel-Plate Coupler for Underwater Wireless Power Transfer

The design theory of a coupler with two pairs of parallel plates for underwater wireless power transfer is summarized in this paper. The accurate prediction of the power transfer efficiency by separating the $kQ$ product into the coupling coefficient $k$ and Q-factor is a difficult task when transmitting power in a high-permittivity medium, such as water, or a high-conductivity medium such as seawater. Two cases are introduced; the pseudo-coupling coefficient $k$ for fresh water and the pseudo-$kQ$ product for seawater, respectively, are adopted.
Modified BER Test for SAR ADCs

This paper presents a new post-processing method to estimate the real bit error rate (BER) of successive approximation register (SAR) analog-to-digital converters (ADCs) based on the conventional test scheme. Conventional testing method acquires BER based on difference between two measured output codes, rather than between a measured output code and its corresponding ideal one. This makes the resulting BER have a wrong trend with increasing sampling speed of ADC. Therefore, this work analyzes the difference between these two cases and proposes a simple post-processing method to obtain a more realistic BER based on the conventional BER test scheme. The experimental results demonstrate the proposed method can effectively obtain the correct BER trend for a SAR ADC.
Wireless Charging Systems for Electrical Vehicle Batteries

At present, one of the challenges in the design and analysis of wireless charging systems for electric vehicle batteries is to analyze and develop an efficient model for the dynamic charging of electric vehicle batteries while the car is on the move. This paper presents the simulation and analysis of a wireless charging system for electric vehicles, where the charging system uses the inductive coupling circuit in various configurations (open circuit, with magnetic flux concentrators made by ferrite, coils arranged on the ferrite surface or embedded in the ferrite). Using the 2D FLUX software application, there are identified the coils electrical parameters and based on these parameters, there are built the equivalent two-port circuits for the two resonators. These equivalent circuits allow the analysis of the wireless power transfer systems using specialized software for electric circuit simulations, like SPICE, CADENCE, SYSEG, SCAP.
Testing the effects of a century of fires: Requirements for post‐fire succession predict the distribution of threatened bird species

Managing fire is critical for the conservation of biodiversity in many ecosystems globally. To manage fire effectively, it is necessary to identify the temporal and spatial scales at which it affects a diverse range of species. This information is challenging to obtain for rare and threatened species for which data often are sparse, and in systems with long fire‐return intervals (e.g. >100 years). We tested the effects of a century of fires on the distribution of 12 threatened bird species across a 100,000 km2 region in which “long‐unburnt” vegetation has been identified as important for the diversity of common species.
Mitigation Technique for Black hole Attack in Mobile Ad hoc Network

Mobile Ad hoc Network is a very important key technology for device to device communication without any support of extra infrastructure. As it is being used as a mode of communication in various fields, protecting the network from various attacks becomes more important. In this research paper, we have created a real network scenario using random mobility of nodes and implemented Black hole Attack and Gray hole Attack, which degrades the performance of the network. In our research, we have found a novel mitigation technique which is efficient to mitigate both the attack from the network.
Performance Analysis of Feedback Field-Effect Transistor-Based Biosensor

To speed up the performance of the device with scaling down the physical size, steep switching has become the major concern for reduction in subthreshold slope. In this paper, in order to achieve steep switching, the subthreshold slope has been obtained~5mV/decade by introducing the feedback field-effect transistor (FBFET) based biosensor which utilizes the positive feedback mechanism in the device. The reduction in the subthrshold slope of the proposed biosensor leads to detection of biomolecules such as biotin, and biotin-streptavidin at the rapid response with higher sensitivity. This detection of biomolecules has been carried out by creating the cavity at the source end. With the immobilization of biotin-streptavidin in the cavity about 75% of the sensitivity has been achieved. In addition to this, we have also studied the impact of cavity parameter modulation on the drive current and on its sensitivity. Further, we have compared the transfer charcteristics and the sensitivity of conventional dielectric modulated FET with the proposed device at different dielectric constant and the negative charge density of biomolecules which shows that proposed FBFET has higher sensitivity than conventional DM-FET. Furthermore, the fabrication process of the proposed device has been included which shows that it can be fabricated with simple steps without any complexity and at lower cost.
Probabilistic Cache Placement in UAV-Assisted Networks With D2D Connections: Performance Analysis and Trajectory Optimization

