Miracle-dz/UniFAR-FTUs huggingface dataset:
Implantes con platform switching: traducción comentada de un artículo científico

Just like almost every other science field, implant dentistry is one that keeps on being improved and updated. Therefore, the amount of new literature being written on the subject increases every year. As it has been a trend for the past years, the most used language in science is English, which means that countries that don’t speak it need to translate the documents so as to keep up to date with the hundreds of studies and new data that are being published at an ever-growing pace. That is the case of the clinical study that has been translated in this paper. One of the goals of the translation into Spanish was to widen the amount of scientific documents related to the subject of dental implant dentistry available to the experts. Therefore, it tried to use terminology specific to the field that would be understood by readers with deep knowledge on the subject. With that in mind, this paper also analysed the main difficulties that a translator can encounter when tackling a scientific translation with little resources at hand, since most of the terms used in the original article were either very recent or so specific that finding an appropriate translation proved to be an arduous task.
Research on Load Balance Method in SDN

In order to improve the performance of data transmission in SDN, this paper proposes a load balance solution scheme by taking advantage of the global network view of SDN. We collect 4 load features from each transmission path. These features are bandwidth utilization ratio, packet loss rate, transmission latency and transmission hops. By using this 4 load features, BP Artificial Neural Network model is trained to predict the integrated load for different path and to choose one with least load as the data-flow transmission path. The contrast experiment results show that load balancing strategy proposed in this paper can select more rational transmission path for data-flow and achieve 19.3% network latency decrease at most.
Feature classification for the satellite modulation based on sparse coding algorithm

In order to improve the characteristics for satellite data expression ability, it is proposed sparse coding with over complete bases, to induce the high dimensional feature vectors form down to up pattern, then to accurately express the original high-dimensional features with very few over complete basis vectors. From top-down semi supervised learning characteristics, to project high dimensional feature to low dimensional space, in order to verify the similarity of coding of the training data, then to express the characteristics of input satellite data. The encoder needs as much as possible reconstruction for the input multi dimensional, and the find the main ingredients for representing the original information about input data. Therefore, the over complete is not only by the coefficient of input data to determine characteristics, but also by the dimensional space. In order to verify the performance of the sparse coding algorithm, using the sparse coding algorithm is to identify the 6 kinds of commonly used digital modulation signal: 4ASK, 4FSK, 4PSK, MSK, 16QAM, π/4QPSK. The performance of correct modulation recognition rate is higher stability. The overall recognition of 6 kinds of modulation rate of SNR is higher, not less than 0dB 99%.
LABORATORIOS VIRTUALES REMOTOS USANDO EASY JAVA SIMULATIONS Y SIMULINK

Actualmente Easy Java Simulations (Ejs) permite reutilizar modelos Simulink para la creacion de laboratorios virtuales interactivos. Sin embargo hasta ahora, si el usuario final del laboratorio virtual no dispone de Matlab/Simulink en su ordenador no podra ejecutar la simulacion. Como solucion al problema anterior esta en proceso de desarrollo y prueba la utilizacion del servidor Java Internet Matlab (Jim), el cual junto con Ejs permite la creacion y ejecucion de laboratorios virtuales remotos, con un alto grado de interactividad, sin necesidad de que el disenador o usuario final requiera en su computador de Matlab/Simulink. Es necesario considerar que la extension propuesta utiliza una licencia normal de Matlab ya que el requisito de una licencia de Matlab Web Server puede resultar en algunos casos prohibitivo debido a su coste. En el presente articulo, por tanto, se exponen las principales ideas existentes tras el desarrollo mencionado.
A STUDY OF EVALUATING THE VALUE OF SOCIAL TAGS AS INDEXING TERMS

AbstractRegardless of their inherent drawbacks as indexing terms, such as semantic ambiguity and the lack of synonymy and polysemy control, the use of social tags is widespread in information organization, filtering, and discovery through social tagging information systems. There are few empirical studies that have evaluated the value of social tags as indexing terms in an operational and experimental setting. The objective of this study is to assess the indexing value of social tags in a context of an information retrieval model using the Latent Semantic Indexing (LSI) method. Socially tagged resources were classified into ten Dewey Decimal Classification (DDC) main classes. Social tags assigned to the resources were used to represent them in LSI. Similarities between resources were measured, and the aggregated similarities according to the ten DDC main classes were compared. Twenty-four different experiments were attempted for optimal results. The empirical data of this study positively demonstrates the value of social tags as indexing term.
Adaptasi Algoritma Harmony Search Untuk Menyelesaikan Capacitated Vehicle Routing Problem (Cvrp) Dengan Permintaan Dinamis

