Miracle-dz/UniFAR-FTUs huggingface dataset:
Singular-Vector Perturbation Growth in a Primitive Equation Model with Moist Physics

Abstract Finite-time growth of perturbations in the presence of moist physics (specifically, precipitation) is investigated using singular vectors (SVs) in the context of a primitive equation regional model. Two difficulties appear in the explicit consideration of the effect of moist physics when studying such optimal growth. First, the tangent-linear description of moist physics may not be as straightforward and accurate as for dry-adiabatic processes; second, because of the consideration of moisture, the design of an appropriate measure of growth (i.e., norm) is subject to even more ambiguity than in the dry situation. In this study both of these problems are addressed in the context of the moist version of the National Center for Atmospheric Research Mesoscale Adjoint Modeling System, version 2, with emphasis on the second problem. Leading SVs are computed in an iterative fashion, using a Lanczos algorithm, for three norms over an optimization interval of 24 h; these norms are based on an expression re.
Persistent Bidirectional Peer Traffic in Fix-network augmented Broadband Wireless Access

Currently, the Internet is experiencing the grid accelerated file transfer phenomenon (swarming). It has gained immense popularity and dominance through BitTorrent and has thus far accounted for a substantial amount of the total Internet traffic. In this paper, we borrow ideas liberally from the literature to argue that the use of swarming protocol for traffic/content delivery within the wireless networking milieu is inefficient. We generalize the problem into the delivery of persistent bidirectional peer traffic in wireless hierarchical topology, and further argue that current approaches for fixnetwork augmented broadband wireless access (e.g. 802.11x) has left the problem ill-addressed. A novel system architecture is sketched to rectify such a shortcoming. Hence, the purpose of this short position paper is to stimulate ideas and proposals that may result into important avenues of future research. Keywords— swarming, cross-layer design, wireless communication architecture
Beyond Multimedia Adaptation: Quality of Experience-Aware Multi-Sensorial Media Delivery

Multiple sensorial media (mulsemedia) combines multiple media elements which engage three or more of human senses, and as most other media content, requires support for delivery over the existing networks. This paper proposes an adaptive mulsemedia framework (ADAMS) for delivering scalable video and sensorial data to users. Unlike existing two-dimensional joint source-channel adaptation solutions for video streaming, the ADAMS framework includes three joint adaptation dimensions: video source, sensorial source, and network optimization. Using an MPEG-7 description scheme, ADAMS recommends the integration of multiple sensorial effects (i.e., haptic, olfaction, air motion, etc.) as metadata into multimedia streams. ADAMS design includes both coarse- and fine-grained adaptation modules on the server side: mulsemedia flow adaptation and packet priority scheduling. Feedback from subjective quality evaluation and network conditions is used to develop the two modules. Subjective evaluation investigated users' enjoyment levels when exposed to mulsemedia and multimedia sequences, respectively and to study users' preference levels of some sensorial effects in the context of mulsemedia sequences with video components at different quality levels. Results of the subjective study inform guidelines for an adaptive strategy that selects the optimal combination for video segments and sensorial data for a given bandwidth constraint and user requirement. User perceptual tests show how ADAMS outperforms existing multimedia delivery solutions in terms of both user perceived quality and user enjoyment during adaptive streaming of various mulsemedia content. In doing so, it highlights the case for tailored, adaptive mulsemedia delivery over traditional multimedia adaptive transport mechanisms.
Een analyse van de relatie tussen KI en woning- prijzen in de Vlaamse centrumsteden

In Belgium property taxes are based on the assessed rental value of a property. This value, the so-called cadastral revenue, is entrenched -but not undisputed- in our tax policy. Due to the rigid and outdated character of this tax base, a growing sense of unfairness surrounds the derived property tax (oov). This paper uncovers the relationship between the cadastral revenue and the selling price of houses in Flanders, focusing on the centre cities. Special attention is paid to the demand for horizontal equity, implying that equal positions lead to equal taxation. The data show a clear linear relation between the cadastral revenue and the sell-ing price, with slightly higher cadastral revenues for similar-priced houses in the centre cities. Further analysis, however, unveils a wide spread in cadastral revenues for equivalent properties. Moreover, the fiscal favor treatment “Klein Beschrijf” is poorly linked to the value of a property, discriminating between equivalent properties. Consequently, it is obvious that the cadastral revenue fails the horizontal equity test and needs far-reaching revisions.
Concept Chain Graphs : A Hybrid IR Framework for Biomedical Text Mining

