Miracle-dz/UniFAR-FTUs huggingface dataset:
Question Answering Practical Report

This report presents an open domain question answering system. The system makes extensive use of various syntactic, semantic knowledges and NLP tools. An initial system based on the relation and argument structure is developed. The issues of the mismatch between qRMRS and aRMRS are addressed. Gate and C&C tools are used to detect the named entity. Question classification use knowledges from WordNet and manual database. Two post-processing filters are imposed to rule out erroneous answers. Finally, a novel semantic similarity measure based on WordNet is applied. In TREC-8, the system produces score 0.634 on training data, and 0.500 on unseen questions.
Dual Pyramid Generative Adversarial Networks for Semantic Image Synthesis

The goal of semantic image synthesis is to generate photo-realistic images from semantic label maps. It is highly relevant for tasks like content generation and image editing. Current state-of-the-art approaches, however, still struggle to generate realistic objects in images at various scales. In particular, small objects tend to fade away and large objects are often generated as collages of patches. In order to address this issue, we propose a Dual Pyramid Generative Adversarial Network (DP-GAN) that learns the conditioning of spatially-adaptive normalization blocks at all scales jointly, such that scale information is bi-directionally used, and it unifies supervision at different scales. Our qualitative and quantitative results show that the proposed approach generates images where small and large objects look more realistic compared to images generated by state-of-the-art methods.
Skin Color-Based Face Detection

In this paper developed and implemented the method for detecting frontal human faces color-based information in images where they appear. Designed a color-based skin classifier to segment human skin regions from non-skin regions. Skin regions are segmented to determine which regions can possibly be determining a frontal human face. Farther on use of template matching to determine if a given skin region represents a frontal human face or not, if it exist while given the coordinates of the face. Experiments with variety of images show that the method proposed here is efficient and useful.
Parenting Characteristics in Native American Families

iii ACKNOWLEDGEMENTS I would like to thank my major adviser, Dr. Maureen Sullivan, for his expertise and mentorship throughout my time at Oklahoma State University. She allowed me a considerable measure of independence on this project, which has been an invaluable professional learning experience. I would also like to express my gratitude to my other committee members, Drs. Their comments and suggestions have been extremely helpful, both with respect to this project, and to my graduate career in general. Further, I would like to thank my fellow lab members for their suggestions regarding the formulation of this project and for assistance with data collection. Finally, I would like to thank my family for their support. My husband, Darrell, has been encouraging throughout this process, as have my father, David Wilburn, and my grandparents, Jack and Doris Wilburn. Their faith in me has truly been invaluable, and I will always be thankful for their patience and love.
Mechanism and Improvement of Direct Anonymous Attestation Scheme

This paper analyzes the implement mechanism of Direct Anonymous Attestation(DAA) scheme,poining out the problems of the DAA scheme.These problems include the breach of anonymity,time expense and authentication between different authentication groups.It also discusses the basic ideas to resolve these problems in some new schemes(including our ongoing research scheme) under development.
Hybrid Approach for Prediction of Cardiovascular Disease Using Class Association Rules and MLP

: In data mining classification techniques are used to predict group membership for data instances. These techniques are capable of processing a wider variety of data and the output can be easily interpreted. The aim of any classification algorithm is the design and conception of a standard model with reference to the given input. The model thus generated may be deployed to classify new examples or enable a better comprehension of available data. Medical data classification is the process of transforming descriptions of medical diagnoses and procedures used to find hidden information. Two experiments are performed to identify the prediction accuracy of Cardiovascular Disease (CVD). A hybrid approach for classification is proposed in this paper by combining the results of the associate classifier and artificial neural networks (MLP). The first experiment is performed using associative classifier to identify the key attributes which contribute more towards the decision by taking the 13 independent attributes as input. Subsequently classification using Multi Layer Perceptrons (MLP) also performed to generate the accuracy of prediction using all attributes. In the second experiment, identified key attributes using associative classifier are used as inputs for the feed forward neural networks for predicting the presence or absence of CVD.
Research on Schemes for Scheduling Video Stream

Scheme for scheduling video stream is one of the key techniques for using I/O bandwidth and network bandwidth effectively. This paper studies several scheduling techniques and analyzes their advantages and disadvantages, then proposes a new patching-based scheme which can support zero- delay VCR replay. Simulation verifies its performances well in user delay and bandwidth use.
Fusion and Perspective Correction of Multiple Networked Video Sensors