Capacitated vehicle routing problem (CVRP) merupakan permasalahan pencarian rute terbaik untuk mendistribusikan barang kepada sejumlah pelanggan menggunakan kendaraan yang memiliki kapasitas terbatas. CVRP merupakan permasalahan np-hard yang berarti diperlukan suatu metode untuk dapat menghasilkan solusi penyelesaian yang optimal dengan waktu komputasi lebih cepat. Pertama, pada penelitian ini terdapat dua kasus, kasus pertama adalah CVRP dengan letak depot berada di pinggir dan kasus kedua letak depotnya berada ditengah dengan masing-masing memiliki koordinat depot, koordinat 70 pelanggan, kapasitas kendaraan, dan permintaan setiap pelanggan. Kemudian, dicari rute terpendek untuk melayani pelanggan yang memiliki permintaan. Pada penelitian ini, CVRP dengan permintaan dinamis diselesaikan dengan algoritma harmony search, GA¬-based clustering algorithm, dan algoritma hybrid harmony search. Hasil yang didapatkan yaitu algortima hybrid harmony search dapat digunakan untuk menyelesaikan CVRP dengan permintaan dinamis dan menghasilkan solusi yang baik dibandingkan dengan algoritma harmony search, dan GA¬-based clustering algorithm. ============================================================================================== Capacitated vehicle routing problem (CVRP) is a matter of finding the best route to distribute goods to a number of customers using vehicles with limited capacity. CVRP is a np-hard problem which means a method is needed that can produce an optimal solution with faster computation time. First, in this research there are two cases, the first case is the CVRP with the location of the depot is on the edge and the second case where the depot is located in the middle. Each case contains coordinate of depot, coordinate of 70 customers, vehicle capacity, and demand of each customers. Then, search for the shortest route to serve customers who have requests. In this study, CVRP with dynamic demands solved by GA-based clustering algorithm, harmony search algorithm and hybrid harmony search algorithm. The results is hybrid harmony search algorithm can be used to solved CVRP with dynamic demands and produce a good solution, while harmony search algorithm and GA-based clustering can not produce a good solution.
Performance Analysis of Flower Pollination Algorithm Based Controllers in AGC of Multi Area Power System

This article presents the design and analysis of two degree of freedom (2DOF) controller with integral plus double derivative (2DOF-IDD) and with proportion plus integral plus derivative (2DOF-PID) controller for Automatic generation control (AGC) of multi area power systems with two thermal and two wind system using Flower pollination algorithm (FPA). Secondary controller gains and other parameters are simultaneously optimized using most recent technique called FPA. The system dynamics responses obtained with 2DOF-IDD controller are compared with that obtained from other 2DOF controllers like 2DOF-PI and 2DOF-PID controller. Investigation shows that 2DOF-PI and 2DOF-PID give nearly same response but 2DOF-IDD gives much better response than other two controllers
Study on the Association between Personal Information Protection Legislation and Information Security Product

ABSTRACT For the past few years, personal information breach incidents, great and small, occurred constantly. Accordingly, the Personal Information Protection related Ordinances are enacted and amend ed persistently, and the information security products also kee p advancing and developing in the same way. There are the certifi cation systems such as Common Criteria Evaluation and Validatio n(CC) and Korea Cryptographic Module Validation Program(KCMVP) for th e information security products. These are also strictly carrie d out. This paper analyzes and categorizes the 5 Personal Informa tion Protection related Ordinances in the aspects of technical protection measures by using key words. Here are the 5 related ordinances; ‘the Personal Information Protection Act’, ‘the Act on Promoti on of Information and Communications Network Utilization and Infor mation Protection, etc’, ‘the Act on the Protection, Use, Etc, of Location Information’, ‘the Use and Protection of Credit Inform ation Act’, and ‘the Electronic Financial Transactions Act. ’ Mo reover, this study analyzes the association between the technical prote ction measures in the 5 relevant laws and the information secur ity products that are obtaining the CC Evaluation & Validation(CC) and the products that are now produced at KISIA’s member compan ies. Keywords: Personal Information Protection, CC, KCMVP, KISIA
Evaluation of Online Video Usage and Learning Satisfaction: An Extension of the Technology Acceptance Model

The aim of the study was to examine the determining factors of students' video usage and their learning satisfaction relating to the supplementary application of educational videos, accessible in a Moodle environment in a Business Mathematics Course. The research model is based on the extension of Technology Acceptance Model (TAM), in which the core TAM constructs – perceived usefulness, perceived ease of use, attitude – and internet self-efficacy were included as the explanatory factors of video usage. As regards the determinants of learning satisfaction, beside the core TAM constructs, the role of learning performance, learner-learner interaction, and learner-teacher interaction was examined. Data were collected from 89 students using a questionnaire, on which the partial least-squares structural equation modelling approach was used to evaluate the research model. The results confirmed that perceived usefulness, attitude, and internet self-efficacy had a direct effect on the video usage. Learning satisfaction was directly influenced by learner-learner interaction, perceived ease of use, and learning performance. Furthermore, the results indicated that video usage had a significant effect both on learning performance and on learning satisfaction. The findings show that the extended TAM model can be applied for predicting the university students' video technology usage and their learning satisfaction regarding the usage.
A continuum model (PSUMEL1) of ice mélange and its role during retreat of the Antarctic Ice Sheet

