Miracle-dz/UniFAR-FTUs huggingface dataset:
Headspace-Solid Phase MicroExtraction and Gas Chromatography Mass Spectrometry Applied to Determination of Volatiles in Natural Matrices

Headspace – solid phase microextraction (HS-SPME) combined with gas chromatography-mass spectrometry-ion trap detector (GC-MSIT) has been used to characterize volatile compounds in several natural matrices. A great number of fibres with different polarities are commercially available, allowing the screening of the highest possible number of components. HS-SPME has several advantages, such as the condensation of extraction, concentration and sample introduction into a single step. In this extraction technique, a medium polarity fibre for flavours (carboxen/polydimethylsiloxane or divinylbenzene/polydimethylsiloxane) is usually used in order to achieve equilibrium between non-polar and polar compounds, thus increasing the screening range. The traditional methodologies using organic solvents, namely dichloromethane (DCM), allow the determination of a considerable number of volatile and semi-volatile compounds in natural matrices. In this review, the main theoretical points involved in GC-MS analysis will be discussed. The application of HS-SPME and other extraction methodologies (hydrodistillation, Soxhlet and solvent extraction), coupled to GC-MS-IT, to several natural matrices (macroalgae, Rumex induratus, Brassica oleracea L. var. costata DC., Catharanthus roseus and mushrooms, with particular emphasis in these last two) will be referred. With this the usefulness of these methodologies in the screening of volatile and semi-volatile compounds will be demonstrated. _____________________________________________________________________________________________________________
The Relationship between Stress and Emotional Intelligence among Postgraduate Students : The Case Study at Perdana School of Science , Technology and Innovation Policy ( STI Policy ) , University Technology Malaysia

Introduction: Students facing one stress typically face multiple risky educational circumstances that threaten an array of their study outcomes. Experiencing multiple academic stress can intensify the negative effects that such disorders has on the whole person’s physical, psychological, emotional, and cognitive development. Methods: This paper is a survey study, and it discusses the effect of academic stress and emotional intelligence on students’ psychological and emotional well-being. The purpose is to understand the relationship between stress and emotional intelligence among postgraduate students of policy school. The data has been collected through online survey that was sent through emails and links on WhatsApp and social networking sites. The accumulated data were then analyzed, and descriptive statistics as well as correlation study were used to interpret and evaluate the respondents’ background, academic stress, and emotional intelligence. Results: The key finding of this research is that stress and emotional intelligence are important; both have effects on the physical and mental well-being of postgraduate students. Indeed, there is academic stress among postgraduate students of Perdana School of (STI Policy) caused by academic workload, performance pressure, selfesteem, time management skills, and study-personal life balancing. Consequently, students use emotional intelligence as a coping mechanism to manage stress. Conclusion: It is highly advisable for the head of the schools, lecturers, and supervisors to look comprehensively at this matter and tackle the consequences of this issue by emphasizing more on students’ wellbeing so they can Graduate On Time (GOT) and enjoy their study life.
Influence of Mass and Heat Transfer onMorphologies of Metal Oxide Nanochannel Arrays Prepared

We discuss the influence of mass and heat transfer on the morphologies of Al, Ti, and Zr nanochannel arrays during anodization process. When these metals are anodized, the nanopores are firstly formed at the metal surface, and the nonuniform distribution of mass transfer in the pores results in the increase of pore depth. The nonuniform temperature distribution and the downward movement of reaction interface lead to the temperature changes and the generation of microcracks inside the pore wall, which results in the conversion of nanopores into nanotubes. The low-valency oxides also make the middle of the pore wall crack easily. The morphologies during metal anodization depend greatly on the temperature at the reaction interface. At low interface temperature, it appears to form the nanopores more easily, and, at high interface temperature, it is more propitious to form the nanotube structure. Many factors including resistivity, thermal conductivity, oxidizing reaction heat, and electric field strength (or current density) affect the reaction interface temperature.
Aalborg Universitet Compact Multiband Sensing MIMO Antenna Array for Cognitive Radio System

This paper presents a new design for a multiband sensing MIMO antenna system that can be used in cognitive radio communication for a mobile platform. The antenna system consists of two identical small-size multiband antennas with dimensions 29.5 x 17 x 5 mm3 and each of them is comprised of a driven strip monopole and a coupled parasitic shorted strip. These antennas are located diagonally to limit the mutual coupling and antenna correlation at low frequencies. The obtained operating bands are 698 990 MHz and 1710 5530 MHz, which include most of the LTE and Wi-Fi frequency bands. A prototype was fabricated and the measured results indicate that the realized efficiency is acceptable for a mobile application considering the compact size. Index Terms MIMO, mobile phone antennas, internal antennas, antenna array, multiband antennas, small antennas, cognitve radio, LTE, Wi-Fi.
Modified work rule for Y-shaped self-balancing line with walk-back and travel time

