Miracle-dz/UniFAR-FTUs huggingface dataset:
On‐line assessment of prediction risk for wind power production forecasts

The paper introduces a new methodology for assessing on-line the prediction risk of short-term wind power forecasts. The first stage of this methodology consists in computing confidence intervals with a confidence level defined by the end-user. The resampling approach is used, which in contrast to existing methods for wind forecasting, does not need to make a restrictive hypothesis on the distribution of the errors. To account for the nonlinearity of the power curve and the cut-off effect, the errors are classified using appropriate fuzzy sets. The confidence intervals are then fine-tuned to reduce their width in case of stable weather conditions. For this purpose, an appropriate index, named as MRI, is defined reflecting the spread of the available Numerical Weather Predictions. A linear relation between that index and the resulting prediction error is shown. The second part of the methodology is to use the MRI-index itself as a preventive on-line tool to derive signals for the operator on the meteorological risk, i.e. the probabilities for the occurrence of high prediction errors depending on the weather stability. Evaluation results of this methodology over a one-year period on the case study of Ireland are given, where the output of several wind farms is predicted using a dynamic Fuzzy-Neural Networks based model. The proposed methodology is generic and can be applied to all kinds of wind power prediction models.
Securing Transmission for UAV Swarm-Enabled Communication Network

Deploying unmanned aerial vehicles (UAVs) in communication networks could achieve desirable degrees of freedom, but resulting from the high line-of-sight link attributes, security threats faced by UAV communications are serious. Taking that into consideration, we focus on a UAV swarm-enabled communication network in this article, where a fixed-wing UAV acts as a legitimate user and a neighboring UAV eavesdropper attempts to eavesdrop the confidential information forwarded by rotary-wing UAV relays. In particular, we jointly optimize transmit power on the base station and UAV relays, power allocation coefficient and beamforming on UAV relays, and trajectory of the fixed-wing UAV to maximize the average secrecy rate. Due to the nonconvexity of the optimization problem, the block coordinate descent method is utilized to solve it. Specifically, the overall optimizing problem is divided into four subproblems in which the transmit power, power allocation coefficient, beamforming vector, and the trajectory of user are optimized, respectively. By employing the successive convex approximate method, subproblems are transformed to convex problems which are numerically tractable. Numerical simulations validate the effectiveness of the proposed algorithm and show that compared with benchmark schemes, the considered transmission scheme with artificial noise and optimized network parameters can improve secrecy rate by about 13.8%.
A Study on 16-Channel LED Driver IC for Full-Color LED Display

This paper proposes the 16-channel LED Driver IC for Full color LED display system. The proposed LED driver IC in this paper can draw current independent of temperature and supply voltage in each channel. Current flow in the channel is configurable via an external resistor. LED brightness is adjusted by 12-Bit PWM(Pulse Width Modulation) and 8-Bit DC(Dot Correction). A real-time monitoring of IC temperature () and LED status (open/short) is provided by LED driver IC and the user can receive warning and get information on problems. A 16-channel LED driver IC is produced using 0.35 um BCD process and the size is . In this paper, channel current characteristic and channel current control function were measured in order to verify am embodied 16-channel LED driver IC by producing a single IC test board.
Inductorless Bidirectional Switched-Capacitor Power Electronics Transformer

The objective of this article is to propose a new inductorless bidirectional switched-capacitor power electronics transformer (IBSCX) for low-power commercial and residential applications. The proposed IBSCX is composed of multiple switched-capacitor converters (SCCs) and two bidirectional unfolders. Compared with the traditional solution which is the use of a low-frequency transformer, the advantages of the proposed IBSCX include control circuit simplicity, high conversion efficiency, and volume and weight reduction for low-power applications. The principle of operation, voltage gain analysis, and design methodology are described in this article. Also, with the interleaved operation between SCCs, the output current ripple can be reduced. Finally, the computer simulations and hardware experimental results are shown to verify the performance of the proposed IBSCX. A prototype IBSCX is built and tested, and the peak and rated power conversion efficiency are 98.26% and 97.95%, respectively.
Enhanced hand tracking using the k-means embedded particle filter with mean-shift vector re-sampling

Particle filters have been applied with great success to 2D and 3D tracking problems. We presents the tracking of two hands based on a statistical model using only a skin colour feature with particle filtering for gesture recognition. The tracking scheme employs the reliability measurement derived from the particle distribution which is used to adaptively weight the skin-pixel colour classification. Our approach chooses shift-vectors to re-weight the particle sample to improve accuracy and reduce the number of samples. The k-means algorithm is used to discriminate the split and merge between left and right hands in case they are close together. Experiments with a set of videos including the movement of two hands in sample and cluttered backgrounds show that adaptive use of our scheme provides improvement compared to use with auxiliary particle filter of the number of samples and accuracy.
Key Issues for Cloud Manufacturing Platform

