Miracle-dz/UniFAR-FTUs huggingface dataset:
Judgement in learning‐curve forecasting: a laboratory study

This study investigates whether human judgement can be of value to users of industrial learning curves, either alone or in conjunction with statistical models. In a laboratory setting, it compares the forecast accuracy of a statistical model and judgemental forecasts, contingent on three factors: the amount of data available prior to forecasting, the forecasting horizon, and the availability of a decision aid (projections from a fitted learning curve). The results indicate that human judgement was better than the curve forecasts overall. Despite their lack of field experience with learning curve use, 52 of the 79 subjects outperformed the curve on the set of 120 forecasts, based on mean absolute percentage error. Human performance was statistically superior to the model when few data points were available and when forecasting further into the future. These results indicate substantial potential for human judgement to improve predictive accuracy in the industrial learning-curve context. Copyright © 1999 John Wiley & Sons, Ltd.
ENDNOTE TRAINING FOR ACADEMIC STAFF AND STUDENTS: THE EXPERIENCE OF THE MANCHESTER METROPOLITAN UNIVERSITY LIBRARY

This article describes how the Manchester Metropolitan University Library delivers EndNote training to its academic staff and students through hands-on workshops and online tutorials. As the demand is user-led and the response extremely positive, the Library considers the provision of EndNote training as analogous to a ‘Trojan horse’ that allows the Library welcomed and unchallenged into the camp of the user. The Library has used the opportunity strategically and, consequently, has benefited in a number of ways, including improved communication with academic staff and increased awareness of library resources on the part of users. A short literature review is provided.
Goals of and open problems in high-performance heterogeneous computing

Ideally, a heterogeneous computing (HC) environment, is a well-orchestrated and coordinates suite of high-performance machines that provides support for computationally intensive applications with diverse computing requirements. Such an HC system includes a heterogeneous suite of machines, high-speed interconnections, interfaces, operating systems, communication protocols, and programming environments. HC is the effective use of these diverse hardware and software components to meet the distinct and varied computational requirements of a given application. Implicit in this concept of HC is the idea that subtasks with different machine architectural requirements are embedded in the applications executed by the HC system. Two types of HC systems, mixed-mode machines and mixed-machine systems, are discussed. The goals of and open problems in HC are overviewed.
More the merrier...or is it? Sensor suite augmentation benefits assessment

It is often implicitly assumed in the information fusion field that augmentation of a multi-sensor suite with additional sensors de facto enhances overall system performance because of the increase in the data being input to the fusion process. In this study, an explicit assessment of the validity of this assumption is made in terms of delineating the sensor characteristics domain wherein this is true (i.e., where fusion benefits do indeed increase) and quantitatively determine the extent of such benefits. Initially for illustrative purposes, a two-sensor suite augmented by a third sensor is used as a case study for this assessment. The consensus fusion logic, which is symmetric relative to the multiple sensors in the sensor suite, is employed as an example in this assessment process. The scope for generalizing this assessment to higher dimensional multi-sensor suites as well as other types of fusion logic is also discussed.
An Approach of Web Page Information Extraction

The Web has become the largest information source, but the noise content is an inevitable part in any web pages. The noise content reduces the nicety of search engine and increases the load of server. Information extraction technology has been developed. Information extraction technology is mostly based on page segmentation. Through analyzed the existing method of page segmentation, an approach of web page information extraction is provided. The block node is identified by analyzing attributes of HTML tags. This algorithm is easy to implementation. Experiments prove its good performance.
"Computer as Data Gatherer" for a New Generation: Martorella's Predictions, the Past, the Present, and the Future of Technology in Social Studies.

In his 1997 article “Technology and the Social Studies - or: Which Way to the Sleeping Giant? ” Peter Martorella made several predictions regarding technology resources in the social studies. Through a 2014 lens, Martorella’s Internet seems archaic, yet two of his predictions were particularly poignant and have had a significant impact on social studies instruction: the phenomenon of “computer as data gatherer” (p. 513) and a “new generation” of the Internet that would become more interactive (p. 512). This paper highlights the literature in these two areas, beginning with a focus on the vantage point from which Martorella was writing. The paper also describes the learning potential inherent in more recent technological developments, particularly mobile technology devices, and the degree to which they are currently being used in K-12 social studies. Books will soon be obsolete in schools. Scholars will soon be instructed through the eye. It is possible to teach every branch of human knowledge with the motion picture. Our school system will be completely changed in ten years (Thomas Edison, 1913, as quoted in Saettler, 1990, p. 100).
Training autoassociative recurrent neural network with preprocessed training data

