Miracle-dz/UniFAR-FTUs huggingface dataset:
Mapping and evaluating sugarcane expansion in Brazil’s savanna using MODIS and intensity analysis: a case-study from the state of Tocantins

ABSTRACT In Brazil, the main biofuel crop is sugarcane, and with its rapid expansion, there is much debate about what land uses and land covers it is replacing, and what are the associated environmental and social impacts. Some argue sugarcane is mainly replacing cattle pasture, thus having minimal impacts on native vegetation and small-scale family farming. In contrast, others claim sugarcane is replacing cropland traditionally under soybeans, rice, beans, and corn. Thus, food security is negatively affected and small-scale family farming livelihoods and culture are threatened. This is a proof-of-concept paper illustrating methods contributing toward the resolution of such debates. First we map land use and cover change in areas undergoing sugarcane expansion using satellite data from MODIS (Moderate Resolution Imaging Spectroradiometer); second, we test the hypothesis that sugarcane is replacing traditional annual crops using intensity analysis, via a case study of land change in the municipality of Pedro Afonso, Tocantins in northern Brazil between the 2008–2013 crop years. Maps matched reference data with overall agreements between 87–91%. Intensity analysis confirmed sugarcane is replacing annual crops much more than cattle pasture and other land uses and covers, pointing to particular economic and social processes driving land change.
Washington University Open Scholarship Washington University Open Scholarship

The increasing popularity of deep learning in workloads across vision, speech, and language has inspired many attempts to develop hardware accelerators for matrix-matrix multiplication. Both application specific integrated circuits (ASICs), and field-programmable arrays (FPGAs) are used for this purpose. However, a trade off between the two platforms is that ASICs provide little flexibility after they are manufactured while designs on FPGAs are flexible but application development on FPGAs is more time-consuming. In this work, we aim to find the balance between reconfigurability and development efficiency by designing a reconfigurable systolic architecture as an overlay on the FPGA. Our contribution to the reconfigurable systolic architectures is a multiplexer based crossbar network that interconnects every processing element in the network. The crossbar network grants user run-time reconfigurability of the topology of the systolic array, enabling the user to specify the shape and size of the systolic architecture on-the-fly. The proposed overlay architecture achieves similar computational hardware resource usage and maximum clock frequency compared to the baseline designs.
Distributed ASR Using Speech Coder Dat Representatio Trond Skogstad and Torb Norwegian University of Science and Technology ,

This paper proposes an alternative approach to distributed speech recognition in scenarios where both reliable feature vectors and the reconstruction of the speech signal are required. By transmitting the difference between speech coded information and the desired feature vectors, this system achieves both excellent quality speech reconstruction and ASR recognition performance. Experiments show that a transparent recognition rate is achieved with as little as 0.6 kbps of additional information supplementing the AMR speech coder operating at 4.75 kbps. The total rate is comparable to the the ETSI 202 211 extended front-end standard.
Computer Methods and Programs in Biomedicine

Background and objective: With the increasing problem of coronavirus disease 2019 (COVID-19) in the world, improving the image resolution of COVID-19 computed tomography (CT) becomes a very important task. At present, single-image super-resolution (SISR) models based on convolutional neural networks (CNN) generally have problems such as the loss of high-frequency information and the large size of the model due to the deep network structure. Methods: In this work, we propose an optimization model based on multi-window back-projection residual network (MWSR), which outperforms most of the state-of-the-art methods. Firstly, we use multi-window to reﬁne the same feature map at the same time to obtain richer high/low frequency information, and fuse and ﬁlter out the features needed by the deep network. Then, we develop a back-projection network based on the dilated convolution, using up-projection and down-projection modules to extract image features. Finally, we merge several repeated and continuous residual modules with global features, merge the information ﬂow through the network, and input them to the reconstruction module. Results: The proposed method shows the superiority over the state-of-the-art methods on the benchmark dataset, and generates clear COVID-19 CT super-resolution images. Conclusion: Both subjective visual effects and objective evaluation indicators are improved, and the model speciﬁcations are optimized. Therefore, the MWSR method can improve the clarity of CT images of COVID-19 and effectively assist the diagnosis and quantitative assessment of COVID-19. © 2021 Elsevier B.V. All rights reserved.
The Response of Simulated Arctic Mixed‐Phase Stratocumulus to Sea Ice Cover Variability in the Absence of Large‐Scale Advection

This study examines the responses of Arctic mixed‐phase stratocumulus boundary layer to sea ice cover variability near the sea ice margins using large eddy simulations. The simulations are conducted for two different atmospheric conditions, based on observations from the Surface Heat Budget of the Arctic Ocean Experiment (SHEBA) (100% sea ice‐covered) and the Mixed‐Phase Arctic Cloud Experiment (M‐PACE) (open ocean). The effect of sea ice cover variability is investigated for both atmospheric conditions by conducting a series of simulations prescribed with varying amounts of sea ice cover and no large‐scale advection. As sea ice cover amount decreases, the SHEBA boundary layer deepens and becomes decoupled. The relative strength of turbulence driven by surface heating to that driven by cloud top radiative cooling increases. Cloud ice and snow grow more efficiently than cloud liquid with moisture transported from the lower boundary layer. On the other hand, as sea ice cover amount increases, the M‐PACE boundary layer becomes shallower and more coupled with the surface as turbulence mainly driven by cloud top radiative cooling. Moisture supply from the surface is reduced, while cloud droplets are generated from turbulence at cloud top with little ice formation. In both atmospheric conditions, the boundary layer turbulence structure is modified according to change in the relative strength of boundary layer turbulent sources as sea ice amount changes, resulting in the growth/decay of the cloud layer. Simulations with smaller sea ice cover amounts are associated with more cloud ice but not necessarily more cloud liquid.
Automation of legal reasoning and decision based on ontologies. (Automatisation du raisonnement et décision juridiques basés sur les ontologies)

