Miracle-dz/UniFAR-FTUs huggingface dataset:
Ein Vergleich von Datenanalysemethoden für eine Affective Engineering Methode

Affective Engineering (AE) is an engineering genre that deals with users’ subjective value creation in technical product design. Therein, quantitative instruments to map subjective quality criteria are dominant. ACADE is such an instrument that focuses on a long-term alignment of product design impres-sions to the subjective needs of users. Due to its quantitative backbone, sev-eral mathematical analysis methods seem convenient, whereas their specific benefits and drawbacks are not yet clear in the AE context. Therefore, anal-yses of nonlinear regression, artificial neural networks, fuzzy logic systems and hybrids are examined under the aspect of ACADE applicability. Different quality indicators unveil characteristics which the designer may use to mine their potential for future AE analyses.
Leadership Roles and Management Practices of Educational Managers and Their Relationships to Teachers’ and Students’ Performance

A was conducted to determine descriptive-correlational research the extent educational managers in the four state universities in Panay Island portrayed their leadership roles and management practices and its relationship to teachers' and students' performance. Ninety three respondents were classified according to highest educational attainment, position occupied, and length of experience. Questionnaire was used to gather data and Performance Evaluation System (PES) of teachers and passing percentage in Board Examination for students' performance. the Results were interpreted at 5% level of significance using One-Way Analysis of Variance and Pearson Product-Moment Correlation Coefficient. Descriptive data were analyzed using frequency, percentage, weighted mean, and standard deviation. Results showed that m holders ajority were doctorate degree , first-line managers, and serve their positions ess than ten years Leadership roles and for l . management practices were rated “to a very large extent. ” Only management practices in physical facilities development performed “to a large extent” were although when taken as a whole in the five years of concern were performed they “to a very large extent. ” Teachers' performance mostly rated Outstanding and a lesser number was rated Very Satisfactory he passing percentage above the national passing set . T was by P R C . the hilippine egulation ommission (PRC) Leadership roles significantly affect teachers' performance and only leadership and human resource development were related to teachers' performance. Leadership roles and management practices were not related to students' performance except in physical facilities development. Only educational attainment was found significant to teachers' performance but not to ly correlated students' performance.
Development of a Face Detection Algorithm Based on Skin Segmentation and Facial Feature Extraction

This paper presents a face detection algorithm capable of detecting face(s) without prior training as a face classifier. The technique employed in developing the algorithm is based on skin segmentation and facial feature extraction of the two eyes and mouth. Skin segmentation was done in the red, green, blue color space. White balance correction was employed to correct the change in image temperature that occurs due to change in lighting conditions at the point of acquiring image. Morphological operations and bounding box were employed to search and extract face region from the segmented skin region. Facial feature, eyes and mouth, were extracted for final verification of the sensed face using the Laplacian of Gaussian filter and the isosceles triangle matching rules. The extracted features were used to develop the face detection algorithm. The developed algorithm was evaluated using random images taken under different lighting conditions. Furthermore, the efficiency of the developed face detection algorithm was evaluated using a standard face detection image database. The result obtained shows that the developed face detection algorithm performed satisfactorily well with 81.37% detection accuracy. Furthermore, the results obtained from the performance evaluation of the developed face detection for this study has shown it clearly that accuracy detection of dissimilar faces in images with complex background is possible and attainable
Vdgraph: A Package for Creating Variance Dispersion Graphs

This article introduces the package Vdgraph that is used for making variance dispersion graphs of response surface designs. The package includes functions that make the variance dispersion graph of one design or compare variance dispersion graphs of two designs, which are stored in data frames or matrices. The package also contains several minimum run response surface designs (stored as matrices) that are not available in other R packages.
Designing a Novel Reversible Systolic Array Using QCA

Many efforts have been done about designing nano-based devices till today. One of these devices is Quantum Cellular Automata (QCA). Because of astonishing growth in VLSI circuits Designs in larger scales and necessity of feature size reduction, there is more need to design complicated control systems using nano-based devices. Besides, since there is a critical manner of temperature in QCA devices, complicated systems using these devices should be designed reversibly. This article has been proposed a novel architecture for QCA circuits in order to utilizing in complicated control systems based on systolic arrays with high throughput and least power dissipation.
Improved collusion‐resisting secure nearest neighbor query over encrypted data in cloud

Securely performing nearest neighbor query over encrypted data in cloud is an important topic in the area of cloud computing, for which Wang et al recently put forward a scheme (ie, CloudBI‐II) to address the challenging security problem: resisting the collusion of cloud server and query users. In this paper, we propose an efficient attack method that indicates CloudBI‐II will reveal the difference vectors under the collusion attack. Furthermore, we show that the difference vector disclosure will result in serious privacy breach and, thus, attain an efficient attack method to break CloudBI‐II. Namely, CloudBI‐II cannot achieve their declared security. Through theoretical analysis and experiment evaluation, we confirm that our proposed attack approach can fast recover the original data from the encrypted data set in CloudBI‐II. Finally, we provide an enhanced scheme that can efficiently resist the collusion attack.
The Effect Of Changes In Speech Features On The Recognition Accuracy Of ASR System: A Study On The Malay Speech Impaired Children

