Miracle-dz/UniFAR-FTUs huggingface dataset:
Clickstream Data Warehousing

From the Publisher: "Clickstream Data Warehousing is a great read for the serious data warehouse designer grappling with clickstream data. With a clear style, the authors explain the intricacies of this important source of customer behavior data. They combine engineering knowledge of the clickstream with state-of-the-art dimensional data warehouse design techniques to produce a very useful book. " Ralph Kimball, author of The Data Warehouse Toolkit and The Data Warehouse Lifecycle Toolkit The Web is an incredibly rich source of business intelligence, and many enterprises are scrambling to build data warehouses that capture the knowledge contained in the clickstream data from their Web sites. By analyzing the user behavior patterns contained in these clickstream data warehouses, savvy businesses can expand their markets, improve customer relationships, reduce costs, streamline operations, strengthen their Web sites, and hone their business strategies. Whether you come from an e-business, Web architecture, or data warehouse background, this book gives you the integrated perspective necessary to create a successful clickstream data warehouse. The first part of the book explains everything you need to know about the Web technology and IT infrastructure required to build a clickstream data warehouse. The second part of the book walks you through the process of designing and implementing a clickstream data warehouse, including: Planning, staffing, and managing the project Designing your clickstream data warehouse schema using the innovative meta-schema design template Picking the appropriate data warehouse software and storage subsystems to support your click-stream data warehouse Building the extract, transformation, and load (ETL) mechanism Delivering data to end users for analysis The companion Web site features additional reference material, an interactive question and answer forum, additional articles and information on data warehousing topics, and links to related Web sites. Wiley Computer Publishing Timely. Practical. Reliable. Author Biography: Mark Sweiger is President and Principal of Clickstream Consulting, a boutique consultancy specializing in clickstream data warehouses and data warehouse education. He is a noted author on data warehousing and is a speaker at The Data Warehousing Institute. Mark R. Madsen is Vice President and Principal of Clickstream Consulting. He has held various high-level positions within IT organizations and technology vendors and has extensive experience in data warehousing and supply chain management. Jimmy Langston is a Senior Consultant at Clickstream Consulting, where he advises clients on optimal data warehouse architectures, implementation, multidimensional database design, database configuration, and performance tuning. Howard Lombard is Chief Architect at Gazelle Consulting, Inc., a consultancy specializing in the design and implementation of large-scale data warehousing and business intelligence solutions.
Change in Teaching about Functions: Content Conceptions and Curriculum Reform.

A high school teacher's flexible and comprehensive mathematical content conceptions supported his implementation of an innovative curricular approach to functions. The teacher (Mr. Allen) was studied for 2 years, and this paper focuses primarily on year 2 findings about the subtle but meaningful changes which were noticeable in Mr. Allen's conceptions and instruction as he gained comfort with the new curriculum. In particular, the paper illustrates how Mr. Allen revised his pedagogical content conceptions through a complex interaction of his mathematical content conceptions and classroom e:. periences with studz,::. Z. :" Thcse results extend what _ means for conceptions and instruction to be interrelated, particularly in the context of instructional reform in mathematics. Contains 13 references. (Author) i.A. **. A**;c*AAA:cA*:::. *i.AAAA*;ckAA*A YAisA;. **. AA:,:cAi.k****************** * Reproductions supplied by EDRS are the best that can be made * * from the original document. * ***********,,,A************* ********. M.AAAA***************************
Caractérisation et détection de malware Android basées sur les flux d'information.

Les flux d’information sont des transferts d’information entre les objets d’un environnement donne. A l’echelle du systeme, pour toute information appartenant a une application donnee, les flux impliquant cette information decrivent comment l’application propage ses donnees dans le systeme et l’ensemble de ces flux peut ainsi etre considere comme un profil comportemental de l’application. A cause du nombre croissant d’applications malveillantes, il est devenu necessaire d’explorer des nouvelles techniques permettant de faciliter voir automatiser l’analyse et la detection de malware. Dans cette these, nous proposons ainsi une methode pour caracteriser et detecter les malware Android en nous basant sur les flux d’information qu’ils causent dans le systeme. Cette methode repose sur deux autres contributions de la these : AndroBlare, la version Android d’un moniteur de flux d’information du nom de Blare, et les graphes de flux systeme, une structure de donnee representant de maniere compacte et humainement comprehensible les flux d’information observes. Nous avons evalue avec succes notre approche en construisant le profil de 4 malware differents et avons montre que ces profils permettaient de detecter l’execution d’applications infectees par les malware dont on a un profil.
EMPIRICAL STUDIES OF ANDROID API USAGE: SUGGESTING RELATED API CALLS AND DETECTING LICENSE VIOLATIONS