In order to realize sharing and collaboration of manufacturing resource and manufacturing capability based on knowledge and to realize added value of manufacturing resource and manufacturing capability. In this paper, we propose an ontology-based architecture for cloud manufacturing platform. Meanwhile, several key issues for cloud manufacturing platform including semantic description of manufacturing resource and manufacturing capability, manufacturing cloud service advertisement, manufacturing cloud service discovery and manufacturing cloud service composition are studied in particular. Thus, the research provides foundation for the future research, development, implementation and application of cloud manufacturing platform.
68.4: Optimal Additive Mixing Approach via Multi‐Color LEDs Platform

On the basis of additive mixing approach via multi‐color LEDs, we demonstrated a universal platform to synthesize the spectral power distribution in accordance with possibly highest color rendering performance and luminous efficacy of radiation under a designated correlated color temperature. The platform associated with the optimization algorithm and LED matrix setup allows the use of a feedback mechanism to validate the feasibility of the proposed scheme for the general lighting applications.
OFDM LDPC performance comparison on an HF multipath fading channel

High Frequency (HF) radio communication channels provide unique challenges to digital communication systems. Typical HF communication systems propagate electromagnetic energy in the 2-30MHz radio spectrum using the earth's ionosphere and surface as both refractors and reflectors for non line of sight communications. Constantly changing ionosphere conditions result in multipath and severe fading channel characteristics. Through numerical simulation, short block length block length (9e+3) Low Density Parity Check (LDPC) forward error correction codes used in conjunction with Orthogonal Frequency Division Multiplexing (OFDM) will be shown to provide excellent communication performance across the HF channel. Average bit error rate performance results will be shown for a 2ms, 1Hz and 2Hz Watterson HF channel model for both regular and irregular LDPC parity check matrices. Some results will also be shown for imperfect channel estimation and its effects upon the performance of the LDPC decoder.
2.4/5.7-GHz CMOS Dual-Band Low-IF Architecture Using Weaver–Hartley Image-Rejection Techniques

A 2.4/5.7-GHz dual-band Weaver-Hartley architecture, using 0.18-mum CMOS technology, is demonstrated in this paper. The 2.4-GHz signal is set to be the image signal when the desired signal is at 5.7 GHz, and vice versa. Since the Weaver and Hartley systems are combined into this architecture, the demonstrated architecture rejects not only the first image signal, but also the secondary image signal. The image-rejection ratios of the first image signal and the secondary image signal are better than 40 and 46 dB, respectively. In this paper, a diagrammatic explanation is employed to obtain the image-rejection mechanisms of the Weaver-Hartley architecture.
Tactile sensing fabrics for detecting impairments in leprosy patients

There has been a rising need for developing a rehabilitation device for patients with leprosy, as most of the present day approach is towards the eradication of the disease. To assist and monitor the extent of damage of a nerve and muscle cells, a new fabric embedded tactile sensor incorporated in gloves and other smart fabrics are used. By incorporating tactile sensing in the gloves, and recording the information off the gloves, the results were evident in showing the effect of prolonged usage of any particular part of the limbs. (6 pages)
Filtering Shrew DDoS Attacks Using A New Frequency-Domain Approach

The stealthy shrew Distributed Denial of Services (DDoS) attacks, also known as Reduction of Quality (RoQ) attacks, could be even more detrimental than the more widely known flooding DDoS assaults. The reason is that such shrew attacks damage the victim servers for a long time without being noticed, thereby denying new visitors to the victim servers, which are mostly e-commerce sites. Thus, in order to minimize the monetary losses, there is a pressing need to effectively detect such attacks in real-time. Unfortunately, effective detection of shrew attacks remains an open problem. In this paper, we meet this challenge by proposing a new signal-processing approach to identifying and detecting the attacks by examining the frequency domain characteristics of incoming traffic flows to a server. Our proposed technique is effective in that its detection time is less than a few seconds. Furthermore, the technique entails simple implementation, making it deployable in real-life network environments.
Increasing cable rating by distributed fiber optic temperature monitoring and ampacity analysis

The allowable current that can be carried by underground cables is limited by the hottest location along the circuit. Deratings of 10% or more can result from deep burial, nearby distribution duct banks or steam mains, or areas of high soil thermal resistivity. Accurate knowledge of thermal conditions along the route will permit confidently rating the cables right up to their maximum ampacity. Distributed fiber optic temperature monitoring uses an enhanced optical time domain reflectometer to inject a laser pulse down a conventional multimode fiber, and develop a temperature profile with one centigrade degree accuracy along every meter of a cable circuit. This paper describes an application where a temperature profile combined with methods developed to relate optical fiber temperature to cable conductor temperature, plus sophisticated ampacity analyses, permitted one utility to obtain an 8% ampacity increase and defer reinforcing a 69 kV circuit by two years.
Uma Arquitectura Experimental para Composição de Animações

