Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of ROC analysis to bayesian classifiers of PERG signals

This paper presents the use of ROC analysis for the assessment of the classifiers’ performance. Either linear or quadratic discriminant analysis assigns objects to classes on the basis of parametric model. Fitting decision boundary according to nonparametric ROC curve allows to achieve demanded criteria like maximum accuracy, minimum risk or Neyman-Pearson’s criterion. This method was applied to measure the quality of bayesian classifiers of PERG signal real data base.
Deployment of new transport services for multimedia flows

Traditional protocols as TCP and UDP propose a very restricted vision of the QoS notion. Under the view of quality of service requirements within the multimedia applications, the limitations of the transport protocols used nowadays in the internet have created the needs to define a new generic transport protocols generation deployable from the applicative quality of service requirements. Nevertheless, the introduction of a new transport protocol proposes the delicate problem of deploying it in big scale. This paper targets to propose a network architecture based on the concept of active networks to make the deployment of new generation services in a transparent way from the point of view of the applications. Some experiments done within the European project GCAP and based on a European network infrastructure show the feasibility of this approach such as the gains obtained in relation with traditional protocols.
Design and realization of a middleware for mobile task coordination

The trend towards interconnection of applications has long been recognized as a key challenge for information systems design. Following this trend, organi- zations have developed and introduced many distributed systems with differ- ent functionalities. Furthermore, computing becomes today increasingly mobile; performances of mobile devices (i.e. PDAs and smartphones) as well as the expansion of high-speed mobile networks allows many tasks to be performed beyond stationary workspaces. The dramatic growth of stand-alone and partly incompatible applications will negatively affect the integration, coordination and communication for entire so- lution. Contemporary solutions focus on stationary systems only; the usage of mobile devices is limited to simple scenarios (i.e. information access). In order to support the seamless integration of mobile devices, future distributed solutions should take services and service meta-information into account (e.g. variation of network bandwidth, battery power, availability, connectivity, reachability, sensors data and locations of services and service providers). In this master thesis we want to analyze how a distributed environment with va- riety of separated (mobile) service providers - implemented with different tech- nologies - can be integrated and coordinated. Finding compromises between performance, comfort and intelligent intercommunication is the main goal of this thesis. Therefore, it is concentrated on the conceptualization and design of a central middleware component that provide the coordination and communication functionalities for stationary and mobile entities. In order to prove some possible communication scenarios, the thesis provides a middleware-based scenario.
Microsoft Office Excel 2007

第１章 データを作成、操作する 第２章 データと内容の書式を設定する 第３章 数式を作成および編集する 第４章 データを視覚的に表示する 第５章 データの共有とセキュリティの設定をする 索引
An improved rebroadcast probability function for an efficient counter-based broadcast scheme in MANETs

Flooding is the simplest mechanism for broadcasting in mobile ad hoc networks (MANETs), where each node retransmits a given broadcast packet exactly once. Despite its simplicity, flooding can result in high redundant retransmission, contention and collision in the network, a phenomenon referred to as broadcast storm problem. Several probabilistic approaches have been proposed to mitigate this inherent phenomenon. However, majority of these schemes uses fixed rebroadcast probability which is quite unlikely to be optimal in other simulation set up. In this paper, we propose an improved rebroadcast probability function which takes into account immediate neighbor information and some key simulation parameters (i.e. network topology size, transmission range and number of nodes) in determining the appropriate rebroadcast probability for a given mobile node. Simulation results reveal that this simple adaptation achieves superior performance in terms of saved-rebroadcast, number of retransmission node and end-to-end delay, without sacrificing reachability in dense network.
Energy efficient hybrid routing protocol for wireless sensor networks

A wireless sensor network is designed to monitor events and report this information to a central location, or sink node. The information is required to efficiently travel through the network. It is the job of the routing protocol to officiate this process. With transmissions consuming the majority of the energy available to a sensor node, it becomes important to limit their usage while still maintaining reliable communication with the sink node. The aim of the research covered in this dissertation was to adapt the flat and hierarchical architectures to create a new hybrid that draws on current protocol theories. The designed and developed protocol, Hybrid Energy Efficient Routing (HEER) protocol, builds upon the initial groundwork laid out by the previously developed Simple Energy Efficient Routing (SEER) protocol designed by C.J. Leuschner. Another aspect of the work was to focus on the current lack of credibilty that is present in the WSN research community. The validity of SEER was examined and tested and this led to the main focus of this research, ensuring that HEER proves to be valid. The HEER protocol for wireless sensor networks is designed such that it is computationally simple, limits the number of transmissions, employs a cross-layer approach, is reliable, is energy-aware, has limited support for mobile nodes, is energy efficient, and most importantly is credible. Sensor nodes are extremely limited when it comes to their available energy resources. To maximise the node and network lifetimes requires the designed algorithm to be energy aware and as efficient as possible. A cross-layer design approach is followed which allows for the different layers of the OSI model to interact. The HEER protocol limits the number of transmissions that are used for network operation. This is achieved by using a minimal amount of messages for network setup and by selecting the optimal route. Route selection is calculated using hop count, current energy available, energy available on the receiving node, and lastly the energy required to reach the destination node. HEER combines and expands upon the method used by SEER for route selection. Network lifetime for networks of large sizes is increased, mainly due to more efficient routing of messages. The protocol was kept computationally simple and energy efficient, thus maintaining network survivability for as long as possible. gehou om daardeur so lang moontlik netwerkleeftyd te verseker. To Sarah and my Parents who supported me through my years of study …
Pixel-by-pixel reduction of atmospheric haze effects in multispectral digital imagery of water