The area of biomedical text mining has seen much research activity due to the increased volume of literature that must be examined. Researchers need to validate and interpret their experimental results; this entails scouring through a massive amount of potentially relevant literature for clues that may shed light on their findings. An ideal situation would allow a user to interactively search through the literature based on a discovery phase after the initial search; this combined searching, text mining/browsing, filtering and repeated search process goes beyond the capability of existing IR frameworks. A new hybrid framework for information retrieval (IR) systems and text mining, namely concept chain graphs (CCG) is discussed. This integrates a traditional word-based IR model with higher-level concepts and associations obtained from an information extraction (IE) system. This probabilistic network is a richer representation of a document collection that facilitates better visualization and analysis of information than existing IR or relational representations. Initial experiments illustrating CCGs for (i) viewing attributes of a gene, and (ii) associations between genes through an attribute are presented.
This Time It's Personal: from PIM to the Perfect Digital Assistant

Interacting with digital PIM tools like calendars, to-do lists, address books, bookmarks and so on, is a highly manual, often repetitive and frequently tedious process. Despite increases in memory and processor power over the past two decades of personal computing, not much has changed in the way we engage with such applications. We must still manually decompose frequently performed tasks into multiple smaller, data specific processes if we want to be able to recall or reuse the information in some meaningful way. "Meeting with Yves at 5 in Stata about blah" breaks down into rigid, fixed semantics in separate applications: data to be recorded in calendar fields, address book fields and, as for the blah, something that does not necessarily exist as a PIM application data structure. We argue that a reason Personal Information Management tools may be so manual, and so effectively fragmented, is that they are not personal enough. If our information systems were more personal, that is, if they knew in a manner similar to the way a personal assistant would know us and support us, then our tools would be more helpful: an assistive PIM tool would gather together the necessary material in support of our meeting with Yves. We, therefore, have been investigating the possible paths towards PIM tools as tools that work for us, rather than tools that seemingly make us work for them. To that end, in the following sections we consider how we may develop a framework for PIM tools as "perfect digital assistants" (PDA). Our impetus has been to explore how, by considering the affordances of a Real World personal assistant, we can conceptualize a design framework, and from there a development program for a digital simulacrum of such an assistant that is not for some far off future, but for the much nearer term.
Error detection of oceanic observation data using sequential labeling

Globally-covered ocean monitoring system Argo with more than 3,600 small and light-weight drifting buoys is always working for oceanic temperature and salinity measurement. The accumulated big ocean observation data helps many studies such as investigation into climate change mechanism. Although human experts visually confirm and revise quality control (QC) labels, it is difficult to regularize the quality of the ocean observation data of all over the world. Therefore, this paper proposes a method for error detection in Argo observation data to realize an automatic QC with high accuracy equal to human experts. The target dataset is imbalanced data and requires consideration of sequence of both features and quality labels for accurate labeling in each depth. The proposed method utilizes Conditional Random Field (CRF) to assign quality labels for observed temperature and salinity values, and adopts Support Vector Machine (SVM) to design a feature function for numerical attributes. Experimental results have shown that the proposed method showed better accuracy of QC label assignments than those of point-wise prediction method using SVM and the actually operated system in Argo project.
An approach for fully automating perspective images based on symmetry and line intersection

Images captured using the camera are perspective in nature and hence has to be converted to a parallel view before being used for any applications to get a photorealistic result. Correction of perspective images are very useful for image based rendering and view metrology. We present a very efficient and simple method for automatically correcting the perspective image based on the intensity variations of objects in the image. The algorithm automates the perspective correction for images and videos (both recorded and online). Here we do not make use of any calibration information or explicit knowledge of any imaging device for carrying out the perspective correction. The method is based on line intersections, Hough Transform and Plane Homography.
Sentiment classification techniques for Arabic language: A survey

With the advent of online data, sentiment analysis has received growing attention in recent years. Sentiment analysis aims to determine the overall sentiment orientation of a speaker or writer towards a specific entity or towards a specific feature of a specific entity. A fundamental task of sentiment analysis is sentiment classification, which aims to automatically classify opinionated text as being positive, negative, or neutral. Although the literature on sentiment classification is quite extensive, only a few endeavors to classify opinionated text written in the Arabic language can be found. This paper provides a comprehensive survey of existing lexicon, machine learning, and hybrid sentiment classification techniques for Arabic language.
The Psychology of Residential Developers

Researchers have repeatedly observed satisficing by residential developers. The phenomenon has been attributed to their bounded rationality. In response, policy makers have designed policies that reduce risks to assist developers in overcoming bounds on their rationality. However, after decades of such policies, there is little evidence that developers have stopped satisficing. This article argues that bounded rationality is an insufficient explanation for satisficing by small developers. Lessons from behavioral economics suggest additional reasons for satisficing by developers. Satisficing is common because developers bracket projects one at a time, bracket each investment decision in isolation of others, create nonfungible investment accounts, establish self-imposed liquidity constraints, and temporally space projects. Policies that group risks to developers are likely to be the most effective. However, additional land-market-specific research is required to design policies that address these psychological traits. Academicians also need to design better survey instruments to investigate developer decision making.
Structural and functional analysis of three D/L-like class I molecules from H-2v: indications of an ancestral family of D/L genes