Speech impairments refers to disability that causes the human speech production to deviate from the norm. Although there have been several researches undertaken to identify the differences between non-impaired and impaired speech, little is known about their effects on the speech intelligibility and the performance of ASR systems in recognizing impaired speech of children. This study investigates the speech features of impaired speech in relation to intelligibility deficits and degradation in ASR performance; which includes, formant frequencies, intensity, fundamental frequency (F0) and perturbation features such as jitter and shimmer. As there is no existing speech database for performing the evaluation, we have developed a speech database of speech impaired children and have analysed the impaired speech features. We have identified significant differences in the selected features. We also have identified the relationship between the ASR system’s Word Error Rate (WER) of impaired speeches with the speech features. The results show that there are significant differences in F0, jitter and shimmer across the Control Group (CG) and the Speech Impaired Group (SIG). This paper explains the differences between impaired speeches and non-impaired speeches that can be used in developing automated speech recognition system. We have observed that F0 affects the ASR performance and was found to be a significant predictor that influences the accuracy of vowel phonemes /e/ and /u/.
Classificação de sinais EGG combinando redes neurais e análise de componentes independentes

Identify digestive traits of people through Electrogastrography (EGG) is important because it is usually an economic, non-invasive and less bother than the traditional Endoscopy procedure. This research evaluates the behavior of artificial neural networks learning on the components extracted by Independent Component Analysis (ICA) algorithms. An experiment with statistical analysis whose goal was to present the relationship between the viewing of neutral, negative or positive images and digestive reactions was performed. The results showed that extract only the stomach signal component may reduce the error rate of learning of the neural network compared with experiment. Resumo. Identificar características digestivas de pessoas através da Eletrogastrografia (EGG) é importante pois esta costuma ser uma opção barata, não-invasiva e incomoda menos que o tradicional procedimento de Endoscopia. Este trabalho avalia o comportamento do aprendizado das redes neurais artificiais diante de componentes extraídas por algoritmos de Análise de Componentes Independentes (ICA). Foi realizado um experimento com análise estatística cujo objetivo foi apresentar a relação entre a visualização de imagens neutras, negativas ou positivas e as reações digestivas. Os resultados mostraram que extrair apenas a componente do sinal do estômago deve reduzir a taxa de erro do aprendizado das redes neurais artificiais diante do experimento realizado.
Effective Vectorization with OpenMP 4.5

This paper describes how the Single Instruction Multiple Data (SIMD) model and its extensions in OpenMP work, and how these are implemented in di ﬀ erent compilers. Modern processors are highly parallel computational machines which often include multiple processors capable of executing several instructions in parallel. Understanding SIMD and executing instructions in parallel allows the processor to achieve higher performance without increasing the power required to run it. SIMD instructions can signiﬁcantly reduce the runtime of code by executing a single operation on large groups of data. The SIMD model is so integral to the processor’s potential performance that, if SIMD is not utilized, less than half of the processor is ever actually used. Unfortunately, using SIMD instructions is a challenge in higher level languages because most programming languages do not have a way to describe them. Most compilers are capable of vectorizing code by using the SIMD instructions, but there are many code features important for SIMD vectorization that the compiler cannot determine at compile time. OpenMP attempts to solve this by extending the C ++/ C and Fortran programming languages with compiler directives that express SIMD parallelism. OpenMP is used to pass hints to the compiler about the code to be executed in SIMD. This is a key resource for making optimized code, but it does not change whether or not the code can use SIMD operations. However, in many cases critical functions are limited by a poor understanding of how SIMD instructions are actually implemented, as SIMD can be implemented through vector instructions or simultaneous multi-threading (SMT). ∗ We have found that it is often the case that code cannot be vectorized, or is vectorized poorly, because the programmer does not have su ﬃ cient knowledge of how SIMD instructions work.
A corrective control for angle and voltage stability enhancement on the transient time-scale

Summary form only given as follows. This paper deals with the development of a nonlinear programming methodology for evaluating load shedding (LS) as a corrective action to improve the dynamic security of power systems when angle or voltage instability is detected. A centralized corrective control is armed, on the basis of on-line DSA computations, in order to ensure corrective actions when a threatening contingency actually occurs. The algorithm is implemented and tested on the actual Italian grid managed by ENEL SpA.
Choosing and Using Utility Functions in Forming Portfolios