In the traditional lines such as assembly lines, usually each worker is assigned to a particular fixed work. However, when the imbalance between workers' speeds exists, if any worker will delay the overall work in the line, the production rate of the particular line will also decrease. For avoiding this problem, "SelfBalancing Line" was introduced. In this type of line, each worker is assigned work dynamically, thus they can keep the balanced production under satisfying the specific conditions, and line is assumed to be serial. Recently, papers that assume Y-shaped type have been published. In this type of line, line has two sub-lines and then combines two sub-lines. In the previous paper of Hirotani et al. (2015), condition for achieving the maximum production rate can be derived. However, any worker takes more time to walk-back or travel according to the worker position. Therefore, to modify rule that introduce waiting for any worker according to the workers position, walk-back and travel time decreases comparing waiting time, and then production rate increases. In this paper, work rule that modify the self-balancing line is proposed and compared with the traditional work rule such as traditional self-balancing line and fix work assignment rule.
Test Automation Architecture for Automotive Online-Services

The car industry undergoes a big change, triggered by modern agile methods for software development. New software features can be rapidly developed and instantly deployed. In contrast to that stands the long development cycle of the vehicle and its hardware. That hinders the development speed due to hardware related dependencies. Vehicle hardware requires extensive security measurements and procedures. Software embedded directly on the hardware holds many dependencies, varying for different car types within the same manufacturer. In the typical software development an Operating System (OS) diminishes these hardware dependencies and in the means of web development even OS dependencies can be resolved, enabling cross platform development. Therefore the following paper focuses on the development of a test automation architecture. It depicts how our architecture can be built to combine long term vehicle development with rapid agile software development and integrate them together. We call this DeepTesting, the complete test coverage of the software system with its services and applications. Additionally the DeepTesting architecture will consume real world test data to test software under nearly real world condition.
Study of Genes Predisposition to The Development of Complications of Metabolic Syndrome

This review presents the most informative genes for the diagnosis of complications of metabolic syndrome. It is shown that the polymorphism G-455A (rs1800790) of the gene FGB, Glu298Asp (rs1799983) of the gene eNOS, G83A (rs2368564) of the gene REN are the most informative markers to as-sess the possibility of fatal complications of metabolic syndrome. Risk assessment and prognosis of the disease course is multifactorial, where the most formative method will be the assessment of the complex of many single-nucleotide polymorphisms of genes, since the presence of a synergistic interac-tion of genetic polymorphisms is important, when the presence of unfavorable variants of genes of several systems increases the probability of the disease and its more severe course.
2 Is Self-regulation under Market Conditions Possible ?

This article discusses various arguments, which question the effectiveness of self-regulation as an instrument to implement societally preferred environmental and social standards. Special focus is set on experimental results. These results indicate that it is not plausible that effective self-regulation in areas such as environmental protection or social standards is actually feasible under market conditions. The experimental evidence is much more in favor with the traditional approach that environmental or social standards should be implemented by general laws under the surveillance of an executive state body.
Virtual Object of Learning for Driving Through Virtual Reality with Development of Peripherals and Glasses for Virtual Reality

The article presents the development of an OVA processed in the 3D multiplatform called Blender, with the creation of a virtual reality hardware with peripherals for driving in a small part of a virtual city. This city consists of a streets with signs and traffic lights where you can drive freely through the use of hardware consisting of a steering wheel whose sensor is a potentiometer, able to measure the angle of the cabilla, plus two foot pedals, Which act as a brake and an accelerator, whose instrumentation consists of the flywheel of two potentiometers that measure the angle of the pedal with respect to the horizontal as it is pressed with the feet. Each potentiometer graduates the voltage due to the voltage divider that is generated when feeding it with TTL at the ends of its pins; The intermediate pin generates a voltage that varies with respect to the angle of the potentiometer, this information is recorded in a microcontroller by means of an analog to digital conversion, where the information of each potentiometer is concatenated in a specific order and separated by comma; Of the microcontroller is sent through a COM port to the computer. Once there the information is received in a script created in Python in the 3d multiplatform Blender, where it is converted into motion actions for a vehicle located in the virtual city. The display of the movement and the movement indicators such as speed and vehicle rotation angle are displayed on a 7-inch screen which is connected to the computer by HDMI port. This screen is located in RV goggles created for this purpose with their respective lenses and focal distances for a correct visualization of the image.
Automatic Generation of Educational Quizzes from Domain Ontologies

