Miracle-dz/UniFAR-FTUs huggingface dataset:
Associated Learning: Decomposing End-to-End Backpropagation Based on Autoencoders and Target Propagation

Backpropagation (BP) is the cornerstone of today's deep learning algorithms, but it is inefficient partially because of backward locking, which means updating the weights of one layer locks the weight updates in the other layers. Consequently, it is challenging to apply parallel computing or a pipeline structure to update the weights in different layers simultaneously. In this letter, we introduce a novel learning structure, associated learning (AL), that modularizes the network into smaller components, each of which has a local objective. Because the objectives are mutually independent, AL can learn the parameters in different layers independently and simultaneously, so it is feasible to apply a pipeline structure to improve the training throughput. Specifically, this pipeline structure improves the complexity of the training time from O(nℓ), which is the time complexity when using BP and stochastic gradient descent (SGD) for training, to O(n+ℓ), where n is the number of training instances and ℓ is the number of hidden layers. Surprisingly, even though most of the parameters in AL do not directly interact with the target variable, training deep models by this method yields accuracies comparable to those from models trained using typical BP methods, in which all parameters are used to predict the target variable. Consequently, because of the scalability and the predictive power demonstrated in the experiments, AL deserves further study to determine the better hyperparameter settings, such as activation function selection, learning rate scheduling, and weight initialization, to accumulate experience, as we have done over the years with the typical BP method. In addition, perhaps our design can also inspire new network designs for deep learning. Our implementation is available at https://github.com/SamYWK/Associated_Learning.
Adjusting Pleasure-Arousal-Dominance for Continuous Emotional Text-to-speech Synthesizer

Emotion is not limited to discrete categories of happy, sad, angry, fear, disgust, surprise, and so on. Instead, each emotion category is projected into a set of nearly independent dimensions, named pleasure (or valence), arousal, and dominance, known as PAD. The value of each dimension varies from -1 to 1, such that the neutral emotion is in the center with all-zero values. Training an emotional continuous text-to-speech (TTS) synthesizer on the independent dimensions provides the possibility of emotional speech synthesis with unlimited emotion categories. Our end-to-end neural speech synthesizer is based on the well-known Tacotron. Empirically, we have found the optimum network architecture for injecting the 3D PADs. Moreover, the PAD values are adjusted for the speech synthesis purpose.
Amur Tiger Re-identification in the Wild

Monitoring the population and movements of endangered species is an important task to wildlife conversation. Traditional tagging methods do not scale to large populations, while applying computer vision methods to camera sensor data requires re-identification (re-ID) algorithms to obtain accurate counts and moving trajectory of wildlife. However, existing re-ID methods are largely targeted at persons and cars, which have limited pose variations and constrained capture environments. This paper tries to fill the gap by introducing a novel large-scale dataset, the Amur Tiger Re-identification in the Wild (ATRW) dataset. ATRW contains over 8,000 video clips from 92 Amur tigers, with bounding box, pose keypoint, and tiger identity annotations. In contrast to typical re-ID datasets, the tigers are captured in a diverse set of unconstrained poses and lighting conditions. We demonstrate with a set of baseline algorithms that ATRW is a challenging dataset for re-ID. Lastly, we propose a novel method for tiger re-identification, which introduces precise pose parts modeling in deep neural networks to handle large pose variation of tigers, and reaches notable performance improvement over existing re-ID methods. The dataset will be public available at this https URL .
Money Cannot Buy Everything: Trading Infinite Location Data Streams with Bounded Individual Privacy Loss

As personal data have been the new oil of the digital era, there is a growing trend perceiving personal data as a commodity. Although some people are willing to trade their personal data for money, they might still expect limited individual privacy loss, and the maximum tolerable privacy loss varies with each individual. In this paper, we propose a framework that enables individuals to trade their location data streams under personalized privacy loss, which can be bounded in w successive time points. However, the introduction of such personalized bounds of individual privacy loss over streaming data raises several technical challenges in the aspects of budget allocation, utility estimation of personalized differentially private mechanism, and arbitrage-free pricing. To deal with those challenges, we modularize three key modules in our framework and propose arbitrage-free trading mechanisms by combining instances of the modules. Finally, our experiments verify the effectiveness of the proposed mechanisms.
Linking geospatial data with Geo-L - analysis and experiments of big data readiness of common technologies

Geospatial Linked Data is an emerging domain, with growing interest in research and industry. The growing sources of open-source geospatial Linked Data need to be interlinked and easily integrated with private and industrial linked data clouds, e.g., in the agricultural domain. The presented paper analyzes common link discovery tools for the feasibility of big linked data processing. Further, it introduces Geo-L, a system for discovery of RDF spatial links based on topological relations. Experiments show that the proposed system improves state-of-the-art spatial linking processes in terms of mapping-time and -accuracy, as well as concerning resources retrieval efficiency and robustness.
The gender wage gap across cohorts : The role of education in twelve countries

