Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient Sampling and Metamodeling for Computational Economic Models

Extensive exploration of simulation models comes at a high computational cost, all the more when the model involves a lot of parameters. Economists usually rely on random explorations, such as Monte Carlo simulations, and basic econometric modelling to approximate the properties of computational models. This paper aims at providing guidelines for the use of a much more parsimonious method, based on an efficient sampling of the parameters space – a design of experiments (DOE), associated with a well-suited metamodel – kriging. We analyze two simple economic models using this approach to illustrate the possibilities offered by it. Our appendix gives a sample of the R-project code that can be used to apply this method on other models.
Hedonic Recommendations : An Econometric Application on Big Data Okay Gunes

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Hedonic Recommendations: An Econometric Application on Big Data Okay Gunes
Location aware keyword query suggestion based on document proximity

Consider a user who has issued a keyword query to a search engine. We study the effective suggestion of alternative keyword queries to the user, which are semantically relevant to the original query and they have as results documents that correspond to objects near the user's location. For this purpose, we propose a weighted keyword-document graph which captures semantic and proximity relevance between queries and documents. Then, we use the graph to suggest queries that are near in terms of graph distance to the original queries. To make our framework scalable, we propose a partition-based approach that greatly outperforms the baseline algorithm.
A Posteriori Typing for Model-Driven Engineering

Model-Driven Engineering (MDE) is founded on the ability to create and process models conforming to a meta-model. In this context, classes in a meta-model are used in two ways: as templates to create objects and as (static) classifiers for them. These two aspects are inherently tied in most meta-modelling approaches, which results in unnecessarily rigid systems and hinders reusability of MDE artefacts. In this work, we discuss the benefits of decoupling object creation from typing in MDE. Thus, we rely on standard mechanisms for object creation, and propose a posteriori typing as a means to retype objects and enable multiple, partial, dynamic typings. This approach enhances flexibility; permits unanticipated reuse, as model management operations defined for a meta-model can be reused with other models once they get reclassified; and enables bidirectional model transformation by reclassification. In particular, we propose two mechanisms to realise model retyping and show their underlying theory and analysis methods. We show the feasibility of the approach by an implementation atop our meta-modelling tool MetaDepth and present several applications of retypings (transformations, reuse, and dynamicity).
Learning Kernel-Based Halfspaces with the Zero-One Loss

We describe and analyze a new algorithm for agnostically learning kernel-based halfspaces with respect to the \emph{zero-one} loss function. Unlike most previous formulations which rely on surrogate convex loss functions (e.g. hinge-loss in SVM and log-loss in logistic regression), we provide finite time/sample guarantees with respect to the more natural zero-one loss function. The proposed algorithm can learn kernel-based halfspaces in worst-case time $\poly(\exp(L\log(L/\epsilon)))$, for $\emph{any}$ distribution, where $L$ is a Lipschitz constant (which can be thought of as the reciprocal of the margin), and the learned classifier is worse than the optimal halfspace by at most $\epsilon$. We also prove a hardness result, showing that under a certain cryptographic assumption, no algorithm can learn kernel-based halfspaces in time polynomial in $L$.
Merkle Tree Authentication in UDDI Registries

Reviewed Papers 1 An Extensible Workflow Architecture through Web Services Jinyoung Jang, Hyunse Systems, Inc., Korea Yongsun Choi, Inje University, Korea, J. Leon Zhao, University of Arizona, USA In this study, the authors propose an extensible workflow architecture based on Web services and object-oriented techniques. The proposed architecture contains three components, the Open Kernel Framework, the Universal Resource Manager, and the Process Definition Publisher.
Spatial Besov regularity for semilinear stochastic partial differential equations on bounded Lipschitz domains

We study the spatial regularity of semilinear parabolic stochastic partial differential equations on bounded Lipschitz domains 𝒪⊆ ℝ d in the scale , 1/τ=α/d+1/p, p≥2 fixed. The Besov smoothness in this scale determines the order of convergence that can be achieved by adaptive numerical algorithms and other nonlinear approximation schemes. The proofs are performed by establishing weighted Sobolev estimates and combining them with wavelet characterizations of Besov spaces.
AIS Electronic Library (AISeL)