Three cDNA with D region gene features have been identified from the H- 2v haplotype. Provisionally, the sequences have been designated as D/Lv1, D/Lv2, and D/Lv3. The coding segments for the antigen binding domain (ABD) of all three D/Lv genes were engineered into a class I genomic expression vector and expressed in L cells. FACS analysis of the three D/Lv-Ld gene transfectants revealed that the D/Lv1 molecules were recognized by both monoclonal antibodies (mAbs) 141 and 142, and the D/Lv2 molecules were recognized by mAb 143. In addition to the D/Lv1 molecules, the mAb 141 also recognized the D/Lv3 molecules. Both the D/Lv1-Ld and D/Lv2-Ld transfectants were killed efficiently by H- 2Dv region-specific alloreactive CTL. The D/Lv3 gene is the first identified D region gene other than D and L that is transcribed abundantly in spleen and the D/Lv3 RNA is present as two alternatively spliced forms. Structural analysis of the D/Lv3 hybrid molecules showed that it was susceptible to proteolysis and thermolabile at 37 degrees C, suggesting D/Lv3 is a transcribed pseudogene. A parsimony tree analysis of three D/Lv sequences with a set of class I gene sequences revealed that the H-2v sequences clustered with D region genes. The presence of a third gene with D/L-like features in H-2v, yet structurally different from the known D/L alleles, raises the possibility that the current D/L genes evolved from a family of D/L- like genes, some of which are no longer represented among many of the mouse major histocompatibility complex haplotypes. The observation that D region alleles cluster into subgroups suggests that the alleles are not all related to each other by linear descent through a single locus. We propose that current alleles are derived from more than one ancestral locus in a manner similar to the origin of the gamma 2 a immunoglobulin constant region alleles.
Local government capacity and social capital

Local authorities vary considerably in their capacity for governance. The dimensions of this capacity can only be developed by drawing on local stocks of social capital. The seminal theories of social capital tend to conceive it as a community resource that is built up through a long tradition of civic engagement. We take issue with the laissez faire implications of these theories, highlighting ways in which local governments can positively contribute to social capital formation by opening their "political opportunity structure" and engaging voluntary organizations and community groups in trust-based partnership arrangements. *Senior Lecturer Department of Economics University of Otago PO Box 56 Dunedin New Zealand Phone: 0064-3-4798650 Fax: 0064-3-4798174 email: jwallis@business.otago. ac.nz ** Professor Department of Economics University of New England Armidale 2351 New South Wales Phone: 00612-67-732500 Fax: 00612-67-733280 Email: bdollery@metz.une. edu.au
Scheduling semiconductor manufacturing plants

In many large systems, such as manufacturing systems and communication networks, whenever a resource becomes available, one has to decide which of several tasks contending for its attention should be performed next. Such problems are called "scheduling" problems. They are control problems of immense economic importance, and have often been formulated and addressed in an open-loop setting. Both to illustrate the types of problems encountered and to serve as focus, in this article we will address scheduling problems in a technological area of much topical interest-semiconductor manufacturing. Being of relatively recent origin, and organized differently from more traditional manufacturing systems such as flow shops and job shops, they are relatively less explored. They are also of significant economic interest, and much in the public limelight, and thus a fertile area for systems and control researchers. We provide an account of some problems in the area, as well as some suggested solutions. <<ETX>>
STABILITY AND UNIFORM APPROXIMATION OF NONLINEAR FILTERS USING THE HILBERT METRIC AND APPLICATION TO PARTICLE FILTERS1

We study the stability of the optimal filter w.r. t. its initial condition and w.r. t. the model for the hidden state and the observations in a general hidden Markov model, using the Hilbert projective metric. These stability results are then used to prove, under some mixing assumption, the uniform convergence to the optimal filter of several particle filters, such as the interacting particle filter and other original particle filters.
Frequency-Domain Block Turbo-Equalization for Single-Carrier Transmission Over MIMO Broadband Wireless Channel