FUSION AND PERSPECTIVE CORRECTION OF MULTIPLE NETWORKED VIDEO SENSORS by Christopher E. Neely ADVISOR: Professor John W. Lockwood May, 2004 Saint Louis, Missouri A network of adaptive processing elements has been developed that transforms and fuses video captured from multiple sensors. Unlike systems that rely on endsystems to process data, this system distributes the computation throughout the network in order to reduce overall network bandwidth. The network architecture is scalable because it uses a hierarchy of processing engines to perform signal processing. Nodes within the network can be dynamically reprogrammed in order to compose video from multiple sources, digitally transform camera perspectives, and adapt the video format to meet the needs of specific applications. A prototype has been developed using reconfigurable hardware that collects and processes real-time, streaming video of an urban environment. Multiple video cameras gather data from different perspectives and fuse that data into a unified, top-down view. The hardware exploits both the spatial and temporal parallelism of the video streams and the regular processing when applying the transforms. Reconfigurable hardware allows for the functions at nodes to be reprogrammed for dynamic changes in topology. Hardware-based video processors also consume less power than high frequency software-based solutions. Performance and scalability are compared to a distributed software-based implementation. The reconfigurable hardware design is coded in VHDL and prototyped using Washington University’s Field Programmable Port Extender (FPX) platform. The transform engine circuit utilizes approximately 34 percent of the resources of a Xilinx Virtex 2000E FPGA, and can be clocked at frequencies up to 48 MHz. The composition engine circuit utilizes approximately 39 percent of the resources of a Xilinx Virtex 2000E FPGA, and can be clocked at frequencies up to 45 MHz.
A Novel Edge Extraction Algorithm with Detail Information in Noisy Image

Firstly, the noisy image is filtered by a small scale Gaussian Filter, then a new Large Template Edge Detector is designed in order to get more accurate lead information for the subsequential sub-edge self-reinforces,the edge detector has good performance on accurately locating, suppressing noise and fake edge. Finally, the real edge of noisy image is extracted from the accumulated search trajectories. Experimental results show that the proposed method can extract real edge in noisy image while keeping the image details and outperforms than the classical algorithm.
Aggregation of spatio-temporal and event log databases for stochastic characterization of process activities

Process-aware information systems are typically used to log events (e.g. transaction logs, logistics, healthcare) describing the execution of such processes. The analysis of these logs can provide meaningful knowledge for organizations to improve the quality of their services as well as their efﬁciency [3]. In logistic domains, transportation planning and scheduling are made based on a-priori knowledge about activities. Thus, a proper identiﬁcation and characterization of process activities is of extreme importance. Given the nature of such logistics business processes, the presence of spatio-temporal databases (form global positioning systems) is common.The analysis of spatio-temporal and event logs databases provide different information on the same business processes. Both databases are important for the correct stochastic characterization of process activities. Spatio-temporal data provide accurate information about location and time but uncertainty about which actions occurred. Event logs clearly identify which activities took place but when they are partially human generated, it is not assured that events are logged at the correct time and location. This leads to uncertainty related to the time at which events (recorded by means of user interaction) are logged. By aggregating both types of data, it is possible to reduce the activity recognition uncertainty. Learning patterns of human behaviour from sensor data is extremely important for high-level activity inference [2]. To derive activity logs from low-level event logs, we deﬁne an activity as a ﬁnite sequence of events, over a ﬁnite period of time, where each event
Research on Differential Power Analysis Attack on SMS4 Algorithm

SMS4 algorithm is a block cipher used in WLAN products. In this paper, the differential power analysis attack on SMS4 algorithm is discussed. Based on analyses of the algorithm structure and principles of differential power analysis technologies, an attack method on every byte of round keys is presented. Through this attack, the round keys of the last four rounds of SMS4 can be obtained, and then the 128bit encryption key can be found out. The results of simulation experiments indicate that this attack method is effective and practical on SMS4 round operation. SMS4 algorithm is vulnerable to differential power analysis attacks, and cryptographic devices should be protected to prevent this kind of attacks.
Aligning the foundations of hierarchical statistical machine translation

