Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining Frequent Closed Patterns by Adaptive Pruning

The set of frequent closed patterns determines exactly the complete set of all frequent patterns and is usually much smaller than the laster. Yet mining frequent closed patterns remains to be a memory and time consuming task. This paper tries to develop an efficient algorithm to solve this problem. The compound frequent item set tree is employed to organize the set of frequent patterns, which consumes much less memory than other structures. The tree is grown quickly by integrating depth first and breadth first search strategies, opportunistically choosing between two different structures to represent projected transaction subsets, and heuristically deciding to build unfiltered pseudo or filtered projections. Efficient pruning methods are used to reduce the search space. The balance of the efficiency and scalability of tree growth and pruning maximizes the performance. The experimental results show that the algorithm is a factor of five to three orders of magnitude more time efficient than several recently proposed algorithms, and is also the most scalable one. It can be used in the discovery of non-redundant association rules, sequence analysis, and many other data mining problems.
An Adaptively refined Cartesian grid method for moving boundary problems applied to biomedical systems

A major drawback in the operation of mechanical heart valve prostheses is thrombus formation in the near valve region potentially due to the high shear stresses present in the leakage jet flows through small gaps between leaflets and the valve housing. Detailed flow analysis in this region during the valve closure phase is of interest in understanding the relationship between shear stress and platelet activation. An efficient Cartesian grid method is developed for the simulation of incompressible flows around stationary and moving three-dimensional immersed solid bodies as well as fluid-fluid interfaces. The embedded boundaries are represented using Levelsets and treated in a sharp manner without the use of source terms to represent boundary effects. The resulting algorithm is implemented in a straightforward manner in three dimensions and retains global second-order accuracy. When dealing with problems of disparate length scales encountered in many applications, it is necessary to resolve the physically important length scales adequately to ensure accuracy of the solution. Fixed grid methods often have the disadvantage of heavy mesh requirement for well resolved calculations. A quadtree based adaptive local mesh refinement scheme is developed to complement the sharp interface Cartesian grid method scheme for efficient and optimized calculations. Detailed timing and accuracy data is presented for a variety of benchmark problems involving moving boundaries. The above method is then applied to modeling heart valve closure and predicting thrombus formation. Leaflet motion is calculated dynamically based on the fluid forces acting on it employing a fluid-structure interaction algorithm. Platelets are modeled and tracked as point particles by a Lagrangian particle tracking method which incorporates
Investigating teaching and learning of Grade 9 Algebra through excel spreadsheets : a mixed-methods case study for Lesotho

The teaching and learning of algebra in the middle school grades in Lesotho is dominated by the mechanistic approach where learners are drilled on procedures for solving certain types of problems in algebra, without making any connection to the experience learners had with arithmetic. This is one of the sources of learners’ difficulties in mathematics. Research indicates that use of spreadsheets such as Excel has a potential of bridging the gap between arithmetic and algebra and thus enhancing the teaching and learning of algebra, making it meaningful to the learners. The study sought to answer the question: How do Grade 9 learners in Lesotho experience teaching and learning of algebra through Excel spreadsheets? The research commenced with a literature review that was followed by the empirical study. The theories of instrumental genesis and instrumental orchestration were identified as the framework for the investigation. Instrumental genesis is the process in which learners develop facility with the artifact as they use it towards achieving lesson objectives; technical (conceptual, mechanical) and personal (attitudes, behavior and preferred learning styles) aspects of learners’ experiences were identified. Instrumental orchestration is the steering of learners’ instrumental genesis by the teacher and the manner in which this process is carried out, depends on the teacher’s Technological Pedagogical Content Knowledge (TPCK). The research was a multi-case study following a mixed-methods approach, where both qualitative and quantitative methods were used. The empirical study was conducted in two schools in Lesotho. In each school, fifteen learners volunteered participation. The investigation was done through classroom teaching by me as the researcher. The focus was on what challenges learners encountered and how they benefited from their “spreadsheets algebra” learning experience. Data were collected through classroom observations where field notes were recorded and an observation schedule was used by the researcher and the Assistant Observer respectively. A questionnaire was also administered to all learner participants after the whole teaching period. Six learners, representative of high, medium and low performances in class, were also interviewed with a goal of finding out their experiences. The Assistant Observer was Stellenbosch University http://scholar.sun.ac.za
Using snort to detect rogue IRC bot programs

