Miracle-dz/UniFAR-FTUs huggingface dataset:
DCM Analysis and Inductance Design Method of Interleaved Boost Converters

In order to use interleaved boost converters in the discontinuous conduction mode (DCM), the variation in the phase current and the input current ripple is analyzed theoretically. Based on the detailed analysis, a numerical formula for the input current ripple is deduced by including three criteria. Using the numerical formula, the optimized inductance that reduces the input current ripple and losses is deduced. The boundary conduction mode (BCM) is also compared with the discontinuous conduction mode to verify their strong points. In order to verify the analysis, simulation and experimental results are compared with theoretical data. The consideration of the BCM is also progressed by comparing with the DCM, and the results were different in terms of the efficiency and the input current ripple.
Merits and limitations of resonant and soft-switched converters

An attempt to classify resonant and soft-switching pulse width modulation (PWM) techniques based on their operation principle and origin is presented. General properties of the most prominent families are summarized. The merits and limitations of the classified families are discussed with the objective of defining their most suitable area of application. <<ETX>>
Self Management of Rest Breaks by VDT Users

Video display terminal (VDT) users can benefit from frequent, short rest breaks in terms of improved productivity and well-being. However, VDT users report that scheduled breaks can seriously disrupt some tasks. This laboratory study tested if performance feedback would promote better self management of discretionary rest breaks. Undergraduate typists (N=31) entered lines of randomized words for 65 min. A mandatory rest break was administered whenever discretionary rest breaks did not total 30 s every 10 min. Typists in the experimental condition received feedback indicating how their discretionary breaks compared to a criterion. Typists in the control condition received no such feedback. Mood and musculoskeletal discomfort were assessed before and after the work period, followed by a questionnaire about the break system. Performance measures included keystroke rate, error rate, and correction rate (backspace use). Measures of heart rate and heart rate variability were also collected. Both the number of full-length mandatory breaks and correction rate were lower in the feedback condition. No significant differences in mood, musculoskeletal discomfort, physiological response, nor acceptance of the break system were found. These results suggest that self management of discretionary breaks as well as keystroke performance are improved by feedback, with no untoward effects on well-being.
Off/on-line FRA condition monitoring technique for power transformer

This letter presents a novel and sensitive frequency response analysis (FRA) technique for off/on-line condition monitoring of expensive power apparatus. The main objective is to investigate the applicability of this predictive maintenance technique to diagnosing power transformer failures, to characterize the transformer in a frequency plane for safe operation, and to develop on-line monitoring technique. The effectiveness of this technique is demonstrated on a 2.5 MVA transformer housed at the High Voltage Laboratory of Pacific Power International (PPI) and then tested on three field transformers. The on-line technique is verified on a single-phase high voltage transformer. This study shows that FRA results are very sensitive to faults. The configuration of the measurement set up, frequency range and terminations play a greater role in getting reproducible, fault-indicating results. The interpretation of the voluminous data and analysis relevant to the faults opens a gateway to develop smart power apparatus.
Study on the Impact of Innovative Self-efficacy on Innovation of Employees Behavior Under the Creative Process Engagement Mediating Model

Recently, under the emphasis on the competitiveness of innovation, the innovation of employees behavior has been paid more attention by managers. It is the key to increase the core competitiveness of companies on how to enhance innovation of employees, but the current research is relatively lacking. By collecting the concepts of self-efficacy, creative process engagement, and innovation of employees behavior, this paper constructs a mediating model. The results show that innovative self-efficacy has an active impact on employee innovation behavior. At the same time, innovation self-efficacy influences employee innovation behavior through creative process engagement. Finally, this paper puts forward the path and strategy of how to improve innovation of employees behavior.
An unsupervised machine-learning-based classification of aerosol microphysical properties over 10 years at Cabo Verde

Abstract. The Cape Verde Atmospheric Observatory (CVAO), which is influenced by both, marine and desert dust air masses, has been used for long-term measurements of different properties of the atmospheric aerosol from 2008 to 2017. These properties include particle number size distributions (PNSD), light absorbing carbon (LAC) and concentrations of cloud condensation nuclei (CCN) together with their hygroscopicity. Here we summarize the results obtained for these properties and use an unsupervised machine learning algorithm for the classification of aerosol types. Five types of aerosols, i.e., marine, freshly-formed, mixture, moderate dust and heavy dust, were classified. Air masses during marine periods are from the Atlantic Ocean and during dust periods are from the Sahara. Heavy dust was more frequently present during wintertime, whereas the clean marine periods were more frequently present during springtime. It was observed that during the dust periods CCN number concentrations at a supersaturation of 0.30 % are roughly 2.5 times higher than during marine periods, but the hygroscopicity (κ) of particles in the size range from ∼30 to ∼175 nm during marine and dust periods are comparable. The long-term data presented here, together with the aerosol classification, can be used as a base to improve our understanding of annual cycles of the atmospheric aerosol in the eastern tropical Atlantic and on aerosol-cloud interactions and it can be used as a base for driving, evaluating and constraining atmospheric model simulations.
Is it Good or Bad to Provide Driver Fatigue Warning During Take-Over in Highly Automated Driving?

