Miracle-dz/UniFAR-FTUs huggingface dataset:
Fogification of electric drives: An industrial use case

Electric drives are used to control electric motors, which are pervasive in industrial applications. In this paper we propose enhancing the electric drives to fulfil the role of fog nodes within a Fog Computing Platform (FCP). Fog Computing is envisioned as a realization of future distributed architectures in Industry 4.0. We identify the system-level requirements of such an FCP, including requirements that are extracted from the current architecture of drives, which we consider as a baseline. These requirements are then used to design a system-level architecture, which we model using the Architecture Analysis & Design Language (AADL). We identify the "technology bricks" (components such as hardware, software, middleware, services, methods and tools) needed to implement the FCP. The proposed fog-based architecture is then used to implement a Conveyor Belt industrial use case. We evaluate the resulting use case on several aspects, demonstrating the usefulness of the proposed fog-based approach. By developing the electric drives as fog nodes, that we call fogification, new offerings like programmability, analytics and connectivity to customer Clouds are expected to increase the added value. Increased flexibility allows drives to assume a larger role in industrial and domestic control systems, instrumenting thus also legacy systems by using drives as the data source.
Towards a Reference Architecture for Leveraging Model Repositories for Digital Twins

In the area of Cyber-Physical Systems (CPS), the degree of complexity continuously increases mainly due to new key-enabling technologies supporting those systems. One way to deal with this increasing complexity is to create a digital representation of such systems, a so-called Digital Twin (DT), which virtually acts in parallel ideally across the entire life-cycle of a CPS. For this purpose, the DT uses simulated or real-time data to mimic operations, control, and may modify the CPS’s behaviour at runtime. However, building such DTs from scratch is not trivial, mainly due to the integration needed to deal with heterogeneous systems residing in different technological spaces. In order to tackle this challenge, Model-Driven Engineering (MDE) allows to logically model a CPS with its physical components. Usually, in MDE such "logical models" are created at design time which keep them detached from the deployed system during runtime. Instead of building bilateral solutions between each runtime environment and every engineering tool, a dedicated integration layer is needed which can deal with both, design and runtime aspects. Therefore, we present a reference architecture that allows on the one side to query data from model repositories to enrich the running system with design-time knowledge, and on the other side, to be able to reasoning about system states at runtime in design-time models. We introduce a model repository query and management engine as mediator and show its feasibility by a demonstration case.
MEMS Resonators for Frequency Reference and Timing Applications

An overview of microelectromechanical systems (MEMS) resonators for frequency reference and timing applications is presented. The progress made in the past few decades in design, modeling, fabrication and packaging of MEMS resonators is summarized. In particular, the state-of-the-art technologies for improving the overall performance of MEMS resonators, such as quality factor ( $Q$ ), motional impedance, temperature sensitivity, and initial frequency uniformity, are reviewed in detail. The challenges and opportunities during the commercialization of MEMS resonators are also stated, and future development trends driven either by technology or market are outlined. This paper intends to provide an outlook for possible research directions of MEMS resonators in frequency reference and timing applications. With outstanding reliability, unique multi-frequency functionality on a single chip, and high accuracy, MEMS resonators show great potential for replacing the quartz crystal resonators which have been dominating the timing market since 1920s. [2020-0106]
A Study on the Ant Communities on West Slope at Different Elevation of the Gaoligongshan Mountain Nature Reserve in Yunnan,China

The ant communities and their species diversity with altitudinal zonation on west slope of the Gaoligongshan Mountain Nature Reserve were studied for the first time. Along with the increasing of altitude,number of dominant species increases at the north and north middle sections of the reserve,but decreases at the south section. While the altitude increasing,percentage of dominant species decreases at the north and north middle sections,but increases at the south section. It is inferred that along with the increasing of altitude the species number decreases. This study also suggested that the density of individuals decrease while the altitude increasing. At the north and north middle sections the predominant index decreases while altitude increasing,but the index increases at middle south and south sections. Along with the altitude increasing,the species diversity index increases at north section,without regularity at north middle section,and decreases at middle south and south sections. At north,north middle and middle south sections,evenness index increases while altitude increasing,but the index decreases at south section. Similarity coefficient between the ant communities on west slope at all the four sections is almost all between 0 00-0 25,with only one coefficient surpasses this range. We think the basic rules of the species diversity of ant communities on west slope under the state of virgin vegetation should be that along with the altitude increasing,number of dominant species decreases,percentage of dominant species increases,species number decreases,individual density decreases,predominant index increases,species diversity index decreases,and evenness index decreases. The unusual situation observed in the practical investigation might be caused by the destroying of vegetation on the foot of the mountain and half way up the mountain.
Genetics of Gracilaria sp. (Rhodophyceae, Gigartinales): II. The life history and genetic implications of cytokinetic failure during tetraspore formation*

