Miracle-dz/UniFAR-FTUs huggingface dataset:
Quasi-maximum-likelihood estimation in conditionally heteroscedastic time series: A stochastic recurrence equations approach

This paper studies the quasi-maximum-likelihood estimator (QMLE) in a general conditionally heteroscedastic time series model of multiplicative form Xt = σt Zt , where the unobservable volatility σt is a parametric function of (Xt−1 ,.,X t−p ,σ t−1 ,.,σ t−q ) for some p, q ≥ 0, and (Zt ) is standardized i.i. d. noise. We assume that these models are solutions to stochastic recurrence equations which satisfy a contraction (random Lipschitz coefficient) property. These assumptions are satisfied for the popular GARCH, asymmetric GARCH and exponential GARCH processes. Exploiting the contraction property, we give conditions for the existence and uniqueness of a strictly stationary solution (Xt ) to the stochastic recurrence equation and establish consistency and asymptotic normality of the QMLE. We also discuss the problem of invertibility of such time series models. 1. Introduction. Gaussian quasi-maximum-likelihood estimation, that is, likelihood estimation under the hypothesis of Gaussian innovations, is a popular method which is widely used for inference in time series models. However, it is often a nontrivial task to establish the consistency and asymptotic normality of the quasi-maximum-likelihood estimator (QMLE) applied to specific models and, therefore, an in-depth analysis of the probabilistic structure generated by the model is called for. A classical example of this kind is the seminal paper by Hannan [18] on estimation in linear ARMA time series. In this paper we study the QMLE for a general class of conditionally heteroscedastic time series models, which includes GARCH, asymmetric GARCH and exponential GARCH. Recall that a GARCH(p, q) [generalized autoregressive conditionally heteroscedastic of order (p, q)] process [4 ]i s def ined by
Geoinformatics & Geostatistics: An Overview

The concept of object identification and modeling has fueled a lengthy scientific effort to convert remotely sensed images into geographic phenomena. The objective of this article was to develop a new concept for characterizing and identifying drought spatial objects from satellite images for improved drought prediction and mitigation using a back propagation artificial neural network (ANN). To characterize drought as a spatial object, 11 attributes from multi-sensors and resolutions (such as Standardized Deviation of Normalized Difference Vegetation Index [SDNDVI], Digital Elevation Model [DEM], Soil Water Holding Capacity, Ecological Regions, Land Cover, Standard Precipitation Index [SPI], and oceanic indices were used. After characterizing and identifying drought spatial objects, the experimental focus was on predicting drought in a one-to four-month time lag using a back propagation ANN. Using this approach, the drought was predicted for one to four months lead time with correlation coefficient ( r ) accuracies of 0.70–0.95. The output of this new concept could help in integrating the available information from multi-sensors and resolutions for a drought mitigation application at different levels of decision making. Future research may focus on experimenting with the approach in wider coverage areas, such as at regional or continental levels, and quantifying the uncertainty level of the approach for its practical use in drought adaptation planning and mitigation applications.
Migration of Deep Low‐Frequency Tremor Triggered by Teleseismic Earthquakes in the Southwest Japan Subduction Zone

Deep low‐frequency tremor triggered by teleseismic surface waves is concentrated in several locations along the ambient tremor source region in the Nankai subduction zone, southwest Japan. We systematically investigated triggered tremor in northern Kii and western Shikoku, at 71 teleseismic earthquakes by applying a matched filter technique. We detected 9 and 17 events of triggered tremor in northern Kii and western Shikoku, respectively. In addition, we observed tremor migration episodes, whose directions were always along‐dip. In northern Kii, seven episodes showed downward migration at a speed of 5–20 km/hr. In western Shikoku, six episodes migrated at a speed of 10–100 km/hr, in which five episodes showed upward migration. Migration of the triggered tremor suggests that dynamic stress perturbation from distant earthquakes may trigger propagating creep events caused by fluid.
A Compilation Model for Aspect-Oriented Polymorphically Typed Functional Languages ( Technical Report )

Introducing aspect orientation to a polymorphically typed functional language strengthens the importance of type-scoped advices ; i.e., advices with their effects being harnessed by type constraints. As types are typically treated as compile time entities, it is desirable to be able to performstatic weavingto determine at compile time the chaining of type-scoped advices to the invocations of their associated join points. In this paper, we describe a compilation model, as well as its implementation, that enables static type inference and static weaving of programs in an aspect-oriented polymorphically typed functional language, AspectFun . We describe a typedirected weaving scheme that successfully, and coherently, weaves type-scoped advices into base programs, in the presence of nested and second-order advices. We also demonstrate how control-flow based pointcuts (such as cflowandcflowbelow) are compiled away, and describe several type-directed optimization strategies that can improve the efficiency of woven code.
Signatures of restarted activity in core-dominated, triple radio sources selected from the FIRST survey

