Miracle-dz/UniFAR-FTUs huggingface dataset:
GSnet: An Integrated Tool for Gene Set Analysis and Visualization

The Gene Set network viewer (GSnet) visualizes the functional enrichment of a given gene set with a protein interaction network and is implemented as a plug-in for the Cytoscape platform. The functional enrichment of a given gene set is calculated using a hypergeometric test based on the Gene Ontology annotation. The protein interaction network is estimated using public data. Set operations allow a complex protein interaction network to be decomposed into a functionally-enriched module of interest. GSnet provides a new framework for gene set analysis by integrating a priori knowledge of a biological network with functional enrichment analysis.
Object detection on the sea surface, based on texture analysis

This paper deals with the problem of OOI detection on the sea surface, based on the definition of proper texture parameters. As the sea texture exhibits a variable nature, the classical algorithms, tailored to work in presence of a specific textured background, can not be applied. However they can be seen as possible components of a hierarchical algorithm, taking into account the variability of the sea texture. In this paper an algorithm (called OBI-FINDER), with these characteristics, is described, and some results are shown.
Theory and design of multipulse multicarrier systems for wireless communications

We introduce multipulse multicarrier (MPMC) modulation, a novel wireless communication scheme that features several advantages over traditional single-pulse multicarrier systems. Multipulse Gabor Riesz bases are provided as mathematical foundation of MPMC systems and vector formulations and equivalent Zak-Fourier domain formulations for MPMC modulator and demodulator are presented. We further derive biorthogonality conditions ensuring perfect symbol recovery for MPMC systems operating over ideal channels. Finally, efficient design methods for MPMC systems are presented and illustrated with numerical examples.
Building and Managing the Meta Data Repository: A Full Lifecycle Guide

From the Publisher: "This is the first book to tackle the subject of meta data in data warehousing, and the results are spectacular . David Marco has written about the subject in a way that is approachable, practical, and immediately useful. Building and Managing the Meta Data Repository: A Full Lifecycle Guide is an excellent resource for any IT professional. " -Steve Murchie Group Product Manager, Microsoft Corporation. Meta data repositories can provide your company with tremendous value if they are used properly and if you understand what they can, and can't, do. Written by David Marco, the industry's leading authority on meta data and well-known columnist for DM Review, this book offers all the guidance you'll need for developing, deploying, and managing a meta data repository to gain a competitive advantage. After illustrating the fundamental concepts, Marco shows you how to use meta data to increase your company's revenue and decrease expenses. You'll find a comprehensive look at the major trends affecting the meta data industry, as well as steps on how to build a repository that is flexible enough to adapt to future changes. This vendor-neutral guide alsoincludes complete coverage of meta data sources, standards, and architecture, and it explores the full gamut of practical implementation issues.Taking you step-by-step through the process of implementing a meta data repository, Marco shows you how to: *Evaluate meta data tools *Build the meta data project plan *Design a custom meta data architecture *Staff a repository team *Implement data quality through meta data *Create a physical meta data model *Evaluate meta data delivery requirements TheCD-ROMincludes: *A sample implementation project plan *A function and feature checklist of meta data tool requirements *Several physical meta datamodels to support specific business functions
Thinking about sound and space: Recording people's emotional responses to spaces

In this paper we explore what EEG techniques teach us about people's responses to environments. We explain two complementary projects: a sound art installation in which a performer was rigged up with an EEG device and required to sit for 30 minutes in a chair. Around him were positioned custom-made instruments for generating electro-mechanical sounds. A screen behind the performer showed a dynamic geometrical image that altered according to his mood state and as picked up by EEG (engagement, meditation, frustration and excitement), while a sound technologist operated the instruments. We used the same sound sources for an experiment in which we tested people's responses to sounds. We discuss the spatial implications of this work.
Efficient Bayesian active learning and matrix modelling