1. INTRODUÇÃO Actualmente são vários os ambientes sintéticos a envolverem animações de humanos virtuais, desde os efeitos especiais da indústria cinematográfica em que a interactividade está completamente ausente, e de que são exemplos o filme “Matrix” dos irmãos Wachowski ou o mais recente “Bewolf 3D” que constitui o actual estado da arte neste campo, passando pelo mundo das comunidades virtuais, com a interactividade de um “Second Life” e o seu ainda concomitante fraco realismo, até aos jogos para consolas em que o “Grand Theft Auto IV” com uma temática de violência gratuita parece estabelecer um novo padrão de realismo e interactividade.
Breast Cancer Detection and Diagnosis Using Machine Learning: A Survey

: Breast cancer is one of the most widespread diseases causing death among women worldwide. Whenever a suspicion is raised, periodical exams usually including digital mammograms (DM), Infrared thermography, magnetic resonance imaging (MRI), ultrasound (US), microscopic (histological) images, microwave images, or other tools or tests might be recommended. Recently, many hardware and software have been applying different techniques for achieving high-quality results, especially the techniques of machine learning. In this paper, a comprehensive survey to review most of the accurate techniques being used for both detecting and diagnosing breast cancer is conducted. Besides, different commercial and non-commercial hardware and software are mentioned with their advantages and disadvantages in the process of detecting and diagnosing breast lesions. This study reveals that many techniques have been raised to help for breast cancer detection and diagnosis, however, there is no perfect modality that can detect and diagnose breast cancer alone. Moreover, a complete system that can deal with different modalities and gives 100% accuracy still a challenge, since the various structure of breast cancer and the different structure of images issued by a group of modalities that have been used.
Economic Impacts of the U.S. Renewable Fuel Standard: An Ex-Post Evaluation

This paper examines the extent to which biofuel production has been driven over time by the U.S. Renewable Fuel Standard (RFS) and the extent to which it was driven by non-RFS policies and market forces. While the RFS has played a critical role in providing a secure environment to produce and use more biofuels, at least in the 2000s, it was not the only factor that encouraged the biofuel industry to grow. While the existing literature has successfully identified the key drivers of the growth in biofuels, it basically has failed to properly quantify the impacts and contributions of each of these drivers separately. This paper develops short- and long-run economic analyses, using Partial Equilibrium (PE) and Computable General Equilibrium (CGE) models, to differentiate the economic impacts of the RFS from other drivers that have helped biofuels to grow. Results show: 1) the bulk of the ethanol production prior to 2012 was driven by what was happening in the national and global markets for energy and agricultural commodities and by the federal and sometimes state incentives for biofuel production; 2) the medium-to long-run price impacts of biofuel production were not large; 3) due to biofuel production, regardless of the drivers, real crop prices have increased between 1.1 and 5.5% in 2004–11 with only one-tenth of the price increases were assigned to the RFS, 4) for 2011–16, the long-run price impacts of biofuels were less than the time period of 2004–11, as in the second period biofuel production increased at much slower rate; 5) biofuel production, regardless of the drivers, has increased the US annual farm incomes by $8.3 billion between 2004–11 with an extra additional annual income of $2.3 billion between 2011–2016; 6) the modeling practices provided in this paper assign 28% of the expansion in farm incomes of the period of 2004–2011 and 100% of the extra additional incomes of the period of 2011–16 to the RFS.
Empirical research on supply chain management: A critical review and recommendations

Despite the growing interest in supply chain management (SCM), our understanding of the subject issue is still limited, largely due to inadequate attention being placed to theory building. To address this problem, this paper highlights some major weaknesses of the extant literature with respect to the conceptualization, operationalization, and modelling of SCM, identifies potential causes underlying these shortcomings, and gives some recommendations to improve theory development in this area. Specifically, it demonstrates that (1) the SCM construct has been perceived narrowly from the perspective of a particular traditional function of a firm; (2) the construct validity is threatened due to inadequate pre-operational explication of the content domain, among other operationalization problems; and (3) the dominant conceptual SCM models focus mainly on the practices-performance relationship, overlooking the context-practices relationship. A greater advance in theory development is possible if researchers adopt a process-based view of SCM, develop conceptual SCM models based on a context-practices-performance framework, and synthesize theories and research of SCM and those of related fields such as organization studies.
Age-related cognitive decline and navigation in electronic environments

