Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of Modified Adaptive Heuristic Critic Algorithm for Novel Scheduling Mechanism in Packet-Switched Networks

In this paper a novel scheduling algorithm of packet selection in a switch node for transmission in a network channel, based on Reinforcement Learning and modified Adaptive Heuristic Critic is introduced. A comparison of two well known scheduling algorithms: Earliest Deadline First and Round Robin shows that these algorithms perform well in some cases, but they cannot adapt their behavior to traffic changes. Simulation studies show that novel scheduling algorithm outperforms Round Robin and Earliest Deadline First by adapting to changing of network conditions.
Deixis, Grammar, and Culture

Many linguists have believed that there is no connection between culture and language structures. This study reviews some of the literature supporting vocabulary connections, hypotheses for other connections, and critical views of this type of hypothesis. Precisely such a connection is developed employing a functional view of language and grammaticization principles. Using a world-wide probability sample of forty-nine languages, an association between culture and the grammatical coding of deictics is tested and statistically found to be corroborated to a very significant extent. Suggestions are included on how some of the concepts used and developed in this study might be extended.
Seguridad en sistemas distribuidos federados

El trabajo objeto del presente articulo se desarrolla en el Laboratorio de Investigacion en Sistemas Distribuidos (LISiDi) del Departamento de Ciencias e Ingenieŕia de la Computacion de la Universidad Nacional del Sur. La ĺinea de investigacion presentada es parte de los Proyectos “Automatizacion de la Deteccion de Intrusos a partir de Poĺiticas de Seguridad” (24/ZN14) dirigido por el Mag. Lic. Javier Echaiz, y “Computacion Distribuida de Alto Rendimiento y Disponibilidad” (24/N024) dirigido por el Mag. Ing. Jorge Ardenghi. Ambos proyectos son financiados por la Secretaria General de Ciencia y Tecnoloǵia de la Universidad Nacional del Sur, y se encuentran acreditados por la Universidad Nacional del Sur, Bahia Blanca.
Debugging and repair of description logic ontologies.

In logic-based Knowledge Representation and Reasoning (KRR), ontologies are used to represent knowledge about a particular domain of interest in a precise way. The building blocks of ontologies include concepts, relations and objects. Those can be combined to form logical sentences which explicitly describe the domain. With this explicit knowledge one can perform reasoning to derive knowledge that is implicit in the ontology. Description Logics (DLs) are a group of knowledge representation languages with such capabilities that are suitable to represent ontologies. The process of building ontologies has been greatly simplified with the advent of graphical ontology editors such as SWOOP, Protege and OntoStudio. The result of this is that there are a growing number of ontology engineers attempting to build and develop ontologies. It is frequently the case that errors are introduced while constructing the ontology resulting in undesirable pieces of implicit knowledge that follows from the ontology. As such there is a need to extend current ontology editors with tool support to aid these ontology engineers in correctly designing and debugging their ontologies. Errors such as unsatisfiable concepts and inconsistent ontologies frequently occur during ontology construction. Ontology Debugging and Repair is concerned with helping the ontology developer to eliminate these errors from the ontology. Much emphasis, in current tools, has been placed on giving explanations as to why these errors occur in the ontology. Less emphasis has been placed on using this information to suggest efficient ways to eliminate the errors. Furthermore, these tools focus mainly on the errors of unsatisfiable concepts and inconsistent ontologies. In this dissertation we fill an important gap in the area by contributing an alternative approach to ontology debugging and repair for the more general error of a list of unwanted sentences. Errors such as unsatisfiable concepts and inconsistent ontologies can be represented as unwanted sentences in the ontology. Our approach not only considers the explanation of the unwanted sentences but also the identification of repair strategies to eliminate these unwanted sentences from the ontology.
Japanese named entity extraction using support vector machine