With the advent of the Internet and growth of storage capabilities, large collections of unlabelled data are now available. However, collecting supervised labels can be costly. Active learning addresses this by selecting, sequentially, only the most useful data in light of the information collected so far. The online nature of such algorithms often necessitates efficient computations. Thus, we present a framework for information theoretic Bayesian active learning, named Bayesian Active Learning by Disagreement, that permits efficient and accurate computations of data utility. Using this framework we develop new techniques for active Gaussian process modelling and adaptive quantum tomography. The latter has been shown, in both simulation and laboratory experiments, to yield faster learning rates than any non-adaptive design. Numerous datasets can be represented as matrices. Bayesian models of matrices are becoming increasingly popular because they can handle noisy or missing elements, and are extensible to different data-types. However, efficient inference is crucial to allow these flexible probabilistic models to scale to large real-world datasets. Binary matrices are a ubiquitous datatype, so we present a stochastic inference algorithm for fast learning in this domain. Preference judgements are a common, implicit source of binary data. We present a hybrid matrix factorization/Gaussian process model for collaborative learning from multiple users’ preferences. This model exploits both the structure of the matrix and can incorporate additional covariate information to make accurate predictions. We then combine matrix modelling with active learning and propose a new algorithm for cold-start learning with ordinal data, such as ratings. This algorithm couples Bayesian Active Learning by Disagreement with a heteroscedastic model to handle varying levels of noise. This ordinal matrix model is also used to analyze psychometric questionnaires; we analyze classical assumptions made in psychometrics and show that active learning methods can reduce questionnaire lengths substantially.
Mobile location tracking by optimal paging zone partitioning

This paper presents a new mobile location tracking strategy in a cellular mobile network. The forward control channel (FOCC) in the cellular mobile network carries the page message and other system order information to a mobile station (MS). The FOCC has been experiencing severe congestion because of overloaded page messages. In order to relieve the bottleneck problem in the FOCC, a new mobile location tracking scheme by optimal paging zone partitioning is developed.
On exploiting interbeat correlation in compressive sensing-based ECG compression

Compressive Sensing (CS) is an emerging data acquisition scheme with the potential to reduce the number of measurements required by the Nyquist sampling theorem to acquire sparse signals. We recently used the interbeat correlation to find the common support between jointly sparse adjacent heartbeats. In this paper, we fully exploit this correlation to find the magnitude, in addition to the support of the significant coefficients in the sparse domain. The approach used for this purpose is based on sparse Bayesian learning algorithms due to its superior performance compared to other reconstruction algorithms and the fact that being a probabilistic approach facilitates the incorporation of correlation information. The reconstruction includes, in the first place, the detection of the R peaks and the length normalization of ECG cycles to take advantage of the quasi-periodic structure. Since the common support reduces as the number of heartbeats increases, we propose the use of a sliding window where the support maintains approximately constant across cycles. The sparse Bayesian algorithm adaptively learns and exploits the high correlation between the heartbeats in the constructed window. Experimental results show that the proposed method reduces significantly the number of measurements required to achieve good reconstruction quality, validating the potential of using correlation information in compressed sensing-based ECG compression.
A modular three-dimensional finite-difference ground-water flow model

A computer program for simulating ground-water flow in three dimensions is presented. This report includes detailed explanations of physical and mathematical concepts on which the model is developed. Ground-water flow within the aquifer is simulated by using a block-centered finite-difference approach. The program is written in Fortran 77 and has a modular structure, which permits the addition of new packages to the program without modifying existing packages.
PDS: Direct Search Methods for Unconstrained Optimization on Either Sequential or Parallel Machines

Abstract : PDS is a collection of Fortran subroutines for solving unconstrained nonlinear optimization problems using direct search methods. The software is written so that execution on sequential machines is straightforward while execution on Intel distributed memory machines, such as the iPSC/2, the iPSC/860 or the Touchstone Delta, can be accomplished simply by including a few well-defined routines containing calls to Intel-specific Fortran libraries. Those interested in using the methods on other distributed memory machines, even something as basic as a network of workstations or personal computers, need only modify these few subroutines to handle the global communication requirements. Furthermore, since the parallelism is clearly defined at the "doloop" level, it is a simple matter to insert compiler directives that allow for execution on shared memory parallel machines. Included here is an example of such directives, contained in comment statements, for execution on a Sequent Symmetry S81.
Paul Klee: Painting Music

Now available in flexi-cover, this fascinating work examines the relationship between music and painting in Paul Klee's art. A talented violinist as well as a painter, Klee drew much of the inspiration for his abstract art from musical rhythms and structures. Like a composer, he developed and harmonized pictorial themes, weaving a complex series of signs and symbols into his painting. The book focuses on Klee's decadelong tenure at the Bauhaus, where the artist's theories and practices first merged. Illustrated throughout with full-color reproductions of Klee's paintings and etchings, as well as entries from his diaries, this unique study sheds light on an important aspect of Klee's work while providing insights into his development as an abstract artist.
Ascertain the information seeking behavior of Computer Science students