When and how the driver should be intervened to relieve the fatigue status in Society of Automotive Engineers Level 3 automated driving has raised numerous debates. In this paper, we identify the driver’s fatigue level according to the driver’s facial features before the system issues the take-over request (TOR), and then perform the fatigue warning (FW) intervention to investigate whether the driver would be better prepared for taking over the vehicle safely and efficiently. In a simulator-based study, we compared the driver’s driving performance under the condition of whether a FW intervention was provided before a possible TOR, with the aim to gain insights into the ability of fatigued drivers to regain manual control and situation awareness after automated driving. A FW + TOR condition was compared with a TOR-only condition using a within-subject design with 30 participants. Under the effect of FW, participants exhibited better take-over performance; for example, they gazed at the road and placed their hands on the steering wheel earlier before taking over the vehicle. Moreover, in the FW + TOR state, they also exhibited better take-over performance, with a shorter average braking reaction time and a higher average speed, which reflects that the driver’s speed is more stable during the take-over of the vehicle and that the take-over task can be completed with a smaller deceleration. Furthermore, it is concluded that the FW (5 s before TOR) + TOR mode has greater potential to increase the safety and acceptance of automated driving, and could reduce the driver’s safety risk in a fatigue state when driving automatically compared with the FW (10 s before TOR) + TOR mode. It is concluded that FW (5 s before TOR) + TOR mode has the potential to increase safety and acceptance of automated driving as compared with systems that provide only TORs. In addition, we need to design take-over scenarios and non-driving-related tasks with different levels of complexity to satisfy subsequent research. The fatigue detection method based on image-processing techniques also needs further improvement.
An approach to Plant Disease Detection using Deep Learning Techniques

Agriculture is the backbone of Indian economy. Conventional farming systems are no longer being followed by our generation, due to lack of knowledge and expertise. Advancement of technologies pave a path that make a transition from traditional farming methods to smart agriculture by automating the processes involved. Challenges faced by today’s agriculture are depletion of soil nutrients and diseases caused by pests which lead to low productivity, irrigation problems, soil erosion, shortage of storage facilities, availability of quality seeds, lack of transportation, poor marketing etc. Among all these challenges in agriculture, prediction of diseases remains a major issue to be addressed. Identifying diseases based on visual inspection is the traditional way of farming which needs knowledge and experience to handle. Automating the process of detecting and identifying through visual inspection (cognitive) is the motivation behind this work. This is made possible with the availability of images of the plant or parts of plants, since most diseases are reflected on the leaves. A deep learning network architecture named Plant Disease Detection Network PDDNet-cv and a transfer learning approach of identifying diseases in plants were proposed. Our proposed system is compared with VGG19, ResNet50, InceptionResNetV2, the state-of-the-art methods reported in [9, 13, 5] and the results show that our method is significantly performing better than the existing systems. Our proposed PDDNet-cv has achieved average classification accuracy of 99.09% in detecting different classes of diseases. The proposed not so deep architecture is performing well compared to other deep learning architectures in terms of performance and computational time.
Performance evaluation of the modified FBLP method for angle of arrival estimation using real radar multipath data

The paper presents the results of a detailed evaluation of the modified forward-backward linear prediction (FBLP) method used for angle of arrival estimation in a low-angle tracking radar environment. The results are based on real radar data pertaining to an angular separation of less than one standard beamwidth between the direct and image components impinging on the radar antenna. The results confirm the superior performance of this method compared to a conventional FFT beamformer. The paper also includes a brief review of the modified FBLP method.
Extended phased array model for the calculation of mechanical bulk wave excitation in SAW reflectors

A new model for mechanical conversion of surface acoustic waves (SAWs) into bulk acoustic waves (BAWs) in SAW reflectors is presented. It is based on the far field computation of a bulk wave source distribution. These sources are derived from a one-dimensional P-Matrix formalism, which is known to be an accurate description of SAW propagation under metallic gratings. The model takes into account the anisotropy of the piezoelectric substrate and is not restricted to a specific acoustic wave type. Furthermore, arbitrary reflector geometries can be considered allowing for the modeling of finger width-weighted, position-weighted and chirped reflectors which are increasingly used in low loss SAW filters. By the use of our model, for the first time bulk wave losses at harmonic stop band frequencies can be predicted and characterized. <<ETX>>
Statistical Modeling and Performance Optimization of a Two-Chamber Microbial Fuel Cell by Response Surface Methodology