Abstract. Rapidly retreating thick ice fronts can generate large amounts of mélange (floating ice debris), which may affect episodes of rapid retreat of Antarctic marine ice. In modern Greenland fjords, mélange provides substantial back pressure on calving ice faces, which slows ice front calving rates. On the much larger scales of West Antarctica, it is unknown if mélange could clog seaways and provide enough back pressure to act as a negative feedback slowing retreat. Here we describe a new mélange model, using a continuum-mechanical formulation that is computationally feasible for long-term continental Antarctic applications. It is tested in an idealized rectangular channel and calibrated very basically using observed modern conditions in Jakobshavn fjord, West Greenland. The model is then applied to drastic retreat of Antarctic ice in response to warm mid-Pliocene climate. With mélange parameter values that yield reasonable modern Jakobshavn results, Antarctic marine ice still retreats drastically in the Pliocene simulations, with little slowdown despite the huge amounts of mélange generated. This holds both for the rapid early collapse of West Antarctica and for later retreat into major East Antarctic basins. If parameter values are changed to make the mélange much more resistive to flow, far outside the range for reasonable Jakobshavn results, West Antarctica still collapses and retreat is slowed or prevented only in a few East Antarctic basins.
Architectural Exploration and Scheduling Methods for Coarse Grained Reconfigurable Arrays

Coarse Grained Reconfigurable Arrays have emerged, in recent years, as promising candidates to realize efficient reconfigurable platforms. CGRAs feature high computational density, flexible routing interconnect and rapid reconfiguration, characteristics that make them well-suited to speed up execution of computational kernels. A number of designs embodying the CGRA concept have been proposed in literature, most of them presenting specific, ad-hoc solutions. This thesis instead takes a more general approach, focusing on techniques that can be adapted to arrays having different architectural features, enabling experimental comparisons and exploration of the design space. At the hardware level, a template virtual prototype, named Expression Grained Reconfigurable Array, is introduced. Instances can be derived from the template at design time, varying the architecture structure as well as the characteristics of its different blocks. Presented design space explorations include the search of an efficient multi-ALU structure to be used as computational cell and exploration of heterogenous elements to support parallel execution of whole kernels. EGRA instances are defined at the RTL level. This feature makes it possible to simulate their behavior employing a digital simulation environment. The thesis illustrates a co-simulation framework to evaluate whole applications compiled for EGRA-accelerated systems, taking into account the impact of non-kernel code and reconfiguration overhead. Success of an architecture paradigm strongly depends on the availability of automated strategies to map applications onto it. The thesis tackles mapping issues at two levels: it proposes a recursive algorithm to partition kernels according to available hardware resources, and it presents a novel modulo scheduling framework, which considers combinatorial chains of computation and routing operations. The thesis touches the areas of architectural exploration, automated kernel mapping and system integration of CGRAs, providing a quantitative analysis of the efficiency of proposed methods over State of the Art ones. It also outlines a comprehensive hardware/software coexploration framewok, able to investigate opportunities and pitfalls of coarse grained reconfiguration.
SEARE: A System for Exercise Activity Recognition and Quality Evaluation Based on Green Sensing

Green-computing technology and energy-saving design have become the focus of research in various fields in recent years. As a ubiquitously deployed infrastructure, WiFi can be considered as a platform for green sensing, and a plethora of efforts have been made in WiFi-based passive detection recently. However, little work has been done on the exercise activity recognition. In this paper, we propose SEARE, a novel energy-efficient solution using WiFi for exercise activity recognition. It is prototyped by fine-grained CSI extracted from existing commercial WiFi devices. Different from traditional features like mean or max value exploited in previous activity recognition works, involving either time or frequency information, we select CSI-waveform shape as activity feature, which contains the information from both of these two domains. A series of de-noise methods are designed, including low-pass, PCA, and median filtering, where PCA can remove the in-band noise that traditional low-pass filters fail to do. Finally the evaluation of activities quality can be made. Extensive experimental result validates the great performance of SEARE in both LOS and NLOS scenarios, with average recognition accuracies of 97.8 and 91.2 percent respectively.
An improvement powerlifters’ training process with the use of information technology

