Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Tracking: Investigation of Genetic Algorithm and LSTM as Fish Trajectory Predictors in Turbid Water

Monitoring the dynamics of fish behavior is impactful both in the research for fisheries and aquaculture production. One of the most explored approaches to monitor the fish is tracking-by-detection along with computer vision. Presently, there are several challenges in this field, including underwater environment conditions and fish movement complexity. This study presents an initial investigation towards tracking the fish by predicting the trajectory 2D coordinates of fish from the sequential sampled frames in underwater videos. Here, the authors explored the Genetic Algorithm based on natural evolution selection and the Long Short-Term Memory (LSTM) algorithm. Results have shown tolerable trajectory prediction inaccuracies using the GA and LSTM. Specifically, it obtained the Mean Absolute Percentage Error at 2.8% to 30.5% and 3.33% to 17.74% for GA and LSTM, respectively. These results have allowed the authors and researchers to extend its study towards tracking the fish using these approaches.
Odour Detection System for Allergy Sufferers

According to the World Health Organization (WHO), about 91% of the global populace live in locations with air quality levels below WHO guidelines. Although ambient air pollution impacts both developed and developing nations, low- and middle-income nations suffer the highest consequences with the highest toll experienced in the Western Pacific and South East Asia regions. Poor air quality results in odour types ranging from chemical combustion smells to fungal smells. Fungal odour is formed due to damp indoor conditions like high humidity and temperature. This damp condition produces microscopic fungi which are allergens (substances that cause allergic reactions), irritants and toxic substances referred to as mould. Inhaling or touching mould spores may cause allergic reactions like sneezing, runny nose, redness of the eyes and skin rash and even respiratory complications. In this era of a global pandemic, having a general-purpose odour detection system becomes imperative. This research, therefore, aims to design and implement an odour detection system that can alert individuals or allergic sufferers to high content of toxic gases in their surroundings or homes. The study is a valuable resource for users to measure their air quality and to support those with respiratory vulnerabilities, especially in the Covid-19 environment of today.
EM and Power SCA-Resilient AES-256 Through >350× Current-Domain Signature Attenuation and Local Lower Metal Routing

Mathematically secure cryptographic algorithms, when implemented on a physical substrate, leak critical “side-channel” information, leading to power and electromagnetic (EM) analysis attacks. Circuit-level protections involve switched capacitor, buck converter, or series low-dropout (LDO) regulator-based implementations, each of which suffers from significant power, area, or performance tradeoffs and has only achieved a minimum traces to disclosure (MTD) of <inline-formula> <tex-math notation="LaTeX">$10M$ </tex-math></inline-formula> till date. Utilizing an in-depth white-box model, this work, for the first time, focuses on signature suppression in the current domain, which provides an <inline-formula> <tex-math notation="LaTeX">$Attenuation^{2}$ </tex-math></inline-formula> enhancement in MTD, leading to orders of magnitude improvement in both power and EM side-channel analysis (SCA) immunities. Using a combination of current-domain “signature attenuation” (CDSA) along with local lower level metal routing, the critical correlated information in the crypto current is significantly suppressed before it reaches the supply pin. Especially, to prevent the EM leakage from its source (metal layers carrying the correlated crypto current acting as antennas), this work embraces lower level metal routing of the CDSA embedding the crypto-IP so that the signature becomes highly suppressed before it passes through the higher metal layers (which radiates significantly) to connect to the external pin. The 65-nm CMOS test chip contains both protected and unprotected parallel AES-256 implementations, running at a clock frequency of 50 MHz. Test vector leakage assessment (TVLA) on the protected CDSA-AES, demonstrated with on-chip measurements for the first time, shows that the higher level metal layers leak significantly more compared with the lower level metal routing. Correlational power and EM analysis (CPA/CEMA) attacks on the unprotected implementation were able to extract the secret key within <inline-formula> <tex-math notation="LaTeX">$8k$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$12k$ </tex-math></inline-formula> traces, respectively, while the protected CDSA-AES could not be broken even after <inline-formula> <tex-math notation="LaTeX">$1B$ </tex-math></inline-formula> encryptions for both power and EM SCA, evaluated both in the time and frequency domains, showing an improvement of <inline-formula> <tex-math notation="LaTeX">$100\times $ </tex-math></inline-formula> over the prior state-of-the-art countermeasures with comparable power and area overheads.
Octanol-water partition coefficients of polychlorinated biphenyl congeners