Signatures of the re-occurrence of activity in radio-loud AGNs, indicated either by the so-called double-double or X-shaped structures, have been observed in a number of radio sources. All such objects known to date have linear sizes of the order of a megaparsec. A number of the sources that are appreciably more compact than this, but that exhibit hints of a past phase of activity, were found in the VLA FIRST survey. Their structures show symmetric relic lobes straddling relatively bright, unresolved cores. Observations of the cores of 15 such structures with MERLIN at 5 GHz have shown that four of them are doubles or core-jets on the subarcsecond scale. Misalignments of ∆PA > 30 ◦ between the axis of the inner structure and the line connecting the fitted maxima of the arcminute-scale relic lobes are clearly visible in three of the four sources. From these results, we can infer that a rapid repositioning of the central engine in each of these three radio sources is the most plausible interpretation of the observed morphology and that a merger is most likely the original cause of such a repositioning. In the case of TXS 1033+026, the optical image extracted from the SDSS archives clearly suggests that two objects separated by only 2.7 kpc (projected onto the sky plane) are indeed merging. The inner parts of TXS 0818+214 and TXS 1312+563 could be interpreted as double-lobed, and consequently, these sources could be of the double-double type; but further multifrequency observations are necessary to provide support for such an interpretation.
NOTE: A Parallel Feature Tracker for Extended Image Sequences

In this paper, we develop a new algorithm for tracking This paper presents a feature tracker for long image sefeatures over long image sequences. Our algorithm is based quences based on simultaneously estimating the motions on the principle of local patch correlation with possible and deformations of a collection of adjacent image patches. bilinear deformations (a generalization of [16, 21, 30, 23]). By sharing common corner nodes, the patches achieve greater In our tracker, adjacent patches share common nodes for stability than independent patch trackers. Modeling full bilinbetter stability. The confidence of the recovered feature ear deformations enables tracking in sequences which have tracks is subsequently determined using local Hessian and large nontranslational motions and/or foreshortening effects. squared error criteria [1, 23]. We demonstrate the advantages of our technique with respect The structure of our paper is as follows. Section 2 reviews to previous algorithms using experimental results.  1997 Acaprevious work. Section 3 describes our spline-based image demic Press
Deducing and Mapping the Class Path of JAR File

Now-a-days, to reduce the effort of human and to improve the efficiency of the process, everything in this world is being computerized. But also the user may face some problems while executing the program. Program is software that contains a set of instructions to perform a task. In order to make the process of developing program, an easier one, some developers develop software and implement them as a package. To access these packages much easier, some of them are released as an Open Source Software. An Open Source Software is a software that is downloaded with free of cost. In this Open Source Software, there exist many packages, classes and methods. While using this Open Source Software, to develop an application, these packages are well-connected with that application. It is necessary to generate a class file to start executing the application. But the user doesn’t know the classes or its properties to compile them. To overcome this situation, in this paper, we propose a method to start compiling the classes in the package automatically. Also if the path is not set correctly, it is also done systematically through the methodology proposed in this paper. Keywords: Classes, Compilation, Computerized, Developers, Download, Efficiency, Instructions, Methods, Open Source Software, Package, Program, Systematically.
Time-Bounded Reachability Probabilities in Continuous-Time Markov Decision Processes

This paper solves the problem of computing the maximum (and minimum) probability to reach a set of goal states within a given time bound in continuous-time Markov decision processes (CTMDPs). For the subclass of locally uniform CTMDPs, we define the class of late total time positional schedulers (TTPDl) and prove that they suffice to resolve all nondeterministic choices in an optimal way. Our main contribution is a discretization technique which, for an a priori given error bound epsilon > 0, induces a discrete-time MDP that approximates the maximum time-bounded reachability probability in the underlying locally uniform CTMDP up to epsilon. In a second part, we consider arbitrary CTMDPs. In this more general setting, TTPDl schedulers are inapplicable and are replaced by the corresponding class of early TTPD schedulers. Using a measure preserving transformation from CTMDPs to interactive Markov chains (IMCs), we apply recent results on IMCs to compute the maximum time-bounded reachability probability under early scheduler in the CTMDP’s induced IMC.
Effects of drought dynamics on vegetation cover in Marigat sub-county , Baringo county, Kenya

