Miracle-dz/UniFAR-FTUs huggingface dataset:
Fire dynamics during the 20 th century simulated by the Community Land Model

Fire dynamics during the 20th century simulated by the Community Land Model S. Kloster, N. M. Mahowald, J. T. Randerson, P. E. Thornton, F. M. Hoffman, S. Levis, P. J. Lawrence, J. J. Feddema, K. W. Oleson, and D. M. Lawrence Earth and Atmospheric Sciences, Cornell University, Ithaca, NY, USA Department of Earth System Science, University of California, Irvine, CA, USA Climate and Ecosystem Processes, Environmental Science Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA Climate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO, USA Department of Geography, University of Kansas, Lawrence, KA, USA Received: 16 November 2009 – Accepted: 7 January 2010 – Published: 26 January 2010 Correspondence to: S. Kloster (sk993@cornell.edu) Published by Copernicus Publications on behalf of the European Geosciences Union.
Multiway Spectral Partitioning and Higher-Order Cheeger Inequalities

A basic fact in spectral graph theory is that the number of connected components in an undirected graph is equal to the multiplicity of the eigenvalue zero in the Laplacian matrix of the graph. In particular, the graph is disconnected if and only if there are at least two eigenvalues equal to zero. Cheeger's inequality and its variants provide an approximate version of the latter fact; they state that a graph has a sparse cut if and only if there are at least two eigenvalues that are close to zero. It has been conjectured that an analogous characterization holds for higher multiplicities: There are <i>k</i> eigenvalues close to zero if and only if the vertex set can be partitioned into <i>k</i> subsets, each defining a sparse cut. We resolve this conjecture positively. Our result provides a theoretical justification for clustering algorithms that use the bottom <i>k</i> eigenvectors to embed the vertices into R<sup><i>k</i></sup>, and then apply geometric considerations to the embedding. We also show that these techniques yield a nearly optimal quantitative connection between the expansion of sets of size ≈ <i>n</i>/<i>k</i> and λ<sub><i>k</i></sub>, the <i>k</i>th smallest eigenvalue of the normalized Laplacian, where <i>n</i> is the number of vertices. In particular, we show that in every graph there are at least <i>k</i>/2 disjoint sets (one of which will have size at most 2<i>n</i>/<i>k</i>), each having expansion at most <i>O</i>(√λ<sub><i>k</i></sub> log <i>k</i>). Louis, Raghavendra, Tetali, and Vempala have independently proved a slightly weaker version of this last result. The √log <i>k</i> bound is tight, up to constant factors, for the “noisy hypercube” graphs.
Breaking the O ( n 2 ) Bit Barrier : Scalable Byzantine Agreement with an Adaptive Adversary

We describe an algorithm for Byzantine agreement that is scalable in the sense that each processor sends only Õ( √ n) bits, where n is the total number of processors. Our algorithm succeeds with high probability against an adaptive adversary, which can take over processors at any time during the protocol, up to the point of taking over arbitrarily close to a 1/3 fraction. We assume synchronous communication but a rushing adversary. Moreover, our algorithm works in the presence of flooding: processors controlled by the adversary can send out any number of messages. We assume the existence of private channels between all pairs of processors but make no other cryptographic assumptions. Finally, our algorithm has latency that is polylogarithmic in n. To the best of our knowledge, ours is the first algorithm to solve Byzantine agreement against an adaptive adversary, while requiring o(n2) total bits of communication.
The Potential for Augmented Reality to Bring Balance betweenthe Ease of Pedestrian Navigation and the Acquisition of Spatial Knowledge

