Miracle-dz/UniFAR-FTUs huggingface dataset:
Aproximación conceptual de la gestión estratégica de la tecnología en pequeñas empresas de manufactura

En el actual contexto económico y social de la Argentina, con tejidos sectoriales extremadamente dinámicos y complejos, resulta imprescindible propiciar el mejoramiento de la gestión de recursos tecnológicos en el ámbito de pequeñas empresas de manufactura, con el propósito de mejorar sus desempeños productivos. El objetivo del artículo se enfoca en el diseño de una aproximación conceptual para gestionar estratégicamente los recursos tecnológicos en las pequeñas empresas de producción. Para llevar a cabo el trabajo se recurrieron a diversos métodos de revisión bibliográfica sobre pensamiento estratégico y recursos tecnológicos aplicados al ámbito empresarial. Como resultado se expone una aproximación conceptual que sustenta la mecánica requerida para aprovechar de manera estratégica los recursos tecnológicos a partir de la dinamización del pensamiento estratégico de los empresarios.
Adaptively Learning Low-high Frequency Information Integration for Pan-sharpening

Pan-sharpening aims to generate high-spatial resolution multi-spectral (MS) image by fusing high-spatial resolution panchromatic (PAN) image and its corresponding low-spatial resolution MS image. Despite the remarkable progress, most existing pan-sharpening methods only work in the spatial domain and rarely explore the potential solutions in the frequency domain. In this paper, we propose a novel pan-sharpening framework by adaptively learning low-high frequency information integration in the spatial and frequency dual domains. It consists of three key designs: mask prediction sub-network, low-frequency learning sub-network and high-frequency learning sub-network. Specifically, the first is responsible for measuring the modality-aware frequency information difference of PAN and MS images and further predicting the low-high frequency boundary in the form of a two-dimensional mask. In view of the mask, the second adaptively picks out the corresponding low-frequency components of different modalities and then restores the expected low-frequency one by spatial and frequency dual domains information integration while the third combines the above refined low-frequency and the original high-frequency for the latent high-frequency reconstruction. In this way, the low-high frequency information is adaptively learned, thus leading to the pleasing results. Extensive experiments validate the effectiveness of the proposed network and demonstrate the favorable performance against other state-of-the-art methods. The source code will be released at https://github.com/manman1995/pansharpening.
A Study of Citations to Wikipedia in Scholarly Publications

ABSTRACT The debate on using Wikipedia as a credible academic information resource is dynamic and controversial. This study used the Web of Science (WoS) database and its “Cited Reference” and “Analyze Results” tools to identify and examine trends in the use of Wikipedia citations in scholarly, peer-reviewed publications for the years from 2002 to 2015. Results indicate that the use of Wikipedia citations in peer-reviewed journals has been increasing since 2002. Given that Wikipedia is considered a nonauthoritative source, it might be assumed that this resource is frequently being cited in open access (OA) journals, which are sometimes considered less rigorous when it comes to publication standards. Alternatively, it might be assumed that Wikipedia is being used by scholars from lesser-quality institutions or from developing countries, where access to authoritative information resources might be limited. This study examines these assumptions and describes the disciplines, research fields, and types of journals that are accepting Wikipedia as an authoritative reference source, thereby increasing its credibility. This research is intended to fuel informed debate on the issue, which will contribute to improvement in scholarly communication.
The Augmented Floor - Assessing Auditory Augmentation

The Augmented Floor is a wooden floor with in-built PyzoFlex® printed electronics. It measures any change of pressure on its surface. For users walking on this floor, we created an auditory augmentation of their footsteps. Different sound designs were implemented, both realistic and synthetic ones. We developed a method based on envelope reusing and compared it to the triggering of step-sounds. The envelope method shows a higher correlation between the input signal and the playback sound; it was rated better. Besides, realistic sounds were preferred over synthetic ones.
Soft Robotics: from scientific challenges to technological applications

Soft robotics is a recent and rapidly growing field of research, which aims at unveiling the principles for building robots that include soft materials and compliance in the interaction with the environment, so as to exploit so-called embodied intelligence and negotiate natural environment more effectively. Using soft materials for building robots poses new technological challenges: the technologies for actuating soft materials, for embedding sensors into soft robot parts, for controlling soft robots are among the main ones. This is stimulating research in many disciplines and many countries, such that a wide community is gathering around initiatives like the IEEE TAS TC on Soft Robotics and the RoboSoft CA – A Coordination Action for Soft Robotics, funded by the European Commission. Though still in its early stages of development, soft robotics is finding its way in a variety of applications, where safe contact is a main issue, in the biomedical field, as well as in exploration tasks and in the manufacturing industry. And though the development of the enabling technologies is still a priority, a fruitful loop is growing between basic research and application-oriented research in soft robotics.
AN EFFECTIVE RECOMMENDATIONS BY DIFFUSION ALGORITHM FOR WEB GRAPH MINING

