Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Prediction of Crashback Performance of Controllable Pitch Propellers

The prediction of propeller performance in crashback conditions with numerical methods is challenging due to the highly unsteady flow field, which is dominated by largescale separation and recirculation regions. For a controllable pitch propeller (CPP), the computations should be carried out for a wide range of pitch angles. Reynolds Averaged Navier-Stokes (RANS) methods are not capable of capturing the most complex flow conditions. Hence, more precise methods like Detached Eddy Simulations (DES) should be applied. The high computational effort in conjunction with the application of these methods demands a strong limitation of the number of investigated operation points. In this paper, the computed open water characteristics curves of a CPP are compared with the experimental results. Thereby, the ranges of the open water diagram are identified, where the RANS methods yield unsatisfying results. In these ranges, DES simulations are carried out to capture the flow details on a propeller in crashback operation condition. DES results are shown to be in good agreement with the experimental data of the thrust and torque coefficient.
Input Clips CNN Features Clip Representation How many times eyes ?

How does machine learn to reason about the content of a video in answering a question? A Video QA system must simultaneously understand language, represent visual content over space-time, and iteratively transform these representations in response to lingual content in the query, and finally arriving at a sensible answer. While recent advances in textual and visual question answering have come up with sophisticated visual representation and neural reasoning mechanisms, major challenges in Video QA remain on dynamic grounding of concepts, relations and actions to support the reasoning process. We present a new end-to-end layered architecture for Video QA, which is composed of a question-guided video representation layer and a generic reasoning layer to produce answer. The video is represented using a hierarchical model that encodes visual information about objects, actions and relations in space-time given the textual cues from the question. The encoded representation is then passed to a reasoning module, which in this paper, is implemented as a MAC net. The system is evaluated on the SVQA (synthetic) and TGIF-QA datasets (real), demonstrating state-of-the-art results, with a large margin in the case of multi-step reasoning.
Unconstrained Face Recognition

The human face is the most well-researched object in computer vision, mainly because (1) it is a highly deformable object whose appearance changes dramatically under different poses, expressions, and, illuminations, etc., (2) the applications of face recognition are numerous and span several fields, (3) it is widely known that humans possess the ability to perform, extremely efficiently and accurately, facial analysis, especially identity recognition. Although a lot of research has been conducted in the past years, the problem of face recognition using images captured in uncontrolled environments including several illumination and/or pose variations still remains open. This is also attributed to the existence of outliers (such as partial occlusion, cosmetics, eyeglasses, etc.) or changes due to age. In this chapter, the authors provide an overview of the existing fully automatic face recognition technologies for uncontrolled scenarios. They present the existing databases and summarize the challenges that arise in such scenarios and conclude by presenting the opportunities that exist in the field.
DANCE: A Framework for the Distributed Assessment of Network Centralities

The analysis of large-scale complex networks is a major challenge in the Big Data domain. Given the large-scale of the complex networks researchers commonly deal with nowadays, the use of localized information (i.e. restricted to a limited neighborhood around each node of the network) for centrality-based analysis is gaining momentum in the recent literature. In this context, we propose a framework for the Distributed Assessment of Network Centralities (DANCE) in complex networks. DANCE offers a single environment that allows the use of different localized centrality proposals, which can be tailored to specific applications. This environment can be thus useful given the vast potential applicability of centrality-based analysis on large-scale complex networks found in different areas, such as Biology, Physics, Sociology, or Computer Science. Since the localized centrality proposals DANCE implements employ only localized information, DANCE can easily benefit from parallel processing environments and run on different computing architectures. To illustrate this, we present a parallel implementation of DANCE and show how it can be applied to the analysis of large-scale complex networks using different kinds of network centralities. This implementation is made available to complex network researchers and practitioners interested in using it through a scientific web portal.
Discussion Paper Series On the Effectiveness of SB 1070 in Arizona

We investigate the effectiveness of Arizona’s omnibus immigration law SB1070, which made it a misdemeanor crime for an alien to not carry proper documentation and asked police to determine the immigration status of any person suspected of being an illegal alien during a lawful stop. We find that SB1070’s enactment coincided with the stalling to slight recovery of the share of non-citizen Hispanics in Arizona three years after the enactment of an employment verification mandate to all employers. Yet, its effectiveness in reducing the share of likely unauthorized immigrants has been minimal and questions the merit of the law.
Complete exchange in 2D meshes

We propose a new algorithm called Cyclic Exchange for all-to-all personalized exchange in a 2D mesh. This algorithm fully interleaves communication in both dimensions of a mesh. We have compared by simulation the performance of this algorithm with that of the Quadrant Exchange method previously proposed by S.H. Bokhari and H. Berryman (1992). The results show that the new algorithm is faster for the range of machine size, problem size and startup/transmission ratio. <<ETX>>
A State Space Model of a Visuomotor Rotation Experiment