Abstract Tetrasporophytes of Gracilaria sp. produce spores of differing size. The larger spores arise from a failure of cytokinesis in tetrasporangia after meiosis and consequently have two or more nuclei. By using nuclear marker genes it was possible to demonstrate that the largest spores often contain all four meiotic products and hence can be used for tetrad analysis under appropriate conditions. Sexually mosaic plants with both male and female fronds developing from a single basal disc were commonly observed.
Gate stresses and threshold voltage instability in normally-OFF GaN HEMTs

This paper presents a study of gate stress and threshold voltage instability in commercially available 600/650V GaN high electron mobility transistors (HEMTs). The technologies evaluated are an ohmic gate GaN HEMT and a Schottky gate GaN HEMT. The gate leakage currents have been evaluated for two different gate contact technologies and its temperature dependency is presented. It is shown that the gate leakage current could be a temperature indicator for both technologies evaluated, with a higher temperature sensitivity in the case of the Schottky gate HEMT (showing a sixtyfold increase from 22°C to 150°C). A novel characterization method based on the third quadrant operation of the device was applied to the two selected GaN HEMTs and the role of temperature, stress level and duration on the threshold voltage instability of GaN HEMTs has been evaluated. The method can capture both the peak shift and transient recovery. The results highlight the clear differences between both gate contact technologies with the Schottky gate HEMT exhibiting higher threshold voltage instability due to gate stress compared to the ohmic gate devices. The Schottky gate HEMT shows a positive threshold voltage shift for a gate stress voltage of 3 V, whereas at 5.5 V the shift is dependent of the stress time. For both HEMTs, the recovery transient after stress removal is accelerated with temperature.
Network Simplification and K-Terminal Reliability Evaluation of Sensor-Cloud Systems

The sensor-cloud system (SCS) integrates sensors, sensor networks, and cloud for managing sensors, collecting and processing data, and decision-making based on data processed. Though the SCS has received tremendous attention from both academia and industry because of its numerous exciting applications, it still faces the challenge in reliability. The reliability of an SCS is generally referred to as the ability to perform required functions for a given period of time. This work is focused on the <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-terminal reliability of an SCS, which is concerned with the successful communication between all pairs of network nodes belonging to a pre-specified subset <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>. The increased complexity and scale of real-life SCSs require new efficient techniques to evaluate their <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-terminal reliability. In this work we make novel contributions by proposing a network simplification method that can effectively remove all redundant network edges and vertices, leading to a significantly reduced network model for accurate and efficient <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-terminal reliability analysis. The method is based on graph decomposition and reconstruction through articulation vertices. Empirical studies show that the proposed simplification method integrated with the binary-decision-diagrams based evaluation algorithm can significantly speed up <inline-formula> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula>-terminal reliability analysis of large real-life SCSs.
Cell Modelling for Battery Management System in Electric Vehicles

Electric Vehicles are the future of mobility in the world plagued by pollution and depleting natural resources. It contains the solution to green, efficient and reliable mode of transportation coupled with other benefits like Vehicle-to-Grid systems. To attain these features, an electric vehicle needs to ensure the proper functioning of the battery system, including, the upkeep and conditioning of the battery parameters to its set, regulated values. This necessitates the need for a proper control mechanism. The control mechanism should provide charge-discharge control, the safety of the battery as well as the user, details about the battery age and health and estimate the range of operation. Each of these properties constitutes the battery management system or BMS. The foundation of an efficient battery management system is an accurate model of the battery. An accurate model helps in accurate identification of battery performance and its characteristics. Thus, necessitating the need for a foolproof cell model imitating the battery performance parameters accordinaly.
Observer-based Event-triggered Model Reference Control for Multi-agent Systems

The main contribution of this paper is the design of an observer-based model reference control for multi-agent systems with event-triggered mechanism using a dynamic-threshold. Since the full state vector is not always available, an observer is considered for each agent. In order to guarantee convergence of all the agents to the reference trajectory, linear matrix inequality (LMI)-based conditions are obtained for computing the controller and observer gains. Based on the closed-loop multi-agent system, an event-triggered mechanism is designed to reduce the information exchange between agents. The effectiveness of the proposed approach is illustrated through numerical examples.
Prior Attention Enhanced Convolutional Neural Network Based Automatic Segmentation of Organs at Risk for Head and Neck Cancer Radiotherapy