Does the increase in tertiary education among women translate into commensurate female wages? Existing studies have shown that countries differ considerably in the gender wage gap. Using selected countries over 30 years, we study whether women’s educational expansion has translated into a closing of the gender wage gap. As education is known to be very cohort dependent, in our view, a Age-Period-Cohort analysis is most appropriate. Applying such an analysis to the Luxembourg Income Study (LIS) data, we show that, while in terms of access to tertiary education women have caught up and in many countries even outperform men, substantial gender wage differences persist in all countries. Using the Blinder-Oaxaca decomposition, we demonstrate that the role of education in explaining the gender gap has been limited and even decreased over cohorts. We thus conclude that gender wage differences at levels far from gender equality will also persist in the future, even if the “rise of women” in terms of education continues.
Conceptual approaches towards sustainability

Sustainability and security assessment currently arises as comprehensive and integrated approach. Sustainable development is a fundamental and overarching objective of the European union (Eu) countries. It aims to improve the quality of life of citizens through sustainable communities that manage and use resources, by linking economic development and security, protection of the environment and social justice. Measuring progress towards sustainable development is an integral part of the Eu Sustainable Development Strategy (SDS), that defines objectives and targets intended to put the European union on a path towards sustainable development. The issue of economic security and sustainability has been analyzed in theory from different perspectives. In many studies the macroeconomic indicator Gross Domestic Product (GDP) is the best-recognized measure of economic performance in the world. However, GDP may measure economic growth but does not involve all aspects of sustainable growth or development. In order to effectively measure progress and wealth, clear indicators are needed that incorporate social and environmental costs and benefits. There is no shortage of research on indicators complementary to GDP, but this remains a subject for academic discussions. In order to manage security and sustainability, society has to formulate clear and measurable goals of sustainability. The level, at which these goals are achieved, might be measured using sustainable development indicators. The paper aims to reveal prevailing conceptual approaches of sustainability from the macroeconomic as well as corporation perspectives, to summarize and compare the key factors describing sustainable development. The method of the research is based on logic abstraction that encompasses generalizations and examinations on theoretical approaches and academics’ surveys.
Injection and Implantation of Mesenchymal Stem Cells for Improvement of Osteoarthritis in Knees

Background: Osteoarthritis is a prevalent disease process that is characterized by degeneration of cartilage in weight-bearing joints. This loss of cartilage results in high levels of pain, joint stiffness, loss of range of motion and function, and psychological distress. Current osteoarthritis treatment focuses on reduction of pain and swelling and improvement of quality of life for the patients. Recently, mesenchymal stem cells have been of interest in this disease process due to their self-renewal, multipotent differentiation, and immunomodulatory properties. Can mesenchymal stem cell injections or implantation in patients with osteoarthritis of the knee improve level of function and magnetic resonance imaging results? Methods: An exhaustive search of available medical literature using MEDLINE-Ovid, CINAHL, and Web of Science was conducted using the key words “mesenchymal stem cell transplantation” and “osteoarthritis, knee”. The results were screened with eligibility criteria. The remaining articles were evaluated and assessed for quality using GRADE. Results: Two studies met inclusion and exclusion criteria and were included in this systematic review. One prospective cohort study looked at 20 patients with osteoarthritis of the knee and performed mesenchymal stem cell implantation. The results showed overall improvement in level of function and magnetic resonance imaging (MRI) results. One therapeutic case series looked at 25 patients with osteoarthritis of the knee and performed mesenchymal stem cell injections. Although seven patients were lost to follow-up, results showed overall improvement in pain, level of function, and MRI results. Conclusion: Mesenchymal stem cell implantation or injections have been found to improve level of function and MRI results at two years after the initial procedure. However, there is not sufficient quality evidence to show that this treatment option should be implemented into standard of care for patients with osteoarthritis. While study results are promising, further research with larger study sizes, variable techniques, and longer follow-up are needed to validate this treatment and determine at what point in the osteoarthritis disease process it should be utilized. Degree Type Capstone Project Degree Name Master of Science in Physician Assistant Studies
Focal Loss based Residual Convolutional Neural Network for Speech Emotion Recognition

This paper proposes a Residual Convolutional Neural Network (ResNet) based on speech features and trained under Focal Loss to recognize emotion in speech. Speech features such as Spectrogram and Mel-frequency Cepstral Coefficients (MFCCs) have shown the ability to characterize emotion better than just plain text. Further Focal Loss, first used in One-Stage Object Detectors, has shown the ability to focus the training process more towards hard-examples and down-weight the loss assigned to well-classified examples, thus preventing the model from being overwhelmed by easily classifiable examples.
Phenolic Compounds Recovery from Grape Fruit and By- Products: An Overview of Extraction Methods