We present a new linear time-invariant (LTI) state space model to explain adaptation in human motor control. We focus on a visuomotor rotation experiment in which a human subject must rapidly move a cursor on a horizontal screen through a target disk. The hand itself is occluded from view, while the cursor is rotated relative to the hand angle by an amount of r degrees. Our model is based on the application of well-known techniques from control theory, in particular regulator theory. The model is simple, yet it reveals a plausible architecture for the high level computations underlying human motor control, including a representation of the internal model. It is a two state LTI model, where each state has a physical interpretation
THERMOHYDRODYNAMIC BUBBLY LUBRICATION ANALYSIS OF HIGH SPEED JOURNAL BEARING

The influence of aerated oil on high-speed journal bearing is numerically examined by classical thermohydrodynamic lubrication theory coupled with analytical models for viscosity and density of air-oil mixture in fluid-film bearing. Convection to the walls, and mixing with supply oil and re-circulating oil are considered. The considered parameters for the study of bubbly lubrication are oil aeration level and air bubble size. The results show that air bubbles can more clearly bring on the increasing load capacity under high-speed operation of a plain journal bearing than previous normal speed operation.
VALIDATING DESIGN METHODS & RESEARCH: THE VALIDATION SQUARE

Validation of engineering research is typically anchored in the scientific inquiry tradition that is based primarily on logical induction and / or deduction. Since much engineering research is based on mathematical modeling, this kind of validation has worked - and still works - very well. There are, however, other areas of engineering research that rely on subjective statements as well as mathematical modeling, which makes this type of validation problematic. One such area is that of design methods within the field of engineering design. In this paper, we explore the question of how one validates design research in general, and design methods in particular. Being anchored in the scientific inquiry tradition, research validation is strongly tied to a fundamental problem addressed in epistemology, namely, what is scientific knowledge and how is new knowledge confirmed? Thus, we first look to epistemology for answers to why an approach solely based on 'formal, rigorous and quantifiable' validation constitutes a problem, and for an augmented approach to research validation. We then propose the 'Validation Square' which we validate by testing its internal consistency based on logic in addition to testing its external relevance based on its usefulness with respect to a purpose. We recognize that no one has the complete answer to the question we pose. To help us converge on an answer to these questions we "think aloud" and invite you to join us in doing the same. It is our hope that in so doing we, the members of this design research community, will all be the richer for it .
Man system interface based on automatic speech recognition: integration to a virtual control desk

This work reports the implementation of a man-system interface based on automatic speech recognition, and its integration to a virtual nuclear power plant control desk. The later is aimed to reproduce a real control desk using virtual reality technology, for operator training and ergonomic evaluation purpose. An automatic speech recognition system was developed to serve as a new interface with users, substituting computer keyboard and mouse. They can operate this virtual control desk in front of a computer monitor or a projection screen through spoken commands. The automatic speech recognition interface developed is based on a well-known signal processing technique named cepstral analysis, and on artificial neural networks. The speech recognition interface is described, along with its integration with the virtual control desk, and results are presented.
DEVELOPING AN ATTACK SIGNATURE STANDARD

A lot of factors contribute to grant access to aggressors into a system, which results in further stealing or disruption of private information. The security, possession and handling of information have become an aspect of crucial importance in the whole society. Piracy acts, intrusion attempts, consummate invasions and break-in actions have occurred frequently. These internal and external computer network attacks occur according to standards and follow a set of subsequent steps, allowing the establishment of patterns, which is the basis of signature analysis made by intrusion detection systems. This work presents a new attack signature proposal to be applied on intrusion detection systems. The AISF (ACME! Intrusion Signature Format) model is built upon XML technology and works on intrusion signatures handling and analysis, from storage to manipulation. Using a standard model, the intrusion signatures process and analysis become a clear and standardized process.
Named Entity Recognition for Punjabi Language Text Summarization

Entity Recognition (NER) is used to locate and classify atomic elements in text into predetermined classes such as the names of persons, organizations, locations, concepts etc. NER is used in many applications like text summarization, text classification, question answering and machine translation systems etc. For English a lot of work has already done in field of NER, where capitalization is a major clue for rules, whereas Indian Languages do not have such feature. This makes the task difficult for Indian languages. This paper explains the Named Entity Recognition System for Punjabi language text summarization. A Condition based approach has been used for developing NER system for Punjabi language. Various rules have been developed like prefix rule, suffix rule, propername rule, middlename rule and lastname rule. For implementing NER, various resources in Punjabi, have been developed like a list of prefix names, a list of suffix names, a list of proper names, middle names and last names. The Precision, Recall and F-Score for condition based NER approach are 89.32%, 83.4% and 86.25% respectively.
The prediction and analysis of protein structure using specialized database techniques