Postgraduate students of computer science have received little empirical attention from researchers in the field of Library Information Science; their information seeking behaviors often resembles those of either other faculties or undergraduates. With higher level of education and information technology background, postgraduate students of computer science ought to have a different information seeking behavior. Therefore it is interesting to explore their information seeking behaviors and to investigate to what extent they might constitute a unique user group. The objective of this research is to explore and analyze computer science postgraduate student’s information seeking behaviors. A Survey was conducted at Faculty of Science Computer and Information Technology, University of Malaya. The sample consists of 140 postgraduate students. The quantitative data were analyzed using the statistical program SPSS. The results provide an insight into how computer sciences postgraduate students seek for information. With their IT skills and experience in seeking information, they can find a lot of information but they have problem with information overload and how to evaluate the information that they find.
Virtual Anthropology and its Application in Cultural Heritage Studies

ABSTRACT The remains that typically compose the human fossil record often bear cracks, damage, and deformations. The recent rapid development of ‘virtual anthropology’ has provided innovative tools to manage, study, and preserve cultural and natural heritage. Such tools include computerized tomography (CT), laser scanning, photogrammetry, 3D imaging, and rapid prototyping. These approaches can contribute to any archaeological context from the discovery of artefacts to research, preservation, and dissemination. 3D imaging techniques can substitute physical intervention with a virtual protocol to restore the original shape of a fossil specimen. In a similar way, digital morphological information can be recovered using data preserved even on a fragment through the use of 3D comparative samples. Here we present an extended and updated review of the most innovative protocols in virtual anthropology, also applicable in other fields such as natural history and cultural heritage studies, through the description of recent cast studies.
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Indoor Spatial Awareness

These proceedings contain the papers selected for presentation at the Second International Workshop on Indoor Spatial Awareness, hosted by ACM SIGSPATIAL and held in conjunction with the18th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS 2010). With the increasing deployment of location-based services, geographic information systems, and ubiquitous computing, we are witnessing a need to consider indoor spaces in addition to the traditional outdoor spaces. Indoor spaces exhibit a highly relevant third dimension; they may have privately regulated access restrictions; they are relatively uniform and lack global landmarks; they feature special indoor positioning systems; and their representations are often poorly integrated with those of outdoor spaces. New theories, data models, and systems are needed in order to provide integrated, seamless services across all spaces. For this reason, research has begun to extend the scope of location-based services and GIS to indoor spaces, with the objective of supporting indoor orientation and navigation services, emergency management, indoor space management, 3D cadastre, etc. This workshop brought together researchers, developers, and practitioners carrying out research and development related to indoor spatial awareness, and it provided a forum for interdisciplinary discussion of diverse aspects of indoor spatial awareness. The full-paper peer-reviewed papers concern roughly two aspects of indoor spatial awareness: indoor positioning and navigation, and modeling of indoor spaces. In addition to the selected papers the program also featured invited talks to each of these themes. Lars Kulik from the University of Melbourne, Australia, presented an overview of several recent research projects in active indoor environments, and keynote speaker Ben Kuipers from University of Michigan, USA, talked about the use of ontologies in spatial exploration and mapping. The combined program made for a thought-provoking, inspiring workshop that offered ample opportunities for the exchange of ideas.
Weak-consistency group communication and membership

Many distributed systems for wide-area networks can be built conveniently, and operate efficiently and correctly, using a weak consistency group communication mechanism. This mechanism organizes a set of principals into a single logical entity, and provides methods to multicast messages to the members. A weak consistency distributed system allows the principals in the group to differ on the value of shared state at any given instant, as long as they will eventually converge to a single, consistent value. A group containing many principals and using weak consistency can provide the reliability, performance, and scalability necessary for wide-area systems. I have developed a framework for constructing group communication systems, for classifying existing distributed system tools, and for constructing and reasoning about a particular group communication model. It has four components: message delivery, message ordering, group membership, and the application. Each component may have a different implementation, so that the group mechanism can be tailored to application requirements. The framework supports a new message delivery protocol, called timestamped anti-entropy, which provides reliable, eventual message delivery; is efficient; and tolerates most transient processor and network failures. It can be combined with message ordering implementations that provide ordering guarantees ranging from unordered to total, causal delivery. A new group membership protocol completes the set, providing temporarily inconsistent membership views resilient to up to k simultaneous principal failures. The Refdbms distributed bibliographic database system, which has been constructed using this framework, is used as an example. Refdbms databases can be replicated on many different sites, using the group communication system described here.
Secrecy, authentication, and public key systems