The Auto-Associative Recurrent Network (AARN), a modified version of the Simple Recurrent Network (SRN) can be trained to behave as recognizer of a language generated by a regular grammar. The network is trained successfully on an unbounded number of sequences of the language, generated randomly from the Finite State Automation (FSA) of the language. But the training algorithm fails when training is restricted to a fixed finite set of examples. Here, we present a new algorithm for training the AARN from a finite set of language examples. A tree is constructed by preprocessing the training data. The AARN is trained with sequences generated randomly from the tree. The results of the simulations experiments are discussed.
Making Distance Learning an Effective Health Information Systems Training Strategy: A Combined Social Network Analysis and Content Analysis Perspective

Health Information Systems (HIS) training have been recognized as one of the important aspects of any HIS implementation which contributes to its success or failure. Providing high quality training in low resource settings have been a challenge for many HIS initiatives including for the Health Information Systems Program (HISP) with regard to its DHIS 2 implementations. In order to tackle these challenges, it was decided to introduce online distance training as a supplement to its face‐to‐face training academies. However, the interactions generated within the online training and the perceived knowledge construction was variable in different training instances. Therefore, the study made use of social network analysis (SNA) and content analysis (CA) as tools to understand the type of interactions that took place within such learning instances and the degree of knowledge constructions that was achieved through such interactions. This enabled the study to assess the best practices when utilizing online distance learning for providing HIS training in low resource settings particularly with regard to ‘short’ online training programs. The findings from the study supports the successful utilization of short online learning programs for the said purpose with adaptation of ‘best practices’ to enable participant interactions and knowledge construction.
Realtime Signal Processing Data∞ow, Visual, and Functional Programming

This thesis presents and justifies a framework for programming real-time signal processing systems. The framework extends the existing “block-diagram” programming model; it has three components: a very high-level textual language, a visual language, and the dataflow process network model of computation. The dataflow process network model, although widely-used, lacks a formal description, and I provide a semantics for it. The formal work leads into a new form of actor. Having established the semantics of dataflow processes, the functional language Haskell is layered above this model, providing powerful features—notably polymorphism, higher-order functions, and algebraic program transformation—absent in block-diagram systems. A visual equivalent notation for Haskell, Visual Haskell, ensures that this power does not exclude the “intuitive” appeal of visual interfaces; with some intelligent layout and suggestive icons, a Visual Haskell program can be made to look very like a block diagram program. Finally, the functional language is used to further extend dataflow process networks, by simulating timed and dynamically-varying networks. The thesis thus draws together a number of previously-separate ideas: a reasonable expectation of efficient execution using established dataflow compilation technology; a powerful and high-level programming notation; and a block-diagram style interface.
Photophysical and Electrochemical Properties of π‐Extended Molecular 2,1,3‐Benzothiadiazoles.

Abstract The reaction of 4,7-dibromo-2,1,3-benzothiadiazole with arylboronic acids (phenyl, 1-naphthyl, 4-methoxyphenyl, 4-chlorophenyl and 4-trifluoromethylphenyl) in the presence of catalytic amounts of a NCP-pincer palladacycle affords photoluminescent π-extended 4,7-diaryl-2,1,3-benzothiadiazoles 4a–e in high yields. These 4,7-diaryl-2,1,3-benzothiadiazoles exhibit high fluorescent quantum yields, high electron affinities and adequate band gap values for testing as OLEDs. The 4,7-bis-naphthyl-2,1,3-benzothiadiazole 4b presents two different lifetimes (bi-exponential decay) due to the presence of two atropisomers. The Sonogashira coupling reaction of 4,7-diethynyl-2,1,3-benzothiadiazole 6 with the corresponding halo-aryl compounds (iodobenzene, 1-bromonaphthalene, 4-iodoanisole, 4-bromo-N,N-dimethylaniline and 2-bromopyridine) afforded the photoluminescent π-extended 4,7-bis-alkynylaryl-2,1,3-benzothiadiazoles 7a–e , also in high yields. These 4,7-diethynyl-2,1,3-benzothiadiazoles also present high fluorescent quantum yields, high electron affinities and adequate band gap values for testing as OLEDs. The 4,7-disubstituted-2,1,3-benzothiadiazoles 4a–e and 7a–e exhibit different electrochemical behavior. The presence of two ethynyl spacers in 2,1,3-benzothiadiazoles 7a–e shifts the reduction potentials to less cathodic values and also results in two well-defined and distinct reduction processes.
Tuning of proportional plus derivative fuzzy logic controller using neural network