Drought is a norm rather than exception in Marigat Sub-County, Baringo County in Kenya where it adversely affects vegetation and water resources which are key resource for pastoralism. However, the effects vary depending on the dynamic of each drought event. This study sought to establish the drought dynamics in in Marigat Sub-Countyand how the dynamics affect vegetation cover in the County. A sample size of 368 households from a total study population of 9,160 households was selected for the survey alongside meteorological datasheets, remotely-sensed images, hydrological datasheets and maps. Droughts were frequent in Baringo County occurring once in every two years. The intensity the droughts ranged from 0.1 to 57.8 percent below the long-term mean. Whereas some droughts were on off events, majority occurred in runs with the longest lasting for up to 5 years (2000-2004). Vegetation cover was severely affected when droughts were prolonged and intense and vice versa. Bare grounds devoid of vegetation cover were common during prolonged and intense droughts as it was experienced during the 2000 La Nina drought (NDVI value of0.07). As the inhabitants strived to cope with the effects of droughts, they turned into their immediate environment exploiting the available resources. This led to destruction of vegetation cover through activities such as overgrazing on wetlands and forested areas, charcoal burning and clearing of vegetation to allow crop farming. Thus with the increasing drought frequency, duration and intensity, if the environmental degradation remains unchecked Marigat Sub-Countywill become a desert devoid of vegetation.
Extreme temperature events on the Iberian Peninsula: Statistical trajectory analysis and synoptic patterns

The occurrence of heat waves and cold spells has been receiving special attention in recent years due to their impact on human health, ecosystems and other aspects, such as the economy. The present work uses a Lagrangian approach to analyse the physical processes leading to temperature extremes in the Iberian Peninsula (IP) for the 20‐year period 1994–2013. Principal component analysis has also been carried out to identify the associated synoptic scale configurations. Spatial pattern analysis shows that the highest temperatures during hot events are reached in the SW region and the lowest ones in the NE, while a latitudinal gradient of 26 K was obtained for the cold events, with the lowest values in the NE regions and the Pyrenees. Most of the extremes persisted between 1 and 3 days for both hot and cold events. Rather than meridional advection, the primary cause behind the occurrence of hot extremes seems to be progressive diabatic warming, which becomes accentuated in its final stage and is caused, on the one hand, by air masses with long residence times over the IP and, on the other hand, by recirculation processes during summer days of weak baric gradient. The air masses producing the extreme cold events have faster trajectories and mainly originate in north and northeast Europe, due to a relative low in the central Mediterranean and a blocking high in the North Atlantic and/or in northeast Europe.
Symbol-Based Query Expansion Experiments at TREC 2005 Genomics Track.

This paper illustrates the activity conducted at the TREC 2005 evaluation campaign in the ad-hoc task of the Genomics track. The retrieval effectiveness of a relevance feedback query expansion algorithm, which is based on symbols, is studied. The experimental results suggest that query expansion based on implicit relevance feedback is not always an effective means for improving effectiveness in this domain-specific context.
Distance-Aware Join for Indoor Moving Objects

Indoor spaces accommodate large parts of people's lives. Relevant techniques are thus needed to efficiently manage indoor moving objects, whose positions are detected by technologies, such as Assisted GPS, Wi-Fi, RFID, and Bluetooth. Among such techniques, the distance-aware join processing is of importance in practice for indoor spatial databases. Such join operators leverage a series of applications, such as indoor mobile service and facility monitoring. However, distance-aware joining over indoor moving objects is challenging because: (1) indoor spaces are characterized by many special entities and thus render distance calculation very complex; (2) the limitations of indoor positioning technologies create inherent uncertainties in indoor moving objects data. In this paper, we study two representative join predicates in indoor settings, semi-range join and semi-neighborhood join. To implement them, we define and categorize the indoor distances between indoor uncertain objects, and derive different distance bounds that can facilitate the join processing. We design a composite index scheme that integrates indoor geometries, indoor topologies, as well as indoor uncertain objects, and thus supports the join processing efficiently. The results of extensive experimental studies demonstrate that our proposals are efficient and scalable in evaluating distance-aware join over indoor moving objects.
Factors affecting e-commerce adoption in small and medium enterprises: An interpretive study of Botswana

This study aimed to investigate the factors that affect e-commerce adoption in small and medium sized enterprises (SMEs) in the developing country context of Botswana. The research was undertaken using an interpretive paradigm with multiple case studies in nine SMEs that were codenamed C1Alpha, C5Home, C6Lodge C2Beta, C3Gamma, C4Teq, C7Panda, C8Estate, and C9Autoco. Data collection tools and techniques involved face-to-face semi-structured and unstructured interviews, telephone interviews, website content analysis, document analysis of SME reports and observations. A conceptual framework was developed to capture elements from extant e-commerce adoption literature that are defined in the research question. Data collected from each of the SMEs was analysed to present the findings based on the elements described above. These elements include the following: 1) the nature and characteristic of the business environment, 2) use of ICT and Web Applications; 3) managerial characteristics and perception of e-commerce; 4) factors that affect e-commerce adoption or the lack of it; 5) the interaction of the factors and how they determine the level of e-commerce adoption, and 6) the role of the local business environment. The main findings of this study are the factors for e-commerce adoption for each of the SMEs. The study emerges with factors of e-commerce adoption that have been derived from various patterns of e-commerce adoption as represented in the nature and characteristics of the SMEs. This study makes a theoretical contribution by proposing a conceptual framework for investigating factors affecting e-commerce adoption in SMEs. Methodologically, the study adds a different blend to the research approach by undertaking in-depth studies on selected SMEs in Botswana, and provides an interpretive assessment of e-commerce adoption research in a developing country context of Botswana. Strategies for improving e-commerce development in the selected SMEs are presented, as well as implications of the research findings. This study provides insights into understanding SME e-commerce adoption factors in other contexts with similar characteristics.
A data-clustering approach based on artificial ant colonies with control of emergence combined with K-Means approach