A study is described in which the effects of the atmosphere on a remotely sensed, multispectral image of water are reduced in a spatially varying manner. The near zero IR reflectance of a water body is used to compute the atmospheric path transmittance and atmospheric path radiance on a pixel-by-pixel basis for a LANDSAT-5 Thematic Mapper image of Lake Ontario. TM Band 4 (0.76-0.90um) image radiance measures are used to define the atmospheric path radiance. Radiosonde data and the LOWTRAN 6 atmospheric model are used to compute the equivalent atmospheric effects for the spectral regions corresponding to the visible wavelength Thematic Mapper image bands on a pixel specific basis. The pixel-bypixel correction technique is shown to provide a useful reduction of atmospheric effects and to significantly reduce the uncertainty in the image derived measurement of water reflectance.
Student-Involved Assessment FOR Learning

PART I: INTRODUCTION TO STUDENT-INVOLVED ASSESSMENT FOR LEARNING. 1. Classroom Assessment for Student Success. 2. Defining Achievement Standards for Assessment. 3. Selecting Proper Assessment Methods. PART II: UNDERSTANDING ASSESSMENT METHODS. 4. Selecting Response Assessment. 5. Essay Assessment. 6. Performance Assessment. 7. Personal Communication as Assessment. 8. Assessing Dispositions. PART III: COMMUNICATING ASSESSMENT RESULTS. 9. Managing and Communicating Achievement Information. 10. Communicating with Standardized Test Scores. 11. Communicating with Report Cards. 12. Communicating with Portfolios. 13. Communicating Through Conferences. Appendix. Rubrics for Judging Classroom Assessment Quality. References. Index.
A Comparative Study of Ensemble Active Learning

Data Stream mining is an important emerging topic in the data mining and machine learning domain. In a Data Stream setting, the data arrive continuously and often at a fast pace. Examples include credit cards transaction records, surveillances video streams, network event logs, and telecommunication records. Such types of data bring new challenges to the data mining research community. Specifically, a number of researchers have developed techniques in order to build accurate classification models against such Data Streams. Ensemble Learning, where a number of so-called base classifiers are combined in order to build a model, has shown some promise. However, a number of challenges remain. Often, the class labels of the arriving data are incorrect or missing. Furthermore, Data Stream algorithms may benefit from an online learning paradigm, where a small amount of newly arriving data is used to learn incrementally. To this end, the use of Active Learning, where the user is in the loop, has been proposed as a way to extend Ensemble Learning. Here, the hypothesis is that Active Learning would increase the performance, in terms of accuracy, ensemble size, and the time it takes to build the model. This thesis tests the validity of this hypothesis. Namely, we explore whether augmenting Ensemble Learning with an Active Learning component benefits the Data Stream Learning process. Our analysis indicates that this hypothesis does not necessarily hold for the datasets under consideration. That is, the accuracies of Active Ensemble Learning are not statistically significantly higher than when using normal Ensemble Learning. Rather, Active Learning may even cause an increase in error rate. Further, Active Ensemble Learning actually results in an increase in the time taken to build the model. However, our results indicate that Active Ensemble Learning builds accurate models against much smaller ensemble sizes, when compared to the traditional Ensemble Learning algorithms.
Processing French: A Psycholinguistic Perspective

