Miracle-dz/UniFAR-FTUs huggingface dataset:
‘Soft’ support infrastructure and the performance of small and medium-sized enterprises in European countries

The purpose of this paper is to examine the relationship between ? soft? support infrastructure (SSI) and the performance of small and medium enterprises (SMEs). The study encompasses European countries? economic activity and SMEs? output in 2015 and 2018. The focus of the research is SMEs in the European Union member states and the Western Balkan countries. The analysis was conducted using partial least squares structural equation modelling (PLS-SEM). This method enabled the examination of links between variables that are not directly observable. The results show that countries investing in SSI have better SME performance. Based on the statistical analysis, among other things, the authors identify the Human Development Index and the use of information and communication technology at the company level as the two most significant factors that impact on SMEs? performance.
Hybrid mode analysis of end effects of planar microwave and millimetrewave transmission lines

The phase shift associated with the reflection of a guided wave at the abrupt open end of planar strip and slot waveguides is determined numerically by solving the relevant frequency-dependent hybrid mode boundary-value problem. In addition, nonideally short-circuted ends are considered, i.e. those where the planar guiding structure terminates in a metallisation layer. The method of analysis employed is a Galerkin approach in conjunction with a spectral-domain Green's function interpolation technique and especially suited expansion functions. Its main features are described, and numerical results are presented for most of the technically important types of planar waveguides (microstrip, suspended substrate, slot/fin and coplanar line). The results are compared with published measured data and quasistatic compuations, as far as these are available. The frequency-dependent behaviour of the different end effects is discussed. In an Appendix, it is shown how the numerical approach of this paper can be extended to the analysis of planar n-ports.
A case study approach to understanding a remote undergraduate research program

Due to the growing concerns surrounding the COVID-19 pandemic, colleges and universities either canceled or remotely hosted their 2020 National Science Foundation Research Experience for Undergraduates (REU) programs. This analysis is part of a larger study examining the impact of these fully remote experiences on professional and psychosocial factors such as mentees’ sense of belonging, identity, and self-efficacy and their retention in STEM degree programs. We present a single-student case study and describe the dramaturgical analysis which centers on identifying five fundamental constructs within the data: objectives, conflicts, tactics, attitudes, and emotions. These items investigate what the participant in the remote REU program experienced and how this experience changed the ways in which he thinks about his future career decision making. Our analysis explored four different sub-narratives: lack of community in virtual REU, mentor support, perception of the “real” nature of the experience in a virtual format, and future career decision-making. The mentee reported that this experience was highly beneficial and that he developed a sense of belonging and identity, despite working remotely – often from his own bedroom. © 2021, American Association of Physics Teachers. All rights reserved.
Neural network based short-term load forecasting using weather compensation

This paper presents a novel technique for electric load forecasting based on neural weather compensation. Our proposed method is a nonlinear generalization of Box and Jenkins approach for nonstationary time-series prediction. A weather compensation neural network is implemented for one-day ahead electric load forecasting. Our weather compensation neural network can accurately predict the change of actual electric load consumption from the previous day. The results, based on Hong Kong Island historical load demand, indicate that this methodology is capable of providing a more accurate load forecast with a 0.9% reduction in forecast error.
Recent Advances in Quantitative Gait Analysis Using Wearable Sensors: A Review

The current gold standard for gait analysis involves performing the gait experiments in a laboratory environment with a constrained space. However, there is growing interest in using flexible, efficient, and inexpensive wearable sensors as tools to perform gait analysis. This review aimed to identify and summarize the current advances in wearable sensors for various aspects of gait analysis, such as the application of wearable gait analysis systems, sensor systems and their attachment locations, and the algorithms used for the analysis. The PRISMA guideline was adopted to find relevant studies from the period 2011 to 2020 from several scientific databases. A total of 76 articles were selected based on the inclusion and exclusion criteria. A wearable inertial measurement unit (IMU) attached to the lower limb region was found to be the most common approach for gait analysis. Temporal, spatial, and spatiotemporal features were the most common quantitative gait features extracted from the wearable sensors. The proposed frameworks showed varying performances, and an increased number of sensors did not necessarily improve the estimation performance metrics. A few studies have integrated various machine learning techniques for classification problems, correction algorithms, crosschecking functions, and scoring functions. Finally, this review paper discusses the challenges and future direction of the research on quantitative gait analysis.
MOCVD TiN diffusion barriers for copper interconnects