Microbial fuel cell, as a promising technology for simultaneous power production and waste treatment, has received a great deal of attention in recent years; however, generation of a relatively low power density is the main limitation towards its commercial application. This study contributes toward the optimization, in terms of maximization, of the power density of a microbial fuel cell by employing response surface methodology, coupled with central composite design. For this optimization study, the interactive effect of three independent parameters, namely (i) acetate concentration in the influent of anodic chamber; (ii) fuel feed flow rate in anodic chamber; and (iii) oxygen concentration in the influent of cathodic chamber, have been analyzed for a two-chamber microbial fuel cell, and the optimum conditions have been identified. The optimum value of power density was observed at an acetate concentration, a fuel feed flow rate, and an oxygen concentration value of 2.60 mol m−3, 0.0 m3, and 1.00 mol m−3, respectively. The results show the achievement of a power density of 3.425 W m−2, which is significant considering the available literature. Additionally, a statistical model has also been developed that correlates the three independent factors to the power density. For this model, R2, adjusted R2, and predicted R2 were 0.839, 0.807, and 0.703, respectively. The fact that there is only a 3.8% error in the actual and adjusted R2 demonstrates that the proposed model is statistically significant.
Broadband shorted‐patch antenna with U‐shaped coupling slot

A shorted‐patch antenna with a U‐shaped coupling slot for broadband operation is presented.The U‐shaped coupling slot etched on the ground plane is located in close proximity to the shorting wall to obtain a good impedance matching. Using an L‐shaped shorting wall with a height of about 6% wavelength at the center operating frequency and a U‐shaped coupling slot, the proposed microstrip patch antenna has a compact size and broadband operation. The proposed antenna yields a wide bandwidth of about 33.6% and a peak gain of 4.2 dBi. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53:2566–2569, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26339
Impact of Faulty Links on Quality-of-Service in Network-on- Chip under Different Traffic Patterns

†† Summary The objective of this paper is to introduce the impact of faulty links on Quality of Service in Network-on-Chip (NoC) under different traffic pattern. NoC paradigm has made it possible to concurrently run multiple applications on IP-core based System on Chip. It is therefore necessary to predict the multi-processor systems-on-chip communication, which is a critical issue and needs to be addressed by the right mix of soft and hard real-time guarantees. To meet this requirement state of the art packet switched NoC provide different levels of quality of service (QoS) such as best effort (BE) and guaranteed throughput (GT). This paper presents a novel scheme which compares and evaluates the performance of guaranteed throughput and best effort traffic in Network-on-Chip under different synthetic traffic generators and highlights its dependence in terms of latency on the type of traffic patterns and number of link failures for mesh topology. It also explores the effect of robustness of a particular traffic pattern in terms of fault tolerance (variation in average latency as the number of link failures increases) for planar adapter routing function on latency of GT and BE traffic class for mesh topology.
Optimal placement of sampling locations for identification of a two-dimensional space

ABSTRACT In recent years, substantial attention has been given to the optimal placement and planning of sampling or monitoring based on the Value of Information (VoI). The drawback of the VoI approach is its typically high computation cost. The method proposed here can significantly reduce the computation cost of VoI by applying the theory of Gaussian Process Regression. Due to the low computation cost, global optimisation algorithms such as particle swarm optimisation can be used to optimise a set of sampling locations. The proposed method was applied to a soil contamination problem. For comparison purposes, twenty-one subjects (persons) were asked to follow a three-step procedure. In the first step, contamination levels at five fixed sampling locations are given. Based on this information, the contaminated area is estimated by the subject, who is then asked to place five additional sampling sites in order to gather more information. The procedure is repeated three times. The subject is ultimately asked to produce a final estimate of the contaminated area. It was found that the proposed method generally produced better agreement with the true contaminated area than did the participants’ empirical human judgment.
The genetics of oil yield inMelaleuca alternifolia andEucalyptus loxophleba