The transformation of an expert's knowledge to control rules in a fuzzy logic controller has not been formalized and arbitrary choices concerning, for example, the shape of membership functions have to be made. The quality of a fuzzy controller can be drastically affected by the choice of membership functions. Thus, methods for tuning fuzzy logic controllers are needed. In the paper, neural networks and fuzzy logic are combined to solve the problem of tuning fuzzy logic controllers. The neurofuzzy controller uses the neural network learning techniques to tune the membership functions while keeping the semantics of the fuzzy logic controller intact. Both the architecture and the tuning algorithm are presented for a general neuro-fuzzy controller. From this, a procedure to tune a proportional plus derivative fuzzy controller is obtained. The algorithm for off-line tuning of the fuzzy controller is demonstrated with a numerical example.
High performance liquid chromatographic profiling of antioxidant and antidiabetic flavonoids purified from Azadirachta indica (neem) leaf ethanolic extract

Abstract Azadirachta indica (neem) is a tropical and semi-tropical tree native to the whole Indian subcontinent. Neem leaves are rich in flavonoids, which exhibit important pharmacological activities targeting almost all human organs. In order to produce a purified extract of neem leaves enriched of antioxidant and antidiabetic flavonoids, the ethanolic extract of neem leaves has been further undergone to liquid-liquid extractions by using three different organic solvents, i.e. dichloromethane, n-butanol and ethyl acetate. Qualitative and quantitative analyses were performed on the extracts obtained by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Astragalin, quercitrin, isoquercitrin, nicotiflorin and rutin were the only flavonoids found among those screened. By comparing all HPLC chromatograms of purified extracts as obtained with different solvents, it was found that the qualitative-quantitative composition of flavonoids depends upon the extraction solvent used; in particular, dichloromethane allows extraction of 89.5 % quercitrin, 5.3 % isoquercitrin, 5.2 % rutin; n-butanol allows extraction of 6.0 % isoquercitrin, 6.2 % nicotiflorin, 87.8 % rutin; ethyl acetate allows extraction of 4.2 % astragalin, 12.0 % quercitrin, 50.3 % isoquercitrin, 6.7 % nicotiflorin, 26.9 % rutin. Thus, depending on the specific purposes and needs, each of these three extraction solvents has the potential to prepare formulations enriched with the most suitable flavonoids composition.
Automatic recognition of malignant lesions in ultrasound images by artificial neural networks

A method for the automatic classification of lesions in ultrasound images by artificial neural nets is presented. The parameters used for training of the network are texture related indicators and shape related indicators. Three lesions have been considered: cysts, fibroadenomas and carcinomas. Solid lesions have been separated from cysts in the first step and carcinomas have been separated from fibroadenomas in a second step. A satisfactory classification between cysts and solid lesions can be achieved using texture parameters only, whereas shape parameters appear to be the most significant ones when classifying between carcinomas and fibroadenomas.
Reduced Complexity Decoder for Orthogonal Space-Time Codes When Using QAM Constellations

Space-time block coding represents a practical and pragmatic method to mitigate the fading effects and to increase the channel capacity, by using spatial diversity. The space-time coding techniques are still preferred in communication systems because of the very simple transmit coding rule and of the relative reduced complexity of the maximum likelihood (ML) receivers with respect to other coding methods (e.g. space-time trellis codes) or other MIMO (Multiple Input Multiple Output) algorithms (e.g., spatial multiplexing). One of the drawbacks when using space-time block codes is the increase in complexity at the ML receiver when increasing the number of transmit antennas and the number of constellation points. This paper deals with this issue and introduces a decoding algorithm applicable only for orthogonal space-time block codes. We show that this decoding algorithm reduces the search space dimension of a regular ML receiver, leading to significant complexity reduction for QAM (quadrature amplitude modulation) constellations.
A mechanism for SIMD execution of SPMD programs

Although the SIMD machine is appreciated because of its simple structure leading to the aptness for integration in a VLSI chip, the programming paradigm applicable for this machine is rather poor. If the SPMD program, which is widely used in the MIMD machine, is efficiently executed on the SIMD machine, the versatility of this machine will be very much improved. The key problem of executing a SPMD program on a SIMD machine is the handling of branch instructions and barrier synchronization. To resolve this problem a new branching mechanism which includes the instruction address broadcast, the target address register and the active flag in the processing element, is proposed. The effectiveness of this mechanism is discussed on example programs.
ONLINE IDENTIFICATION OF HEAT DISSIPATERS USING ARTIFICIAL NEURAL NETWORKS

