Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlaciones e información cuántica con fotones

En un principio, la Teoría de la Información [1] fue concebida en forma abstracta, en base a una formulación matemática. Sin embargo, la habilidad y eficiencia para procesar o transmitir información dependerá en última instancia del sistema físico elegido para codificar esa información. Es así que, al codificar la información en las propiedades físicas de sistemas cuyo comportamiento se describe por las leyes de la mecánica cuántica, se abren nuevas posibilidades que son irrealizables clásicamente. Entre ellas, la posibilidad de generar algoritmos cuánticos para ciertos cálculos que requieren un número de pasos significativamente menor que cualquier algoritmo clásico, reduciendo su complejidad [2], o mantener comunicaciones seguras sin importar las capacidades tecnológicas de un potencial espía [2, 3]. Entre las características fundamentales de la mecánica cuántica que posibilitan estos desarrollos, sobresalen el principio de superposición y el entrelazamiento cuántico, el cual denota un tipo de correlaciones, sin análogo clásico, que pueden exhibir los sistemas cuánticos compuestos [4, 5]. Una de las implementaciones más accesibles para la comunicación cuántica y el procesamiento cuántico de la información emplea fotones individuales como portadores de la información. Estos pueden viajar entre dos estaciones distantes siendo poco afectados por el ruido que introduce el entorno. Además, poseen varios grados de libertad en los cuales es posible codificar la información y pueden manipularse con un alto grado de control utilizando tecnología estándar. En este trabajo se describen algunas aplicaciones de la implementación fotónica, realizadas en colaboración con el Laboratorio de Procesado de Imágenes (LPI) del Depto. de Física de la UBA. En primer lugar, se describe la determinación experimental de medidas de correlaciones cuánticas en estados no puros de un par de fotones correlacionados en polarización [6], mediante técnicas de tomografía de estados cuánticos [7, 8]. Luego se describe la utilización de moduladores espaciales de luz programables para entrelazar la polarización con grados de libertad espaciales, y así poder simular los denominados estados historia de evoluciones temporales cuánticas [9, 10, 11]. Se muestra que este último es un esquema eficientemente para el cálculo de promedios temporales de los observables del sistema [12].
The Influence of Perceived Organizational Support and Leader Member Exchange Against Cunter-Productive Work Behaviors on Civil Servants in Organization X

This study aimed to determine the influence between Perceived Organizational Support (POS) and Leader Member Exchange (LMX) to Counter Productive Behavior on civil servants in Organization X. This study used a quantitative approach. The number of respondents in this study is 271 employees with civil servant status who have the position of executor. Based on the result of the research, the result of Perceived Organizational Support (POS) and Leader Member Exchange (LMX) has negative effect on counterproductive work behavior either simultaneously or partially. In addition, Perceived Organizational Support (POS) and Leader Member Exchange (LMX) had an effect of 84.1% on counter-productive work behaviors. Dimension of Perceived Organizational Support (POS) and Leader Member Exchange (LMX) such as dimension of Perceived Fairness of Treatment, dimension of Perceived Supervisor Support, and dimension of Perceived Organizational Rewards and Job Conditions, Affect dimension, loyalty dimension, and professional respect dimension have a significant effect on counter-productive work behavior. On the other hand, the contribution dimension does not affect the counter-productive work behavior.
The Position of a Company in the Production Chain of the Pulp and Paper Industry Focusing on the Adoption of Eco-Innovation Strategies

This study sought to gauge to what extent companies in the production chain focus on the relationship between contextual factors and the definition of eco-innovation strategies. The methodology is based on a quantitative approach using a survey in 117 companies. The results show that, in general, the companies in the sample the correlation with proactive innovation strategies was especially strengthened for those at the beginning of the production chain, with an increase in the mean for this group. This result is not in keeping with the literature when it comes to the sample data. In the literature, companies that operate in the latter stages of the production chain ought to have a greater impact at the environmental actions, as they have more direct contact with consumers of the end product. This improved performance for companies at the beginning of the production chain could be explained by the fact that these are the most polluting companies and have become the focus of environmental legislation.
The effect of magneto-crystalline anisotropy on the properties of hard and soft magnetic ferrite nanoparticles

Recent advances in the field of magnetic materials emphasize that the development of new and useful magnetic nanoparticles (NPs) requires an accurate and fundamental understanding of their collective magnetic behavior. Studies show that the magnetic properties are strongly affected by the magnetic anisotropy of NPs and by interparticle interactions that are the result of the collective magnetic behavior of NPs. Here we study these effects in more detail. For this purpose, we prepared CoxFe3−xO4 NPs, with x = 0–1 in steps of 0.2, from soft magnetic (Fe3O4) to hard magnetic (CoFe2O4) ferrite, with a significant variation of the magnetic anisotropy. The phase purity and the formation of crystalline NPs with a spinel structure were confirmed through Rietveld refinement. The effect of Co doping on structure, morphology and magnetic properties of CoxFe3−xO4 samples was investigated. In particular, we examined the interparticle interactions in the samples by δm graphs and Henkel plots that have not been reported before in literature. Finally, we studied the hyperthermia properties and observed that the heat efficiency of soft Fe3O4 is about 4 times larger than that of hard CoFe2O4 ferrite, which was attributed to the high coercive field of samples compared with the external field amplitude.
Deep Learning with GPUs