Purpose: improving the training process powerlifters’ with use of information technologies. Material & Methods: analysis and generalization of the literary sources and data of the Internet, pedagogical observations and the method of information modeling. Results: computer program "Bench Press" has been developed for the organization and management of the training process. Conclusion: developed an innovative software product that allows you to plan training loads based on the proposed sets of exercises.
Traffic Signal Optimization under Uncertain Traffic Demands

The paper presents a traffic signal optimization model based on Cell Transmission Model (CTM) under uncertain traffic demands, and then a genetic algorithm is used to optimize the traffic signal settings at an isolated intersection. The simulation results show that the proposed model can effectively reflect the impact of the traffic flow fluctuation under various traffic conditions (non-saturated, over-crowding and saturation of traffic flow), and can obtain the optimal traffic signal settings at an isolated intersection.
Perception of Electrical Engineering UTM students on task-based speaking activities in fostering students communication in English

Salah satu isu utama di dalam pembelajaran Inggeris sebagai bahasa kedua adalah pelajar mengabaikan kepentingan berkomunikasi dalam Bahasa Inggeris kerana kelemahan mereka dalam menguasai bahasa tersebut. Kajian ini telah menggunakan tinjauan soal selidik ke atas pelajar kejuruteraan elektrik Universiti Teknologi Malaysia dengan tujuan mengetahui perspektif pelajar terhadap aktiviti lisan berdasarkan tugas (task-based speaking activities) dalam menggalakkkan komunikasi dalam Bahasa Inggeris. Kajian ini juga ingin mengenalpasti jenis-jenis aktiviti lisan berdasarkan tugas (task-based speaking activities) yang paling menggalakkan komunikasi dalam Bahasa Inggeris. Jenis-jenis aktiviti tersebut adalah penyelesaian masalah, jurang informasi, dan perkongsian pengalaman atau perasaan. Keputusan kajian menunjukkan bahawa kebanyakan pelajar bersetuju aktiviti lisan berdasarkan tugas (task-based speaking activities) telah memberi mereka peluang dan mempertingkatkan kemahiran berkomunikasi di dalam Bahasa Inggeris. Dapatan kajian juga telah menunjukkan beberapa jenis-jenis aktiviti lisan berdasarkan tugas (task-based speaking activities) yang menggalakkan komunikasi dalam Bahasa Inggeris. Di akhir kajian, beberapa cadangan aplikasi di masa depan dalam pengajaran Bahasa Inggeris telah dikemukakan.
Collusion Attacks on Browser Extensions Revealing hidden extensions colluding against the user

Browser extensions have been created to extend and enhance web browsers in order to improve the user experience. Because of this, browser extensions can access a range of different resources that pose a great privacy risk for users. These sensitive resources include users’ browser history, passwords and banking information. Therefore browser extensions have become a great source of interest for those with malicious intent. In order to obscure the intent behind a browser extension, a set of extensions can be created that when analysed individually does not raise any suspicion. However, by analysing the entire set of extensions, a relationship between each extension can be revealed. Namely, each extension is extracting user information under different sets of permissions, and relaying this data to a common external server. Such extensions are said to be colluding, and possibly performing a collusion attack. This form of attack is the focus of this research paper. We propose a method for downloading and performing static analysis of the collected browser extensions. The static analysis is based on regular expressions and defined to match and extract domain names and IP addresses from the downloaded browser extensions. In order to discover domains or IP addresses that are malicious, Recorded Future’s threat intelligence is used to provide classification and information behind each classification. Recorded Future collects data from technical sources, open sources and closed sources. By combining their machine learning and natural language processing, Recorded Future can identify, classify and predict events. In this work, over 250,000 Mozilla Firefox and Google Chrome extensions have been analysed by our proposed method and as a result, 1037 browser extensions have been found to be possibly colluding. Recorded Future classified 131 domains as Malicious.
The Scored Society: Due Process for Automated Predictions

Big Data is increasingly mined to rank and rate individuals. Predictive algorithms assess whether we are good credit risks, desirable employees, reliable tenants, valuable customers — or deadbeats, shirkers, menaces, and “wastes of time. ” Crucial opportunities are on the line, including the ability to obtain loans, work, housing, and insurance. Though automated scoring is pervasive and consequential, it is also opaque and lacking oversight. In one area where regulation does prevail — credit — the law focuses on credit history, not the derivation of scores from data. Procedural regularity is essential for those stigmatized by “artificially intelligent” scoring systems. The American due process tradition should inform basic safeguards. Regulators should be able to test scoring systems to ensure their fairness and accuracy. Individuals should be granted meaningful opportunities to challenge adverse decisions based on scores miscategorizing them. Without such protections in place, systems could launder biased and arbitrary data into powerfully stigmatizing scores.