Being completely lost in an unfamiliar environment can be inconvenient, stressful and, at times, even dangerous. Maps are the traditional tools used for guidance but many people find maps difficult to use. In recent years, new tools like outdoor Augmented Reality (AR) have become available which allow virtual navigation cues to be directly overlaid on the real world, potentially overcoming the limitations of maps. However, it has been hypothesized that lower effort invested in processing navigation guidance may lead to diminished spatial knowledge (SK) thereby making users of such navigation tools far more vulnerable to getting lost should the tools fail for any reason. This thesis explores the research question of how AR and maps compare as tools for pedestrian navigation guidance as well as for SK acquisition and if there is a potential for AR tools be developed that would balance the two. We present a series of studies to better understand the consequences of using AR in a pedestrian navigation tool. The first two studies compared time-on-task performance and user preferences for AR and Map navigation interfaces on an outdoor navigation task. The results were not aligned with expectations, which led us to build a controlled testing environment for comparing AR and map navigation. Using this simulated setting, our third study verified the assumption that AR can indeed result in more efficient navigation performance and it supported the hypothesis that this would come at the cost of weaker SK. In our fourth study, we used a dual task design to compare the relative cognitive resources required by map and AR interfaces. The quantitative data collected indicated that users could potentially accept additional workload designed to improve SK without incurring significantly more effort. Our fifth and final study explored an interface with additional AR cues that could potentially balance navigation guidance with SK acquisition. The contributions of this thesis include insights into performance issues relating to AR, a classification of user types based on navigation tool usage behavior, a testbed for simulating perfect AR tracking in a virtual setting, objective measures for determining route knowledge, the capacity that pedestrian navigation tool users may have for performing additional tasks, and guidelines that would be helpful in the design of pedestrian navigation tools.
USING THE ISO / IEC 9126 S TANDARD

This work proposes a methodology for source code quality and static behaviour evaluation of a software system, based on the standard ISO/IEC-9126. It uses elements automatically derived from source code enhanced with expert knowledge, in the form of quality characteristic rankings, allowing software engineers to assign weights to source code attributes. It is flexible in terms of the set of metrics and source code attributes employed, even in terms of the ISO/IEC-9126 characteristics to be assessed. We applied the methodology to two case studies, involving five open source and one proprietary system. Results demonstrated that the methodology can capture software quality trends and express expert perceptions concerning system quality in a quantitative and systematic manner.
Ultra-high Dimensional Multiple Output Learning With Simultaneous Orthogonal Matching Pursuit: A Sure Screening Approach

We propose a novel application of the Simultaneous Orthogonal Matching Pursuit (S-OMP) procedure for sparsistant variable selection in ultra-high dimensional multi-task regression problems. Screening of variables, as introduced in \cite{fan08sis}, is an efficient and highly scalable way to remove many irrelevant variables from the set of all variables, while retaining all the relevant variables. S-OMP can be applied to problems with hundreds of thousands of variables and once the number of variables is reduced to a manageable size, a more computationally demanding procedure can be used to identify the relevant variables for each of the regression outputs. To our knowledge, this is the first attempt to utilize relatedness of multiple outputs to perform fast screening of relevant variables. As our main theoretical contribution, we prove that, asymptotically, S-OMP is guaranteed to reduce an ultra-high number of variables to below the sample size without losing true relevant variables. We also provide formal evidence that a modified Bayesian information criterion (BIC) can be used to efficiently determine the number of iterations in S-OMP. We further provide empirical evidence on the benefit of variable selection using multiple regression outputs jointly, as opposed to performing variable selection for each output separately. The finite sample performance of S-OMP is demonstrated on extensive simulation studies, and on a genetic association mapping problem. $Keywords$ Adaptive Lasso; Greedy forward regression; Orthogonal matching pursuit; Multi-output regression; Multi-task learning; Simultaneous orthogonal matching pursuit; Sure screening; Variable selection
AN ANALYSIS IN THE IMPLICATION OF THERMAL ENERGY DISTRIBUTION TOWARDS HUMAN COMFORT IN AN OFFICE SPACE