This is a report on the use of deep learning (DL) with neural networks powered by graphical processing units (GPU). The report is aimed at students and researchers to assist them in getting started within this vital field. This work began at the University of Leeds and led me to my current career within NVIDIA, the inventor of the GPU. These co-processors are, along with massive datasets and efficient algorithms, powering the DL renaissance worldwide. The pace of progress is so great within deep learning that NVIDIA are constantly reshaping their ecosystem and recently became the #1 on the Green500 with their 5 Petaflop SATURN V facility, housed in Santa Clara, California. The first task it will be given, externally, is to help on the Cancer Moonshot project in the US, realising my dream that AI be used within Healthcare. Google DeepMind are also now working directly with the NHS. I hope you find this useful.
Analysis of Online Sleep Apnea Data Streams for Mobile Platforms

Sleep apnea is a sleeping disorder characterized by disruption in the natural breathing cycles during sleep. The disorder is common and is linked together with other disabilities and disorders that have serious ramifications to a person’s health. Diagnostic tools such as the polysomnography and portable monitoring devices can record physiological signals to determine a diagnose and severity rating of a patient. Before a diagnose can be determined, the recorded data needs to be manually analyzed by physicians which is a costly and time consuming process. With data mining, machine learning and event analysis the process can be redefined to be more efficient, automatic and require a fraction of the resources. Smart phone devices we have today are very capable of running advanced and complex software, and in some terms can be comparable to laptops. Data mining is a concept of classifying and predicting large amounts of data based on patterns and data analysis built using models. Esper is an open source Complex Event Processing engine and library component that use event series analysis to extract information and patterns in various types of data streams. In this thesis we design and implement four commonly used data mining methods: K-Nearest Neighbor, Support Vector Machine, Artificial Neural Network and Decision Tree. Along the data mining methods, we also design and implement two different detection methods in combination with statistical methods such as a Moving Average and Standard Deviation using the Event Processing Language utilized by Esper. We test both sets of classification methods on input data from three different database sources from PhysioNet. In addition, we analyze the performance utilization of the implementation with comparison with smart phone hardware to gather knowledge that can help develop a future automatic diagnosis application on smart phones. By streaming the data sets from a client to a server running Esper we achieve an accuracy of 90.89% using Decision Tree in a combination of four non-invasive signals. Overall accuracy results from all the data mining methods above 85% accuracy and close to 90% except for three signal combinations. Results from the two apnea detection methods score an accuracy of 93.26% and 93.13% for the Moving Average and Standard Deviation respectively. From the performance measurements we conclude that smart phones that is labeled as budget in terms of hardware and price is suitable to run data mining methods. The results overall show that both data mining methods and our designed detection method based on Esper combined with the performance metrics are suitable to implement as a standalone automatic diagnosis application on budget smart phones.
High-reliability Vehicle Detection and Lane Collision Warning System

In the last two decades, developing Driving Assistance Systems for security has been one of the most active research fields in order to minimize traffic accidents. Vehicle detection is a vital operation in most of these applications. In this paper, we present a high reliable and real-time lighting-invariant lane collision warning system. We implement a novel real-time vehicles detection using Histogram of Oriented Gradient and Support Vector Machine which could be used for collision prediction. Thus, in order to meet the conditions of real-time systems and to reduce the searching region, Otsu’s threshold method play a critical role to extract the Region of Interest using the gradient information firstly. Secondly, we use Histogram of Oriented Gradient (HOG) descriptor to get the features vector, and these features are classified using a Support Vector Machine (SVM) classifier to get training base. Finally, we use this base to detect the vehicles in the road. Two sets generated the training data of our system a set of negative images (non-vehicles) a set of positive images (vehicles), and the test is performed on video sequences on the road. The proposed methodology is tested in different conditions. Our experimental results and accuracy evaluation indicates the efficiency of your system proposed for vehicles detection.
Research on the Construction of China's Emission Trading System from the Perspective of Transaction Cost Theory