The information on the World Wide Web grows in an explosive rate. Societies are relying more on the Web for their miscellaneous needs of information. Recommendation systems are active information filtering systems that attempt to present the information items like movies, music, images, books recommendations, tags recommendations, query suggestions, etc., to the users. Various kinds of data bases are used for the recommendations; fundamentally these data bases can be molded in the form of many types of graphs. Aiming at provided that a general framework on effective DR (Recommendations by Diffusion) algorithm for web graphs mining. First introduce a novel graph diffusion model based on heat diffusion. This method can be applied to both undirected graphs and directed graphs. Then it shows how to convert different Web data sources into correct graphs in our models.
Mobile Learning in Higher Education

In recent years, there has been an explosion in the growth of mobile learning across all sectors of education. Keen interest in mobile learning has led to a proliferation of views, perspectives, and diverse activities underpinned by different learning theories. This chapter focuses on various dimensions of mobile learning, including definitions, theoretical dimensions, mobile learning applications in higher education, and future research directions. Mobile learning is still an emerging and immature field. The chapter provides broad definitions and discussions of mobile learning drawing upon existing work. By exploring the experiences and views of various researchers, the chapter reveals the opportunities and challenges involved with mobile learning. DOI: 10.4018/978-1-61350-080-4.ch015
Selected aspects of lifestyle of active boys in the older school age

The main objectives of this thesis was to identify and evaluate selected aspects of lifestyle (physical activity/inactivity, sedentary behaviour – watching TV and DVD, playing PC games, negative eating habits, substance abuse and sexual experience) in the research sample of 105 young boys from Olomouc, Prostějov and Přerov aged 11, 13 and 15 years, with regularly controlled physical activity (ice hockey) and compare them with the same old boys from the HBSC study (The Health Behavior in School-aged Children). The results show that these young active boys have an overall healthier lifestyle than boys in the HBSC study. This pilot study can become the basis for other possible hypotheses and further research investigations.
Differentially Private Utility Item Mining

In today's business world there is excess of available data & a great need to make good use of it. Data mining is art of extracting pattern and knowledge from large amount of data. Frequent itemset plays essential role in many Data Mining tasks that try to find out interesting patterns from database such as association rules. Association rule mining is a finding association among large databases variables. Mining of frequent itemset is most popular problem in data mining. The frequent itemsets recognition is valuable for economic & research purpose. But valuable discovered frequent itemsets should not only assure security but also achieve high data utility & offer time efficiency. The frequent itemsets are patterns or items like itemset, substructures or subsequences that comes out in data set frequently. There are several Frequent Item mining algorithms for frequent item mining such as Apriori, Frequent Pattern growth, Eclat, Utility Pattern growth algorithms. To provide security or privacy here we use differentially private Utility Item mining algorithm using Utility Pattern- growth algorithm. It consists of Preprocessing & mining phase. In preprocessing phase, to enhance utility & privacy advance smart splitting method is proposed to transform database. For given Database preprocessing phase should be performed only once. In mining phase run time estimation & dynamic reduction performed. To cover the information loss by smart splitting, we contrive run time estimation to calculate actual support of itemsets in original database. For privacy we have added noise in the database, we put forward dynamic reduction method to reduce the noise dynamically which guarantees privacy during mining process. In this paper we proposed new algorithm for mining high utility itemsets called as UP growth which consider not only frequency of itemset but also utility associated with the itemset. Keywords— Frequent Item Mining, є- differential privacy, FP- growth, UP-growth.
Concept of software interface for BCI systems

Brain Computer Interface (BCI) technology is intended to control external system by brain activity. One of main part of such system is software interface, which carries about clear communication between brain and either computer or additional devices connected to computer. This paper is organized as follows. Firstly, current knowledge about human brain is briefly summarized to points out its complexity. Secondly, there is described a concept of BCI system, which is then used to build an architecture of proposed software interface. Finally, there are mentioned disadvantages of sensing technology discovered during sensing part of our research.
Cell size is a key ecological trait associated with biogeographic patterns of microbial eukaryotes in coastal waters