Aimed to automate the segmentation of organs at risk (OARs) in head and neck (H&N) cancer radiotherapy, we develop a novel Prior Attention enhanced convolutional neural Network (PANet) based Stepwise Refinement Segmentation Framework (SRSF) on full-size computed tomography (CT) images. The SRSF is built with a multiscale segmentation concept, in which OARs are segmented from coarse to fine. PANet is a pyramidal architecture with elements of inception block and prior attention. In this study, the developed PANet based SRSF is applied for OARs segmentation in H&N radiotherapy. 139 CT series and manually delineated contours of twenty-two OARs by experienced oncologists are collected from 139 H&N patients for training and evaluating the proposed PANet based SRSF. The mean testing Dice similarity coefficients (DSC) on 39 CT series range from 76.1± 8.3% (left middle ear) to 91.9± 1.4% (right mandible) for large volume OARs(mean volume >1cc) while the corresponding ranges are 63.4± 12.3%(chiasm) to 81.0± 14.1% (right lens) for small and challenging OARs(mean volume ≤1cc). Furthermore, the proposed method also achieved superior segmentations over reference methods on the MICCAI 2015 H&N dataset with mean DSC of 95.6± 0.7%, 81.3± 4.0%, 77.6± 4.5%, 77.5± 4.6%, and 69.2± 7.6%, on the mandible, left submandibular, left and right optical nerve, and chiasm, respectively. The accurate segmentation of OARs is obtained on both the self-collected testing data and public testing dataset, which implies that the proposed method can be used as a practicable and efficient tool for automated OARs contouring in the H&N cancer radiotherapy.
An Automated CNC Machine

-With the advancement of technology, demand for computer numerical control(CNC) plotter machines in educational institutions and laboratories rapidly rising. The networking of objects which have the connectivity that enables them to communicate independently with one another via the internet. This project aims to develop the model of CNC plotter machine which is able to draw a circuit layout on PCB or any other solid surface using the electronic component. Initially the user needs to convert any image file or text file into G-code using inkscape software and then feed it to machine using processing software. Arduino Uno with an atmega328p microcontroller is used as the control device for this project. The microcontroller convert G-code into a set of machine language instruction to be sent to the motor driver of the CNC plotter. The main objective of project is to design and implement a CNC plotter machine which will be able to draw a PCB layout on a solid surface. A plotter is a 3D controlled 2D plotting machines which uses a pen to draw text or image on any given solid surface with complex line drawings. The machine will have three motors to implement the X,Y and Z axis. A servo motor will be used along the Z axis for positioning the pen which will go up and down. CNC technology has major contribution in industries. CNC machine are main platform in the contribution of good quality products in industries. The main aim of this project is to reduce time consumed for plotting and it r educes human involvement which eventually reduces rate of error and also increases the production.
The Importance of Speckle Tracking Echocardiography Evaluating of Nonobstructive Coronary Artery Stenosis and Its Correlation with Microvascular Angina

This study aims to evaluate patients with limited state of changes in coronary arteries detected by coronary angiography, the dynamics of these changes over the two years, identify the relevant diagnostic criteria, and assess the efficacy of applied treatment by using speckle tracking echocardiography. Peak radial and circumferential strain and SR (systolic, early, and late diastolic strains) were measured based on the short-axis view; peak longitudinal strain and SR were measured from the apical side of fourtwoand three-chamber views. Radial, longitudinal (GLS), circumferential global and regional strains were calculated as an average of measurements. All patients (n − 146) were assigned to normal (control) and CAD groups according to cardiac angiography results. 128 of them were evaluated repeatedly after two years. Depending on angiography findings, LAD (85.83%) stenosis predominate, when subsequently fewer instances of RCA (52.5%) or LCX (40.83%) were observed. Most (about 80%) of the patients had one or two-vessel disease and only 20% had systemic all three-vessel disease. Analysis of STE data in groups during a two-year study period showed statistically reliable differences associated with a particular coronary artery. In the control group: RCA – myocardial circumferential strain (p − 0.037); LAD – no changes; LCX – early (p − 0.013) and late diastolic longitudinal (p − 0.033) strains. Subsequently, in the CAD group: RCA – diastolic circumferential strain rate (p−0.007); LAD – myocardial longitudinal strain (p − 0.006), systolic longitudinal (p − 0.038) and circumferential strain (p − 0.012) rates, early diastolic circumferential (p − 0.008) and late diastolic longitudinal (p − 0.037) strain rates; LCX – myocardial longitudinal (p−0.049) strain. Between groups, we detected significant changes in such circumferential strain rates, respectively: RCA – systolic (p = 0.037), early diastolic (p = 0.019), and late diastolic (p = 0.024) strain rates; LAD – no changes; LCX – early diastolic longitudinal ∗Corresponding author. 524 K. Morkunaite et al. strain (p − 0.004). The clinical condition of our patients over the two years has improved both in control and CAD groups, according to GLS. We hold the opinion that microvascular angina (MVA) may be responsible for such an improvement because the main diagnostic criteria and common treatment with ACE inhibitors, statins, β-blockers, antithrombotic, and nitrates was typical and effective for MVA treatment.
Barrier Lyapunov Function based Trajectory Tracking Controller for Autonomous Vehicles with Guaranteed Safety Bounds