The family Myrtaceae is known for its high foliar terpene concentrations as well as significant qualitative and quantitative variation in foliar terpenes between taxa, populations and individuals. To date, few studies have investigated the genetic and biochemical processes, which underlie this variation, much of which is known to be under genetic control. Differences in yield are both ecologically and commercially important and a better understanding of its basis will allow a greater understanding of Australian ecosystems, as well as improve commercial viability of essential oil industries. Over the past decade a good understanding of the genes involved in terpene biosynthesis has developed in other species and several important regulatory steps have been identified. Much of this work has been done in transgenic plants, so our understanding at a molecular level is strong. Nonetheless, it remains unclear if these processes are transferrable to wild populations, or indeed how ecologically important quantitative variation in terpenoids arise and are maintained in natural ecosystems. In this review we summarize what is known about terpene biosynthesis and the control of flux through the terpene biosynthetic pathways. Then we argue that this platform of work provides a great resource for Myrtaceae, as well as other plants, to identify candidate genes that control flux through the biosynthetic pathways and how this will inform further studies into the ecological implications of quantitative variation of terpenes. Work into terpene biosynthesis would also provide a framework to improve the profitability of essential oil crops.
Time Error in Project Management: A Case Study in Yanbu, Saudi Arabia

Time error is a reality in the majority of projects. This paper presents empirical research which investigates the influence of time error during project life cycle. Data were collected using interviews with project managers and analyzed using content analysis. The findings explore the causes of time error in projects in Yanbu, Saudi Arabia. This study gives an introductory insight into the influence of time error. It finds that time error affects the triple constraints of project management.
An Unbiased Mineral Compositional Analysis Technique for Circumstellar Disks

A circumstellar disk that surrounds a star is composed of gas, dust, and rocky objects that are in orbit around it. Around infant stars, this disk can act as a source of material that can be used to form planetesimals, which can then accrete more material and form into planets. Studying the mineral composition of these disks can provide insight into the processes that created our solar system. The purpose of this paper is to analyze the mineral composition of these disks by using a newly created python package, Min-CaLM. This package determines the relative mineral abundance within a disk by using a linear regression technique called non-negative least square minimization. The circumstellar disks that are capable of undergoing compositional analysis must have a spectrum with both a detectable mid-infrared excess and prominent silicate features. From our sample, there are only eight debris disks that qualify to be candidates for the Min-CaLM program. The mineral compositions calculated by Min-CaLM are then compared to the Tholen asteroid classification scheme. HD 23514, HD 105234, HD 15407A, BD+20 307, HD 69830, and HD 172555 are found to have a compositions similar to that expected for C-type asteroids, TYC 9410-532-1 resembles the composition of S-type asteroids, and HD 100546 resembles D-type asteroids. Min-CaLM also calculates the mineral compositions of the comets Tempel 1 and Hale-Bopp, and they are used as a comparison between the material in our early solar system and the debris disk compositions. KEYWORDS: Debris disk; Mineral; Composition; Analysis; Asteroid; Circumstellar; Spectroscopy; Python
Methodology for Modeling Tidal Turbine

In tidal turbine engineering it is common place to use the theory of wind energy engineering in the modeling of turbines. This paper identifies the common design principles in the field, addresses the pitfalls of adopting this theory, and attempts to identify other modeling techniques that might add to the knowledge base used in preparing power production estimates. A methodology for modeling different turbine designs is postulated. I. INTRODUCTION In stream tidal turbines, or marine current turbines are often designed on the adaptation of wind energy principles to a sub sea environment, and thus the most commonly used analysis technique in the industry is that of blade element momentum theory, which is the theory used in analyzing wind turbines power coefficients. It is important to note that there exist fundamental differences between the two resources, and it is necessary to investigate all of the potential modeling techniques, and to identify the most appropriate model for each design ofturbine. The overall goal of this paper will be the identification of a methodical approach to turbine investigation, in doing so it will highlight the differences and similarities between wind and tidal turbine technologies. This comparison between the two technologies is often cited; however it is important at this stage in development of the industry to ensure that assumptions are not being made unduly, and to recognize the areas in which the two technologies differ. Wind and tidal energy use a moving fluid to drive a device, or turbine, to convert fluid kinetic energy into electrical energy. The wind energy industry has become a staple in the renewable energy market since the 1970's. In the early stages of wind energy engineering, there existed several designs for turbines, from vertical to horizontal axis, ducted to un-ducted. However the turbine that has become the industry standard is the three bladed horizontal axis turbine. Tidal energy is currently pre-commercial, with several unique designs being proposed by different manufacturers. However the different characteristics of tidal streams may mean that there is not one clear choice for tidal turbine design, and that a methodology for tidal turbine selection might benefit the industry. It is important to explain that wind and tidal energy differ dramatically in some fundamental ways. Wind and tidal differ significantly in density and constraint. Sea water is considerably denser than air, and thus will behave differently.