The subject of this thesis is the use of specialized database methods to analyze and predict protein structure. I have developed techniques for extracting and organizing the wealth of information in the protein structure and sequence databases. More specifically, the goal has been to identify and correlate sequence patterns with structural patterns. This approach has been applied to three general problems. First, the exhaustive pairwise structural comparison of known protein domains has led to the identification of shared structural topologies at the subdomain level (SSTs). I have provided evidence that these recurring substructures represent meaningful structural units and may form the basis of a new taxonomy for describing protein architecture. Secondly, I have used a nearest-neighbor classifier to predict secondary structure to an accuracy of 68% among the best results to date. Moreover, I have devised a scheme to assign an a priori confidence level to each prediction, thereby distinguishing the more reliable predictions from the less reliable. The third project has been the development of an iterative procedure for predicting the fold of a protein. This method termed Iterative Template Refinement (ITR) involves the construction of templates combining structure-based and sequence-based information and employs an iterative search procedure to detect related proteins and to add them sequentially to the templates. On 6 test cases, ITR has demonstrated excellent sensitivity and selectivity. Thesis Supervisor: Eric S. Lander Title: Professor of Biology
Une méthode pour le prétraitement et le calcul de matrices de crosstalk pour des images couleur issues d'une caméra tri-CCD

This work is as a tool within the framework of the 3D reconstruction using a structured light projection associated with a 3CCD camera. The principle is easy: it is necessary to lay out a 3CCD camera and a LCD projector like a traditional stereovision system, in front of the studied scene. The use of a structured light raises a lot of ambiguities compared to a stereovision system with two cameras. However, the use of the color to code projection reduces the use of the system to white or pale objects. To determine the color and the 3D reconstruction of the object at the same time, it is necessary to have perfectly cleaned color images. We thus will describe a method of pre-processing of the color images from the 3CCD camera used. The images thus treated can be used in the color model which we will follow to give information of color of structured light to raise ambiguities of matching, and the color of the scene at the considered points.
Improving adaptive honeypot functionality with efficient reinforcement learning parameters for automated malware

ABSTRACT This paper presents an intelligent honeypot that uses reinforcement learning to proactively engage with and learn from attacker interactions. It adapts its behaviour for automated malware to optimise the volume of data collected. Malware employs highly automated methods to create a global botnet. These automated methods are used to self-propagate and compromise hosts. Honeypots have been deployed to capture these automated interactions. Machine-learning techniques have previously been employed to retrospectively model botnet interactions. We develop a honeypot that uses reinforcement learning with a specific state action space formalism to interact with automated malware. It compares functionality with similar intelligent honeypots which target human interaction. It also demonstrates that datasets collected from an intelligent honeypot deployment are considerably larger than standard high interaction deployments and existing adaptive honeypots.
Construction of Related Terms Thesauri from the Web

本論文ではWeb上の情報を利用し, 自動的に関連語のシソーラスを構築する手法を提案する. 検索エンジンを利用し, x2値による語の関連度の指標を用い, 従来のWebを用いた関連度の指標の問題点を解決する. また, 新しいクラスタリング手法であるNewman法を用いて語のネットワークをクラスタリングすることで, 従来手法より適切に関連語を同定する. コーパスおよび既存のシソーラスから生成した関連語正解セットを用い, 提案手法の効果についての検証を行う.
VALIDATION OF A NUMERICAL SIMULATION OF THE COMBUSTION OF NATURAL GAS IN A CYLINDRICAL CHAMBER

This work presents the results of a numerical simulation of the combustion of natural gas and atmospheric air in an axissymmetrical cylindrical chamber. The simulations is performed assuming staged non pre-mixture combustion process in two global steps, where the fuel is injected through a central circular duct, and air is injected through an annular external duct, both in the same plane. The mass, momentum, energy and chemical species conservation equations are solved. Thermal radiation in the interior of the chamber is modeled by the zonal method, in which the wavelength dependence of the gas properties is resolved by the Weighted-Sum-of-Gray-Gases-Model (WSGGM). Turbulent flow is described by the k ε − model. For the chemical reactions, the Eddy Breakup-Arrhenius model is employed. The resulting differential governing equations are solved by the Control Volume approach. The results include all the flow regions, the chemical species distributions, the velocity fields and the net heat transfer by radiation.
Scaling Genetic Programming to Challenging Reinforcement Tasks through Emergent Modularity

xi List of Abbreviations Used . xii Chapter
Lens-Antenna Coupled Superconducting Hot-Electron Bolometers for Terahertz Heterodyne Detection and Imaging