We mine the API method calls used by Android App developers to (1)suggest related API calls based on the version history of Apps, (2) suggest related API calls based on StackOverflow posts, and (3) find potential App copyright and license vio- lations based the similarity of API calls made by them. Zimmermann et al suggested that i? ½Programmers who changed these functions also changedi? ½ functions that could be mined from previous groupings of functions found in the version history of a system. Our first contribution is to expand this approach to a community of Apps. Android developers use a set of API calls when creating Apps. These API methods are used in similar ways across multiple applications. Clustering co-changing API methods used by 230 Android Apps, we are able to predict the changes to API methods that individual App developers will make to their application with an average precision of 73% and recall of 25%. Our second contribution can be characterized as i? ½Programmers who discussed these functions were also interested in these functions.i? ½ Informal discussion on Stack- Overflow provides a rich source of related API methods as developers provide solu- tions to common problems. Clustering salient API methods in the same highly ranked posts, we are able to create rules that predict the changes App developers will make with an average precision of 64% and recall of 15%. Our last contribution is to find out whether proprietary Apps copy code from open source Apps, thereby violating the open source license. We have provided a set of techniques that determines how similar two Apps are based on the API calls they make. These techniques include android API calls matching, API calls coverage, App categories, Method/Class clusters and released size of Apps. To validate this approach we conduct a case study of 150 open source project and 950 proprietary projects.
Cluster detection and analysis with geo-spatial datasets using a hybrid statistical and neural networks hierarchical approach

Spatial datasets contain information relating to the locations of incidents of phenomena for example, crime and disease. Areas that contain a higher than expected incidence of the phenomena, given background population and census datasets, are of particular interest. By analysing the locations of potential influence, it may be possible to establish where a cause and effect relationship is present in the observed process. Cluster detection techniques can be applied to such datasets in order to reveal information relating to the spatial distribution of the cases. Research in these areas has mainly concentrated on either computational or statistical aspects of cluster detection. Each clustering algorithm has its own strengths and weakness. Their main weaknesses causing their unreliability can be estimating the number of clusters, testing the number of components, selecting initial seeds (centroids), running time and memory requirements. Consequently, a new cluster detection methodology has been developed in this thesis based on knowledge drawn from both statistical and computing domains. This methodology is based on a hybrid of statistical methods using properties of probability rather than distance to associate data with clusters. No previous knowledge of the dataset is required and the number of clusters is not predetermined. It performs efficiently in terms of memory requirements, running time and cluster quality. The algorithm for determining both the centre of clusters and the existence of the clusters themselves was applied and tested on simulated and real datasets. The results which were obtained from identification of hotspots were compared with results of other available algorithms such as CLAP (Cluster Location Analysis Procedure), Satscan and GAM (Geographical Analysis Machine). The outputs are very similar.
The Key Dimensions of Criteria for the Evaluation FNA Selection of ISPS: An Exploratory Study

The progressive advancements in information technology (IT) coupled with the global expansion of communication infrastructure has enabled firms to create and sustain large scale strategic advantages, with the result of an ever-increasing demand from firms for new types of information services (IS) to facilitate and coordinate their daily operations. Hence, the aim of this research is to explore the underlying dimensions of criteria for the evaluation and selection of information service providers (ISPs). By undertaking a review of the literature, we first analyze the dynamics of ISPs to define their present day role before going on to develop a questionnaire for the field survey. Based on the data collected from 57 firms, two distinct procedures are adopted to carry out the exploratory factor analyses in order to derive the preliminary factor solutions. Followed by a process of post-analysis validation, these empirically derived factor solutions are reviewed and refined in accordance with domain experts' opinions, and as a result, the final factor solution is obtained. It is hoped that through the utilization of mechanical factor analyses and subsequent manual validation, it will be possible to achieve both “parsimony” and “inclusiveness” of the final factor solution. This study results that there are seven dimensions of criteria which are critical to the evaluation and selection of ISPs: (1) performance of information systems; (2) awareness of and response to customer requirements; (3) ISP's market capability; (4) performance of networking; (5) ISP's credibility and fame; (6) provision of customized professional services; and (7) innovative R&D into technology.
Three-dimensional gyrokinetic particle-in-cell simulation of plasmas on a massively parallel computer: Final report on LDRD Core Competency Project, FY 1991--FY 1993

One of the programs of the Magnetic fusion Energy (MFE) Theory and computations Program is studying the anomalous transport of thermal energy across the field lines in the core of a tokamak. We use the method of gyrokinetic particle-in-cell simulation in this study. For this LDRD project we employed massively parallel processing, new algorithms, and new algorithms, and new formal techniques to improve this research. Specifically, we sought to take steps toward: researching experimentally-relevant parameters in our simulations, learning parallel computing to have as a resource for our group, and achieving a 100 {times} speedup over our starting-point Cray2 simulation code`s performance.
Named entities : recognition, classification and use