Body size is an important ecological trait, but it has been poorly explored in microbial communities. Here, we examined the effect of cell size on coastal eukaryotic communities across a size continuum of 0.2–3 (pico-), 3–20 (nano-), and 20–200 μm (micro-sized), which were characterized via high-throughput sequencing based on the V4 region of the 18S rRNA gene. We found that, at the alpha diversity level, there was a decreasing trend across the pico-, nano-, and micro-sized eukaryotic communities regarding both amplicon sequence variant (ASV) richness and Shannon index. At the beta diversity level, the three categories were significantly different, and these were accompanied by a relatively high local contribution to beta diversity in contrasting freshwater and seawater locations. The community variations observed for the microbial eukaryotes could largely be explained by the environmental effects which decreased between the pico- (40.5%), nano- (37.3%), and micro-sized (27.3%) fractions. These environmental effects were mainly contributed by several ASV modules showing opposing responses to environmental conditions. This might partly indicate the coalescence of the freshwater and seawater groups of microbial eukaryotes. In summary, our findings suggest that the cell size of microbial eukaryotes is a phylogenetically conserved trait, which is tightly associated with biogeographic patterns.
Studying Human Intelligence by Creating Artificial Intelligence When considered as a physical symbol system, the human brain can be fruitfully studied by computer simulation of its processes

Although we speak of the natural and the artificial as polar contrasts, yet in almost all the objects and phenomena we encounter in our everyday lives, the natural and the artificial are inextricably blended (2). No one would object to my calling a baseball an artificial object, yet it must obey the laws of mechanics just as strictly as does a boulder dislodgecl by an avalanche. A cornfield is an artifact created by man; even the corn plant itself is a genetic artifact. Yet the laws of biology apply to cornfields and corn plants. It is hard to think of anything more artifactual than a television commercial? but its transmission and reception are gov erned by Maxwell's equations. There is no contradiction in extending the methods and findings of the natural
Assessment of Multiple MapReduce Strategies for Fast Analytics of Small Files

Hadoop, an open-source implementation of MapReduce, is used widely because of its ease of programming, scalability, and availability. Hadoop distributed file system (HDFS) and Hadoop MapReduce are two important components of Hadoop. Hadoop MapReduce is used to process the data stored in HDFS. With the explosive development of cloud computing, increasing business and scientific application needs to take advantages of Hadoop. The sizes of files processed in Hadoop are not bound to very large files any more. Large amount of small files both in business and scientific areas are processed by MapReduce, such as document type files, bioinformatics files, geographic information files, and so on. In this situation, MapReduce performance of Hadoop is impacted severely. Although Hadoop and other frameworks provide some MapReduce strategies, they are not directly designed for small files. In addition, there is no theoretical analysis for evaluating MapReduce strategies for small files. In this paper, I conduct an analysis of existing different MapReduce strategies for small files and use theoretical and empirical methods to evaluate these strategies for processing small files. The experimental results demonstrate the correctness and efficiency of our analysis.
Oil Consumption and Economic Growth in Turkey: An ARDL Bounds Test Approach in the Presence of Structural Breaks

The aim of this study is to investigate the relationship between oil consumption and income in Turkey, using annual data from 1961 to 2016. The stationarity properties of the series are analyzed with Lee and Strazicizh (2003), unit root test allowing for two structural breaks, along with the conventional unit root tests namely ADF, PP and KPSS. Due to conflicting findings of the unit root tests, ARDL bounds test approach to cointegration is used to capture the relationship between oil consumption and income. The findings of the ARDL bounds test indicated that oil and income are cointegrated. The causal relationship between the variables is also examined by employing Toda and Yamamoto (1995), approach to Granger non-causality. The outcomes of the Toda and Yamamoto (1995), procedure showed that the direction of the causality is running from real GDP to oil consumption, but not vice versa. Both bounds test and Toda and Yamamoto (1995), test results reveal that, energy conservation policies will not harm economic growth in Turkey.
A New implementation for Secure Authorized Data-Deduplication

This paper represents that, many systems are using for the removing of replica copies of repeating data, from that approaches, one of the crucial important knowledge compression system is data duplication. Many advantages with this knowledge duplication, ordinarily it is going to lower the quantity of storage space and save the bandwidth when utilising in cloud storage. To protect confidentiality of the sensitive data whilst helping de-duplication data is encrypted via the proposed convergent encryption system before out sourcing. Issues licensed data duplication formally addressed by using the primary attempt of this paper for better safeguard of data protection. This is one-of-a-kind from the normal duplication techniques. The differential privileges of users are additional regarded in duplicate check apart from the data itself. In hybrid cloud structure licensed replica assess supported by means of several new duplication constructions. Based on the definitions specified in the proposed security model, our scheme is comfortable. Proof of the suggestion carried out on this paper by way of conducting experiment-mattress experiments. Key Words: Data deduplication; Convergent encryption; Confidentiality; Hybrid cloud; Authorized Duplicate check.
H-minima transform for segmentation of structured surface