Both astronomic observation and atmospheric remote sensing in the terahertz (THz) frequency range (0.1-10 THz) have driven the demand for highly-sensitive mixers and receivers [1-4]. Interstellar molecule spectrum information obtained through those THz receivers provides the basic clues to understand the formation of the universe. Also, the observation and monitoring of the earth’s own atmosphere may allow strategies to be developed to address issues such as global warming or ozone depletion [5, 6]. Other terahertz radiation detection applications include plasma diagnostics [7], military radar and radiometry [8], chemical spectroscopy and analysis [9], bio-particle reorganizations [10, 11], security screening and terahertz imaging [12-14].
Performance Status of Public Elementary and Secondary Schools in the District of San Simon , Pampanga : An Analysis

AbstractPerformance Status of schools reflects the kind of teachers and administrators that the schools have. This research used the mixed evaluation design: qualitative for statistical treatment and descriptive method as in the use of the “Performance Evaluation Instrument” and interviews to determine the relative performance of schools. The respondents of the study included 50 students from each of the thirteen elementary and five secondary schools in San Simon, Pampanga. This study used the SPSS (Statistical Package for the Social Sciences). The salient findings of the study were identified despite the fact that the survey showed satisfactory performance in the elementary and secondary level, the researcher found various gaps in all aspects: teacher’s behavior, facilities, and student’s services. The necessity to remediate and innovate as in the context of Continuous Improvement Program is emphasized. The researcher recommended various program enhancements in the spirit of continuous improvement anchored most especially on Systems Theory and Quality Management Theory in connection to the findings and conclusions to improve the performance status of public elementary and secondary schools in the District of San Simon, Pampanga.
THE RELATIONSHIP BETWEEN INTELLECTUAL CAPITAL , ORGANIZATIONAL LEARNING , AND ORGANIZATIONAL LEARNING : A STUDY OF PE TEACHERS IN TEHRAN *

The purpose of this study was to examine the relationship between intellectual capital, organizational culture, and organizational learning in physical education (PE) teachers. The population of this survey consisted of 1500 PE teacher of which 306 were randomly selected as the sample based on Krejcie and Morgan’s (1970) table. Data were collected using the Intellectual Capital Questionnaire of Bontis (1998), the Organizational Culture Inventory of Robbins (1996), and the Organizational Learning Questionnaire of Neefe and Furst-Bowe (2001). Data were analyzed in SPSS using Kolmogorov-Smirnov test of normality and Spearman correlation. The results showed that there is a significant relationship between intellectual capital and organizational learning. Moreover, organizational culture was significantly associated with organizational learning. Intellectual capital and organizational learning also had a significant effect on the components of organizational learning. Therefore, it be concluded that improving intellectual capital and organizational culture can promote organizational learning. Implications for research and practice are provided.
Information structure marking in Sandawe texts

This article considers data from the Sandawe language (Khoisan, Tanzania) and discusses how information structure is marked in the language. Previous research on Sandawe has mainly been restricted to sentence-level investigations, with discourse being largely ignored. The research presented in this paper is based on a corpus of seven Sandawe texts which provide examples of how two morphemes, the realis pronominal clitic (pc) and the subject focus (sf) marker, are used to mark information structure. In addition to being discourse markers, ­these two morphemes have core grammatical functions, namely, marking the clause type and identifying the subject. Sandawe can thus be cited as a clear example of how languages may exhibit a close relationship between information structure and core grammar.
Working Paper 2014-115 Performance Persistence of Islamic Equity Mutual Funds

The debate over the under-performance or the over-performance of Islamic funds is not over yet. Hence, our literature review exhibits that all the previous works studied the Islamic equity funds without exploring the persistence of their performance, even if this issue is very important to address several questions in financial management. Our article contributes to the current literature by addressing this shortage; we proceed further with the aim of finding any consistency in funds’ performance. Using a sample of 111 Islamic equity funds over the period 2005 to 2011, the study is carried out through applying different performance measures and non-parametric tests of performance persistence over three equal sub-periods. Our measures of performance show that Islamic funds do not constitute a homogenous group, but over the whole period, Malaysian and Saudi Arabian funds perform better. We find evidence that supports non-persistence in performance or rather the persistence of non-performance of Islamic mutual funds during and after the last financial crisis. This raises the question of the management strategies implemented by the banks managing Islamic funds.