AbstrakKajian ini bertujuan untuk menyiasat pengedaran tenaga haba terhadap prestasi seorang pekerja disebuah bangunan pejabat. Hawa dingin adalah penting untuk mengekalkan keselesaan terma persekitarandalam ruang tertutup, terutama untuk iklim di Malaysia. Untuk menyiasat sensasi berkesan haba daripadamereka yang bekerja dalam persekitaran yang tidak seragam, adalah amat penting untuk menentukanbutir-butir pemindahan haba tempatan. Dalam konteks ini, tujuan kajian ini adalah untuk membandingkanantara haba keselesaan dan suhu tetapan penyaman udara. Suhu dikekalkan pada lima tahap yangberbeza iaitu 19, 21, 23, 26 dan 29oC. Kajian ini telah dijalankan di dalam ruang alam sekitar di UniversitiMalaysia Pahang. Hasil kajian menunjukkan bahawa suhu antara 21-29oC dan kelembapan relatif antara50-60% boleh memberi perubahan kepada tahap suhu kulit yang menunjukkan tahap keselesaan yangdialami oleh subjek. AbstractThis study aims to investigate thermal energy distribution on a worker’s performance in an officebuilding. Air conditioning is essential for maintaining environment thermal comfort in indoor space,especially for the climate in Malaysia. In order to investigate an effectual thermal sensation of thoseworking in a non-uniform environment, it is very important to define the local heat transfer details. Inthis context, the purpose of this study is to compare between thermal comfort and temperature settingsof air conditioning. The temperature was maintained at five different levels which are 19, 21, 23, 26and 29oC. The study was carried out in the environmental chamber at University Malaysia Pahang.The result shows that the temperature settings between 21-29oC and relative humidity between 50-60% can give a difference to skin temperature level that indicates the level of comfort experienced bythe subjects.
The Tiny-Tasks Granularity Trade-Off: Balancing overhead vs. performance in parallel systems

Models of parallel processing systems typically assume that one has $l$ workers and jobs are split into an equal number of $k=l$ tasks. Splitting jobs into $k>l$ smaller tasks, i.e. using ``tiny tasks'', can yield performance and stability improvements because it reduces the variance in the amount of work assigned to each worker, but as $k$ increases, the overhead involved in scheduling and managing the tasks begins to overtake the performance benefit. We perform extensive experiments on the effects of task granularity on an Apache Spark cluster, and based on these, developed a four-parameter model for task and job overhead that, in simulation, produces sojourn time distributions that match those of the real system. We also present analytical results which illustrate how using tiny tasks improves the stability region of split-merge systems, and analytical bounds on the sojourn and waiting time distributions of both split-merge and single-queue fork-join systems with tiny tasks. Finally we combine the overhead model with the analytical models to produce an analytical approximation to the sojourn and waiting time distributions of systems with tiny tasks which include overhead. Though no longer strict analytical bounds, these approximations matched the Spark experimental results very well in both the split-merge and fork-join cases.
User Empowerment in the Internet of Things

A key concern in the Internet of Things (IoT) has been the integration of mundane objects in the Internet. Although increasingly interconnected, the IoT ecosystem is largely industry-centered. This leads to the creation of limited and incompatible services disempowering users by hampering their participation. In this thesis, we address this issue by empowering users to create, personalize, and distribute services in the IoT ecosystem. We define a general framework for user empowerment relying on the concepts of People, Places, Things and Applications and study their interactions. These concepts are used as design elements to implement an IoT Service Platform. The general framework, the reference implementation and the evaluation provide the design guidelines for building IoT service platforms enabling user empowerment in the IoT.
The Routing of Complex Contagion in Kleinberg ’ s Small-World Networks

In Kleinberg’s small-world network model, strong ties are modeled as deterministic edges in the underlying base grid and weak ties are modeled as random edges connecting remote nodes. The probability of connecting a node u with node v through a weak tie is proportional to 1/|uv|α, where |uv| is the grid distance between u and v and α ≥ 0 is the parameter of the model. Complex contagion refers to the propagation mechanism in a network where each node is activated only after k ≥ 2 neighbors of the node are activated. In this paper, we propose the concept of routing of complex contagion (or complex routing), where we can activate one node at one time step with the goal of activating the targeted node in the end. We consider decentralized routing scheme where only the weak ties from the activated nodes are revealed. We study the routing time of complex contagion and compare the result with simple routing and complex diffusion (the diffusion of complex contagion, where all nodes that could be activated are activated immediately in the same step with the goal of activating all nodes in the end). We show that for decentralized complex routing, the routing time is lower bounded by a polynomial in n (the number of nodes in the network) for all range of α both in expectation and with high probability (in
The Quantum-Like Brain Operating on Subcognitive and Cognitive Time Scales