To date, there has been limited research on the role of an internal IT service innovation in a strategic business process. An IT service innovation supports organizational business processes and is designed, developed and deployed following the notion of service logic characterized by intangible resources, the co-creation of value, and relationships. We examine the influence of an IT service innovation – an IT-enabled collaboration platform – on collaboration outcomes in the product development process. We develop and test a model that posits that the use of the platform will lead to positive service quality conceptualized as collaboration quality that in turn influences collaboration satisfaction. We conducted a study of a collaboration platform implementation by a major pharmaceutical company (N = 1,746) and found support for our model. Our findings contribute to the literature by providing insights on how employees utilize the capabilities of an IT service innovation in their work processes to achieve desired outcomes.
Original Investigation

Rationale Brain histaminergic system is involved in the regulation of the dopaminergic circuitry. The role of histamine H3 receptor (H3R) in behaviors linked to amphetamine addiction and other behaviors induced by dopaminergic compounds has remained unclear. Objective Our aim was to study whether H3R antagonist JNJ-39220675 inhibits amphetamine-induced stimulation and reward. The effects of JNJ-39220675 on dopamine D2-like receptor (D2R-like) agonist quinpirole-induced behaviors were also investigated in order to clarify whether the possible effects of H3R antagonists are D2R-like dependent. Methods The effects of JNJ-39220675 on amphetamine and quinpirole-induced behavioral responses in mice were studied assessing the locomotor activation after both acute and repeated administrations of amphetamine and quinpirole. The place conditioning paradigm was also used as a measure of reward or aversion. Results JNJ-39220675 inhibited amphetamine-induced stimulation acutely but not after repeated administrations. Amphetamine (2 mg/kg) induced conditioned place preference that was not affected by either of the tested doses of JNJ-39220675 (1 and 10 mg/kg). Quinpirole (0.5 mg/kg) induced conditioned place aversion to which the pretreatment by JNJ-39220675 (10 mg/kg) had no effect. In repeated administration, JNJ-39220675 did, however, inhibit quinpirole-induced tolerance to hypokinesia. Conclusions Our results show that although H3R antagonists inhibit ethanol reward, they may not possess the same ability on psychostimulants, such as amphetamine. However, if H3R antagonists will become clinically available, it is of importance that these compounds potentiate neither the rewarding nor aversive effects of other drugs.
Sixth International Joint Conference on Natural Language Processing The Companion Volume of the Proceedings: System Demonstrations

We demonstrate a web-based, languageindependent annotation framework used for manual correction of a large Arabic corpus. Our framework provides intuitive interfaces for annotating text and managing the annotation process. We describe the details of both the annotation and the administration interfaces as well as the back-end engine. We also show how this framework is able to speed up the annotation process by employing automated annotators to fix basic Arabic spelling errors.
Internet Engineering Task Force Internet-draft Te Working Group Daniel O. Awduche January 2000 Uunet (mci Worldcom)

Internet-Drafts are working documents of the Internet Engineering Task Force (IETF), its areas, and its working groups. Note that other groups may also distribute working documents as InternetDrafts. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use InternetDrafts as reference material or to cite them other than as "work in progress. " The list of current Internet-Drafts can be accessed at http://www.ietf. org/ietf/1id-abstracts.txt The list of Internet-Draft Shadow Directories can be accessed at http://www.ietf. org/shadow.html.
A System towards Indian Postal Automation

In this paper, we present a system towards Indian postal automation. In the proposed system, at first, using Run Length Smoothing Algorithm (RLSA), we decompose the image into blocks. Based on the black pixel density and number of components inside a block, non-text block (postal stamp, postal seal etc.) are detected. Using positional information, the destination address block (DAB) is identified from text block. Next, pin-code box from the DAB is detected and numerals from the pin-code box are extracted. Since India is a multi-lingual and multi-script country, the address part may be written by combination of two languages: Arabic and a local language. For the sorting of postal documents written in Arabic and a local language Bangla, a two-stage MLP based classifier is employed to recognise Bangla and Arabic numerals. At present, the accuracy of the handwritten numeral recognition module is 92.10%.
K2/Kleisli and GUS: Experiments in Integrated Access to Genomic K2/Kleisli and GUS: Experiments in Integrated Access to Genomic Data Sources Data Sources

