Miracle-dz/UniFAR-FTUs huggingface dataset:
Inductive learning of decision rules from attribute-based examples: a knowledge-intensive genetic algorithm approach

Genetic algorithms are stochastic adaptive systems whose search method models natural genetic inheritance and the Darwinian struggle for survival. Their importance results from the robustness and domain independence of such a search. Robustness is a desirable quality of any search method. In particular, this property has led to many successful genetic algorithm applications involving parameter optimization of unknown, possibly non-smooth and discontinuous functions. Domain independence of the search is also a praised characteristic since it allows for easy applications in different domains. However, it is a potential source of limitations of the method as well. In this dissertation, we present a modified genetic algorithm designed for the problem of supervised inductive learning in feature-based spaces which utilizes domain dependent task-specific knowledge. Supervised learning is one of the most popular problems studied in machine learning and, consequently, has attracted considerable attention of the genetic algorithm community. Thus far, these efforts have lacked the level of success achieved in parameter optimization. The approach developed here uses the same high level descriptive language that is used in rule-based supervised learning methods. This allows for an easy utilization of inference rules of the well known inductive learning methodology, which replace the traditional domain independent operators. Moreover, a closer relationship between the underlying task and the processing mechanisms provides a setting for an application of more powerful task-specific heuristics. Initial results indicate that genetic algorithms can be effectively used to process high level concepts and incorporate task-specific knowledge. In this particular case of supervised learning, this new method proves to be competitive to other symbolic systems. Moreover, it is potentially more robust as it provides a powerful framework that uses cooperation among competing solutions and does not assume any prior relationships among attributes.
Multi-stage deplyoment of robot control software

For future robot control, there is a strong need for tools and methods supporting the development and deployment of control software. To this end, we propose a method for developing hard real-time software based on the standard Java language and multi-stage deployment and verification towards the embedded platform. This allows us to develop embedded Java software on the desktop using standard software tools for implementation, testing, and verification, to later be deployed onto the embedded platform. The deployment is done in stages from pure Java to hard real-time embedded C. This allows us to easily find and cope with platform-related problems due to different run-time environments and thread models. The proposed method has been experimentally tested in the development of a robot control application. (Less)
Adaptive Lossless Data Compression Algorithm

The traditional lossless compression algorithms are aim for higher compress ratio,but they can not meet the requirement of the network environment.This paper raises an adaptive algorithm with adjustable compression ratio by parameter to meet the requests of different enviroments.The experimental result shows that the improved algorithm is more efficient than the tradional one in the process of remote transmission.
Transforming UML class diagrams into relational data models

The Entity-Relationship (ER) method is the most popular method for relational database design. On the other hand, the Unified Modeling Language (UML) is widely used in object-oriented analysis and design. Despite the increasing use of object-oriented techniques for software design and development, there is a large installed base of relational databases. Additionally, object-oriented databases are still not in widespread use. Thus, software designers and developers often turn to the relational databases to make their application objects persistent. Considering the fundamental differences between the two methods, the transformation from UML to a relational data model could be a non-trivial task. The purpose of this chapter is to describe a process that can be used to map a UML class diagram into an ER diagram, and to discuss the potential of using the UML notation to draw ER diagrams. An example of an actual systems design is used throughout to illustrate the mapping process, the associated problems encountered, and how they could be resolved.
Design of Multiple Model Fuzzy Predictors using Data Preprocessing and its Application

It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.
AADL Model Transformations

The Architectural Analysis and Design Language (AADL) is an Architecture Description Language (ADL) that has been standardized in November 2004 by the Society of Automotive Engineers (SAE), Aerospace Avionics Systems Division. The scope of this language is quite wide. It targets critical developments and offers appropriate modelling techniques to cover system and software engineering activities. Taking a Software Engineering point of view, this paper firstly presents a few possible benefits of using the AADL within a critical software development process, then describes the model transformations plugins that have been implemented into the Stood 5.0 software design tool to support AADL 1.0 in connection with UML 2.0 graphical notation while preserving the benefit of HOOD top-down modelling process and HRT-HOOD real-time semantics. 1 Using the AADL in a Software development process Let’s consider some of the main concerns that arise during Software Engineering activities: • How to import System Engineering architectures as blueprints for the Software Architectural Design activities? • How to refine System Engineering Components with the output of the Software Design activities? • How to build a repository of reusable Components from legacy source code? The use of a language that can carry the common application architecture throughout the development lifecycle, while accepting the customized detailed that are needed by each modelling step, is required to reach these goals. In addition, such a language must be able to efficiently carry advanced concepts like real time paradigms. Such a common language could be simply UML or XML, but the former is often perceived as being too “software oriented” for System Engineering purposes, which seems confirmed by the current OMG effort to define SysML, and the latter is only standardized at a syntactic level and thus requires the definition of a dedicated DTD or Schema, which raises an issue while considering it as a really recognized international standard.
Language-aware text editing