In this paper, we propose a method for Japanese named entity (NE) extraction using Support Vector Machines (SVM). The generalization performance of SVM does not depend on the size of dimensions of the feature space, even in a high dimensional feature space, such as named entity extraction task using lexical entries, part-of-speech tags and character types of words as the primitive features. Furthermore, SVM can induce an optimal classifier which considers the combination of features by virtue of polynomial kernel functions. We apply the method to IREX NE task using CRL Named Entities data. The cross validation result of the F-value being 83 shows the effectiveness of the method.
Susceptibility Weighted Imaging in MRI: Basic Concepts and Clinical Applications

Description: This book presents the first in–depth reference to discuss Susceptibility Weighted Imaging for students and professionals Within the pages of this book, the reader will find comprehensive coverage of the major concepts that underlie the origins of susceptibility weighted imaging (SWI) in magnetic resonance imaging (MRI) and its wide range of applications. This book provides readers a thorough understanding of the technique now commonly called SWI, a major enhancement of traditional MRI with the power to produce high–resolution images that are exquisitely sensitive to blood products and iron. Since its inception, SWI has become a powerful tool for investigating a number of important clinical aspects of neuro–imaging, especially the diagnosis and pathophysiology of traumatic brain injury, the detection of acute hemorrhagic stroke, and the detection of microbleeds in dementia. Edited by the originators of SWI, this groundbreaking text is the definitive resource on this critically important technology. Featuring contributions from the top leaders in the science and clinical use of the modality, the book: Introduces the fundamentals of SWI Presents an even balance between the technical aspects and its clinical applications Explains how to image brain tumors, cerebral microbleeds, and hemorrhage as well as many other clinical applications Explains how to quantify iron content for diseases such as multiple sclerosis, Parkinson's disease, and other neurodegenerative diseases Introduces the use of SWI in visualizing the vessel wall Covers the use of SWI at ultra–high magnetic fields Introduces the important concept of susceptibility mapping as the next generation of SWI Includes over 100 high–quality images and tables This reference also covers more advanced topics, from improved contrast in MRI of the midbrain using SWI to functional susceptibility weighted MRI, automated vein segmentation and lesion detection, rapid acquisition methods, and more. Suitable for all levels of experience, Susceptibility Weighted Imaging in MRI is the ideal source for neuroradiologists, radiologists, imaging and medical physicists, cardiologists, oncologists, biochemists, and students who want authoritative information on the basic elements and practical applications of this exciting new medical imaging technique.
Development of SEROPI as a wheel-based humanoid robot

Abstract Many researchers are studying on humanoid robots in all over the world. However the humanoid robots are still limited in doing works like picking up objects on the ground or moving rapidly. In this study, a humanoid robot based on the wheel-driving was developed. It can operate with a human working area keeping the stability. Also, the developed robot can take up the object on the floor since it has knee(1DoF) and waist(3DoF), and do service quickly and steadily. The hardware and software structure and algorithms of the developed robot, SEROPI are introduced in this paper. Keywords : Humanoid Robot, Wheel-base, SEROPI 1. 서 론 [5][6]10년여 전부터 우리나라에서도 비 산업용 로봇에 대한 관심이 커지고 연구 개발에 대한 투자도 늘어나고 있다. 투자된 금액만큼 결과물도 많이 나오고 있으며 관련 산업의 분위기도 활성화 되어 로봇을 하겠다는 기업들도 우후죽순처럼 늘어나고 있는 실정이다 [1] . 하지만 그러한 연구 개발에 대한 결과물들의 실용화를 살펴보면 많이 미흡한 것이 사실이다. 개인용 서비스 로봇 분야만 보면 바퀴기반의 로봇 중 청소용 로봇과 교육용 로봇, 경비 로봇이 일부 제품화 되고 있을 뿐이다. 대중매체의 영향으로 소비자의 로봇에 대한 기대치는 매우 높아져 있지만, 이 기대치에 로봇 기술은 아직 미치지 못하고 있고, 연구 개발에 비해 실용화에 대한 노력은 많이 부족하였다. 로봇에 대한 지원과 대중적인 관심을 지속시키기 위해서는 원천 기술 개발도 중요하지만 현재 개발되어 있는 기술을 이용하여 실용화하는 연구에도 많은 노력을 기울여야 한다. 대표적인 서비스 로봇 중 하나인 2족형 인간형 로봇
Evaluación de metodologías ágiles para desarrollo de software