"Processing French" presents a groundbreaking empirical study of the processing of morphologically simple and complex French words. Peter Golato's research offers an insightful account of the lexical storage and retrieval of isolated words and words within sentences. "Processing French" investigates the native-language processing of French, a language for which findings have not definitively supported a dual-mechanism account of morphological processing. Through word- and sentence-level studies, the book accomplishes two goals. First, it offers behavioral evidence in support of a dual-mechanism processing account at the word level. In contrast to English, however, the evidence with French does not turn upon a contrast in inflectional regularity among verbs but instead hinges upon a diachronic contrast, with synchronic relevance, in the productivity of derivational suffixes among nouns. Second, by incorporating the findings of the word-level studies into sentence-level studies, the book offers a window onto the morphological processing of displaced sentential elements, specifically morphologically simple and complex "wh"-moved nouns and raised lexical verbs.Peter Golato is assistant professor of French at the University of Illinois at Urbana-Champaign. "Processing French" is decidedly original, and it is equally and decidedly sound. This book makes a superb shelf reference for anybody working in psycholinguistics, first- and second-language acquisition, and the syntactic study of French.and draws some fascinating conclusions about what might really be at play in human language acquisition. " -Fred Davidson, University of Illinois at Urbana-Champaign
On Repairing Sentences: An Experimental and Computational Analysis of Recovery from Unexpected Syntactic Disambiguation in Sentence Parsing

This thesis contends that the human parser has a repair mechanism. It is further contended that the human parser uses this mechanism to alter previouslybuilt structure in the case of unexpected disambiguation of temporary syntactic ambiguity. This position stands in opposition to the claim that unexpected disambiguation of temporary syntactic ambiguity is accomplished by the usual first pass parsing routines, a claim that arises from the relatively extraordinary capabilities of computational parsers, capabilities which have recently been extended by hypothesis to be available to the human sentence processing mechanism. The thesis argues that, while these capabilities have been demonstrated in computational parsers, the human parser is best explained in the terms of a repair based framework, and that this argument is demonstrated by examining eye movement behaviour in reading. In support of the thesis, evidence is provided from a set of eyetracking studies of reading. It is argued that these studies show that eye movement behaviours at disambiguation include purposeful visual search for linguistically relevant material, and that the form and structure of these searches vary reliably according to the nature of the repairs that the sentences necessitate.
General Architecture for Text Engineering (GATE) Developer for Entity Extraction: Overview for SYNCOIN

Abstract : The integrated development environment of the General Architecture for Text Engineering (GATE), or GATE Developer, is used to annotate entities in a text document consisting of messages in and around the Baghdad area (SYNCOIN data). Highlighting entities, such as person(s), location(s), and organization(s), may result in a more structured format for faster comprehension of the data. The application for entity determination is called a nearly-new information extraction, or ANNIE: a system of seven processing resources (PRs) in GATE. ANNIE is executed from the graphical user interface (GUI). Other PRs, such as those for machine learning, and the capability for user-defined applications are managed as a collection of reusable objects for language engineering (CREOLE); an icon for the CREOLE plug-in manager exists at the GUI as well.
A Similarity-Based Analysis Tool for Scientific Application Porting

Porting applications to a new system is a nontrivial job in the HPC field. It is a very time-consuming, labor-intensive process, and the quality of the results will depend critically on the experience of the experts involved. In order to ease the porting process, we propose a methodology to address an important aspect of software porting that receives little attention, namely planning support. When a scientific application consisting of many subroutines is to be ported, the selection of key subroutines greatly impacts the productivity and overall porting strategy, because these subroutines may represent a significant feature of the code in terms of functionality, code structure, or performance. They may also serve as indicators of the difficulty and amount of effort involved in porting a code to a new platform. The proposed methodology is based on the idea that a set of similar subroutines can be ported with similar strategies and result in a similar-quality porting. By viewing subroutines as data and operator sequences, analogous to DNA sequences, we are able to use various bio-informatics techniques to conduct the similarity analysis of subroutines while avoiding NP-complete complexities of other approaches. To further improve accuracy for porting, we also merged some other code metrics and costmodel metrics for similarity analysis to capture the internal code characteristics. In this dissertation, we describe our methodology, which includes presentation of a tool called Klonos. To evaluate the effectiveness of Klonos, we used it to conduct experiments to find strategies for porting of several scientific benchmarks and a large scientific application. Our experiment shows Klonos is very effective for providing a systematic porting plan to guide the users during their porting process of reusing similar porting strategies for similar code regions.
Interactive Data Visualization for the Web

Create and publish your own interactive data visualization projects on the Webeven if you have little or no experience with data visualization or web development. Its easy and fun with this practical, hands-on introduction. Author Scott Murray teaches you the fundamental concepts and methods of D3, a JavaScript library that lets you express data visually in a web browser. Along the way, youll expand your web programming skills, using tools such as HTML and JavaScript.This step-by-step guide is ideal whether youre a designer or visual artist with no programming experience, a reporter exploring the new frontier of data journalism, or anyone who wants to visualize and share data.Learn HTML, CSS, JavaScript, and SVG basics Dynamically generate web page elements from your dataand choose visual encoding rules to style them Create bar charts, scatter plots, pie charts, stacked bar charts, and force-directed layouts Use smooth, animated transitions to show changes in your data Introduce interactivity to help users explore data through different views Create customized geographic maps with data Explore hands-on with downloadable code and over 100 examples
IIR: an Identifier-based Intermediate Representation To Support Declarative Compiler Specifications