Educational quizzes are very valuable resources to test or evaluate the knowledge acquired by learners and to support lifelong learning on various topics or subjects, in an informal and entertaining way. The production of quizzes is a very time-consuming task and its automation is thus a real challenge in e-Education. In this paper, we address the research question of how to automate the generation of quizzes by taking advantage of existing knowledge sources available on the Web. We propose an approach that allows learners to take advantage of the knowledge captured in domain ontologies available on the Web and to discover or acquire a more in-depth knowledge of a specific domain by solving educational quizzes automatically generated from an ontology modelling the domain. The implementation and experimentation of our approach is presented through the use case of a world-famous French game of manually generated multiple-choice questions.
Classification of toddler nutritional status using fuzzy inference system (FIS)

Nutrition is a major health problem and concern for parents when it is relating with their toddler. The nutritional status is an expression of the state caused by the status of the balance between the number of intake of nutrients and the amount needed by the body for a variety of biological functions. The indicators that often used to determine the nutritional status is the combination of Weight (W) and Height (H) symbolized by W/H, because it describe a sensitive and specific nutritional status. This study aims to apply the Fuzzy Inference System Mamdani method to classify the nutritional status of toddler. The inputs are weight and height of the toddler. There are nine rules that used and the output is nutritional status classification consisting of four criteria: stunting, wasting, normal, and overweight. Fuzzy Inference System that be used is Mamdani method and the defuzzification use Centroid Method. The result of this study is compared with Assessment Anthropometric Standard of Toddler Nutritional Status by Ministry of Health. The accuracy level of this fuzzy model is about 84%. Nutrition is a major health problem and concern for parents when it is relating with their toddler. The nutritional status is an expression of the state caused by the status of the balance between the number of intake of nutrients and the amount needed by the body for a variety of biological functions. The indicators that often used to determine the nutritional status is the combination of Weight (W) and Height (H) symbolized by W/H, because it describe a sensitive and specific nutritional status. This study aims to apply the Fuzzy Inference System Mamdani method to classify the nutritional status of toddler. The inputs are weight and height of the toddler. There are nine rules that used and the output is nutritional status classification consisting of four criteria: stunting, wasting, normal, and overweight. Fuzzy Inference System that be used is Mamdani method and the defuzzification use Centroid Method. The result of this study is compared with Assessment Anthropometric Standard of Toddler Nutritional .
OPTIMIZED SINK MOBILITY AWARE HETEROGENEOUS PROTOCOL OF WSN

: Wireless Sensor Network (WSN) has been extraordinary in facilitating human being by taking a control over the each aspects of modern technology. WSN has limited power constraints which makes it limited in its applicability. The routing if made energy efficient, sensor network might runs for longer duration. In the heterogeneous WSN, the main emphasis has been on the cluster heads selection by modifying the various probabilistic selection of CH. i-MBEENISH protocol is an improved version of BEENISH protocol with sink mobility incorporated in its operation. It has worked on the four levels of energy heterogeneity. The important aspect that it has worked on is the avoidance of penalizing the advanced nodes for the frequent selection as a cluster head. In this paper, sink mobility is optimized using Honey Bee Optimization (HBO) technique in the network by considering the parameters of energy and distance. HBO-iMBEENISH is proposed which outperforms iMBEENISH and MBEENISH protocols in terms of stability period and network lifetime.
Audio And Video Tempo Analysis For Dance Detection

The amount of multimedia in existence has become so extensive that the organization of this data cannot be performed manually. Systems designed to maintain such quantity need superior methods of understanding the information contained in the data. Aspects of Computer Vision deal with such problems for the understanding of image and video content. Additionally large ontologies such as LSCOM [1] are collections of feasible high-level concepts that are of interest to identify within multimedia content. While ontologies often include the activity of dance it has had virtually no coverage in Computer Vision literature in terms of actual detection. We will demonstrate the fact that training based approaches are challenged by dance because the activity is defined by an unlimited set of movements and therefore unreasonable amounts of training data would be required to recognize even a small portion of the immense possibilities for dance. In this thesis we present a non-training, tempo based approach to dance detection which yields very good results when compared to another method [2] with state-of-the-art performance for other common activities; the testing dataset contains videos acquired mostly through YouTube. The algorithm is based on one dimensional analysis in which we perform visual beat detection through the computation of optical flow. Next we obtain a set of tempo hypotheses and the final stage of our method tracks visual beats through a video sequence in order to determine the most likely tempo for the object motion. In this thesis we will not only demonstrate the utility for visual beats in visual tempo detection but we will demonstrate their existence in most of the common activities considered by state-of-the-art methods.
A Portable Platform for Accelerated PIC Codes and Its Application to Multicore and Many Integrated Cores Architectures Using MPI and OpenMP