Statistical machine translation (SMT) plays an important role in the automatic translation of the large and increasing volume of documents that has become globally available. The results of SMT are often still lacking in various aspects including word order. This thesis focuses on the improvement of hierarchical SMT, in particular Hiero. Hiero rules lack nonterminal labels. This gives them little context and makes their combination into full translations poorly coordinated, and strongly dependent on the language model. In this thesis, bilingual labels are added to Hiero rules. These bilingual labels lead to more coherent translations with better word order, as demonstrated by extensive experiments on three language pairs. The proposed labels require no syntactic information, and use only the information from word alignments. This distinguishes them from various types of syntactic labels earlier proposed in the literature. Bilingual labels are based on a newly proposed framework called hierarchical alignment trees (HATs). HATs are bilingual trees that represent the hierarchical translation equivalence structure induced from word alignments. HATs maximally decompose word alignments into phrase pairs, and provide an explicit description of the local reordering taking place within each phrase pair. The last part of the thesis is concerned with the complexity of empirical translation equivalence. Given a word alignment and a grammar, it studies the question what it means for the grammar to cover the word alignment. HATs play a key role in answering this question exactly and efficiently, and are applied to characterize alignment complexity for various language pairs.
Network Communication based on Buffering Queues in VxWorks

Networking is being the developing trend of modern monitoring systems.The quality of the network communication program directly influences the reliability of the monitoring system.In use of VxWorks' good support to multitasks and Network,this paper presents a network communication mode which is based on buffering queues.The principle and process of network-status monitoring are expatiated.The reliability of this communication mode has been validated through experiments.
Sozialisation von Jugendlichen in geschlechtsuntypischen Berufslehren

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Hybrid CPU and GPGPU Volunteer Computing Framework over the Extensible Messaging and Presence Protocol for Prallel Branch and Bound Optimization of Truss Structures

A new fault-tolerant message passing interface framework for a hybrid parallel computing in distributed volunteer-based networks is presented in this paper. It is a new programming core library being able to link together many CPUs and promising General Purpose Graphic Processing Unit (GPGPU) devices over the Internet. We successfully developed a high-level programming interface on the top of wellknown XMPP communication protocol to exchange and synchronize controlling messages among computing processes executed remotely via the Internet on distributed computing clusters. In this short paper, we briefly present the architecture of our fault-tolerant parallel programming framework called XMPP-MPI, together with preliminary results obtained. We conclude this paper with best practices and improvements that will be needed to solve computational problems like presented parallel branch an bound algorithm for topology optimization of truss structures using larger amount of volunteer computing resources.
High-Level Design Flows for VLSI Circuit

Design flows for very-large-scale integration circuit are considered. The problems arising from the realization of the project using top-down and system design methods are highlighted. The technology of an architecture-independent design for computer systems on a chip is suggested. The technology is based on a functional data-flow presentation of the initial algorithms and their subsequent step-bystep transformation at the register transfer level into description of the system being designed. Using methods of formal description and verification allows developers to transfer initial high-level parallel algorithms on topologies of the configurable integrated circuits being developed.
A Teaching Methodology That Works! Organizing A Class

The teaching methodology described in this paper is used extensively by faculty members in the Department of Civil and Mechanical Engineering at the United States Military Academy. The methodology predates both of the authors’ experience at West Point and, indeed, may trace its origins to the earliest years of the Academy’s existence. Though it can hardly be considered new or innovative, the technique is both effective and flexible. It has been used successfully throughout the civil and mechanical engineering curricula, from sophomore-level engineering mechanics courses to senior level design courses. It is highly structured, yet easily adaptable to the needs of individual courses and instructors. Each year, this methodology is taught to new faculty members as part of an intensive five-week new instructor training program. Most new instructors find it so effective that they choose to continue using it for the remainder of their teaching careers. On course critiques and surveys, the vast majority of students rate it as the most effective teaching style they have experienced.
Research on Localization Method for Indoor Autonomous Mobile Robot

Localization is the process of finding the position and orientation of the robot. Reliable localization based on sensors is one of the most fundamental and important tasks for autonomous mobile robots. This paper reviews the relevant indoor autonomous mobile robot localization technologies, introduces the present situation on the research of localization method for autonomous mobile robot. At the same time, some typical internal and foreign research methods were introduced in detail, and presents some general localization methods for indoor autonomous mobile robot especially introduces the map building and pose estimation methods. Finally, with an emphasis on the main problems of localization system and map building for autonomous mobile robot and solutions to them, future trend in this field is pointed out.
Coherent 3D line drawings for stylized animation