With the exponential growth of data traffic, caching is regarded as a promising solution to combine with unmanned aerial vehicle (UAV)-assisted networks, which can offload cellular traffic and improve the system performance. Moreover, the cache capacity at user side can be leveraged, e.g., through local data storage or device-to-device (D2D) sharing. In this paper, we focus on the performance analysis and trajectory optimization of cache-enabled UAV-assisted networks with underlaid D2D communications. We consider both static and dynamic UAV deployments. For static UAV deployment, we first formulate an optimization problem to design the cache placement in order to maximize the cache hit probability. Then, the successful transfer probability (STP) and sum-rate are analyzed by using stochastic geometry, and their closed-form expressions are derived. For dynamic UAV deployment, the UAV moves over the cell and stops at several path points to serve users. To shorten the time required for the UAV to cover all users, a spiral algorithm is proposed to optimize the UAV trajectory, aiming at minimizing the number of UAV path points. Moreover, since at different locations, the UAV communication will incur different interference on D2D users, we derive the outage probability for the D2D users. Simulation results show the significant performance gain of our proposed probabilistic cache placement over existing strategies. For a given user density, we show that the optimal values for the UAV height which lead to the maximum UAV-STP and sum-rate exist.
Entrepreneurial and Commercialization Pathway through Project-based Learning in Higher-Education

Digital disruption creates a lot of new entrepreneurship opportunities, affecting existing businesses at a very fast pace. Therefore using traditional classroom method to teach entrepreneurship to only business schools students no longer applicable. Students in the 21st century should be trained via project-based learning by leveraging the strength of the members from multi-disciplines. This research proposes a model on how entrepreneurship education (EE) could be introduced into university undergraduate programs across faculties towards entrepreneurial and commercialization pathway. The model has been developed and tested within 2 years, with few hundreds of computing and information technology students, supported by other faculties, related centers and representatives from the industry. It is believed that project-based learning does not only affect students’ attitudes to be more industry-relevant and stimulate entrepreneurial intention, but also creating actual start-up and commercialization opportunities.
A Comprehensive Analysis on Undergraduate Student Academic Performance using Feature Selection Techniques on Classification Algorithms

Educational Data Mining (EDM) is a growing research field that is applied to analyze and predict student's academic performance and makes intervention approaches to elevate that performance. It is a field of study, which is related to various attributes for analysis student's details such as name, attendance, class test, lab test, spot test, assignment and result in the educational institution. In this study, we mainly focus on calculating the academic performance of undergraduate students with a predictive data mining model by using feature selection techniques with classification algorithms. Feature selection techniques are introduced on the data preprocessing process to find the most inherent and important attributes so that we analyze and evaluate the student's better performance by using classifiers with those selected attributes. For this purpose, we collected 800 student's records of the final year, studying at the undergraduate level of the department of Computer Science and Engineering from North Western University, Khulna. Here, we used and evaluated the performance of four feature selection methods: genetic algorithms, gain ratio, relief, and information gain and five classification algorithms: K-Nearest Neighbor, Naïve Bayes, Bagging, Random forest, and J48 Decision Tree. The experimental results depict that Genetic algorithms method provides the best accuracy 91.37% with KNN classifier.
Improved Signal Models for Nuclear Quadrupole Resonance Spectroscopy

One of the applications of nuclear quadrupole resonance spectroscopy is the detection of prohibited substances in security checkpoints. Numerous signal processing and analysis techniques have been proposed over time to improve detection. However, they are based on signal models that do not exactly resemble the spin echo shape obtained in real measurements. This work represents a comparative study of several signal models for obtaining a more realistic representation of a spin echo response, that can be used in the future development and simulation of signal processing and analysis techniques for nuclear quadrupole resonance detection.
Muscle Activation Patterns Estimation during Repeated Wrist Movements from MRI and sEMG*

Functional electrical stimulation (FES) is a widely used method to bypass spinal chord damages and bring the neurological input to muscles. FES methods that allow the activation of both superficial and deep muscles were proposed in the literature. However, even if many studies using surface electromyography (sEMG) for the estimation of muscles’ activation were presented, it still remains impossible to access information of deep muscles. Our group proposed a solution that exploits the morphological information of magnetic resonance imaging (MRI) and the sEMG for the estimation of the average muscles’ activation pattern during isometric muscle contractions of forearm muscles. With this work we introduce the time dimension to study how the activation patterns changes while performing 3 simple wrist movements. The study involved data collected from a single row of electrodes wrapped around the forearm of a single healthy participant. Morphological information are extracted from the MRI to build a model that is then used to estimate the muscles’ activation pattern. The results show that the method is able to provide an estimation of the muscles’ activation patterns that explain more than 93% of the input sEMG information and that have a corresponding in anatomical information from the literature.