This paper focuses on the feasibility of online identification of thermal systems. The transfer function is not looked for, but a black box model is obtained. In the first part, the principles of online identification are reminded. This leads to the definition of the regression vector and of the regressors. Then these principles are applied to neural based techniques which are adapted from standard ARX (AutoRegressive structure with eXtra inputs) and OE (Output-Error) models. For the Neural Network ARX (NNARX) model, only one example is given, which leads to a not fully satisfactory identification. This identification is based on the response of the system to random heat rates during random times. The validation is based on the response to another set of random heat rates and on the response of the system to a step function. For Neural Network OE (NNOE) model, the influence of the number of regressors is presented along with the influence of the number of neurons on the hidden layer. It is shown that many architectures lead to a good identification, but that some particular models may lead to a very poor result. To make the comparison possible between the proposed models, a distance criterion is computed. This leads to the choice of the best adapted architecture.
The Effects of In ovoInjection of Ascorbic Acid on Hatchability, Growth Performance, Intestinal Morphology, and Tibia Breaking Strength in 36h Post Hatch Fasted Broiler Chickens

An experiment was conducted to evaluate the efficacy of intra-amnion administration of different doses of ascorbic acid (AA) on hatchability, growth performance, blood metabolites, jejunal morphology, and tibia breaking strength in 36h post hatch fasted broiler chickens. Two hundred eighty-eight Ross-308 fertile eggs at the 15thday of incubation were divided into four treatment groups, each containing four replicates of 18 eggs. The treatments included non-injected (control), injected into the amnion with 0.7 mL diluent (distilled water; sham treatment), and injected with 0.7 mL diluent containing 3 or 6 mg AA. The neonatal chicks were deprived of feed and water for 36 h. Hatched chicks were raised till 10 d of age. Hatch percentage was increased due to in ovo injection of 6 mg/egg AA.In ovo injection of different levels of AA had no significant effect on body weight gain, feed intake, and feed conversion ratio. In ovo injection of AA, especially at the 6 mg level, significantly increased villus height, villus width, and villus height: crypt depth ratio at 3 d of age. Tibia resistance and breaking strength were improved by in ovo injection of 6 mg AA when compared to the control at 10 d of age. In conclusion, it seems in ovo injection of 6 mg AA/egg on 15th d of incubation could have a positive impact on hatchability, intestinal morphology, and bone characteristics in broiler chickens.
Poster: Symbolic Execution of MPI Programs

MPI is widely used in high performance computing. In this extended abstract, we report our current status of analyzing MPI programs. Our method can provide coverage of both input and non-determinism for MPI programs with mixed blocking and non-blocking operations. In addition, to improve the scalability further, a deadlock-oriented guiding method for symbolic execution is proposed. We have implemented our methods, and the preliminary experimental results are promising.
User-Tailored 3D Visualization of Multimedia Data

This paper presents a visual content creation and manipulation system applied to a corpus of television archives. We focus on interactive visualization and navigation for a set of multimedia data. What is novel here is that visualization is user-tailored—it is structured by the criteria established by the user so that he can more easily locate his position in the data set and conduct information research. The application creates a 3D visual representation of the data contents. The data are multimedia -video, pictures, sound, and text. The current article presents generic tools used to obtain a three-dimensional visualization, which the user can parameterize. In addition, specially designed widgets are used to make visualization interactive. The prototype was developed in Java Swing and Java 3D.
Effects Of Road Traffic Scenarios On HumanExposure To Air Pollution

Human exposure to air pollution has been identified as a major problem due to its known impact on human health. Particulate matter is a pollutant which rises special concern due to the adverse health effects on sensitive groups of the population, such as asthmatic children. This study is part of the SaudAr research project which main objective was to assess the air quality effects on the health of a population group risk (asthmatic school children) living in an urban area (Viseu). The aim of this paper is to investigate the influence of road traffic emissions on air quality and consequently, on human exposure. For this purpose, the CFD model VADIS integrating an exposure module has been applied over the town of Viseu, for the periods of one week in winter and one week in summer, to four different situations: the reference year (2006) and three future scenarios for the year 2030, BAU, Green and Grey scenario. The differences among the scenarios include changes on the existing land use, the vehicle fleet composition, the mobility, the vehicle technologies and the fuel types. Field campaigns were performed in order to obtain information about vehicle fleet in the town of Viseu and mobility patterns. The quantification of road traffic emissions and the hourly traffic emissions patterns for all scenarios was carried out by the application of the TREM model. The results reveal an increase in PM10 emissions, concentrations and exposure in all future scenarios, particularly in winter with an increase around 80% in the BAU and Grey scenarios and only 34% in the Green scenario.