An apparatus for the thermal-catalytic abatement of hydrocarbons, carbon monoxide, nitrogen oxides and particulates from effluent gas streams. The apparatus has a preheat section wherein the effluent is heated to 400 DEG -1000 DEG F by hot combustion gases. The effluent and combustion gases are directed by a baffle through a filter where combustible particulates are incinerated and noncombustible particulates are collected. The baffle followed by a diffuser cone, axially located on the filter, intimately mixes the effluent with the combustion gases so as to provide uniform flow and temperature distribution of the mixed gases across the filter. The filtered gases then pass through a catalytic reactor section containing a catalyst, preferably catalyst-coated ceramic honeycombs. In the presence of the catalysts the hydrocarbons and carbon monoxide in the heated gas stream are oxidized to carbon dioxide and water and the nitrogen oxides are reduced.
Test plan for 32-bit microcomputers for the Water Resources Division; Chapter A, Test plan for acquisition of prototype 32-bit microcomputers

1 1. General information . 1 1.1 Summary . 1 1.2 Pretest background . 2 1.3 Objectives of the plan . 2 2. Plan for testing microcomputers . 3 2.1 Identifying qualified vendors . 3 2.2 Tests performed . 3 2.3 Test requirements . A 2.A Work group organization . A 3. Evaluation methodology . 5 3.1 Test scripts . 5 3.2 Evaluation criteria . 5 A. Test descriptions (scripts) . 6 A.1 Shared data access . 6 A.2 Basic performance . 6 A.3 Test Fortran 77 compilation and execution . 7 A.A Data base management system test . 7 A.5 Tymnet connection . 8 5. Selected references . 8
Evolution of Networks: From Biological Nets to the Internet and WWW (Physics)

Only recently did mankind realise that it resides in a world of networks. The Internet and World Wide Web are changing our life. Our physical existence is based on various biological networks. We have recently learned that the term "network" turns out to be a central notion in our time, and the consequent explosion of interest in networks is a social and cultural phenomenon. The principles of the complex organization and evolution of networks, natural and artificial, are the topic of this book, which is written by physicists and is addressed to all involved researchers and students. The aim of the text is to understand networks and the basic principles of their structural organization and evolution. The ideas are presented in a clear and a pedagogical way, with minimal mathematics, so even students without a deep knowledge of mathematics and statistical physics will be able to rely on this as a reference. Special attention is given to real networks, both natural and artifical. Collected empirical data and numerous real applications of existing theories are discussed in detail, as well as the topical problems of communication networks. Available in OSO: http://www.oxfordscholarship. com/oso/public/content/physics/9780198515906/toc.html
The Standard Vector Library: a software framework for coupling complex simulation and optimization

Object oriented design solves a fundamental programming problem arising in simulation driven optimization: the separation in code of multiple levels of abstraction naturally appearing in solution algorithms for such problems. The Standard Vector Library provides classes expressing core concepts (vector, function,.) of calculus in Hilbert space with minimal implementation dependence, and standardized interfaces behind which to hide application-dependent implementation details (data containers, function objects). Important innovations introduced by this project and its predecessor (the Hilbert Class Library) include vector space and function evaluation objects, natural product structures, and extensive tool or wrapper classes to ease application construction. The library features extensive use of ISO standard C++ support for both object-oriented and generic programming models, a component-friendly structure for support of distributed computing via client-server frameworks, and systematic extensibility of class capabilities through method-forwarding.
Reinforcement learning for job shop scheduling