With the aim of developing efficient optimizations and parallelization algorithms for porting application PIC codes to new multiand manycore HPC platforms, a test bed called the pic engine has been developed as a simple and portable abstraction of the PIC algorithm. In this work, we use it to test the hybrid MPI/OpenMP implementation as well as different algorithmic optimizations. Among them, a counting sort method is implemented to increase data locality in the memory and thus increase the performance. Thanks to the portability of the pic engine, several optimization algorithms are tested on the two Cray XC30 and XC40 machines from CSCS in Switzerland and the Bullx B510 supercomputer at IFERC-CSC in Japan equipped with both CPUs and Intel Xeon Phi processors. The results show that with our optimizations the performance can be increased by at least a factor 2.15 compared to the initial non-optimized version of the pic engine.
On a Generalized Linear Model of Coregionalization

The practice of modeling the cross and direct semivariograms together to describe the covariation of p attributes can be a cumbersome task since the models that are fitted must lead to a positive semi definite matrix. This requirement is satisfied when linear model of coregionalization is used for the fitting process. One major limitation of the linear model of coregionalization is the constraint that all direct and cross semivariogram share the same set of basic structures, which can prove time-demanding and can produce a poor fit. In this paper, we generalize the linear model of coregionalization and prove that we can still ensure the positive semi definiteness requirement of the coregionalization matrices without necessarily requiring the same set of basic structures. We provide an example of such model of coregionalizalition where the classic linear model of coregionalization (LMC) cannot be applied. A real data example from the mining is also used for illustration.
COMBINING MECHANISTIC MODELLING WITH MACHINE LEARNING IN AN INDUSTRIAL CASE STUDY : PREDICTING CREAM CHEESE FERMENTATION

The modelling of the fermentation of a live culture using solely regressed dynamic models can be improved by incorporating deep learning recurrent models such as long-short term memory (LSTM). Not only do these models improve the predictability of a key component during the reaction, the very fact that they work so well challenges a key assumption that the output variable is only algebraically related to the states. This example shows that machine learning has a place even when fundamental models exist.
FLUIDS 3 , 123902 ( 2018 ) Self-sustaining process in Taylor-Couette flow

The transition from Tayor vortex flow to wavy-vortex flow is revisited. The selfsustaining process (SSP) of Waleffe [Phys. Fluids 9, 883 (1997)] proposes that a key ingredient in transition to turbulence in wall-bounded shear flows is a three-step process involving rolls advecting streamwise velocity, leading to streaks which become unstable to a wavy perturbation whose nonlinear interaction with itself feeds the rolls. We investigate this process in Taylor-Couette flow. The instability of Taylor-vortex flow to wavy-vortex flow, a process which is the inspiration for the second phase of the SSP, is shown to be caused by the streaks, with the rolls playing a negligible role, as predicted by Jones [J. Fluid Mech. 157, 135 (1985)] and demonstrated by Martinand et al. [Phys. Fluids 26, 094102 (2014)]. In the third phase of the SSP, the nonlinear interaction of the waves with themselves reinforces the rolls. We show this both quantitatively and qualitatively, identifying physical regions in which this reinforcement is strongest, and also demonstrate that this nonlinear interaction depletes the streaks.
Developing Serious Games (Game Development Series)

With the impressive growth the games industry has enjoyed for the past decade, game developers, educators, and marketing firms are excitedly envisioning serious games applications for computer game technologies. These applicationsserious gamesrepresent opportunities for game developers to apply their talents to areas outside of the entertainment CiteULike is a free online bibliography manager. Register and you can start organising your references online. industry. Developing Serious Games is a practical handbook that details what's involved in developing these serious games. It explores the emergence of serious games as a viable niche in the multi-billion dollar gaming industry, and it covers the various types of serious games, including military, academic, medical, and training & development. From there it continues with a discussion of the enabling technology trends, emerging standards, and the tools that promise to reinforce the current trajectory of development and user demand for serious games. The second half of the book emphasizes the economic realities of the serious games industry, including and evaluation of the market, the economic potential of the space, and the customer base. The book culminates with a serious game design document that illustrates the important differences between entertainment games and serious games. It also provides a look to the future of serious gaming from a developer's perspective. The book is written for students, established game developers, and professionals in related fields, such as modeling and simulation or instructional design, who are skilled in training with traditional approaches and tools. It is also applicable to programmers, graphic artists, and management contemplating or involved in the development of serious games. medida's tags for this article
An Empirical Study of the Effect of Endorser on Purchase Intention --Evidence from UNIQLO

UNIQLO is a Japanese fast-fashion brand which is popular and famous in Taiwan. This study uses UNIQLO as an example to investigate the relationships and effects of endorser, self-concept, brand image, and purchase intention using questionnaires from June 1, 2016 to September 30, 2016. The research findings show that endorser has a direct effect on self-concept, brand image and purchase intention. It also has an indirect effect on purchase intention via brand image. However, endorser does not have an indirect effect on purchase intention via self-concept.