We propose a {\it quantum-like} (QL) model of the functioning of the brain. It should be sharply distinguished from the reductionist {\it quantum} model. By the latter cognition is created by {\it physical quantum processes} in the brain. The crucial point of our modelling is that discovery of the mathematical formalism of quantum mechanics (QM) was in fact discovery of a very general formalism describing {\it consistent processing of incomplete information} about contexts (physical, mental, economic, social). The brain is an advanced device which developed the ability to create a QL representation of contexts. Therefore its functioning can also be described by the mathematical formalism of QM. The possibility of such a description has nothing to do with composing of the brain of quantum systems (photons, electrons, protons,.). Moreover, we shall propose a model in that the QL representation is based on conventional neurophysiological model of the functioning of the brain. The brain uses the QL rule (given by von Neumann trace formula) for calculation of {\it approximative averages} for mental functions, but the physical basis of mental functions is given by neural networks in the brain. The QL representation has a {\it temporal basis. } Any cognitive process is based on (at least) two time scales: subcognitive time scale (which is very fine) and cognitive time scale (which is essentially coarser).
Many particle approximation of the Aw-Rascle-Zhang second order model for vehicular traffic

We consider the Follow-The-Leader approximation of the Aw-Rascle-Zhang (ARZ) model for traffic flow in a multi-population formulation. We prove rigorous convergence to weak solutions of the ARZ system in the many particle limit in presence of vacuum. The result is based on uniform $\mathbf{BV}$ estimates on the discrete particle velocity. We complement out result with numerical simulations of the particle method compared with some exact solutions to the Riemann problem of the ARZ system.
ec 2 00 6 An efficient algorithm for positive realizations

We combine recent ideas from the theory of positive systems to give an efficient general algorithm for positive realizations of transfer functions. With the help of our algorithm we determine the minimal order of positive realizations for a family of transfer functions, which complements an earlier result of [6]. Finally, we improve a lower-bound of [18] to indicate that our algorithm is indeed efficient in general.
ON DATA QUALITY ASSURANCE AND CONFLATION ENTANGLEMENT IN CROWDSOURCING FOR ENVIRONMENTAL STUDIES

Abstract. Volunteer geographical information (VGI) either in the context of citizen science, active crowdsourcing and even passive crowdsourcing has been proven useful in various societal domains such as natural hazards, health status, disease epidemic and biological monitoring. Nonetheless, the variable degrees or unknown quality due to the crowdsourcing settings are still an obstacle for fully integrating these data sources in environmental studies and potentially in policy making. The data curation process in which a quality assurance (QA) is needed is often driven by the direct usability of the data collected within a data conflation process or data fusion (DCDF) combining the crowdsourced data into one view using potentially other data sources as well. Using two examples, namely land cover validation and inundation extent estimation, this paper discusses the close links between QA and DCDF in order to determine whether a disentanglement can be beneficial or not to a better understanding of the data curation process and to its methodology with respect to crowdsourcing data. Far from rejecting the usability quality criterion, the paper advocates for a decoupling of the QA process and the DCDF step as much as possible but still in integrating them within an approach analogous to a Bayesian paradigm.
Finding the best semantic expansion to query PubMed: automatic performance assessment of four search strategies on all MeSH descriptors