The watershed segmentation method has been used in surface metrology to determine the feature parameter and the segment of areal surfaces. However, during segmentation, over-segmentation always happens, which may overshadow the significant features. Thus, a new method is required to reduce this over-segmentation, as well as to retain the necessary information for further improvement in the signal processing data. Hence, this paper proposed a new method to overcome over-segmentation for segmentation of structured surface. Over-segmentation happens when the surface area is over-segmented into a large number of insignificant, tiny, and shallow hills and dales features rather than a few significant dales/hills features. H-minima transform was proposed to overcome this issue. From the results, the data pertaining to simulated and measured surface topographies, as well as height threshold value of H-minima transform had depended on the irregularities of the surface to obtain the required features. As a result, it had been concluded that H-minima transform is possible to reduce over-segmentation.
Stochastic Processes And Filtering Theory

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Open Scope: A Pragmatic JavaScript Pattern for Modular Instrumentation

We report on our experience instrumenting Narcissus, a JavaScript interpreter written in JavaScript, to allow the dynamic deployment of dynamic program analyses. Instrumenting an interpreter is a cross-cutting change that can affect many parts of the interpreter source code. We propose a simple open scope pattern that minimizes the changes to the interpreter, while allowing us to implement program analyses in their own files, and to compose them dynamically. We apply our pattern to Narcissus using standard JavaScript features, and find that the gain in extensibility offsets a small loss in performance.
Time-frequency features for speech recognition

Conventional speaker independent, continuous speech recognition systems are built upon assumptions that are, in general, not met. This dissertation focuses on one deficiency in particular, that the non-stationary speech signal is modeled as a single series of stationary spectral estimates. Time-frequency representations (TFRs) have the potential to be powerful features for nonstationary signals. Whereas short-term spectral estimates must make implicit time and frequency resolution tradeoffs, a single TFR simultaneously contains both short-term and long-term spectral estimates. Unfortunately, the proper way to harness this power is still a matter of debate. This dissertation proposes a class dependent time-frequency feature for speech recognition. The feature is automatically derived from time-frequency representations of speech signals by maximizing the discriminability within classes. A two-stage speech recognition system incorporating these representations achieves 1.6% error rate. This is 39% lower than the best published result for the chosen task.
Efecto de una secuencia didáctica basada en los estilos de aprendizaje y el aprendizaje activo en el logro de aprendizaje de cinemática

espanolEl objetivo es establecer el efecto que una secuencia didactica de cinematica unidimensional, que incluye informar al grupo de estudiantes aspectos relacionados con sus estrategias de aprendizaje y metacognitivas, tiene en el logro de aprendizaje (desempeno academico). El diseno metodologico considero pretest y postest con un grupo control y un grupo experimental. Los instrumentos utilizados son: Metacognition Strategies Learning Query MSLQ-P para el contexto de la fisica, Kolb Standard Learning Instrumento KLSI y medir logro de aprendizaje fisico se diseno y valido (con pares, expertos y prueba piloto) la prueba relacionada con la cinematica unidimensional. La secuencia didactica propuesta considera los estilos de aprendizaje de los estudiantes asi como su autorreulacion. Los resultados muestran que el MSLQP, con una confiabilidad corregida de Cronbach de 0.951, se identifica el nivel de autoeficacia como una fortaleza de los estudiantes (arriba del 80%), los estilos de aprendizaje de los estudiantes (mayor tipo 1 y 4) se alejan del que usualmente se presentan los ingenieros (Tipo 3), asi mismo la secuencia didactica que incluyo informar al grupo de estudiantes tuvo efecto positivo y significativo en comparacion con el grupo que no fue informado. El estado de desarrollo de la investigacion indica que modificar las estrategias de aprendizaje es un factor que, entre multiples factores, afecta el logro de aprendizaje. El logro academico obtenido por los estudiantes esta relacionado positivamente con la participacion de la secuencia didactica. EnglishThe objective of this article is to establish the effect of a didactic sequence of one-dimensional kinematics, which includes informing the group of students about aspects related to their learning strategies and metacognitive, has in the achievement of learning (academic performance). The methodological design considered pretest and posttest. The instruments used are: Metacognition Strategies Learning Query MSLQ for the context of physics, Kolb Standard Learning Instrument KSLI and Measurement Achievement of Physical Learning was designed and validated (with peers, experts and pilot test) test related to one-dimensional kinematics. The results show that the MSLQ-P, with Cronbach's corrected reliability of 0.96, identifies the level of self-efficacy as a strength of students (above 80%), student learning styles (major type 1 and 4 ) Are away from the usual engineers (Type 3), and the didactic sequence that included informing the group of students had a positive and significant effect compared to the group that was not informed. The state of development of research indicates that modifying learning strategies is a factor that, among many factors, affects achievement of learning.