Copper barrier effectiveness of ultra-thin 100 /spl Aring/ MOCVD titanium nitride (TiN) and silane treated titanium nitride (TiN:Si) films was investigated and compared to the industry standard 150 /spl Aring/ PVD Ta barrier. The metallurgical stability of the film and barrier failure was determined by sheet resistance change, optical and electron microscopy after Secco etch and C-V measurements. Copper drift through the barrier was tested under bias temperature stress conditions (200/spl deg/C and 2 MV/cm) using leakage current vs. time measurement on MOS capacitors.
Economic analysis of evaporatively cooled storage of horticultural produce

An analysis was carried out to observe the economic feasibility of evaporatively cooled (EC) storage structures for storage of horticultural produce. Two types of storage structures, one made with brick-sand-brick walls and the other with wood wool pad walls were considered for the analysis. It was observed that in 0.25 m3 EC structures (100 kg capacity) the cost of storage was Rs. 0.07 per kg of commodity per day. Hence, EC storage structures can be advantageously utilised for extending the shelf life of highly perishable commodities to about 6–7 days, which would otherwise get spoilt in 2–3 days under ambient storage conditions. However, for semiperishable commodities like potato, the cost of storage for a period of 100–120 days would be about Rs. 7.001 kg. Therefore, under this situation, the small capacity EC structures do not offer any economic advantage over the ambient storage conditions. The cost of storage would reduce with increase in size of the structure, and the costs of storing potato for 100 days in 1 m3 EC structures (400 kg capacity) made with pad walls and brick walls were Rs.1. 22 and Rs. 2.38, respectively. The cost of storage in a 25 m3 EC structure (8 MT capacity) fitted with artificial ventilation system has also been analyzed, which is Rs. 0.81 for a storage period of 100 days. The break-even costs for potato stored under EC conditions were Rs. 3.58 and Rs. 3. 12 for wood wool pad EC storage structures of 1 m3 and 25 m3 capacity, respectively. Therefore, the EC structures could be adopted in places where cold storage facilities are not available or the transportation cost to the cold storages is very high to of fset the advantages of keeping produce in cold storages. Utilising such EC storage structures for other operations like mushroom cultivation, curing of horticultural produces, etc. and extending the number of days of operation per year would reduce the unit cost of storage and of fer a better economic picture of the EC storage structures.
Determinants of an Organization's Readiness for Drone Technologies Adoption

Increased use of unmanned arial vechieles has generated interest in the scope of its applications in alternate fields motivating organizations to integrate these smart flying robots in their systems. Looking at the significant rise in drone usage in diversified fields of industrial operations, organization must capture on its value for competetive advantage and outreach to vast customer community. Theoretical foundations of technology-organisation-environment and diffusions-of-innovation are taken along with expert opinion to identify the determinants of an organizations readiness for the adoption of drone in their systems. A multicriteria decision analysis method, the best worst method is applied here to evaluate and priortize the determinants of drone adoption. The results depict cost parameters of technology, competiton, trading partners' advantage and top management as strong supporters of the adoption. The complexity and compatibility along with customer perception and regulations need more considerations for effective results. This article offers valuable insights to practitioners as well as future researchers regarding soft dimensions of drone adoption and navigates them to work on their operational and industrial environemnt to derive maximum benefits.
Proposal of Virtual Transformer-based Back-to-Back Asynchronous Loss Measurement using a Single Set of Measurement Instruments for One Inverter and Experimental Verification

In this study, a virtual transformer-based loss measurement method is proposed for inverter power conversion efficiency measurements, and the accuracy of this method is theoretically analyzed. This concept is further extended to a practical measurement procedure, wherein asynchronous loss measurements are conducted for powering and regenerating operations using a single set of measurement instruments. The average efficiency can be obtained with a very high accuracy after calibration of the measurement instruments. A high-efficiency system inverter was selected as the converter under test, and its efficiency and accuracy were experimentally measured and validated. An efficiency of 99.75% ± 0.006% was obtained at an output of 1600 W.
Extending the information-theoretic measures of the dynamic complexity of manufacturing systems

This paper revisits and extends the structural and dynamic complexity measures of manufacturing systems, which are based on an information-theoretic interpretation of the amount of information that is needed to describe the state of a manufacturing system. In this paper, a generic manufacturing system is modelled as a set of interacting resources and queues. At any moment in time, the combined specific states of the resources and queues define the overall state of the manufacturing system. The main contribution of this paper is a set of dynamic complexity measures that quantify the rate at which information is generated by the facility, and which may be applied with or without reference to the facility's schedule. A worked example demonstrates the step-by-step calculations to obtain values of the complexity measures, and guidance is provided on how to obtain the data needed to carry out the calculations. The links between these complexity measures and the behaviour of a facility are identified and described.
Isolated flyback-current-fed push-pull converter for power factor correction