Background: With the continuous expansion of available biomedical data, efficient and effective information retrieval has become of utmost importance. Semantic expansions of queries using synonyms may improve information retrieval. Objective: The aim of this study was to propose an innovative method that could estimate automatically the three main metrics used in information science (precision, recall and F-measure) of four different semantic expansion strategies, assessed on all the descriptors in the MeSH thesaurus (n=28,313). Methods: Four search strategies were assessed in this study: the standard Automatic Term Mapping (ATM) of PubMed and three strategies that use semantic expansion. ATM queries were of the form: (“preferred term”[MH] OR “preferred term”[All fields]). The queries of the other three strategies were of the form: (“preferred term”[MH] OR “preferred term”[All fields] OR “synonym 1”[All fields] OR “synonym 2”[All fields] OR etc.). These three strategies differed by the number and provenance of the synonyms used to build the queries: MeSH synonyms, UMLS mappings and custom mappings (CISMeF). Metrics were assessed by computing (A): the number of all relevant citations, using NLM indexing as gold standard ((“preferred term”[MH]), (B): the number of citations retrieved by the added terms, and (C): the number of relevant citations retrieved by the added terms (combining the previous two queries with an “AND” operator). Therefore, it was possible to compute programmatically the metrics for each strategy using every MeSH descriptor as a “preferred term”. 239,724 different queries were built and sent to PubMed API. The four search strategies were ranked and compared for each metric. Results: ATM had the worst performance of the four strategies, for all three metrics. MeSH strategy had the best mean precision (50.93 %, SD = 23 %). UMLS strategy had the best recall and F-measure (40.57 %, SD = 31 % and 35.51 %, SD = 24 %, respectively). CISMeF had the second best recall and F-measure (40.11 %, SD = 31 % and 35.10 %, SD = 24 %, respectively). However, considering a cut-off of 5%, CISMeF had better precision than UMLS for 1180 descriptors, better recall for 793 descriptors and better F-measure for 678 descriptors. Conclusions: This study highlights the importance of using semantic expansion strategies to improve information retrieval. However, the performances of the strategies were greatly variable depending on the MeSH descriptor, for each metric. These results confirm there is no ideal search strategy for all descriptors. Different semantic expansions should be used depending on the descriptor and the user’s objectives. This led our team to develop an interface that allows users to input a descriptor and then proposes the best semantic expansion to maximize the three main metrics, precision, recall or F-measure.
DISTRIBUCIÓN DE LA MATERIA ORGÁNICA EN CLASES DE AGREGADOS EN UN LATOSOL ARCILLOSO ROJO BAJO FORESTACIÓN Y PASTIZAL ORGANIC MATTER DISTRIBUTION IN CLASSES OF AGGREGATES OF A RED CLAY LATOSOL UNDER FORESTRY AND PASTURES

Studies of the concentration of total organic carbon (TOC) in soil and organic matter fractions contribute significantly to the evaluation of soil quality, particularly in the study region, where there is no information on this topic. Moreover, there is also a worldwide concern about the carbon cycle, depending on the greenhouse effect that harms the world’s climatic conditions. The aim of this study was to evaluate the effect of production systems in TOC concentration in a soil classified as dystrophic red clayey latosol, in the fraction of particulate organic carbon and in the mineral carbon fraction, i. e. , the fraction of carbon associated with soil minerals and in various classes of aggregates of the soil planted with: 1) 13 and 20-year-old eucalyptus (Eucalyptus saligna), 2) pastures and 3) native forest where hygrophilous species and deciduous xerophytes dominate. Soil samples were collected in the district of Butia, Rio Grande do Sul (Brazil) in 2006 in the depths 0.00 to 0.05, 0.05 to 0.10, 0.10 to 0.20 and from 0.20 to 0.40 m. Samples were air-dried at 20 °C and sieved according to the classes of granulometric fractionation, considering the aggregate classes of 4.76 to 8.00 mm, 2.00 to 4.76 mm, 1.00 to 2.00 mm, 0.50 to 1.00 mm, 0.25 to 0.50 mm and 0.25 mm. For each class of aggregate, particulate organic carbon and TOC was determined. The highest TOC concentrations, particulate organic carbon and mineral carbon occurred in the largest fraction (8.00 to 4.76 mm). In pasture soils greatest TOC accumulation was found at depth of 0.05 to 0.20 m, in classes of aggregates 8.00 to 0.50 mm.