China's pollutant discharge management is based on the current government-led administrative approval system. Although some regions have carried out the pilot work of emission trading, they have not formed a legal basis and a system of standardization and haven't been promoted. The purpose of this paper is to analyze the causes and design and construct the framework of China's emissions trading system. Firstly, the resource allocation efficiency of emission trading is analyzed from the micro-economic point of view, and the total transaction cost is analyzed by the dynamic analysis method. Then the obstacle principle of system implementation is found. Although the establishment of a market with clear property rights contributes to the reduction of total transaction costs, the rapid increase of government transaction costs in the short term has affected the implementation of the system. The conclusion is that the government should bear the short-term cost, and use the electronic trading system and establish a broad market with a wide range of participants to reduce the operating cost of the system, so as to achieve the promotion and effective operation of the emission trading system. Keywords—transaction cost theory; emission trading; system construction
Expressive Aprosodia Following Stroke to the Right Basal Ganglia: A Case Report

Presented here is a case report of a 16-year-old adolescent who, after experiencing an embolic stroke to subcortical structures of the right hemisphere, evidenced motor aprosodia. The patient was administered a test of receptive emotional prosody. In addition, the patient was asked to state a series of stimulus sentences to determine if she was able to spontaneously convey emotions (happy, sad, mad) appropriately and was asked to repeat a series of stimulus sentences to determine if she could convey the same emotions as the speaker. She demonstrated aprosodic-agestural speech, aprosodic repetition, and good prosodic comprehension. This case report supports the notion of right-hemisph ere organization of the emotional aspects of language and the existence of subcortical aprosodias analogous to subcortical aphasias. John Hughlings Jackson (Taylor, 1958) stated that there are two modes of expression, emotional and intellectual. The intellectual mode of expression (e.g., vocabulary and grammar) is related to Jackson's concept of prepositional speech, which he believed to be a function of the languagedominant (typically left) hemisphere (Taylor, 1958). Jackson's emotional mode of expression is related to Monrad-Krohn's (1947) concept of prosody, which involves the melodic line of language produced by the variations of pitch, rhythm, and stress of pronunciation that bestows certain semantic and emotional meaning to speech. Emotional prosody represents the insertion of emotional feeling into speech to convey anger, pleasure, fear, sorrow, and so forth (Ross & Mesulam, 1979). In fact, Jackson
Resposta afetiva e motivação como preditores de aderência a prática de exercício físico em academia

Atualmente tem se verificado a importância da pratica de exercicios fisicos sobre a saude fisica e psicologica das pessoas. No entanto, tem-se observado altas prevalencias de inatividade fisica em todos os estratos da populacao. Dentre as possiveis causas da nao adesao a pratica destaca-se a motivacao e a resposta afetiva. Desta forma, o objetivo do presente estudo foi avaliar a relacao entre a resposta afetiva e a motivacao com a aderencia a pratica de exercicio fisico de academia. Foram avaliados 37 praticantes de duas academias de ginastica de Brasilia com media de idade de 28,1 (± 7,0) anos, sendo 17 homens (47,2%) e 19 mulheres (52,8%). Para avaliacao da motivacao foi utilizada a Motives for Physical Activity Measure (MPAM) e a para a resposta afetiva, escala de Afeto Positivo e Negativo. A aderencia foi verificada por meio dos meses em que o individuo esteve envolvido na pratica de exercicio fisico na academia. Os dados foram tratados utilizando-se a estatistica descritiva apropriada, alem dos testes inferenciais teste U de Mann Whitney para comparacao de todas as variaveis entre os sexos e o teste de Correlacao de Spearman para relacionar a resposta afetiva e a motivacao com a aderencia, utilizando o pacote estatistico SPSS®, versao 20.0. O nivel de significância adotado foi de 5%. Dentre os sujeitos avaliados, 28 (77,8%) nao aderiram a pratica de exercicio fisico, sendo esta prevalencia maior entre os homens (82,4%). Com relacao a associacao entre motivacao e resposta afetiva com a aderencia, o dominio aparencia do constructo motivacao foi a unica variavel associada. Conclui-se que dentre todos os fatores investigados a preocupacao com a aparencia demonstrou ser determinante para proporcionar a adesao a pratica de exercicios fisicos de academia entre a populacao investigada.
Développement d'un agent BDI pour la prise de décision d'ordonnancement dans un environnement Cloud Computing.