This dissertation studies applying reinforcement learning algorithms to discover good domain-specific heuristics automatically for job-shop scheduling. It focuses on the NASA space shuttle payload processing problem. The problem involves scheduling a set of tasks to satisfy a set of temporal and resource constraints while also seeking to minimize the total length (makespan) of the schedule. The approach described in the dissertation employs a repair-based scheduling problem space that starts with a critical-path schedule and incrementally repairs constraint violations with the goal of finding a short conflict-free schedule. The temporal difference (TD) learning algorithm TD($\lambda$) is applied to train a neural network to learn a heuristic evaluation function for choosing repair actions over schedules. This learned evaluation function is used by a one-step lookahead search procedure to find solutions to new scheduling problems. Several important issues that affect the success and the efficiency of learning have been identified and deeply studied. These issues include schedule representation, network architectures, and learning strategies. A number of modifications to the TD($\lambda$) algorithm are developed to improve learning performance. Learning is investigated based on both hand-engineered features and raw features. For learning from raw features, a time-delay neural network architecture is developed to extract features from irregular-length schedules. The learning approach is evaluated on synthetic problems and on problems from a NASA space shuttle payload processing task. The evaluation function is learned on small problems and then applied to solve larger problems. Both learning-based schedulers (using hand-engineered features and raw features respectively) perform better than the best existing algorithm for this task--Zweben's iterative repair method. It is important to understand why TD learning works in this application. Several performance measures are employed to investigate learning behavior. We verified that TD learning works properly in capturing the evaluation function. It is concluded that TD learning along with a set of good features and a proper neural network is the key to this success. The success shows that reinforcement learning methods have the potential for quickly finding high-quality solutions to other combinatorial optimization problems.
The Software Therapist: Usability Problem Diagnosis Through Latent Semantic Analysis

Abstract : The work we report on here addresses the problem of low return on investment in software usability engineering and offers support for usability practitioners in identifying, understanding, documenting, and fixing usability problems. It does this by (1) validating and extending a structured knowledge framework of usability concepts for organizing and relating usability data to design flaws and solutions, (2) specifying a usability data management cycle to support a diagnosis process that is iteratively interleaved with data collection, and (3) developing a software system for usability engineering practitioners that includes components to support the activities of usability data collection, organization, and problem analysis and reporting, as well as automated support for usability problem diagnosis using a sophisticated statistical technique for the analysis of text. In this report, we briefly review the motivations and background for this work and describe the User Action Framework (UAF) and Latent Semantic Analysis (LSA); describe the design, development, and use of the Software Therapist system; discuss the research done on applying LSA to usability engineering; describe the usability content library collected as part of the project; and discuss the evaluation of the system as well as some lessons learned and possible future directions resulting from the project.
Identifying experts and authoritative documents in social bookmarking systems

Social bookmarking systems allow people to create pointers to Web resources in a shared, Web-based environment. These services allow users to add free-text labels, or “tags”, to their bookmarks as a way to organize resources for later recall. Ease-of-use, low cognitive barriers, and a lack of controlled vocabulary have allowed social bookmaking systems to grow exponentially over time. However, these same characteristics also raise concerns. Tags lack the formality of traditional classificatory metadata and suffer from the same vocabulary problems as full-text search engines. It is unclear how many valuable resources are untagged or tagged with noisy, irrelevant tags. With few restrictions to entry, annotation spamming adds noise to public social bookmarking systems. Furthermore, many algorithms for discovering semantic relations among tags do not scale to the Web. Recognizing these problems, we develop a novel graph-based Expert and Authoritative Resource Location (EARL) algorithm to find the most authoritative documents and expert users on a given topic in a social bookmarking system. In EARL’s first phase, we reduce noise in a Delicious dataset by isolating a smaller sub-network of “candidate experts”, users whose tagging behavior shows potential domain and classification expertise. In the second phase, a HITS-based graph analysis is performed on the candidate experts’ data to rank the top experts and authoritative documents by topic. To identify topics of interest in Delicious, we develop a distributed method to find subsets of frequently co-occurring tags shared by many candidate experts. We evaluated EARL’s ability to locate authoritative resources and domain experts in Delicious by conducting two independent experiments. The first experiment relies on human judges’ n-point scale ratings of resources suggested by three graph-based algorithms and Google. The second experiment evaluated the proposed approach’s ability to identify classification expertise through human judges’ n-point scale ratings of classification terms versus expert-generated data.
SOFTWARE REUSE WITH ANALYSIS PATTERNS

The purpose of this article is to promote reuse of domain knowledge by introducing patterns already in the analysis phase of the software life-cycle. We propose an outline template for analysis patterns that strongly supports the whole analysis process from the requirements analysis to the analysis model and further on to its transformation into a flexible and reusable design and implementation. As an example we develop a family of analysis patterns in this paper that deal with a series of pressing problems in cooperative work, collaborative information filtering and sharing, and knowledge management. We evaluate the reuse potential of these patterns by analyzing several components of an information system, that was developed for the Virtual University project of the Vienna University of Economics and Business Administration. The findings of this analysis suggest that using patterns in the analysis phase has the potential to reducing development time significantly by introducing reuse already at the analysis stage and by improving the interface between analysis and design phase.
An Introspection Approach to Querying a Trainer