Octanol-water partition coefficients (K{sub OW}) for 13 polychlorinated biphenyl (PCB) congeners were accurately determined by the generator column technique. These values were used to confirm a highly significant linear relationship between log K{sub OW} and the logarithm of the relative retention time on a nonselective gas chromatographic stationary phase. The total surface areas (TSA) for all the PCB congeners were determined by assuming planar molecules, van der Waal's radii for component atoms, and appropriate values for solvent radius, bond angles, and distances. The TSA was highly significantly correlated with log K{sub OW} and the relationship used to calculate log K{sub OW} values for all the PCB congeners. Further development of these relationships gave an expression for aqueous solubility which can be used to calculate the solubility for these PCB's where appropriate data are available.
Scattering Mechanism and Low Temperature Mobility of MOS Inversion Layers

For the interpretation of observed low temperature mobility in n-channel inversion layers of Si MOS, two scattering mechanisms are discussed theoretically. The one is the scattering due to interface roughness and a simplified model is investigated. The other is the scattering by the charged centers. The former can explain the carrier concentration dependence of the mobility in high carrier concentration region. The latter is introduced for the interpretation of the mobility at low carrier concentration with some considerations of the charge distribution.
Periodic slip processes and the formation of polytypes in zinc sulphide crystals

Inherent deformations of ZnS polytype regions are determined by measuring angles between linear markings. The deformations are correlated to the crystallographic structures of the polytypes as well. The relations clearly indicate that polytype formation occurred by a periodic slip process after crystal growth had been completed. Further observations substantiating this model are quoted.
Analysis of the Relationship Between University Attendance and Grades by Data Mining

It has been suggested that teachers at most universities have heavy workloads; hence, they may either not be able to provide sufficient education to each student or provide education based on incorrect policies. In recent years, the use of data mining technology for extracting useful knowledge and trends from large-scale data has attracted considerable attention. Therefore, we use data mining in this study to analyze student data, understand students’ tendencies, and help teachers in educating their students. In particular, we analyze students’ attendance at a university and its relationship with their grades by determining relevant student characteristics.
Exploring the curricular content of engineering ethics education in Ireland

Our contribution aims to determine the main curricular themes employed in engineering ethics instruction. In the use of the term ‘curricular content", the study is guided by an understanding of curriculum in terms of the syllabus content of a specific discipline or set of units taught to students [1]. The research study has been conducted in cooperation with the national accrediting body Engineers Ireland and includes 23 Engineering programmes from 6 institutions in Ireland that underwent accreditation between 2017-2019. The research method employed is a documentary analysis of the materials prepared by the programmes for accreditation or made available on the website of all participant programmes. The findings reveal three themes amenable to the implementation of ethics across the curriculum (sustainability, Health and Safety, legislation), which are present in a variety of courses, such as technical courses, design courses, professional formation courses, capstone projects, legal studies courses, business studies courses, as well as in work placement. The curricular themes purporting to professional ethics, responsibility and the societal context of engineering have a strong presence in courses of professional formation, which have the role of acculturating students to the profession of engineering and its norms. Thus the main conclusion of our study highlights the need for a hybrid implementation of ethics across the curriculum as well as in dedicated single modules, in order to promote a comprehensive engineering ethics education.
Extracting features of body sway for baggage weight classification