This paper presents a new class of block turbo-equalizers for single-carrier transmission over multiple-input multiple-output (MIMO) broadband wireless channels. The key underlying idea consists in equalizing (nonoverlapping) groups of symbols and detecting their individual space-time components in a disjoint and iterative fashion. This functional split naturally induces new design options that have been accurately listed and described, i.e., choice of distinct criteria for intergroup interference (IGI) equalization and intragroup components detection, yielding hybrid structures, multiple iterative loops, and related scheduling variants. Selected algorithms in the proposed class are compared in terms of performance under various transmission scenarios. For all of them, minimum mean square error IGI equalization certainly occupies a central role (at least for the first iteration) and may be identified as the computational bottleneck. Fortunately, block spread transmission together with cyclic prefix operations make the channel matrix block circulant, thus allowing low-complexity inversion in the Fourier domain
Lipid and NDF Analysis of Ethanol Byproduct Feedstuffs

A newly developed biphasic feed lipid extraction procedure has increased accuracy relative to Goldfisch ether extraction , especially for condensed corn distillers solubles samples. A pre-NDF fat extraction must be completed prior to analyzing high fat feeds for NDF. Corn should be ground through a 1-mm screen on a Tecator Cyclotec sample mill to accurately determine corn NDF content.
How to intelligently make sense of real data of smart cities

This paper analyzes the benefits of big data for smart cities and the potential of the knowledge discovery from sensed data, which enables real-time systems monitoring, management, optimization and anticipation. In this work we present some examples of applications of big data analysis in two scenarios of smart cities. One of them is focused on the SmartSantander testbed, which offers fixed sensors that record temperature, traffic, and noise. The second example describes the services provided in the SmartCampus of the University of Murcia (UMU), as part of the SMARTIE EU project. The results obtained after applying the most appropriate big data techniques in both scenarios show how it is possible to provide efficiently services like the management of the transport congestion and the energy consumption and comfort of buildings in the context of Smart Cities.
Probabilistic Characterization of Decision Trees Probabilistic Characterization of Decision Trees

In this paper we use the methodology introduced in Dhurandhar and Dobra (2006) for analyzing the error of classifiers and the model selection measures, to analyze decision tree algorithms. The methodology consists of obtaining parametric expressions for the moments of the Generalization error (GE) for the classification model of interest, followed by plotting these expressions for interpritability. The major challenge in applying the methodology to decision trees, the main theme of this work, is customizing the generic expressions for the moments of GE to this particular classification algorithm. The specific contributions we make in this paper are: (a) we completely characterize a subclass of decision trees namely, Random decision trees, (b) we discuss how the analysis extends to other decision tree algorithms, and (c) in order to extend the analysis to certain model selection measures, we generalize the relationships between the moments of GE and moments of the model selection measures given in Dhurandhar and Dobra (2006) to randomized classification algorithms. An extensive empirical comparison between the proposed method and Monte Carlo, depicts the advantages of the method in terms of running time and accuracy. It also showcases the use of the method as an exploratory tool to study learning algorithms.
On-Chip Trifilar-Transformer-Coupled Quadrature Signal Generation Methodology

The circuit analyses of four elemental building blocks for a quadrature signal generator are provided. From these block analyses, a set of equations forming a closed-loop relation in node voltages is obtained. This equation set represents a cross-coupled system that will oscillate in quadrature. By reconfiguring these building blocks, a novel integrated quadrature voltage-controlled oscillator (QVCO) utilizing two trifilar transformers can be constructed for the low-voltage / low-power operation. A 7-GHz QVCO based on this proposed configuration is successfully demonstrated in this paper. This oscillator core dissipates only 2.2 mW from a 1-V supply. The measured phase noise at 1-MHz and 10-MHz offset from the center frequency are around -111 dBc/Hz and -132 dBc/Hz, respectively, over the whole tuning range of 260 MHz.
Depressive patients are more impulsive and inconsistent in intertemporal choice behavior for monetary gain and loss than healthy subjects--an analysis based on Tsallis' statistics.

OBJECTIVES Depression has been associated with impaired neural processing of reward and punishment. However, to date, little is known regarding the relationship between depression and intertemporal choice (delay discounting) for gain and loss. This examination is potentially important for advances in neuroeconomics of intertemporal choice, because depression is associated with reduced serotonergic activities in the brain. DESIGN AND SETTING We compared impulsivity and inconsistency in intertemporal choice for monetary gain and loss between depressive patients and healthy control subjects. METHODS We conducted delay discounting tasks for gain and loss in depressed and healthy control subjects. We then quantified impulsivity and inconsistency in the delay discounting with parameters in the q-exponential discount function based on Tsallis' statistics. RESULTS We observed that depressive patients were more impulsive and time-inconsistent in intertemporal choice action for gain and loss, in comparison to healthy controls. MAIN FINDINGS Depressed patients were more irrational in temporal discounting. CONCLUSIONS The usefulness of the q-exponential discount function for assessing the impaired decision-making by depressive patients was demonstrated. Furthermore, biophysical mechanisms underlying the altered intertemporal choice by depressive patients are discussed in relation to impaired serotonergic neural systems.