This paper introduces the Introspection Approach, a method by which a learning agent employing reinforcement learning can decide when to ask a training agent for instruction. When using our approach, we find that the same number of trainer''s responses produced significantly faster learners than by having the learner ask for aid randomly. Guidance received via our approach is more informative than random guidance. Thus, we can reduce the interaction that the training agent has with the learning agent without reducing the speed with which the learner develops its policy. In fact, by being intelligent about when the learner asks for help, we can even increase the learning speed for the same level of trainer interaction.
Dynamic Ambient Occlusion Using Homogeneous Subdivision

A metal silicide contact to silicon devices which has broad application to almost all of the variety of silicon semiconductor devices is described. This contact with a substantial side component has particular advantage as the base contact for a bipolar transistor. However, contacts can be made to regions of any desired device regions with a variety of P+, N+, P, N, P-, N- and so forth conductivity types. Further, the contact can be an ohmic or Schottky contact.
The effects of sampling and semantic categories on large-scale supervised relation extraction

The purpose of relation extraction is to identify novel pairs of entities which are related by a pre-specified relation such as hypernym or synonym. The traditional approach to relation extraction is to building a dedicated system for a particular relation, meaning that significant effort is required to repurpose the approach to new relations. We propose a generic approach based on supervised learning, which provides a standardised process for performing relation extraction on different relations and domains. We explore the feasibility of the approach over a range of relations and corpora, focusing particularly on the development of a realistic evaluation methodology for relation extraction. In addition to this, we investigate the impact of semantic categories on extraction effectiveness.
Mind the gap! Policies and practices of educational reception in Rotterdam and Barcelona

Maria Bruquetas Callejo onderzocht hoe middelbare scholen omgaan met het bestaande beleid voor de eerste opvang van allochtone studenten. Ze bekeek in welke mate de schoolpraktijken samenvallen met het beleid en in hoeverre zij afwijken van de basisbeginselen. Bruquetas Callejo vergeleek de situatie in Nederland (Rotterdam) en Spanje (Barcelona), twee landen die sterk verschillen op het gebied van nationaal integratiebeleid, onderwijssysteem en specifieke opvangprogramma’s. Ze laat zien dat er in beide gevallen een policy gap bestaat: de scholen in beide landen hebben opvangpraktijken die afwijken van het officiele integratiebeleid en van de opvangprogramma’s. In Barcelona is de kloof groter; men reageert vooral op de onmiddellijke pragmatische eisen van de situatie. In Rotterdam voldoen schoolpraktijken in het algemeen wel aan het ontvangstprogramma, maar maken scholen van eigen bevoegdheden gebruik om onderwijskansen van leerlingen te verbeteren. Bruquetas Callejo toont de relevantie van de lokale praktijk voor de beleidsuitvoering. Institutionele regelingen beinvloeden de praktijk in verschillende mate in verschillende lokale omstandigheden; het is dan ook belangrijk te onderzoeken welke contextuele elementen de naleving of de niet-naleving ondersteunen.
The Benchmark Book

Preface. 1. Introduction. 2. Scientific Benchmarks. 3. Graphics Benchmarks. 4. Network Benchmarks. 5. SPEC Benchmarks. 6. Business Application Performance Corporation (BAPCo) Benchmarks. 7. Transaction Processing Performance Council Benchmarks. 8. Neal Nelson & Associates Benchmarks. 9. AIM Technology Benchmarks. 10. Ziff-Davis Benchmarks. 11. Other Windows Benchmarks. 12. AutoCAD Benchmarks. 13. Hard Disk Benchmarks. 14. Other Benchmarks. Appendix 1: Summary of Benchmarks (Source, Purpose, History). Appendix 2: Benchmarks by Category. Appendix 3: Benchmarks by Applicaiton Area. Appendix 4: Resources. Annotated Bibliography. Acronym List. Glossary. Index.
Program understanding task in the contest of PSP

Our experiences with professional programming and software process improvement as well as our recent experience adapting the Personal Software Process (PSP) for a university undergraduate course lead us to formulate a PSP level 2.1 process script for a new task, Program Understanding. We recognize this task to be crucial in the software maintenance process in which an existing system must be understood before change can be planned and implemented. Personal Software Maintenance Process is our derivative of the PSP (4) with the program understanding task being its main addition. The paper presents this step following the standard PSP format.