We propose a method for extracting features of body sway to classify the weight of baggage carried by a person as heavy or light by using a video sequence of depth images. The slight swaying movement naturally occurring in the body can be measured using a video sequence of a standing person acquired using an overhead camera. We hypothesize that body sway varies with the weight of the baggage carried by a person. Our method extracts a temporal feature of body sway used to discriminate between people carrying light and heavy baggage using a frequency analysis technique. We collected a dataset of video sequences from 40 participants for an experiment to test the proposed method to classify the weight of baggage. The results confirmed that feature extraction using body sway can help classify baggage as light or heavy with an accuracy of 95%.
DockSDN: A Hybrid Container-Based SDN Emulation Tool

The next step on computer networks is based on Software Defined Networks (SDNs). The evolution of Internet-based services needs to be agile and efficient nowadays. SDNs promise to bring the previous to next-generation networks, in order to cope with the demand of millions of interconnected devices, with an ever-growing demand of bandwidth for such services. From 5G wireless networks, WiFi6 and new Internet Service Provider (ISPs) backbones, the need for a flexible and fast way to create and test new protocols and applications, push the development of SDNs and its new way of thinking about networks. Like any new technology, SDN protocols and new applications need better test-beds that are close to real environments as possible so they can be tested thoroughly enough to be deployed in production environments. Various tools have been developed over the last years aiming to do the previous, but have lacked some distinct features, limiting the scenarios and results. Our experience and approach of using containers (Dockers) and being able to provide a tool that meets current and future needs, is our biggest contribution to the community. DockSDN is presented on this work, which proposed various benefits and advantages over other tools and provides fast deployment of SDNs scenarios and that is fully scalable through local hardware available or elastic through cloud services. The scientific community will be able to test current or new SDN protocols in environments that are close to real-world as you can get.
RetinaNet With Difference Channel Attention and Adaptively Spatial Feature Fusion for Steel Surface Defect Detection

Surface defect detection of products is an important process to guarantee the quality of industrial production. A defect detection task aims to identify the specific category and precise position of defect in an image. It is hard to take into account the accuracy of both, which makes it be challenging in practice. In this study, a new deep neural network (DNN), RetinaNet with difference channel attention and adaptively spatial feature fusion (DEA_RetinaNet), is proposed for steel surface defect detection. First, a differential evolution search-based anchor optimization is performed to improve the detection accuracy of DEA_RetinaNet. Second, a novel channel attention mechanism is embedded in DEA_RetinaNet to reduce information loss. Finally, the adaptive spatial feature fusion (ASFF) module is used for an effective fusion of shallow and deep features extracted by convolutional kernels. The experimental results on a steel surface defect data set (NEU-DET) show that DEA_RetinaNet achieved 78.25 mAP and improved by 2.92% over RetinaNet. It has better recognition performance compared with other famous DNN-based detectors.
Resistivity Size Effect in Epitaxial Rh(001) and Rh(111) Layers