para Desarrollo de Software Karla Mendes Calo, Elsa Estevez, Pablo Fillottrani Dpto. de Ciencias e Ingeniería de la Computación, Universidad Nacional del Sur Av.Alem 1253, (8000) Bahia Blanca, Argentina +54 291 459-5135 Comisión de Investigaciones Científicas de la Provincia de Buenos Aires, Argentina {kmca,ece,prf}@cs.uns. edu.ar RESUMEN Las metodologías de desarrollo ágiles permiten a los grupos de desarrollo producir software de manera iterativa e incremental. De esta manera facilitan la introducción de cambios a los requerimientos durante el proceso de desarrollo. El objetivo de este trabajo es presentar una línea de investigación sobre el uso de metodologías ágiles, focalizándose en el estudio de un marco de evaluación para dichas metodologías. Se espera que el marco de evaluación propuesto permita evaluar en qué medida las metodologías de desarrollo cumplen con los postulados y principios declarados por el Manifiesto Ágil. Asimismo, se pretende que el marco sirva como herramienta para facilitar la toma de decisión al momento de seleccionar una metodología.
Detecting object in the dynamic background from the noisy image in visual surveillance

Detecting an object from a dynamic background is a challenging process m computer vision and pattern matching research. The proposed algorithm identifies moving objects from the sequence of video frames which contains dynamically changing backgrounds in the noisy environment. In connection with our previous work, here we have proposed a methodology to perform background subtraction and modernized from moving vehicles in traffic video sequences that combines statistical assumptions of moving objects using the previous frames in the dynamically varying noisy situation. For that, a binary moving objects hypothesis mask is constructed. Then, Kalman filter is utilized for the amalgamation of current background. Shadow and noise removal algorithms are proposed to operate at the lattice which identifies object-level elements. The results of post-processing can be used to detect object more efficiently. Experimental results and comparisons using real data demonstrate the pre-eminence of the proposed approach.
The Effect of Social Presence and Affection on Participation in the UCC Service

In this study, we investigate the effect of social presence and affection on the UCC service participation. We have conducted a face-to-face survey along with an e-mail survey and obtained a total of 329 responses. The findings show that social presence has a significant impact on pleasure and arousal. Social presence in turn show a positive impact on participation in the UCC service. Meanwhile, pleasure shows a negative effect on the UCC service participation, while arousal very strongly and positively affects the UCC service participation. The significance of this study can be found in that it empirically demonstrates the importance of social presence and affection in promoting the UCC service.
Essays on autoregressive conditional heteroskedasticity

This paper discusses general issues related to estimation of multivariate GARCH models. The estimation is a numerical procedure and therefore understanding the model at hand and the algorithms used, as well as recognizing potential numerical problems encountered along the way, are of tantamount importance in order to produce reliable model estimates. Special emphasis is put on the computational aspects, such as numerical methods, software programs, use of object oriented programming, and efficiency of computer code.
Characterization of a Phased Array Feed Model

CHARACTERIZATION OF A PHASED ARRAY FEED MODEL David Jones Department of Electrical and Computer Engineering Master of Science Creating accurate software based models of phased array feeds (PAFs) is one of many steps to successfully integrating PAFs with current and future radio telescopes, which is a goal of many groups around the globe. This thesis characterizes the latest models of a 19 element hexagonal PAF of dipoles used by the BYU radio astronomy research group and presents comparisons of these models with experimental data obtained using a prototype array. Experiments were performed at the NRAO site in Green Bank, West Virginia, and utilized the outdoor antenna test range and 20 meter radio telescope. Accurate modeling of the PAF requires modeling the signal and noise characteristics of the array, which is a computationally large problem. It also requires accurate modeling of the noise contribution of the receivers connected to the coupled array, which is something that has only recently been understood. The modeled and measured element receive patterns, array impedance matrix, signal and noise correlation matrices, and efficiencies and sensitivities of the PAF are compared and promising levels of agreement are shown. Modeled sensitivity is 30 to 46% larger than measured.
Rendimiento del algoritmo AES sobre arquitecturas de memoria compartida