Phenolic compounds are considered as bioactive compounds having beneficial effects on human health. Because of their biological properties, they have wide applications on pharmaceutical and food industries, and for this reason, it is important to identify most appropriate procedures, which permits the standardization for recovery of these compounds from several plant materials including grapes. Grape fruit and by-products are excellent sources of bioactive compounds such as pigments, organic acids, and phenolic compounds. Several convectional and emerging technologies have been evaluated in order to recover phenolic compounds from grape fruits and wastes such as chemical, physical, and biotechnological techniques, which offer different advantages related to economic, environmental, time-saving, and yield aspects. Nowadays, there is no updated information, which provides an overview about the techniques applied of these bioactive compound recovery in order to obtain high-quality and high-activity extracts rich in phenolic compounds from grape fruit and by-products. This chapter offers relevant aspects related to the techniques employed during the last five years by researches for phenolic compound recovery from grapes. three seed oil extraction methods (screw pressing, extraction by supercritical CO 2 percolation, and the combination of these two processes) and evaluated their efficiency for producing oil rich in phenolic compounds. The results suggested that the processes using supercritical CO 2 permit an increase in the co-extraction of phenolic with oil. tissue structure of the source and the PEF treatment conditions applied. El Darra et al. [59] evaluated the influence of PEF (0.8–5 kV/cm, 1–100 ms, 42–53 kJ/kg) on the recuperation of phenolic compounds from Cabernet Franc grapes and its relationship with the process fermentation compared with a conventional treatment (50°C for 15 min). The study showed a significant improvement in phenolics extraction (anthocyanin and tannin contents), color intensity, and scavenging activity of the samples during red wine fermentation after applying PEF (51–62%) and thermal treatments (20%). In addition, Delsart et al. [60] determined the presence of phenolic compounds from Merlot grapes and the effect of PEF on the fermentation process of this grape variety and the related wine characteristics. The experiments focused in the application of PEF treatments (500–700 V/cm) with times of incidence of 40–100 ms where the measured responses were color intensity, anthocyanins, and phenolic content during the alcoholic fermentation and seven months during storage. The results suggest that pulsed electric field treatment has the advantage of nonthermal-selective extraction (<5°C) involving no loss of product quality in with respect to the classical process.
Heavy metal concentrations and environmental quality in three Wisconsin lakes

Humans have impacted most of the Earth’s surface, and lake sediments are a particularly useful means of examining that impact because they preserve biologic, geologic, and chemical data in a continuous record progressing back in time (Dietl et al., 2015). Aquatic ecosystems are more susceptible to the effects of pollution than terrestrial ecosystems, because they have less relative biomass spread over a higher order of trophic levels. Among aquatic ecosystems, lakes are especially sensitive because they serve as receptacles for effluents. (Forstner and Wittman, 1983). This study examines heavy metal pollution in three Wisconsin lakes spanning a range of environmental and human influence: Sparkling Lake is the least impacted and is found in sparsely populated northern Wisconsin; Shadow Lake, located in a small urban environment in central Wisconsin, is moderately impacted and has been chemically remediated; and Lake Monona is the most impacted in southern Wisconsin in a large urban environment.
An Analysis of Classroom Discourse

The literature suggests that the U.S. system of higher education has developed and maintained conservative norms govern behavior in the classroom and discourage open dialog by dictating what is and is not appropriate to discuss in academic settings. The question is raised of the appropriateness of these norms. Classroom dialog was analyzed to test the hypothesis that in a college course where students frequently discuss ways to improve education for disadvantaged and minority children, the number of times students discussed their personal experiences as teachers would be significantly higher than the number of times they discussed personal experiences as disadvantaged or minority students. Participants in the study were 41 education students of whom 86 percent were teachers, 69 percent claimed to have come from disadvantaged backgrounds, and 77 percent claimed to be minorities. Results supported the hypothesis; also the students seemed uncomfortable talking about their experiences as disadvantaged or minority students. Additional analyses indicated that men and women made about the same number of comments in class. Although this finding suggesLs a more equal representation of women's voices than has been reported in the past, other factors were noted. For example, some women were excluded from the study because they never talked in class, and a higher percentage of men in the class were seeking advanced degrees. (Contains 2 tables and 26 references.) (ND) that ******************************************),-****---)%4i-******** Reproductions supplied by EDRS are the best that can be made from the original document. ' ******************************************************************** * When do Education Students Talk about Personal Experience ? An Analysis of Classroom Discourse Pamela LePage University of California, Berkeley San Francisco State University H1011.SION TO Ili. PRODUCE AND Dips,EMINATE THI1, MA1 E1.11AI i4A' BF E.N B'r
Native Speakers' Perceptions of Nonnative Speakers: Related to Phonetic Errors and Spoken Grammatical Errors.