1. Foreword 2. Articles 3. A survey of named entity recognition and classification (by Nadeau, David) 4. Diversity in logarithmic opinion pools (by Smith, Andrew D.M.) 5. Handling conjunctions in named entities (by Mazur, Pawel) 6. Complex named entities in Spanish texts: Structures and properties (by Galicia-Haro, Sofia N.) 7. Named Entity Recognition and transliteration in Bengali (by Ekbal, Asif) 8. A note on the semantic and morphological properties of proper names in the Prolex project (by Vitas, Dusko) 9. Cross-lingual Named Entity Recognition (by Steinberger, Ralf) 10. Index
Identification of Auto Programs by Using Decision Tree Learning for MMORPG

Auto-playing programs are often used in behalf of human players in MMORPG(Massively Multi-player Online Role Playing Game). By playing automatically and continuously, it helps to speed up the game character's level-up process. However, the auto-playing programs, either software or hardware, do harm to games servers in various ways including abuse of resources. In this paper, we propose a way of detecting the auto programs by analyzing the window event sequences produced by the game players. In our proposed method, the event sequences are transformed into a set of attributes, and the Decision Tree learning is applied to classify the data represented by the set of attribute values into human or auto player. The results from experiments with several MMORPG show that the Decision Tree learning with proposed method can identify the auto-playing programs with high accuracy.
Layout Essentials: 100 Design Principles for Using Grids

This book will outline and demonstrate basic layout/grid guidelines and rules through 100 entries including choosing the right typeface for a project, striving for rhythm and balance with type, combining typefaces, using special characters, and kerning and legibility. These essentials of grid design are critical to the success of any job.
An exploration of distributed parallel sorting in GSS

11 1 Introduction 12 1.1 Purpose of the research 15 2 Achieving convergence in collaborative environments 17 2.1 The facilitation bottleneck 18 2.1.1 The characteristics of a skilled facilitator 19 2.1. 2 The costs of a skilled facilitator 20 2.2 The importance of backchannel feedback 21 2.3 The next generation of collaboration methods and design 22 2.3.1 ThinkLets 22 2.3.2 Participant-driven GSS (PD-GSS) 23 2.4 Cognitive load 26 2.4. 1 The measurement of cognitive load 29 2.5 Normalized clustering error (NCE) 31 3 Methods 34 3.1 Research questions and hypotheses 34 3.2 Independent variables and experimental treatments 35 3.3 Dependent variables and data collection 36
Machine learning email prediction system (MLEPS)

Nowadays, email has become one of the most critical personal and business applications and email users would experience serious consequences if email messages could not be available or experience high volume of messages which lead to congestions, overloads and limited storage space coupled with unstructured messages in mail boxes. A few years ago, the means of communication are via letters by post, telegraph, fax, couriers to mention a few but now the focus has changed to a faster means of obtaining quick responses and faster ways of communication-emails. We propose a new framework to help organise and prioritize email better; Machine learning email prediction system (MLEPS). The goal is to organise emails better in mail boxes, prioritise emails based on the focus of the email content. The intelligent email prediction system helps to improve email users’ performances, saves time, very effective and efficient tool and is cost effective for businesses and for personal use. The system is evaluated against a corpus of human-judged predictions, reaching satisfactory level of performance.
Traffic Sign Recognition Using Hybrid Camera System

Traffic sign recognition systems can be used to assist drivers and improve road safety. The system is expected to recognize traffic signs at even greater distances in order to give drivers as much warning as possible based on the road conditions. A hybrid camera system is proposed in this paper with the goal of increasing the recognition distance compared to the conventional systems. In this system, an active telephoto camera is used as an assistant to a wide angle camera. Traffic sign detection and classification are processed separately for the different images from the wide angle camera and telephoto camera, respectively. The image from the telephoto camera provides enough information for a classification when the resolution of the detected traffic sign is low from the wide angle camera. The experimental results demonstrated that the recognition distance of the proposed system is improved compared to the conventional systems.
Secureqemu: Emulation-Based Software Protection Providing Encrypted Code Execution and Page Granularity Code Signing