Data-clustering mainly aims in forming the amount of unmanaged data to manageable piles, by discovering homogeneous groups. It is a combinatorial problem, because the number of partitions that can be obtained grows exponentially with the volume of data to be classified and the number of clusters. In this paper, we deal with the problem from the perspective of distributed optimization and we present a new approach for data-clustering based on combination of K-Means approach with our approach for data-clustering based on artificial ant colonies with control of emergence recently published in [14]. Since the objective is to optimize the partitioning, a comparative study will be done between K-Means approach and our method published in [14] and the combination of both of them. A multi-agent platform was used to implement the proposed approach. The obtained results in terms of internal and external performance measures on a set of real and synthetic benchmarks show the excellence of the proposed approach.
A Hybrid Approach to Data Assimilation for Reconstructing the Evolution of Mantle Dynamics

Quantifying past mantle dynamic processes represents a major challenge in understanding the temporal evolution of the solid earth. Mantle convection modeling with data assimilation is one of the most powerful tools to investigate the dynamics of plate subduction and mantle convection. Although various data assimilation methods, both forward and inverse, have been created, these methods all have limitations in their capabilities to represent the real earth. Pure forward models tend to miss important mantle structures due to the incorrect initial condition and thus may lead to incorrect mantle evolution. In contrast, pure tomography‐based models cannot effectively resolve the fine slab structure and would fail to predict important subduction‐zone dynamic processes. Here we propose a hybrid data assimilation approach that combines the unique power of the sequential and adjoint algorithms, which can properly capture the detailed evolution of the downgoing slab and the tomographically constrained mantle structures, respectively. We apply this new method to reconstructing mantle dynamics below the western U.S. while considering large lateral viscosity variations. By comparing this result with those from several existing data assimilation methods, we demonstrate that the hybrid modeling approach recovers the realistic 4‐D mantle dynamics the best.
Journal of Geophysical Research: Atmospheres Methyl, Ethyl, and Propyl Nitrates: Global Distribution and Impacts on Reactive Nitrogen in Remote Marine Environments

Alkyl nitrates (RONO 2 ) are important components of tropospheric reactive nitrogen that serve as reservoirs for nitrogen oxides (NO x ≡ NO + NO 2 ). Here we implement a new simulation of atmospheric methyl, ethyl, and propyl nitrate chemistry in a global chemical transport model (GEOS-Chem). We show that the model can reproduce the spatial and seasonal variability seen in a 20-year ensemble of airborne observations. Methyl nitrate accounts for 17 Gg N globally, with maxima over the tropical Paciﬁc and Southern Ocean. Propyl nitrate is enhanced in continental boundary layers, but its global impact (6 Gg N) is limited by a short lifetime (8 days vs. 26 days for methyl nitrate and 14 days for ethyl nitrate) that inhibits long-range transport. Ethyl nitrate has the smallest impact of the three species (4 Gg N). We ﬁnd that methyl nitrate is the dominant form of reactive nitrogen (NO y ) in the Southern Ocean marine boundary substantial NO x emissions growth in southern Africa, South America, and Southeast Asia (Turnock et al., 2018). Our results imply that such growth may lead to enhanced RONO 2 and associated NO x release over downwind ocean regions in the southern hemisphere and tropics—regions that are already among the most sensitive to RONO 2 cycling.
Geoinformatics & Geostatistics: An Overview

This paper presents a method of texture modelling using geostatistic theory. From variographics abacus and variogram proprieties, fractal and exponential models have been used to characterize Brodatz textures. In this approach, a texture is modelled by a vector called feature vector whose components are parameters characterizing the experimental variogram, notably the “Slope”, the “Range”, the “Landing” and the “Fractal Dimension (FD)”. The parameters estimated by this approach help to promote an adequate method of quantitative analysis of the variogram of textured images. A comparative study of the proposed method for the evaluation of FD and the one proposed in the literature shows that the results obtained are identical to the nearest hundredth with the texture images of Brodatz used in this work for the experimentations. To demonstrate the applicability of the approach, a SAR image of ERS-1 from the Atlantic coast of Cameroon has been classified using an algorithm classification of type supervised. It is based on the methods of structural classification. The particularity of this approach lies in the fact that each pixel is fully characterized by its feature vector.