Rh(001) and Rh(111) layers with thickness <inline-formula> <tex-math notation="LaTeX">${d} = {8}$ </tex-math></inline-formula>–181 nm are sputter deposited onto MgO(001) and Al<sub>2</sub>O<sub>3</sub>(<inline-formula> <tex-math notation="LaTeX">${11}\bar {{2}}{0}$ </tex-math></inline-formula>) substrates and their resistivity <inline-formula> <tex-math notation="LaTeX">${\rho } $ </tex-math></inline-formula> measured <italic>in situ</italic> and <italic>ex situ</italic> at room temperature and 77 K in order to quantify the resistivity size effect. Rh(001) layers are epitaxial single crystals and show a resistivity increase with decreasing <inline-formula> <tex-math notation="LaTeX">${d}$ </tex-math></inline-formula> that is well described with the classical Fuchs and Sondheimer model, indicating an effective electron mean free path <inline-formula> <tex-math notation="LaTeX">${\lambda }_{\text {eff}} = {9.5}\pm {0.8}$ </tex-math></inline-formula> nm at 295 K. Rh(111) layers exhibit an epitaxial microstructure with two 60°-rotated domains with a lateral width of 19 ± 2 nm, as determined from the X-ray coherence length. The grain boundaries between the domains cause a thickness-independent resistivity contribution <inline-formula> <tex-math notation="LaTeX">${\Delta \rho }_{\text {gb}} = {0.74}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$0.59~ {\mu \Omega } $ </tex-math></inline-formula>cm at 295 and 77 K, indicating an electron reflection coefficient <inline-formula> <tex-math notation="LaTeX">${R} = 0.16\,\,\pm \,\,0.03$ </tex-math></inline-formula> for a boundary characterized by a 60° rotation about the <inline-formula> <tex-math notation="LaTeX">$\langle 111\rangle $ </tex-math></inline-formula> axis. Air exposure causes a nearly negligible (<6%) resistivity increase which suggests a possible reduction in the surface scattering specularity by <inline-formula> <tex-math notation="LaTeX">${\Delta } {p}_{{1}} = -{0.3}\,\,\pm \,\,0.2$ </tex-math></inline-formula> during surface oxidation. The overall results yield a temperature-independent product of the bulk resistivity times the electron mean free path <inline-formula> <tex-math notation="LaTeX">${\rho }_{o} {\lambda } =$ </tex-math></inline-formula> (4.5 ± 0.4) <inline-formula> <tex-math notation="LaTeX">$\times 10^{-{16}} \,\, {\Omega }\text{m}^{{2}}$ </tex-math></inline-formula>. This is 1.4 times larger than previously predicted from first principles, but 33%, 55%, 63%, and 11% smaller than for Cu, W, Co, and Ru, respectively, suggesting great promise for Rh as an alternative metal for narrow interconnects.
Pelee-Text++: A Tiny Neural Network for Scene Text Detection

Scene text detection has become an important field in the computer vision area due to the increasing number of applications. This is a very challenging problem as textual elements are commonly found in “noisy” and complex natural scenes. Another issue refers to the presence of texts encoded into different languages within the same image. State-of-the-art solutions rely on the use of deep neural network approaches or even ensembles of them. However, such solutions are associated with “heavy” models, which are computationally expensive in terms of memory and storage footprints, which hampers their use in real-time mobile applications. In this work, we introduce Pelee-Text++, a lightweight neural network architecture for multi-lingual multi-oriented scene text detection, especially tailored to running on devices with computational restrictions. Additionally, to the best of our knowledge, this is the first work to evaluate the performance of text detection methods in commercial smartphones. Over this scenario, Pelee-Text++ processes 2.94 frames per second and it is the only evaluated approach that did not cause memory issues on smartphones, even using an input image of $1024\times 1024$ pixels. Our proposal achieves a promising trade-off between efficiency and effectiveness, with a model size of 27 Megabytes and F-measure of 91.20%, 85.78%, 81.72%, 80.30%, 82.53% and 66.51% on ICDAR 2011, ICDAR 2013, ICDAR 2015, MSRA-TD500, ReCTS 2019 and Multi-lingual 2019 datasets, respectively.
Cyclic Fixed-Bed Operations over K2CO3-on-Carbon for the Recovery of Carbon Dioxide under Moist Conditions

A modified chemical-absorption method capable of cyclic fixed-bed operations under moist conditions for the recovery of carbon dioxide from flue gases has been proposed employing K2CO3-on-carbon. Deliquescent potassium carbonate was favorably supported on activated carbon as well as on bound carbon dioxide in the presence of water vapor by the following reaction: After breakthrough, the entrapped carbon dioxide was released by the decomposition of hydrogencarbonate at a higher temperature above 150 °C to shift the reaction in reverse by steam, which could be condensed by cooling to afford high-purity carbon dioxide. An effective use of the pore space as microtanks for aqueous potassium carbonate was verified with XRD evidence under a very humid condition of 7.3% H2O, as anticipated. The amount of CO2 uptake was very small under a dry condition, but increased abruptly in the presence of moisture. Potassium carbonate on carbon was crystalline 2K2CO3·3H2O, even when in contact with moisture of 1.7% H2O; this.
bIoTope: Building an IoT Open Innovation Ecosystem for Smart Cities