Utility functions offer a means to encode objectives and preferences in investor portfolios. The functions allow one to place a score on outcomes and then identify optimal portfolios by maximizing utility. The central theme of this article is that utility functions should be tailored to the investor. I discuss how an appropriate function might be chosen and demonstrate concepts for power utility and reference-dependent utility. A modeling approach is presented that may be applied without resorting to dynamic optimization. The selection of utility functions is illustrated for four investor types. Disclosure: The author reports no conflict of interest. Editor’s Note The original version had a typographical error in Figure 4B, which has been corrected in this version. Submitted 1 October 2018 Accepted 20 March 2019 by Stephen J. Brown
Activation of Mouse and Human Peroxisome Proliferator-Activated Receptors ( , / , ) by Perfluorooctanoic Acid and Perfluorooctane Sulfonate

This study evaluates the potential for perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) to activate peroxisome proliferator‐activated receptors (PPARs), using a transient transfection cell assay. Cos-1 cells were cultured in Dulbecco’s Minimal Essential Medium (DMEM) with fetal bovine serum in 96-well plates and transfected with mouse or human PPARa, b/d, or g reporter plasmids. Transfected cells were exposed to PFOA (0.5‐100mM), PFOS (1‐250mM), positive controls (i.e., known agonists and antagonists), and negative controls (i.e., DMEM, 0.1% water, and 0.1% dimethyl sulfoxide). Following treatment for 24 h, activity was measured using the Luciferase reporter assay. Inthisassay,PFOAhadmoretransactivitythanPFOSwithboththe mouse and human PPAR isoforms. PFOA significantly increased mouse and human PPARa and mouse PPARb/dactivity relative to vehicle. PFOS significantly increased activation of mouse PPARa and PPARb/d isoforms. No significant activation of mouse or human PPARg was observed with PFOA or PFOS. The PPARa antagonist, MK-886, significantly suppressed PFOA and PFOS activity of mouse and human PPARa. The PPARg antagonist, GW9662, significantly suppressed PFOA activity on the human isoform. In conclusion, this study characterized the dose response and differential activation of mouse and human PPARa, b/d, g by
COMPARISON OF RENEWABLE AND CONVENTIONAL ENERGY COSTS BY WAVELET TECHNIQUES

This paper aims to compare the cost of renewable energy to conventional energy sources in production. It is argued that advantage in cost of production would support competitiveness of Turkish manufacturing industry in international trade. In this paper an export model has been developed to forecast competitive advantage of Turkish manufacturing industry on international trade by using renewable energy in production. Data on the cost of energy on Turkish manufacturing industry and export performance in past 10 years were processed. This study utilizes 1D wavelet packets and continuous wavelets on historical cost and export values in Turkey. Wavelet and regression analysis have been applied to define variation in temporal and spatial patterns. Wavelet techniques detect sudden changing, increasing and decreasing trends of data and define the role of factors small and large scale effects. Actual share of energy usage in production cost and usage of renewable energy instead of conventional energy values were compared to other countries data analyses
Productive performance of soybean plants originated from seed lots with increasing vigor levels

Abstract: The objective of this work was to evaluate the productive performance of soybean crops, in response to the use of seeds from lots with increasing vigor levels. The study was developed during the 2014/2015 and 2015/2016crops. In the first period, 14 treatments were evaluated, consisting of two factors, two genotypes (Syn 1059RR and NK7059RR), and seven seed lots. In the second seven treatments were considered, involving one genotype (Syn 1158RR) and seven seed lots. In both crop years, seed lots had vigor levels of 65, 70, 75, 80, 85, 90 and 95%, as determined by the accelerated aging test. The experiment was performed in a randomized block design, with a factorial scheme and five replications. Plant height, yield components, and grain yield were assessed throughout the culture cycle. The reflex of seed vigor in crop performance depended on the genotype employed. Also, there was an increase in both vegetative and reproductive performances of the crop as a function of seed vigor level. In this sense, every percentage point augmented in the vigor level of the lots resulted in a grain yield expansion of up to 28 kg.ha-1.
The Impact of Out-of-Pocket Health Expenditure on Maternal Health: Empirical Evidence from Central and Latin American Countries

Objective: The aim of this paper is to assess the impact of out-of-pocket (OOP) health expenditure on maternal health outcomes using a panel of twenty Central and Latin American countries between 2000 and 2015.Material and Methods: Six different estimation techniques were used in the analysis in order to check the robustness of the findings. Those estimation techniques were: the ordinary least squares method, the Prais-Winsten correlated panels corrected standard errors regression, the fixed and the random effects models, the generalized least squares method and the bias-corrected least squares dummy variable method.Results: After controlling for female education, gross domestic product and remittances, it was found that a surge in (OOP) health expenditure significantly deteriorates maternal health as it leads to a decrease in skilled birth attendance and an increase in maternal mortality. It was also found that in Central and Latin American countries, educated women tended to be healthier, and maternal health care was mainly financed with the money received from friends and family members living abroad.Conclusion: It is therefore recommended that public health authorities design and implement protective health care financing programs, such as health insurance.
A PBPK model to elucidate processes governing distribution and excretion of polyacrylamide nanoparticles