While software developers have various power tools at their disposal that make the writing of computer programs more efficient, authors of texts do not have the support of such power tools. Text processors still operate on the level of characters and strings rather than on the level of word forms and grammatical constructions. This forces authors to constantly switch between low-level, character oriented, editing operations and high-level, conceptual, verbalisation processes. We suggest the development of language-aware text editing tools that simplify certain frequent, yet complex editing operations by defining them on the level of linguistic units. Pluralizing an entire noun phrase plus the verb forms governed by it would be an ambitious example, swapping the elements of a conjunctive construction a more modest one. We describe a pilot implementation for German where these operations are seamlessly integrated with the standard functions of an existing open-source editor. The operations can be invoked on demand and do not intrude on the authoring process. Changes can be performed locally or globally, thus simplifying the writing process considerably, and making the resulting texts more consistent.
Familles minimales d'implications informatives résultant d'un tableau de données binaires

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Adaptive Multimodal Perception for a Virtual Museum Guide

Smart environments that aim to provide personalized services must identify and keep track of their human inhabitants. Our project involves the deployment of embodied conversational agents to help guide visitors around museum exhibits. The visitors are not known in advance, so to achieve the personal touch, we need to learn about each visitor while they are exploring the museum. The solution we propose has three ingredients: online training for face recognition; automated segmentation of speakers; and social dialogue with the agent. Using a combination of boosted classifier cascades and optical flow tracking, faces are extracted from live video, and classifiers are trained on these. Lip motion is then correlated to speech signals obtained from blind signal separation of the audio. The objective is to distinguish individuals from a crowd of visitors and engage them in dialogue to obtain and offer information relevant to the museum experience. The main challenge is the computational cost of online training, which we plan to address through intelligent load balancing and a GPU-based acceleration scheme.
PostMark: A New File System Benchmark

Existing file system benchmarks are deficient in portraying performance in the ephemeral small-file regime used by Internet software, especially: electronic mail; netnews; and web-based commerce. PostMark is a new benchmark to measure performance for this class of application. In this paper, PostMark test results are presented and analyzed for both UNIX and Windows NT application servers. Network Appliance Filers (file server appliances) are shown to provide superior performance (via NFS or CIFS) compared to local disk alternatives, especially at higher loads. Such results are consistent with reports from ISPs (Internet Service Providers) who have deployed NetApp filers to support such applications on a large scale.
Concurrency and Parallel Methods for multi-core Platforms

This master thesis has been written at Saab Electronic Defence Systems. Its main purpose is to evaluate the amount of resources needed to rewrite sequential Java components running in Saabs systems, in such a way that they can take advantage of multi-core processors. The research of the thesis addresses issues with concurrent programming in Java, available frameworks and methods and how they can be implemented for different kinds of applications. The research has been used to parallelize a Saab component called Threat Evaluation and Weapons Allocation (TEWA). As a result of the parallelization, a general purpose concurrency framework, called Concurrent Eventhandling and Loop Parallelization (CELP) framework, has been developed. CELP can be used, together with standard Java concurrency tools, to parallelize more of Saabs event based components, making them scalable and safe. This has been shown with the results of the parallelized TEWA, which includes good scalability, 15 times performance increase compared to the sequential version and improved deterministic behavior.
The Conservation of a Photograph Album at the National Arciuves of Canada