The Internet of Things (IoT) has led towards a digital world in which everything becomes connected. Unfortunately, most of the currently marketed connected devices feed vertically-oriented closed systems (commonly referred to as vertical silos) which prevent the development of a unified global IoT. This issue is all the more valid in complex environments, such as smart cities, in which exceedingly large amounts of heterogeneous sensor data are collected, and in which platforms and stakeholders should also be able to interact and cooperate. Therefore, it is of utmost importance to move towards the creation of open IoT ecosystems to support efficient smart city service integration, discovery and composition. This paper contributes to the specifications of such an ecosystem, which has been developed as part of the EU’s H2020 bIoTope project. The novelty of this ecosystem compared with the current literature is threefold: (i) it is based on the extensive use of open communication and data standards, notably O-MI and O-DF standards, that foster technical, syntactic and semantic interoperability over domains; (ii) it proposes an innovative service marketplace for data/service publication, discovery and incentivization; (iii) it integrates security functionalities at the IoT gateway level. The practicability of our ecosystem has been validated through several smart city proofs-of-concept set up in three distinct cities: Helsinki, Lyon and Brussels. Given the five major themes defined in the CITYKeys (a smart city performance indicator framework), namely People, Planet, Prosperity, Governance and Propagation, bIoTope mainly contributes to Prosperity-related metrics, as discussed in this paper.
Effect of Preharvest Sprays of Calcium on Cracking and ‘Schattenmorelle’ Sour Cherry Fruit Quality Harvested Mechanically

The aim of the study was to examine effect of preharvest sprays of calcium (Ca) in the form of Ca-chloride (CaCl2), Ca-nitrate [Ca(NO3)2], or a mixture of Ca-formate, Ca-acetate, CaCl2, and Ca(NO3)2 on cracking and quality of ‘Schattenmorelle’ sour cherry fruit harvested mechanically. The experiment was conducted in 2008–2009 at a commercial orchard in central Poland. Mature trees grew on a coarse-textured soil poor in organic matter, at a spacing of 4.0 × 1.5 m. The spray treatments of Ca were performed at 7-day intervals, starting 28 days before harvest, at the rates of 5.0–5.6 kg Ca ha−1 per season. The trees sprayed with water were treated as the control. Fruit were harvested mechanically when peduncle-fruit detachment force dropped below 3 N. The results showed that preharvest Ca sprays caused no leaf damage. This measure did not affect yield, mean fruit weight, soluble solids concentration and titratable acidity of fruit, and weight loss of fruit during 24 h after harvest. Fruit sprayed with Ca had improved status of this nutrient, and were less liable to juicy leakage from the stem scar, rain-induced cracking, and preharvest decay caused by Glomerella cingulata. The above effects of Ca sprays did not depend on the tested material. It was concluded that preharvest sprays of Ca as CaCl2 and/or Ca(NO3)2 should be recommended in ‘Schattenmorelle’ sour cherry orchards to reduce fruit losses resulting from rain-induced cracking, leakage of juice, and the incidence of cherry bitter rot.
Gold Nanoparticle-Based Sensing of “Spectroscopically Silent” Heavy Metal Ions

A simple colorimetric technique for the detection of small concentrations of aqueous heavy metal ions, including toxic metals such as lead, cadmium, and mercury, is described. Functionalized gold nanoparticles are aggregated in solution in the presence of divalent metal ions by an ion-templated chelation process; this causes an easily measurable change in the absorption spectrum of the particles. The aggregation also enhances the hyper-Rayleigh scattering (HRS) response from the nanoparticle solutions, providing an inherently more sensitive method of detection. The chelation/aggregation process is reversible via addition of a strong metal ion chelator such as EDTA. Suggestions for improving the sensitivity and selectivity of the technique are given.