Creating hand-drawn animation is traditionally a laborious task, in which artists are highly involved to draw key frames and, thereafter, create inbetween frames from each pair of key frames. Although the development of paperless animation systems and autoinbetween techniques somehow relieves artists’ burden of creating many inbetween frames by hand, artists still have to painstakingly do all key-frame drawings by hand or using a computer. An alternate approach to avoid the laborious manual drawing task is to incorporate automatic feature line extraction from animated 3D models to create 2D animations. Computer-generated lines could be used as initial drawings for artists, where they can further refine or exaggerate lines with personal styles for animation production. This thesis proposes a solution consisting of several techniques and an integrated framework for automatic line extraction in 2D animation. The first technique is a 3D line extraction method to extract lines from 3D triangle mesh models to closely resemble what artists would perceive and draw. The second technique is a method to generate temporally coherent 3D lines from 3D models using innovative hysteresis thresholding. The third technique is a matching algorithm to create correspondence of 3D individual lines (i.e., paths) across a sequence of frames. The second and the third techniques are used for sequencing the extracted lines frame-by-frame into an animation for temporal coherence. Each of the three algorithms is a valued contribution to Non Photorealistic Rendering. Finally, an integrated framework is proposed with a novel interactive tool set for ii artists to create 2D stylized animations by incorporating automatic line extraction from animated 3D models. The framework is artist driven – it allows artists to edit or stylize line work in 2D, similar to what they do in a traditional animation pipeline but utilizing 3D information. The framework is validated with a 2D animation software. We demonstrate the effectiveness of the framework in creating an animation with the software.
Automated Extraction of Typical Expressions Describing Product Features from Customer Reviews

The paper presents a procedure that helps in revealing topics hidden in large collections of textual documents (such as customer reviews) related to a certain group of products or services. Together with identification of the groups containing the topics the lists of important expressions is presented which helps in understanding what characterizes these aspects most typically from the semantic point of view. The procedure includes determining an appropriate number of groups representing the prevailing topics, partitioning the documents into a desired number of groups using clustering, extracting significant typical features of documents from each group with application of feature selection methods, and evaluating the outcomes with the assistance of a human expert. The results show that the presented approach, consisting mostly of automated steps, is able to separate and characterize the aspects of a certain product as discussed by the customers and be later useful, e.g., for handling customer complaints, designing promotional campaigns, or improving the products.
What more can we learn from PISA tests? A comparative Analysis of the Long-term Dynamics of the Israeli International Educational Achievements

One of the most prominent comparative international tests in recent years is conducted by the Programme for International Student Assessment (PISA), which is used to assess students' knowledge of reading comprehension, mathematics, and science. PISA is most known for its goal to compare nations according to a league table ranking system. Israel has taken part in these assessments from its conception and since then it has been gradually decreasing in the world ranking. By 2015 the Israeli students are located between 37-40 out of 70 countries, down from 31-33 in 2000. Using Israel's data throughout the PISA cycles, we aim to offer an alternative comparative view for these international results, based on measures of self-change. These measures show a consistent and significant system-wide improvement of the Israeli educational performance in all three PISA tests since 2000. Not only does this contrast with its downward trend in the international ranking which is biased due to inclusion of more countries, the rate of change was consistently positive over time and surpassing that of its European and American counterparts. Indeed, these measures of change show a general growth of about 23 points over 15 years, which reflects a consistent improvement of 6 to 9 points in average per cycle since 2000 results. In light of these findings, the paper discusses the significance of measurements of change in comparative international tests.
Integrated reference circuits for low-power capacitive sensor interfaces

OF DOCTORAL DISSERTATION AALTO UNIVERSITY SCHOOL OF SCIENCE AND TECHNOLOGY P.O. BOX 11000, FI-00076 AALTO http://www.aalto. fi Author Matti Paavola Name of the dissertation Manuscript submitted May 24, 2010 Manuscript revised August 24, 2010 Date of the defence October 1, 2010 Article dissertation (summary + original articles) Monograph Faculty Department Field of research Opponent(s) Supervisor Instructor Abstract
Carving verb classes from corpora

In this paper, I discuss some methodological problems arising from the use of corpus data for semantic verb classification. In particular, I present a computational framework to describe the distributional properties of Italian verbs using linguistic data automatically extracted from a large corpus. This information is used to build a distribution-based classification of a set of Italian verbs. It is small scale notwithstanding, this case study will provide evidence for the complex interplay between syntactic and semantic verb features.