The older population is increasing, as is life expectancy. Technical devices are becoming more widespread and used for many everyday tasks. Knowledge about new technology is important to remain as an active and independent part of the society. However, if an old user group should have equal access to this technology, new demands will be placed on the design of interfaces and devices. With respect to old users it is and will be important to develop technical devices and interfaces that take the age-related decline in physical and cognitive abilities into account. The aim of this work was to investigate to what extent the age-related cognitive decline affects performance on different computer-related tasks and the use of different interfaces. With respect to the use of computer interfaces, two studies were conducted. In the first study, the information was presented with a hierarchical structure. In the second study the information was presented as a 3D-environment, and it was also investigated how an overview map could support navigation. The third study examined the age-related cognitive decline in the use of a small mobile phone display with a hierarchical information structure. The results from the studies showed that the most pronounced age-related difference was found in the use of the 3D-environment. Within this environment, prior experience was found to have the largest impact on performance. Regarding the hierarchical information structures, prior experience seemed to have a larger impact on performance of easy tasks, while age and cognitive abilities had a larger impact on performance of more complex tasks. With respect to navigation aids, the overview map in the 3D-environment did not reduce the age-differences; however, it contributed to a better perceived orientation and reduced the feeling of being lost.
Machine learning methods for perioperative anesthetic management in cardiac surgery patients: a scoping review

Background Machine learning (ML) is developing fast with promising prospects within medicine and already has several applications in perioperative care. We conducted a scoping review to examine the extent and potential limitations of ML implementation in perioperative anesthetic care, specifically in cardiac surgery patients. Methods We mapped the current literature by searching three databases: MEDLINE (Ovid), EMBASE (Ovid), and Cochrane Library. Articles were eligible if they reported on perioperative ML use in the field of cardiac surgery with relevance to anesthetic practices. Data on the applicability of ML and comparability to conventional statistical methods were extracted. Results Forty-six articles on ML relevant to the work of the anesthesiologist in cardiac surgery were identified. Three main categories emerged: (I) event and risk prediction, (II) hemodynamic monitoring, and (III) automation of echocardiography. Prediction models based on ML tend to behave similarly to conventional statistical methods. Using dynamic hemodynamic or ultrasound data in ML models, however, shifts the potential to promising results. Conclusions ML in cardiac surgery is increasingly used in perioperative anesthetic management. The majority is used for prediction purposes similar to conventional clinical scores. Remarkable ML model performances are achieved when using real-time dynamic parameters. However, beneficial clinical outcomes of ML integration have yet to be determined. Nonetheless, the first steps introducing ML in perioperative anesthetic care for cardiac surgery have been taken.
A K-band AlGaN/GaN HFET MMIC Amplifier on Sapphire using novel superlattice cap layer

We have developed a K-band AlGaN/GaN HFET MMIC amplifier by applying an AlGaN/GaN superlattice (SL) capped structure on sapphire substrate. Owing to the lowest (0.4 Ω · mm) source resistance of AlGaN/GaN HFETs, the HFETs exhibited excellent DC and RF characteristics, and sufficient ability to operate in the K-band frequency range is obtained. The fabricated MMIC with a CPW-line structure exhibited a small-signal gain higher than 10 dB with a 3-dB bandwidth of 20-24.5 GHz and that of 13 dB at 21.6GHz when biased at a supply voltage of 7 V. The 1dB compression point (P1dB) referred to output of 15.4 dBm at 21.6 GHz was obtained. This work is the first report of MMIC amplifier fabricated on sapphire successfully operating in the K band.
Theoretical model of high temperature effects on uniaxial concrete member under elastic restraint

An analytical solution to a uniaxial benchmark problem of a concrete member restrained by an elastic spring and subject to heating and subsequent cooling is given. The model demonstrates the effect of load-induced thermal strain, which has so far only been described through experiments. Heating a concrete specimen under constant compressive load shows a significant contraction rather than expansion, which would be the case if the specimen were heated without any constraints. The magnitude of this contraction is beyond that of conventional creep and mechanical strain even though the stiffness degradation from high temperature exposure is taken into account. Thus, it is attributed to a special thermo-mechanical coupling, taking place during the first transient heating process. Furthermore, the analytical model describes the tensile stresses, developing during cooling, including non-linear material behaviour arising from fictitious cracking. Through several examples the effect of the various parameters is ev.
Microsimulation-Based Framework for Freeway Travel Time Forecasting

This paper presents a microsimulation-based framework for generating short-term forecasts of travel time on freeway corridors. The microsimulation model that was developed replicated freeway capacity drop and relaxation phenomena critical for modeling non–steady state conditions. This framework was evaluated offline on a real-world freeway corridor by using data from manual counts and the Georgia Department of Transportation's video detection system. The travel time forecasts were compared with ground truth travel time data; the comparison demonstrated the efficacy of this framework to produce realistic forecasts.