Accurate trajectory tracking is essential in many applications involving autonomous vehicles. However, due to the coupled nonlinear dynamics of the vehicle and external disturbances, this may not be the case. This paper presents a Barrier Lyapunov Function (BLF) based trajectory tracking controller design technique for autonomous vehicles with task-specific constrained state requirements. A BLF candidate is introduced based on the constraints and using the Lyapunov direct method a controller is designed which guarantees that the tracking errors remain within the defined bounds. The proposed technique is demonstrated on two applications. In the first scenario, we consider a trajectory tracking problem with a safety bound (circle) around the desired trajectory and in the second we consider a moving target tracking problem using an unmanned aerial vehicle (UAV) with guaranteed visibility. The simulation results along with the software-in-the-loop (SITL) results show the adaptability of the proposed method to various applications.
Safe flyable and energy efficient UAV missions via biologically inspired methods

In this article the offline Unmanned Aerial Vehicle (UAV) path planning problem is addressed for real environments whilst enhancing energy requirements. In particular, a two-step procedure is adopted for the determination of the energy efficient safe flyable path that satisfies a-priori defined criteria. By the former step, via principles of mechanics, safe flyable candidate paths are designed meeting functional/physical limitations of the aerial vehicle. By the latter step, those paths are fed in the Genetic Algorithm (GA) setup, and the best path that fulfils mission’s objectives and satisfies constraints is determined. The efficacy of the approach is shown via simulation examples, where a UAV is deployed to safely navigate with the least energy demand in an a priori known environment whilst meeting mission objectives.
Road Extraction Based on Level Set Approach From Very High-Resolution Images With Volunteered Geographic Information

The road network is of great importance to the modern traffic system, which changes frequently as its high speed of development. Simultaneously, a growing number of satellites provide a considerable number of remote sensing images that can be used for road extraction. However, most existing methods cannot get accurate results in the high-resolution remote sensing, since the complex background like the shadows and occlusions. Consequently, we proposed a method utilizing the volunteered geographic information data to extract the road from satellite images. At first, from Mapbox platform, the Volunteered Geographic Information data, OpenStreetMap vector tiles are collected to guide the downloading of corresponding road satellite images. Then a level set method is used to extract the road areas from the satellite images supported by the road vector. After that, a superpixel method is applied to improve the road areas by fusing the superpixels with the previous results. Experiments are performed on the satellite images from Mapbox, Google, and Yahoo in the Tianjin Port district on accuracy and efficiency. Experimental results demonstrate that our approach is more accurate and of higher performance than the other two state-of-the-art methods.
Adding Compound Splitting and Analysis to a Semantic Tagger of Modern Standard Finnish - On the Way to FiSTComp

This study continues a work in progress for implementing a full-text lexical semantic tagger for Finnish, FiST. The tagger is based on a 46,226 lexeme semantic lexicon of Finnish that was published in 2016 [1]. Kettunen [2], [3] describes the basic working version of FiST. FiST is based on freely available components: the first implementation uses Omorfi and FinnPos for morphological analysis and disambiguation of Finnish words. The current paper describes work with compound splitting for semantic tagging and its effects on the lexical coverage of the tagger. We try out two different approaches to morphological analysis and disambiguation of words for an improved version of FiST, FiSTComp: FinnPos [4], and Turku Dependency Parser [5], [6], UD1. Both these tools disambiguate morphological interpretations of words and provide boundary markings for compounds, but details and granularity of constituent decomposition vary. Our results with two-, three and four-part compounds show that analysis of compounds through their constituents with UD1 may improve the lexical coverage of the tagger with about 6.6 % units at best. Although we are able to proceed in basic problems of compound splitting, the results are still initial and further work is needed as compounds are a complex phenomenon.
Modeling of timber harvesting options using timber prices as a mean reverting process with stochastic trend

Proper characterization of the timber price process plays a vital role in forest management decisions. The process of long-run timber prices and its implications for harvesting decisions are analyzed for a forest in Ontario, Canada. Timber prices are modeled as a mean reverting process with stochastic trend. The Kalman filter is used to estimate the state–space model. The forecasted prices from the model are used in real options analysis to determine the optimal investment time and optimal investment rule. The results provide insight different from that of other specifications used in earlier literature.