This paper presents a physiologically based pharmacokinetics (PBPK) model that has been calibrated using experimental measurements of biodistribution and excretion of polyacrylamide nanoparticles in rats. Distribution to the organs of the reticular endothelium system is rapid and reach saturation depending on the dose level. The liver contains is dominating the accumulation of nanoparticles in organs. Excretion through urine occurs shortly after injection and is not dependent of the total concentration of nanoparticles in blood. In an opposite manner, excretion in faeces is slow and proportional to the blood concentration. Overall, excretion through faeces and urine are not major routes of eliminations since they only account for ~5% of the injected dose after 120hr. Finally, transfer from the blood to the carcass is responsible for the greatest amount of nanoparticles sequestered after 120hr, although the kinetic is slow (apparent half-life=40hr). The model predicts that accumulation in peripheral tissues would be significantly lower if the dose was not sufficient to saturate the organs.
Evaluation of Mobility Models with AODV & OLSR Protocol by Varying Node Speed in MANET

A Mobile Ad-hoc Network (MANET) is a collection of mobile devices dynamically forming a communication network without any centralized control and pre-existing network infrastructure. Due to the presence of mobility in the MANET, the interconnections between stations are likely to change on a continual basis, resulting in frequent changes of network topology. Consequently, routing becomes a vital factor and a major challenge in such a network. This research aims to study the impact of mobility models with routing protocols on MANETs and thereby comprehensively analyzes their performance under varying node mobility rates. In this research paper the main objective is to analyze, simulate and do a comparative analysis of different Mobility Model with MANET routing protocols namely AODV (Ad Hoc On Demand Distance Vector) and OLSR (Optimized Link State Routing). This paper will perform a comparison between these models considering the following performance metrics (Average End to End Delay, Throughput and Overheads with respect to different node Speed).
Generating description with multi-feature fusion and saliency maps of image

Generating description for an image can be regard as visual understanding. It is across artificial intelligence, machine learning, natural language processing and many other areas. In this paper, we present a model that generates description for images based on RNN (recurrent neural network) with object attention and multi-feature of images. The deep recurrent neural networks have excellent performance in machine translation, so we use it to generate natural sentence description for images. The proposed method uses single CNN (convolution neural network) that is trained on ImageNet to extract image features. But we think it can not adequately contain the content in images, it may only focus on the object area of image. So we add scene information to image feature using CNN which is trained on Places205. Experiments show that model with multi-feature extracted by two CNNs perform better than which with a single feature. In addition, we make saliency weights on images to emphasize the salient objects in images. We evaluate our model on MSCOCO based on public metrics, and the results show that our model performs better than several state-of-the-art methods.
Refreshing peer observation through Walkabout Weeks: observers as voyagers, not vampires

When one observes, two learn. This viewpoint piece argues that peer observation can serve an important role in facilitating profound conversations about teaching, expanding tutors’ ‘significant networks’. HE tutors are traditionally wary of inviting spectators into their classrooms, observers relying on invitations in the same way that vampires require invites before they are can enter a room. It is argued that observers are better conceptualised as voyagers, exploring new environments for personal development. It is within this context that Walkabout Weeks were born, a fortnight each year where science tutors open their classrooms to colleagues. This initiative has enhanced the visibility of casual peer observation, further normalising this practice, and has provided a rich source of diverse observation opportunities for inexperienced staff. By also welcoming non-academics into classrooms, administrative staff have gained deeper insights into the academic lives of the students that they support, a distinctive feature of the scheme.
Recognizing and Stopping Rumors Patterns in Social Networks

Objectives: In this study, a proposed Colored Petri Net Model (CPNM) is used for recognizing and stopping rumors in Social Networks (SN). Methods/Analysis: Detecting and blocking rumors represent an open security issue in social networks. In response to this issue, the proposed CPNM is experimentally simulated on dataset consists of 863-newsworthy tweets collected from the trending topic #CharlieHebdo in Twitter. The performance of CPNM is analyzed and evaluated using Precision, Recall, and Accuracy metrics. In addition, the CPNM is verified against the Reachability as a major behavior property in Petri Nets. Findings: The practical results disclosed a superiority of the proposed CPNM in detecting accurately rumors patterns compared with other approaches in the literature. In addition, verifying the Reachability using Reachability Graph proved that detecting and blocking rumors tweets are reachable states according to the firing life-cycle of tokens. Novelty/Improvement: Detecting rumors in social networks in more accuracy and low False Positive Rate (FPR) as well as blocking its propagation over the Social Network.