This paper presents a single-stage high-power factor isolated power supply based on the classical flyback-current-fed push-pull converter. The proposed converter operates as a buck one at a duty-cycle below 50% and as a boost one at duty-cycle above this range. Therefore, when properly driven, this converter is suitable for high power factor applications, with many advantages when compared with the boost-isolated current-fed converter, including inrush current control and less voltage stress over the power semiconductors. Theoretical analysis, design methodology, design example, control strategy, and experimental results are presented is paper.
Human-Centered Design of an Acc-With-Braking and Forward-Crash-Warning System

This paper addresses the development of driver assistance systems whose functional purposes are to provide both adaptive cruise control (ACC) and forward collision warning (FCW). The purpose of the paper is to combine concepts from human factors psychology, vehicle-dynamics, and control theory, thereby contributing to the body of knowledge and understanding concerning human-centered approaches for designing and evaluating driver assistance systems. Conceptual and experimental results pertaining to driving manually and with the assistance of ACC and FCW are presented. The following human-centered aspects of driver-assistance systems are analyzed and presented: the looming effect; including rule-based and skill-based behavior in the design of ACC systems; using desired dynamics in controlling the driving process; braking rules that trade headway range for deceleration level; and collision-warning rules based on two different stress indicators. Field-test data are examined to justify and verify the parametric values selected for use in human-centered ACC systems. Measured data from on-road driving are used to evaluate the performance of proposed FCW systems in braking situations. The paper concludes with observations concerning the difficulty of developing a clear understanding of when and why drivers brake.
Unsupervised Word Representations Learning with Bilinear Convolutional Network on Characters

In this paper, we propose a new unsupervised method for learning word embedding with raw characters as input representations, bypassing the problems arising from the use of a dictionary. To achieve this purpose, we translate the distributional hypothesis into a unsupervised metric learning objective, which allows to consider only an encoder instead of an encoder-decoder architecture. We propose to use a convolutional neural network with bilinear product blocks and residual connections to encode co-occurrences patterns. We show the eﬀectiveness of our approach by comparing it with classical word embedding methods such as fastText and GloVe on several benchmarks.
SystemDesign and SoftwareArchitecture of Traction VehicleControl Computer

The overview ofsystemdesignandsoftware architecture ofthedistributed control computer (DCC)of anelectric locomotive ispresented. TheDCC isorganized as alocal computer network withthemaster-slave nodeaccess methodwithadualserial bus.Usertaskactivities innodes areorganized by thepreemptive RealTimeOperating System withdynamic planning orbysimple static executive. Networkcommunication services areuniformly usedinall nodestosupportreliable anduserfriendly transfer of process datainside DCC.Thesystemdesign isbasedon criteria asfunctionality, reliability, faulttolerance and maintainability I.INTRODUCTION A control computer of electric locomotive will demonstrate commondesign issues andmethodology of computer system design andsoftware architecture. An electric locomotive as complex of electric drives, pneumatic brakes, security devices, engine driver stands andmanyother parts canbeseenfromsoftware design point ofviewasa mid-range design problem. The software architecture ofcomputer controlled systems has manymodifications anddepends ontheapplication size, required speed, available design time,budgetsize, experience ofsoftware designer andmanyother factors. In simple drive systems (locomotive isnotthecase) with sufficient numberof hardware interrupt resources interrupt-background orinterrupt-no-background
Mangrove Zoning Study Unmanned Aerial Vehicle in Mangrove Forest of Nagari Mandeh, West Sumatra

Mangrove has physical and ecological functions that are very influential on coastal ecosystems. Mandeh area is currently one of the ecotourism areas that has a fairly extensive Mangrove forest. However mangrove condition is being threatened due to various reasons. This study to determine the zoning pattern of the Mandeh mangrove forest using two different methods: (a) field survey using belt transect method with determination of plot points determined by purpose sampling (b) method with unmanned aircraft using 3- dimensional visual analysis by utilizing orthophoto data recorded by unmanned aerial vehicles (UAV). Data were presented in tabulation form, then analyzed qualitatively and quantitatively. The results revealed that the zonation pattern of mangrove forests using the field survey method can provide results in the form of a more detailed zonation pattern, the number of individual trees, tree diameters, and the types of species that dominate. Observation of the zonation pattern of mangrove forests using UAV method providing accurate results in the form of general profiles of mangroves, and individual tree heights. The implication of this research will be useful as a consideration in making policies on mangrove conservation in Nagari Mandeh.
PREDICTION OF A SEQUENTIAL SHORT-TIME OD MODEL BASED ON PERSON TRIP DATA IN AN URBAN AREA