Abstract : This research presents an original emulation-based software protection scheme providing protection from reverse code engineering (RCE) and software exploitation using encrypted code execution and page-granularity code signing, respectively. Protection mechanisms execute in trusted emulators while remaining out-of-band of untrusted systems being emulated. This protection scheme is called SecureQEMU and is based on a modified version of Quick Emulator (QEMU). RCE is a process that uncovers the internal workings of a program. It is used during vulnerability and intellectual property (IP) discovery. To protect from RCE program code may have anti-disassembly, anti-debugging, and obfuscation techniques incorporated. These techniques slow the process of RCE, however, once defeated protected code is still comprehensible. Encryption provides static code protection, but encrypted code must be decrypted before execution. SecureQEMUs' scheme overcomes this limitation by keeping code encrypted during execution. Software exploitation is a process that leverages design and implementation errors to cause unintended behavior which may result in security policy violations. Traditional exploitation protection mechanisms provide a blacklist approach to software protection. Specially crafted exploit payloads bypass these protection mechanisms. SecureQEMU provides a whitelist approach to software protection by executing signed code exclusively. Unsigned malicious code (exploits, backdoors, rootkits, etc.) remain unexecuted, therefore, protecting the system. SecureQEMUs' cache mechanisms increase performance by 0.9% to 1.8% relative to QEMU. Emulation overhead for SecureQEMU varies from 1400% to 2100%. SecureQEMUs' performance increase is negligible with respect to emulation overhead. Dependent on risk management strategy, SecureQEMU's protection benefits may outweigh emulation overh
Optimal Downlink BeamformingUsing Semidefinite Optimization

When using antenna arrays at the base station of a cellular system, one critical aspectis the transmission strategy. An optimal choice of beamformers for simultaneous transmissionto several co-channel users must be solved jointly for all users and base stations in anarea. We formulate an optimal transmit strategy and show how the solution can be calculatedefficiently using interior point methods for semidefinite optimization. The algorithmminimizes the total transmitted power under certain constraints to guarantee a specificquality of service. The method provides large flexibility in the choice of constraints andcan be extended to be robust to channel perturbations.
Radio Channels Modeling for Adaptive Antennas Applications – Analysis of Elevation, Azimuth and Delay Spread

Research of modeling urban environment channel has been presented in this paper. Measurements were performed for 2.2 GHz band. Test environment was based on existing 3G sites. Elevation, delay and azimuth spreads were analyzed. Both theoretical channel modeling and similar tests campaign were subject for analysis in this paper. Based on radio channel modeling further investigations are presented and the adaptive antenna implementation was proposed. Keywords—adaptive antenna, cellular systems, radio channel modeling.
Dynamics, causation, duration in the predicate-argument structure of verbs : a computational approach based on parallel corpora

This dissertation addresses systematic variation in the use of verbs where two syntactically different sentences are used to express the same event. We show that the frequency distribution of the syntactic alternants depends on the meaning of the verbs: force dynamics in light verb constructions, external causation in lexical causatives, and duration in verb aspect classes. Both intra-linguistic and cross-linguistic variation in morphological and syntactic realisations of semantically equivalent items are taken into account by analysing data extracted from parallel corpora. The three semantic properties are empirically induced on the basis of the observations automatically extracted from large parallel corpora, which are automatically parsed and word-aligned. The generalisations are learned from the extracted data automatically using statistical inferences and machine learning techniques. The accuracy of the predictions made on the basis of the generalisations is assessed experimentally on an independent set of test instances.
COMPARA: Sentence alignment revision and markup

Note: COMPARA is a project developed under the scope of Linguateca, supported by grant POSI/PLP/43931/2001 from Fundação para a Ciência e Tecnologia (Portugal), co-financed by POSI. Ana Frankenberg-Garcia and Diana Santos are joint project leaders of COMPARA. For further information, please see
Practical Byzantine fault tolerance for service oriented architectures

OF THE DISSERTATION Practical Byzantine Fault Tolerance for Service Oriented Architectures by Sajeeva Lakmal Bandara Pallemulle Doctor of Philosophy in Computer Science Washington University in St. Louis, 2009 Research Advisor: Dr. Kenneth J. Goldman Mission-critical services must be replicated to guarantee correctness and high availability in spite of arbitrary (Byzantine) faults. Prior Byzantine-fault-tolerance (BFT) protocols guarantee safety and liveness of a limited class of replicated services that adhere to a severely restrictive service model. These protocols support only passive services that do not process long-lived computations in ongoing threads. Furthermore, most protocols support only self-contained services that do not process nested computations where sub-tasks are outsourced to third-party services. Additionally, protocols that support nested computations fail to preserve the safety and liveness of replicated calling services when target services are faulty, leading to cascading failures in tiered architectures. Prior protocols also do not support asynchronous invocations from replicated calling services leading to greatly reduced throughput. These and other limitations make these protocols unsuitable for Service Oriented Architectures that combine the functionality advertised by mutually-independent services to perform high-level tasks.