Abstract The integration of heterogeneous data sources and software systems is a major issue in the biomed ical community and several approaches have been explored: linking databases, "on-the-fly" integration through views, and integration through warehousing. In this paper we report on our experiences with two systems that were developed at the University of Pennsylvania: an integration system called K2, which has primarily been used to provide views over multiple external data sources and software systems; and a data warehouse called GUS which downloads, cleans, integrates and annotates data from multiple external data sources. Although the view and warehouse approaches each have their advantages, there is no clear "winner". Therefore, users must consider how the data is to be used, what the performance guarantees must be, and how much programmer time and expertise is available to choose the best strategy for a particular application.
Integrating Behavioral Science with Mobile (mHealth) Technology to Optimize Health Behaviour Change Interventions

The feasibility and potential for mobile technology to effect change in health-related outcomes for chronic disease is enormous. According to the European Commission (2014) among the world’s population of 7 billion, there are over 5 billion mobile devices and over 90% of the users have their mobile device near them 24 hours a day. This provides a huge opportunity for behaviour change, and one that health psychologists have already begun to address. However, research evidence to date is limited and research is falling behind the rapid pace of new technology developments. Much of the research published to date reports low effect sizes and lack of sustained usage of mHealth technology over time which highlights the need to further understand how engagement with, and effectiveness of mHealth interventions can be optimised. The European Commission carried out a public consultation in 2016 on the issues surrounding the use of health and wellbeing apps and found that a lack of global standards were a significant barrier to their effective use. Recently, the WHO mHealth Technical Evidence Review Group developed the mHealth evidence reporting and assessment (mERA) checklist to specify the evidence-based content of mHealth interventions. Health psychologists play a key role in the development of mHealth solutions to foster behaviour change, particularly in the management of chronic disease. This article discusses the current challenges facing a widespread integration of mobile technology solutions into self-management of chronic disease including issues around security and regulation, as well as investigating potential solutions to overcoming these barriers.
ScholarWorks @ UTRGV ScholarWorks @ UTRGV

We study the problem of minimizing total completion time on parallel machines subject to varying processing capacity. In this paper, we develop an approximation scheme for the problem under the data stream model where the input data is massive and cannot ﬁt into memory and thus can only be scanned for a few passes. Our algorithm can compute the approximate value of the optimal total completion time in one pass and output the schedule with the approximate value in two passes
Semantic matching

We think of match as an operator that takes two graph-like structures (e.g. database schemas or ontologies) and produces a mapping between elements of the two graphs that correspond semantically to each other. The goal of this paper is to propose a new approach to matching, called semantic matching. As its name indicates, in semantic matching the key intuition is to exploit the model-theoretic information, which is codified in the nodes and the structure of graphs. The contributions of this paper are (i) a rational reconstruction of the major matching problems and their articulation in terms of the more generic problem of matching graphs, (ii) the identification of semantic matching as a new approach for performing generic matching and (iii) a proposal for implementing semantic matching by testing propositional satisfiability.
Pattern Matching

An important subtask of the pattern discovery process is pattern matching, where the pattern sought is already known and we want to determine how often and where it occurs in a sequence. In this paper we review the most practical techniques to find patterns of different kinds. We show how regular expressions can be searched for with general techniques, and how simpler patterns can be dealt with more simply and efficiently. We consider exact as well as approximate pattern matching. Also we cover both sequential searching, where the sequence cannot be preprocessed, and indexed searching, where we have a data structure built over the sequence to speed up the search.
Recognition of Arabic handwritten words Recognition of Arabic handwritten words

Recognizing Arabic handwritten words is a difficult problem due to the deformations of different writing styles. Moreover, the cursive nature of the Arabic writing makes correct segmentation of characters an almost impossible task. While there are many sub systems in an Arabic words recognition system, in this work we develop a sub system to recognize Part of Arabic Words (PAW). We try to solve this problem using three different approaches, implicit segmentation and two variants of holistic approach. While Rothacker found similar conclusions while this work is being prepared, we report the difficulty in locating characters in PAW using Scale Invariant Feature Transforms under the first approach. In the second and third approaches, we use holistic approach to recognize PAW using Support Vector Machine (SVM) and Active Shape Models (ASM). While there are few works that use SVM to recognize PAW, they use a small dataset; we use a large dataset and a different set of features. We also explain the errors SVM and ASM make and propose some remedies to these errors as future work.
Vehicle Tracking and Speed Estimation using Optical Flow Method