For compiler developers, one big issue is how to describe a specification of its intermediate representation (IR), which consists of various entities like symbol tables, syntax trees, analysis information and so on. As IR is a central data structure of a compiler, its precise specification is always strongly desired. However, the formalization of an actual IR is not an easy task since it tends to be large, has complex interdependency between its entities, and depends on a specific implementation language. In this paper, as a first step to solve this problem, we propose a new data model for IR, called IIR. The goal of IIR is to describe a specification of IR declaratively without depending on its concrete implementation detail. The main idea is to model all entities of IR as relations with explicit identifiers. By this, we can develop an IR model transliterally from an actual IR, and describe its specification by using the full expressiveness of conventional logic languages. The specification is inherently executable and can be used to check the validity of IR in compile time. As a practical case study, we formalized an IR of our production compiler in IIR, and developed a type system for it in Prolog. Experimental results about size and performance are shown.
Formal analysis of gameplay

Formal analysis is the name for research where an artifact and its specific elements are examined closely, and the relations of the elements are described in detail. Formal analysis has been used, for example, in art criticism, archaeology, literature analysis, or film analysis. Although the context of the studied artifact may complement the research, and different artifacts may be compared with each other, formal analysis can be done on individual artifacts in isolation. Formal analysis can be seen as a fundamental or underlying method in that it provides an understanding of the game system that can in a later step be used for further analysis (cf. Munsterberg, 2009). The results of formal analysis can also be contrasted or tested against other sources, for example, information from players, designers, and reviewers.
Stereo Vision for Autonomous Micro Aerial Vehicles

Small unmanned and lightweight aircrafts, known as Micro Aerial Vehicles (MAVs), have gained much attention in recent years. In this thesis we approach the problem of enabling such MAVs to fly autonomously without the need for human intervention. The sensor technology that is chosen for this task is stereo vision. As research platform for this work serves a small quadrotor MAV that has been equipped with four cameras in two stereo configurations. We study a broad range of problems that need to be solved for the construction of a stereo vision based autonomous MAV. The first problem that we examine is stereo matching. We introduce a new sparse stereo matching algorithm that achieves very high processing rates while also delivering accurate results. A key component of this algorithm is a combined consistency and uniqueness check that evaluates a dense disparity range. This new stereo algorithm is used for processing the imagery of both stereo camera pairs that are available on the used MAV platform. For the first camera pair that is facing forward, we process the stereo matching results with a simplified Simultaneous Localization and Mapping (SLAM) algorithm, which tracks the cameras’ pose (i.e. position and orientation). A different method is applied to the second stereo camera pair that is facing downwards. Here, the stereo matching results are used for detecting the dominant ground plane. From this plane and a method based on frame-to-frame tracking, we are able to derive another estimate of the MAV’s pose. Both pose estimates are then fused and used for controlling the MAV’s flight. The ability of this MAV to fly autonomously is demonstrated in several flight experiments and evaluations. We successfully demonstrate autonomous take-off, landing, hovering, 360◦ yaw rotation, shape flight and error recovery. Finally, we examine the problem of sensing free and occupied space, which would be needed to facilitate autonomous path planning for our MAV. For this purpose, we extend an existing volumetric occupancy mapping method, such that it provides more robust results when used in conjunction with stereo vision. The performance improvement is mainly achieved by introducing a more complex update mechanism for voxels in this map, which considers the probability that a voxel is currently visible. Furthermore, the expected depth error is modeled and considered during map updates, and the overall run-time performance of the method is improved. The resulting method is fast enough to perform occupancy mapping in real-time, including the necessary dense stereo matching.
Estimators of extra-sample error for non- parametric methods. A comparison based on extensive simulations.

In this technical report we examine and compare the estimators most widely used to evaluate the prediction error of a non-parametric regression model. An extensive simulation approach allowed us to compare the estimators with respect to different data characteristics: the linearity of the relation, the signal-to-noise ratio, and the amount of model overfitting. We compared estimators based on resampling methods such as Leave-one-out, parametric and nonparametric Bootstrap, as well as repeated Cross Validation methods and Hold-out. The models used were Regression Trees, Projection Pursuit Regression and Neural Networks. The simulations show that the repeated corrected 10-fold cross-validation proposed by Burman and the Parametric Bootstrap proposed by Efron have the best performance.