Abstract The full conservation treatment performed on a large 19th-century Canadian photograph album at the National Archives of Canada is outlined in detail. The Jacobs Album, considered to be one of the most valuable in the collection, was completely taken apart. All 913 photographs were lined and remounted onto new pages, and new bindings were constructed. The original pages and binding jackets were treated and stored separately. Also outlined are the treatment options presented prior to treatment and the decision-making process that resulted in this treatment.
1998 Broadcast News Benchmark Test Results: English and Non-English Word Error Rate Performance Measures

This paper documents the use of Broadcast News test materials in DARPA-sponsored Automatic Speech Recognition (ASR) Benchmark Tests conducted late in 1998. As in last year’s tests [1], statistical selection procedures were used in selecting test materials. Two test epochs were used, each yielding (nominally) one and one-half hours of test material. One of the test sets was drawn from the same test epoch as was used for last year’s tests, and the other was drawn from a more recent period. Results are reported for two types of systems: one (the “Hub”, or “baseline” systems) for which there were no limits on computational resources, and another (the “less than 10X realtime spoke” systems) for systems that ran in less than 10 times real-time. The lowest word error rate reported this year for the “Hub” systems was 13.5%, contrasting with last year’s lowest word error rate of 16.2%. For the “less than 10X real-time spoke” systems, the lowest reported word error rate was 16.1%. Results are also reported, for the second year, on non-English language Broadcast News materials in Spanish and Mandarin.
Kajian terhadap penggunaan perisian dan perkakasan multimedia di kalangan guru dalam P & P di sekolah menengah zon Skudai

This study is conducted to determine of using multimedia software and hardware among teachers in the process of teaching and learning and to look the usage of PBK at secondary school in Zone of Skudai. The population of the respondent were 1028 teachers from 12 school in Zone of Skudai. The sample of this study were 202 teachers. This is quantitative research using 70 item questionnaire. Descriptive statistic analysis will be used and the finding are presented by using mod, percentage and mean. The data were collected by using the Statistical Package For The Social Science (SPSS). The trusted of the questionnaire were alpha=0.940. Overall of this analysis was shown that teachers at secondary school in zone of Skudai using PBK in teaching and learning and they always used Microsoft Office software and the hardware, example: computer, LCD and television. The result in this study will shown that the respondent was not expert to use the high technology of software and hardware.
Case Studies in Symbolic Model Checking

Formal veri cation of hardware and software systems has long been recognized as an essential step in the development process of a system It is of importance especially in concurrent systems that are more di cult to debug than sequential systems Tools that are powerful enough to verify real life systems have become available recently Model checking tools have become quite popular because of their ability to carry out proofs with minimal human intervention In this paper we report our experience with SMV a symbolic model veri er on practical problems of signi cant sizes We present veri cation of a software system a distributed shared memory protocol and a hardware system the crossbar arbiter We discuss modeling of these systems in SMV and their veri cation using temporal logic CTL queries We also describe the problems encountered in tackling these examples and suggest possible solutions Case Studies in Symbolic Model Checking Ganesh Gopalakrishnan Dilip Khandekar Ravi Kuramkote and Ratan Nalumasu Department of Computer Science University of Utah Salt Lake City UT email fganesh khands kuramkot ratang cs utah edu
Impact of Cooperative Relays on the Capacity of Rank-Deficient MIMO Channels

We study the impact of multiple linear amplifyand-forward relays on the capacity of rank-deficient MIMO channels. We derive a general system model for wireless networks with one source/destination pair and several linear amplify-and-forward relay nodes which assist the communication between source and destination. All nodes may be equipped with multiple antennas. For a given allocation of gain factors at the relay nodes we give an analytical expression of the capacity by generalizing the results in [1], [2]. We compare the performance of a relay assisted MIMO link in a line-of-sight environment with a MIMO link without relay nodes. Our results show that the proposed cooperative signaling scheme solves a fundamental problem of MIMO systems: the rich scattering requirement.
Real-time particle systems in the Blender Game Engine