Resumen Actualmente AES (Advanced Encryption Standard) es uno de los algoritmos de cifrado simétrico más utilizados para encriptar información. El volumen de datos sensibles que se trasmiten en las redes se incrementa constantemente y cifrarlos puede requerir un tiempo significativo. Por lo anterior, es importante adaptar este algoritmo para aprovechar la potencia de cómputo de las arquitecturas paralelas emergentes. En este trabajo presentamos un análisis del rendimiento de AES sobre diversas arquitecturas de memoria compartida (multicore Intel E52695v4, Xeon Phi 7230 y GPU Nvidia GTX 960), para datos de entrada de distinto tamaño. Los resultados revelan que la GPU es la mejor alternativa para cifrar datos de entrada que no superan los 32MB. Sin embargo, para un volumen mayor de datos, el multicore alcanza el mejor rendimiento, seguido por el Xeon Phi.
Female High School Biology Students' Biofilm -Focused Learning: the Contributions of Three Instructional Strategies to Patterns in Understanding and Motivation.

This exploratory study examined three instructional strategies used with female high school biology students. The relative contributions o f the strategies to student understanding o f microbiology and motivation in science were analyzed. The science education community targeted underachievement in science by implementing changes in content and practices (NRC, 1996). Research suggested that teachers facilitate learning environments based on human constructivism (Mintzes, Wandersee, & Novak, 1997) that is rooted in meaningful learning theory (Ausubel, Novak & Hanesian, 1978). Teachers were advised to use both visual and verbal instructional strategies (Paivio, 1983) and encourage students to construct understandings by connecting new experiences to prior knowledge. The American Society for Microbiology supports the study of microorganisms because o f their prominence in the biosphere (ASM, 1997). In this study, two participating teachers taught selected microbiology concepts while focused on the cutting edge science o f biofilms. Biology students accessed digitized biofilm images on an ASM web page and adapted them into products, communicated with biofilm researchers, and adapted a professional-quality instructional video for cross-age teaching. The study revealed improvements in understanding as evidenced on a written test; however, differences in learning outcomes were not significant. Other data, including student journal reflections, observations o f student interactions, and student clinical interviews indicate that students were engaged in cutting edge science and adapted biofilm images in ways that increased understanding o f microbiology (with respect to both science content and as a way o f knowing) and motivation. An ASM
Cloud-Induced Uncertainty for Visual Navigation

Abstract : This research addresses the numerical distortion of features due to the presence of clouds in an image. The research aims to quantify the probability of a mismatch between two features in a single image, which will describe the likelihood that a visual navigation system incorrectly tracks a feature throughout an image sequence, leading to position miscalculations. First, an algorithm is developed for calculating transparency of clouds in images at the pixel level. The algorithm determines transparency based on the distance between each pixel color and the average pixel color of the clouds. The algorithm is used to create a dataset of cloudy aerial images. Matching features are then detected between the original and cloudy images, which allows a direct comparison between features with and without clouds. The transparency values are used to segment the detected features into three categories, based on whether the features are located in the regions without clouds, along edges of clouds, or with clouds. The error between features on the cloudy and cloud-free images is determined, and used as a basis for generating a synthetic dataset with statistically similar properties. Lastly, Monte Carlo techniques are used to nd the probability of mismatching.
M2M Communications in LTE Systems

In wide-area applications, low-cost and massive machine to machine (M2M) communications provided bycellular networks will be one main driver for the success of future Internet of Things (IoT) development. The first directconsequence of the proliferation of IoT is that large numbers of devices will produce huge quantities of sporadic data andsignificantly higher capacity of cellular networks will be needed - not in terms of megabits transported, but the numberof machines sustained. In this paper, we will investigate the support of M2M communications in LTE systems. The goalof this paper is to survey how the existing LTE architecture supports M2M traffic in terms of capacity, coverage, andsignaling, assuming a certain usage scenario and traffic pattern. Solutions are suggested for issues that arise whena large amount of M2M traffic is transported over an LTE network. We will show that the capacity and coverage arenot the key issues; instead the signaling is the main bottleneck, especially the ones related to the RACH. Finally, as atypical illustrating example, we will study in detail how Smart Metering application can be supported in LTE systems andinvestigate thoroughly solutions to the key bottlenecks in this paper.
Antecedent Decision Rules of Personal Pronouns for Coreference Resolution