Task scheduling in cloud computing environment is subject to specific constraints. The distributed nature of cloud computing does not allow a centralized approach. The distributed approach is confronted to the limitations of the visibility of the overall state of the dynamic system. In this report, we developed algorithms to solve the problem of task scheduling. The algorithms are based on BDI agent’s paradigm by implementing a collaborative model for dynamic scheduling tasks.
Students’ perception of use of social media as interactive resources for teaching and evaluation in University of Maiduguri, Nigeria

- This study investigated students’ perception towards the use of social media tools as interactive resources for teaching and evaluation in the University of Maiduguri. A survey of 2,466 undergraduate students was carried out in two semesters. The students were the 200 level of a 4/5 -year degree programme in 2017/2018 session offering Educational psychology in the Faculty of Education. The aim was to determine the students’ perception on the use of social media tools for interaction in their educational pursuits for teaching and evaluation. 11 Social media tools were identified by the students. Students have used a variety of social media tools to submit assignments, write projects and share educational materials with lecturers and co-students. The most preferred social media tools identified by students are Facebook, Whatsapp, Google Plus, Instagram, and YouTube. Majority of the students spend 1-5 hours engaging in social media activities per day. Female students spent more time in social media than their male counterparts. Due to the inaccessibility of Wi-Fi, students spend huge amount of money buying data from different network providers. The study recommended that the University should provide the cloud for easy access to networks. Interactive boards provided by the University could not be used due to lack of Wi-Fi facility. There should be more training and retraining of staff to engage students in social media to facilitate e-learning that is the global best practice.
The Effects of Emoji in Sentiment Analysis

This study investigates the usage of Emoji characters on social networks and the effects of Emoji in text mining and sentiment analysis. As it provides live access to text based public opinions, we chose Twitter as our information source in our analysis. We collected text data for some global positive and negative events to analyze the impact of Emoji characters in sentiment analysis. In our analysis, we noticed that the utilization of Emoji characters in sentiment analysis results in higher sentiment scores. Furthermore, we observed that the usage of Emoji characters in sentiment analysis appeared to have higher impact on overall sentiments of the positive opinions in comparison to the negative opinions.
Enhancing Visual Explanation of Deep Neural Networks by Activation Freezing

The “black box” nature of deep neural networks hinder us from inspecting the logic hidden inside the networks. To alleviate this difficulty, for image recognition tasks, several visual explanation methods are proposed. The aim of visual explanation is to highlight a segment of the image as a clue of the network’s recognition. In this paper, we propose a method for enhancing the highlights of the existing visual explanation methods. In the proposed method, we freeze the activations of the some of the network nodes in middle layers. With the proposed method, we can obtain clear highlights with less noises than the existing methods.
A performance comparison of nonlinear filtering techniques based on recorded radar datasets

In this paper, several nonlinear filters (EKF/CMKF/CMEKF, UKF and PFs) are compared using real datasets and simulations based on two representative radar datasets. The first dataset was collected from an air traffic control (ATC) radar experiment with several aircraft. The second dataset was recorded from a high frequency surface wave radar (HFSWR) trial that was characterzed by a very long integration time and a limited set of manoeuvre types. RMSE, NEES and NIS are used as measures of performance. Comments on the performance, computational requirements of the nonlinear filters, practical modelling and filter tuning issues for the two types of radars are also presented.
Using Unmanned Aerial Vehicles for surveys of marine mammals in Australia: test of concept

The following technical report describes the approach and algorithm used to detect marine mammals from aerial imagery taken from manned/unmanned platform. The aim is to automate the process of counting the population of dugongs and other mammals. I have developed an algorithm that automatically presents to a user a number of possible candidates of these mammals. I tested the algorithm in two distinct datasets taken from different altitudes. The analysis and discussion are presented in relation to the complexity of the input datasets and the detection performance.
User Experience Evaluation Based on Arbitration QoS Parameters in Video Stream Using NetFPGA in a Controlled Environment

A streaming video has some features that are different from others, such as the occupation of a large amount of bandwidth, and the possible scenes variation with a consequent increase or decrease in the amount of transmitted bytes. Applications for the video streaming transmission (YouTube, Vimeo, Netflix, Telecine Play, etc) have aroused the interest of the scientific community regarding to the networks behavior. The purpose of this paper is to measure, through a video stream, the user experience, also known as Quality of Experience (QoE) based on the arbitration of QoS parameters in a controlled environment using NetFPGA. Keywords–QoS; QoE; DiffServ; Correlation Models; NetFPGA.
A robust methodology for tracking and evaluating student engagement

Digital solutions for tracking and evaluating student engagement are limited. This paper reviews the implementation of a digital solution used to transform two Student Engagement schemes at the University of Exeter: ‘Peer Learning’ and ‘Students as Change Agents’. By means of the workflow function in CareerHub, an online career management system, workflows have been created to enable the management, in one efficient platform, of student recruitment, training, tracking and learner reflection. Since all student engagement records and knowledge of interactions are in one place, asignificant reduction in administration and enhanced opportunities for effective evaluation have been achieved. Previously, student skills development and reflection to enhance student employability had not been a significant feature of either Peer Learning or Students as Change Agents. With the automated workflow, students can now access the right guidance at the right time, thereby making more effective step-by-step progress through either scheme. Students are also able to track their own progress and manage their involvement with the projects more effectively. The workflows have created clear audit trails so that these activities are verifiable and easily articulate with student Exeter Award profiles and the Higher Education Achievement Report (HEAR).