Advances in computational power have lead to many developments in science and entertainment. Powerful simulations which required expensive supercomputers can now be carried out on a consumer personal computer and many children and young adults spend countless hours playing sophisticated computer games. The focus of this research is the development of tools which can help bring the entertaining and appealing traits of video games to scientific education. Video game developers use many tools and programming languages to build their games, for example the Blender 3D content creation suite. Blender includes a Game Engine that can be used to design and develop sophisticated interactive experiences. One important tool in computer graphics and animation is the particle system, which makes simulated effects such as fire, smoke and fluids possible. The particle system available in Blender is unfortunately not available in the Blender Game Engine because it is not fast enough to run in real-time. One of the main factors contributing to the rise in computational power and the increasing sophistication of video games is the Graphics Processing Unit (GPU). Many consumer personal computers are equipped with powerful GPUs which can be harnassed for general purpose computation. This thesis presents a particle system library is accelerated by the GPU using the OpenCL programming language. The library integrated into the Blender Game Engine providing an interactive platform for exploring fluid dynamics and creating video games with realistic water effects. The primary system implemented in this research is a fluid simulator using the Smoothed Particle Hydrodynamics technique for simulating incompressible fluids such as water. The library created for this thesis can simulate water using SPH at 40fps with upwards
Effects of data passing semantics and operating system structure on network i/o performance

Abstract : Elimination of data and control passing overheads in I/O has been a long-sought goal. Researchers have often proposed changing the semantics of I/O data passing, so as to make copying unnecessary, or the structure of the operating system, so as to reduce or eliminate data and control passing. However, most such changes are incompatible with existing applications and therefore have not been adopted in conventional systems. My thesis is that, in network I/O, optimizations that preserve data passing semantics and system structure can give end-to-end improvements competitive with those of data and control passing optimizations that change semantics or structure. Moreover, current technological trends tend to reduce differences in such improvements. To demonstrate the thesis, I introduce new models of I/O organization, optimization, and data passing, emphasizing structure and compatibility rather than implementation. I review previous network I/O optimizations and propose many new ones, including emulated copy, for data passing without copying but with copy semantics between application and system buffers, and I/O-oriented IPC, for efficient data passing to and from user-level server buffers. I examine in detail network adapter requirements for copy avoidance. I describe the implementation of the different optimizations in Genie, a new I/O framework. Using Genie, I experimentally compare the optimizations on a variety of platforms and with different levels of hardware support. The experiments confirm the thesis, showing that: (1) Emulated copy performs competitively with data passing schemes with move or share semantics; (2) Emulated copy performs competitively with data and control passing optimizations enabled by extensible kernels; and (3) I/O-oriented IPC gives user-level I/O servers performance approaching that of kernel-level ones.
MW²P-Bus: A New Bus Structure for Datapath Synthesis

Datapath optimisation has a great impact on the efficiency of computationally intensive embedded designs such as DSP blocks. Bus-oriented design is one of the low cost approaches to datapath synthesis but which suffers from a low data communication bandwidth %uniformly provided for all the connected units. It has been shown, on the other hand, that the word-length of functional units has a great impact on design costs. A combination of both methods is the core idea of this paper by offering an improved bus-oriented structure for datapath synthesis. In this method a datapath is partitioned into groups which are connected to a set of shared buses. Every bus segment has a different width and all the functional units connected to a bus segment have the same word-length. Having controlled the group binding and word-length of the functional units, as well as the other synthesis parameters, a high-level synthesis tool is introduced to implement DSP algorithms in register transfer level specification. The tool uses a multi-objective optimization algorithm to minimize the circuit area, delay, power consumption and digital noise by selecting optimal grouping and word-length for the bus structure. Results demonstrate that 25% to 75% savings can be made in the latency cost by applying this method.
AI Tools: A Short Introduction to YALE

In this term paper I introduce the machine learning framework called YALE (Yet Another Learning Environment). The paper motivates by introducing some aspects about the usefulness of machine learning in general and provides some examples of areas of its application. After that, I note some of the main aspects of machine learning frameworks followed by an in depth look at the inner workings of YALE, wherein I compare it to another open source machine learning framework called WEKA. I focus especially on the aspects that lead the creators of YALE to implement a new machine learning framework instead of using an existing one. These aspects are the way machine learning experiments are constructed and the way simple building blocks can be combined into more complex ones, some aspects about the way data is represented and handled internally, preprocessing and the overall open design of the framework. The second part of the paper is concerned with the seamless integration of YALE into one’s own Java projects. After which I summarize the main differences of YALE and WEKA. A sideways look towards related work and a section where I conclude on which might be reasonable scenarios for the application of either YALE or WEKA, will complete this document.