An automatic control system for a tube expander tool of the type having a hydraulically powered rotary tool which is advanced and retracted by a reversible linear motor. Operation of automatic cycling is initiated by a manual control whereas axial movement of the tool can be interrupted at any time by operating a hold control while rotation of the tool continues as long as necessary to iron out excess metal or to reposition the tube in the bore should this be desirable. The tool is maintained under constant load at all times by load sensor means in the tool advancing circuit and operable to vary the rate of tool advance to maintain a desired constant load and to prevent overloading. Accordingly, the rate of tool advance varies inversely as the load on the tool.
Controlling fine grain nonnumeric parallelism on a combinator-based multiprocessor system

ion Rules A X [hd •. tl] = O [ S p ( A X [ h d ] ) (A x [f/])] A X [f g] = O [5 (A X [/]) (A x [g])] A x [. r] = / A x [i/] = K y if X does not occur in y Optimization Rules for Regular Combinators o Is (An ni ° f «' *>1 = ^1/ Optimization Rules for List-Oriented Combinators 0 [ S p { K f ) { K g ) ] = K i f : g ) O [ S p ( K f ) g ] = B p f g O [ S p f { K f l ) ] = C p f g A a; [/]: Abstracting x from /. O [e]: Optimizing expression e. Figure 2.4: Turner's Original Abstraction Algorithm
Type-based analysis of security APIs

A Security API is an interface between processes running at different levels of trust with the aim of assuring that a specific security policy holds. It allows an untrusted system to access the functionalities offered by a trusted secure resource assuring that no matter what sequence of the API commands are invoked, the intended security policy is satisfied. This kind of API is often developed having in mind a target application and how it will typically use the available services. It is thus easy to miss the fact that some functionalities could be used in a malicious way to break the intended security policy. In fact, a number of attacks to existing security APIs have been found in the last years. This thesis proposes a type-based analysis to verify the security of these critical components. Language-based analysis is, in fact, a powerful tool to formally prove security and, at the same time, helps API developers to understand the root-causes of known vulnerabilities affecting APIs and guides them in programming secure code. A security API which slowly leaks secret data to an attacker capable to spot interferences between input parameters and a command output can be secured by a noninterference policy. The thesis extends the setting of language-based information flow security to account for cryptographic expressions (both randomized and deterministic ones) and applies the obtained results to analyse the ATM PIN verification API. A possible fix to it is also proposed and shown to be secure by typing. A security API which, instead, directly releases a secret value as the result of a sequence of legal commands will be analysed with a type system ensuring that data secrecy is preserved at run-time. The thesis presents the case of programs implementing key management functionalities and proposes a type system to reason on the security of RSA PKCS#11 API and verify the correctness of a novel patch to it.
Combining theoretical knowledge and artificial neural networks for power system topology verification

Topology errors, i.e. errors resulting from incorrect modelling of power network connections may be a source of serious errors in various power system applications. Errors in power-system topology are difficult to handle with classical methods based on state estimation. The problem of power system topology verification has been also solved using artificial neural networks (ANNs). It should be pointed out that implementation of pure neural models, where theoretical knowledge on power system is neglected, are not too effective. The paper presents new approach to topology verification based on combining ANN's technique and larger theoretical knowledge on the power system (and its model) than it is in the case of other approaches. After utilized knowledge on the power system (and its model) is characterized the idea of the approach is outlined. Then, a computational example of the verification using the new approach is given. At the end, the features of the considered approach are discussed.
Multilevel Security with Data Compression and Restricted Character Set Translation

Abstract : Multilevel military communication security can be implemented with the notion of master keys. Naval message traffic is transmitted with restricted character set and optionally files are compressed. Both character translation and data compression can be used as add-on data encryption. A master key is constructed from a set of service keys from which master key is allowed to access. This thesis presents the principles of multilevel security with restricted character translation, data compression, and master key implementation. Master key; LZSS; Shannon-Fano coding; Expansion Ratio; Recovery.