In this paper, the structure of a time-of-day travel demand forecasting model system is discussed. A short-time Origin-Destination (OD) model is constructed to estimate traffic volume in each time class during a day. A short-time traffic assignment is also proposed considering some trips do not always arrive at a destination within the same time class and link into the next phase. Also, Sequential short-time modal split must consider traffic conditions of each time class. Therefore, joint modal split and assignment model is constructed. In these models, time distributions and trip-length are required. These models are analyzed considering differences in characteristics of trip purposes and personal attributes and estimated by model parameters from the Person trip survey data.
Model reference safety‐critical adaptive control for a class of nonlinearly parameterized systems

Safety is the most fundamental problem of safety‐critical systems. Safety control addresses the problem whether a given unsafe region of the state space can be avoided by a specific control‐input. Moreover, linearly parameterized dynamical system is a general assumption in most safety‐critical adaptive control literature; however, unknown parameters in real systems are usually nonlinear. The control problem of nonlinearly parameterized systems is really difficult without linear‐in‐the‐parameters (LIP) assumptions, which tends to be complicated and computationally intensive. In this paper, a novel model reference safety‐critical adaptive control (MRAC) approach is proposed for a class of nonlinearly parameterized systems. The proposed approach involves a novel controller architecture with a modified update law, which specifically filters out the unsafe behavior (the system is in a state which the system cannot operate normally, i.e., the given unsafe region), while preserving favorable tracking capability and robustness. The novelty of this paper is that the nonlinearly parameterized systems can be enforced safety, without LIP assumptions and complex calculations. Most importantly, this approach is effective for nonlinearly parameterized systems as well as linearly parameterized systems. Finally, three illustrative numerical examples are presented to demonstrate the effectiveness of the proposed design approach.
Contrasting narratives: a randomised control study comparing Conflict Analysis and narrative disclosure

ABSTRACT This online randomised controlled study evaluates benefits associated with structured topic-focussed narrative writing tasks versus unstructured narrative writing tasks, monitoring to what extent tasks impact well-being, psychopathology and satisfaction. Participants were randomised to structured topic-focussed or unstructured narrative writing conditions. Structured condition consisted of Conflict Analysis (CA), a self-guided narrative-based therapeutic assessment. Unstructured conditions consisted of narrative disclosure tasks about traumatic experiences. Both conditions consisted of ten 20-minute tasks completed within one week. One hundred and three participants completed baseline measures. Eighty-two participants completed two-week follow-up measures. Repeated measure ANOVA and t-tests were used to evaluate differences over time. Follow-up data suggest that CA participants had significantly improved outcomes when compared to narrative disclosure participants. Evidence supports continued structured narrative writing research.
A comparative Evaluation of Swarm Intelligence Algorithm Optimization: A Review

Swarm intelligence (SI), an important aspect of artificial intelligence, is increasingly gaining popularity as more and more high-complexity challenges necessitate solutions that are sub-optimal but still feasible in a fair amount of time. Artificial intelligence that mimics the collective behavior of a group of animals is known as swarm intelligence. Attempting to survive. It is primarily influenced by biological systems. The main aim of our article is to find out more about the guiding principle, classify possible implementation areas, and include a thorough analysis of several SI algorithms. Swarms can be observed in ant colonies, fish schools, bird flocks, among other fields. During this article, we will look at some Swarm instances and their behavior. We see many Swarm Intelligence systems, like Ant colony Optimization, which explains ant activity, nature, and how they conquer challenges; in birds, we see Particle Swarm Optimization is a swarm intelligence-based optimization technique, and how the locations must be positioned based on the three concepts. The Bee Colony Optimization follows, and explores the behavior of bees, their relationships, as well as movement and how they work in a swarm. This paper explores some of the methods and algorithms.
Robust Fixed-Time Sliding Mode Attitude Control of Tilt Trirotor UAV in Helicopter Mode

In this article, we address the problem of robust fixed-time attitude stabilization for tilt trirotor unmanned aerial vehicle subjects to parameter uncertainties and external disturbances. First, a novel fixed-time stable system with a faster convergence rate is proposed. Second, a nonsingular fixed-time sliding mode surface is developed, which has better convergence performance than existing methods. Third, a continuous fast fixed-time sliding mode control law is proposed by applying the developed sliding mode surface and adaptive technique. As a result, the convergence time of the closed-loop system is bounded and independent of the initial conditions. Simulation and experiments are presented to verify that the proposed scheme can effectively and rapidly achieve attitude stabilization while maintaining high control precision and robustness.