: This paper presents a novel velocity estimation method for ground vehicles. The task here is to automatically estimate vehicle speed from video sequences acquired with a fixed mounted camera. The vehicle motion is detected and tracked along the frames using optical flow algorithm. The distance traveled by the vehicle is calculated using the movement of the centroid over the frames and the speed of the vehicle is estimated. The accuracy of our method was calculated by measuring the velocity manually and comparing with calculated values. The application is developed using MATLAB and SIMULINK.
A cegar approach for stability verification of linear hybrid systems

This document summarizes results related to an algorithmic approach for stability analysis of hybrid systems. Classical approaches rely on Lyapunov function search and suffer from numerical issues. In addition, an unsuccessful template for the Lyapunov function does not provide insights on the choice of a better template. To overcome these issues, we present a counterexample guided-abstraction refinement (cegar) approach which iteratively searches for a stability certification over an abstract system, and provides insights to obtain more accurate abstract systems if needed.
Horizontal Grid Spacing Comparison Among Random Forest Algorithms to Nowcast Cloud-to- Ground Lightning Occurrence

This paper discusses the use of Random Forest (RF), a popular Machine Learning (ML) algorithm, to perform spatially explicit nowcasting of cloud-to-ground lightning occurrence. An application to the Italian territory and the surrounding seas is presented. Specifically, 1-hour ahead lightning occurrences over the months of August, September and October from 2017 to 2019 have been modelled using a dataset including geo-environmental features. Results obtained with three different spatial resolutions have been compared, for nowcasting both positive and negative strokes. The features’ importance resulting from the best RF models showed how datadriven models are able to identify the relationships between meteorological variables, in agreement with previous physically based knowledge of the phenomenon. The encouraging results obtained in terms of forecasting accuracy support the idea to use ML-based algorithms in early warning procedures for disaster
Image Similarity Using Color Histograms

In this thesis an evaluation of multiple methods of image classification is presented. We explore the application of color spaces and several histogram distance calculation algorithms to achieve a classification system that’s able to determine whether an image belongs to a certain set with a specific theme. For this thesis a C++ program has been build using OpenCV to extract color information from images in either RGB or HSV color space, then this information is used to calculate similarity between images using one of the following algorithms: Euclidian distance, Intersection distance, Quadratic cross distance and Earth’s mover’s distance. Precision and recall are then used to evaluate the combination of the chosen colorspace and algorithm.
Sensemaking and implications for information systems design: Findings from the Democratic Republic of Congo's ongoing crisis

International humanitarian aid and development organizations active in the Democratic Republic of Congo (DRC) are faced with an ongoing crisis situation. Using any formal or informal information source available, they are constantly acquiring and processing information that may indicate the possible surge of an acute crisis. Information systems (IS) that enable effective and efficient information processing and decision making within and among the organizations are therefore a critically important asset to these organizations. We present a concise set of design premises that have been developed for dynamic emergency response management information systems, and we introduce the theory of Sensemaking as a lens to observe and analyze the information processing and decision making behavior of organizations. Based on interviews conducted among senior management of international aid and development organizations operating in the DRC, our findings illustrate the constant Sensemaking behavior of these organizations and provide a motivation for the proposed IS design premises. © 2008 Wiley Periodicals, Inc.
An improved quantum-behaved particle swarm optimization algorithm

Quantum-behaved particle swarm optimization (QPSO) algorithm is a global convergence guaranteed algorithm, which shows good search ability in many optimization problems. In this paper, we present an improved QPSO algorithm, called IQPSO, by combining QPSO and an opposition-based learning concept. Experimental studies on four well-known benchmark problems show that IQPSO achieves better results than QPSO and other variants of PSO on majority of test problems.
An Improved Quantum-behaved Particle Swarm Optimization Algorithm Based on Chaos Theory Exerting to Local Optimal Position ⋆

In this paper, we introduce chaos theory into QPSO and propose an improved Quantum-behaved Particle Swarm Optimization (QPSO), in which the logistic map is exerted to every particle’s local optimal position P (t) at a certain probability. In this improved QPSO, the logistic map is used to generate a set of chaotic offsets and produce multiple positions around P (t). According to their fitness values, the particle’s position X(t) and P (t) are updated. In order to further enhance the diversity of particles, mutation operation is introduced into and acts on one dimension of the particle position. In improved QPSO, the chaos and mutation probabilities are carefully selected. Through several typical function experiments, its results show that the convergence accuracy of the improved QPSO is better than those of QPSO, so it is feasible and effective to introduce chaos theory and mutation operation into QPSO.