When we extract a representative term from text for information retrieval system or a special information for information retrieval and text milling system, we often need to solve the anaphora resolution problem. The antecedent decision problem of a pronoun is one of the major issues for anaphora resolution. In this paper, we are suggesting a method of deciding an antecedent of the third personal pronouns, such as “he/she/they” to analyze the contents of documents precisely. Generally, the antecedent of the third personal Pronouns seem to be the subject of the current statement or previous statement, and also it occasionally happens more than twice. Based on these characteristics, we have found rules for deciding an antecedent, by investigating a case of being an antecedent from the personal pronouns, which appears in the current statement and the previous statements. Since the heuristic rule differs on the case of the third personal pronouns, we described it as subjective case, objective case, and possessive case based on the case of the pronouns. We collected 300 sentences that include a pronoun from the newspaper articles on political issues. The result of our experiment shows that the recall and precision ratio on deciding the antecedent of the third personal pronouns are 79.0% and 86.8%, respectively.
A Novel Estimating Method of the Gait State and Velocity Control in the Initial Stance Phase for the Intelligent Ankle Foot Orthosis with Compact MR Fluid Brake (i-AFO)

Ankle–foot orthoses (AFOs) are orthotic devices for the disabled people, for example, those suffering from hemiplegia or peroneal nerve palsy, to support the movements of the ankles. We have developed intelligently controllable AFOs (i-AFO) in which the ankle torque is controlled with a compact magnetorheological fluid brake (CMRFB). In this paper, we propose a novel prototype of the i-AFO, in which the sensor system, the build-in CMRFB, the gait estimating method and torque control method were improved from those of the previous prototype. Gait-control tests with the novel i-AFO were performed for a patient with flaccid paralysis of his ankles. According to the experimental results, the estimation of the gait state and the velocity control in the initial stance phase were concurrently carried out.
Effects of supervised and unsupervised categorization on visual and haptic object representations

The way we perceive objects can be shaped by how we learn to categorize them, such as increasing the saliency of diagnostic dimensions, but most evidence of this comes from unimodal studies in vision. Does category learning have comparable effects when objects are perceived using touch? In this study, subjects learned to categorize a set of 25 novel, 3D objects which varied parametrically in shape and texture, using either vision or touch, and then provided similarity ratings on the objects. Multidimensional scaling (MDS) was used to construct a perceptual stimulus space and estimate the relative importance of shape and texture dimensions for each subject. The effects of categorization were quantified by comparing dimension weights when similarity ratings were performed 1) without prior categorization experience, 2) after an unsupervised categorization task, and 3) after a supervised task in which subjects learned groupings based on texture. In preliminary results (5 subjects per condition), significant differences between unimodal dimension weights found in condition 1 (shape dominating for vision; shape and texture equally weighted for touch) were not observed in conditions 2 and 3. These findings suggest that externally as well as internally-guided categorization could serve as a mechanism for reducing initial differences in unimodal representations of novel objects.
Evaluating the Curvature Analysis as a Key Feature for the Semantic Description of Architectural Elements

The recent developments in the ﬁelds of photogrammetry and laser scanning, have made possible mass acquisitions of heritage artifacts with a particularly high level of geometric accuracy. A processing of the digital model will be necessary to isolate some characteristics in order to carry on an analysis of the architectural object. In this poster, the potentialities of the curvature maps, extracted from digital acquisitions, are deﬁned to conduct the study on the morphology of architectural elements. The current work focuses on the technical and theoretical issues that will ultimately result in an average surface signature. This will allow to identify the degree of remoteness of each attribute.