A study investigated the perceptions of native English-speakers concerning the spoken grammatical and phonetic (accent) errors of non-native speakers. Speech samples were collected from tilree non-native speakers of English of varied linguistic backgrounds (German, Spanish, and Arabic) and one speaker of North American English. Each of the four speakers recorded two speech samples, one containing a grammatical error only and one containing a phonetic error only. A group of 124 Florida college freshmen then heard the speech samples and completed a semantic differential scale questionnaire for each. Analysis revealed significant differences in reactions across languages and error types. Phonetic error was rated lower than'grammatical error, despite the fact that grammatical errors sometimes obscured meaning Vale phonetic errors did not. Spanish and German accents were rated about the same, but the Arabic accent was rated lower than the others. It is suggested that American students be taught greater tolerance of international students' speech. The appendix includes one table and two graphs. Contains 38 references. (MSE) *********************************************************************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ********************1. ************************************************** Native Speakers' Perceptions of Nonnative Speakers: Related to Phonetic Errors and Spoken Grammatj:cal Errors Ruth Johnson Southern Illinois University Department of Linguistics Mailcode 4517 Carbondale IL 62901 Frederick L. Jenks The Florida State University CIES 918 West Park Avenue Tallahassee FL 32306 Acknowledgements The authors thank Drs. Paul Angelis, Usha Lakshmanan, and Kim Hughes Wilhelm for their comments on earlier versions of this article. "PERMISSION TO REPRODUCE THIS MATERIAL HAS BEEN GRANTED BY TO THE EDI'CATIONAL RESOURCES INFORMATION CENTER (ERIC). U S. DEPAFTTMENT OF EDUCATION Office 04 Educationsi ROSearCh and Inwovernent EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) his document has been reproduced as kceived from the perSon or organization originating it o Minor changes have been made to improve reproduction Quality Points 01 view or opinions stated in this dOCu went do not necessardy represent offic.at OE RI position Or pohcy
Illumination-Invariant Image Matching Based on Simulated Kalman Filter (SKF) Algorithm

In this paper, a novel image template matching approach to tackle illumination-invariant problem has been proposed. The traditional algorithm to solve image matching problem takes a lot of memory and computational time. Therefore, the image matching problem is assigned to optimization problem and can be solved precisely. Although there are some methods presented recently for image matching illumination-invariant, all of them have limitations in term of dealing with the pixels complexity and many unknown parameters in a certain algorithm. The search of the image template has been performed exhaustively by using Simulated Kalman Filter (SKF) algorithm. The experiment is conducted using an image taken from the database and the contrast image is changed to get the illumination effect. Experimental results show the comparison between SKF and Particle Swarm Optimization (PSO) to get the performance of the correct matching. The percentage of the matching result for the image within six conditions are 24%, 16%, 16%, 12%, 28% and 4% accordingly, which are higher than the PSO algorithm, which obtained 0% correct matching for all conditions.
Multiculturalism and successful integration - A capable system or contradiction? A situation analysis of migrants in Germany and France

Now over one year has passed since the murder of Theo van Gogh, the director of a critical film on Islam, by a radical Islamist in 2004 in the Netherlands. Since then a discussion has been arisen about the integration of ethnic minorities in different European countries. Especially in Germany many politicians, journalists and other intellectuals started making up their mind whether the countries` integration policy has failed. Looking at official statistics it becomes clear that especially in the field of education and employment migrants are disadvantaged to their German fellow citizens. It is more likely that they leave school earlier and that the unemployment rate within this group is higher. (compare www.eurostat.com;24.11.2005) Also in France this discussion has become relevant since two 15 and 17 year old boys with migrant background had died when they flew from the police in the end of October 2005. This was the start of nightly occurring fights between extremist youth, living in Clichy-sous-Bois a suburb (Banlieue) of Paris, and the police. The riots lasted for over two weeks mainly in districts with a high percentage of inhabitants with migrant backgrounds but also extended to places all over France. (Hahn,D. die Tageszeitung;11.11.2005) It was assumed that they wanted to gain attendance by public for their disadvantaged situation in terms of living conditions, education and the labour market. (compare www.tagesschau.de 12.11.2005) Angela Merkel the German Chancellor is of the opinion that idea of a multicultural society has failed (iz3w;2005.p.2) therefore the questions arises: Is the idea of multiculturalism still valid for a future coping strategy? Or do we even have to blame multiculturalism for the existing problems? Proceeding from these questions I will compare the situation of people with a migrant background living in Germany and France in the following work.