This thesis analyses the problem of building well-founded domain ontologies for reasoning and decision support purposes. Specifically, it discusses the building of legal ontologies for rule-based reasoning. In fact, building well-founded legal domain ontologies is considered as a difficult and complex process due to the complexity of the legal domain and the lack of methodologies. For this purpose, a novel middle-out approach called MIROCL is proposed. MIROCL tends to enhance the building process of well-founded domain ontologies by incorporating several support processes such as reuse, modularization, integration and learning. MIROCL is a novel modular middle-out approach for building well-founded domain ontologies. By applying the modularization process, a multi-layered modular architecture of the ontology is outlined. Thus, the intended ontology will be composed of four modules located at different abstraction levels. These modules are, from the most abstract to the most specific, UOM(Upper Ontology Module), COM(Core Ontology Module), DOM(Domain Ontology Module) and DSOM(Domain-Specific Ontology Module). The middle-out strategy is composed of two complementary strategies: top-down and bottom-up. The top-down tends to apply ODCM (Ontology-Driven Conceptual Modeling) and ontology reuse starting from the most abstract categories for building UOM and COM. Meanwhile, the bottom-up starts from textual resources, by applying ontology learning process, in order to extract the most specific categories for building DOM and DSOM. After building the different modules, an integration process is performed for composing the whole ontology. The MIROCL approach is applied in the criminal domain for modeling legal norms. A well-founded legal domain ontology called CriMOnto (Criminal Modular Ontology) is obtained. Therefore, CriMOnto has been used for modeling the procedural aspect of the legal norms by the integration with a logic rule language (SWRL). Finally, an hybrid approach is applied for building a rule-based system called CORBS. This system is grounded on CriMOnto and the set of formalized rules.
An Investigation into Children’s Out-of-School Physical Activity

This thesis used a multi-methods approach to explore children’s out-of-school physical activity (PA). Study 1 found that children living in the most deprived neighbourhoods represent an important target group for future PA and health interventions. Further, the study also revealed that self-reported PA was positively associated with independent mobility. Study 2 confirmed that the weekend was a period of low moderate-to-vigorous PA (MVPA), and revealed that raw PA levels derived from the wrist-worn GENEActiv are not comparable with hip-worn ActiGraph. Agreement between the devices differed according to PA intensity and time of day, with the greatest difference occurring in light PA (LPA) during school hours. Using children’s recounted perceptions and experiences of out-of-school PA, study 3 demonstrated how an inclusive, interactive and child-centred methodology (i.e., write, draw show and tell; WDST) may be advantageous when compared to traditional singular qualitative methods. In study 4 parental safety concerns were reported to be the most consistent barrier to children’s out-of-school PA. The family case studies demonstrated how family perceptions and constraints can influence children’s out-of-school PA levels and activity mode (i.e., active school travel, outdoor play and organised sport). Such constraints include factors such as, school proximity, neighbourhood perceptions and family context. Study 5 revealed substantial intra-individual variability in children’s weekend MVPA. PA diary data revealed that children's weekend PA was mostly unstructured in nature and undertaken with friends, whereas a greater proportion of parents’ weekend PA was undertaken alone in structured settings. Family case studies demonstrated that in the selected cases MVPA levels and variability across weekends were contingent on mode of PA participation. This thesis contributes evidence to inform future out-of-school PA interventions. The research has demonstrated that children’s out-of-school PA is influenced by a complex interaction of individual, social and environmental factors. Specific highlights include the family and neighbourhood environment. The weekend is associated with low PA and as such represents an important time period to promote PA in children. Future weekend PA interventions should target specific modes of activity, as the facilitators and barriers to these activities vary considerably. Moreover, in future, research and practice should focus on ways in which to modify neighbourhood attributes to support children’s out-of-school active living.
Coordinate-descent for learning orthogonal matrices through Givens rotations

Theorem 1. Convergence to local optimum (a) The sequence of iterates Ut of Algorithm 4 satisfies: limt→∞ ||∇f(Ut)|| = 0. This means that the accumulation points of the sequence {Ut}t=1 are critical points of . (b) Assume the critical points of f are isolated. Let U∗ be a critical point off . ThenU∗ is a local minimum off if and only if it is asymptotically stable with regard to the sequence generated by Algorithm 4.
Real-Time Industrial Parameter Measurement Using CAN , Zigbee and Ethernet Web Server

The demand of energy is increased day by day so we have to save the energy for our future generation. To reduce the energy consumption of various equipment running in industry, Real-Time Industrial Parameter Measurement Using CAN, Zigbee and Ethernet Web Server plays a key role. This paper presents various methods to measure and record the parameters of equipments running in an industry. Here Power consumption, Temperature, speed of rotation and voltage are the parameters. After monitoring the parameters data will send to gateway section using CAN protocol. Gateway section is connected to the web server using wireless Zigbee. User can access the each and every machine using IP. The purpose of temperature sensor is to control the equipment based on the threshold level. If the machine is having high temperature it will be turned off automatically and if the temperature is below the level it will be turned on.
Renewable energy for rural development in Turkey

In last three decades, Turkey’s rural energy development has achieved some success. The average cooking efficiencies increased from 25% in 1980 to 60% in 2010, more than 99% of townships and villages have electric connection, remarkable progress in biomass, hydropower and other renewable energy also has been made. Since the late 1980s, both the rural economy and rural energy consumption have changed dramatically. In order to reduce dependency on imported expensive fossil fuels, Turkey should be used the renewable energy sources, because they are domestic and abundant. However considering the total cost of renewable energy production, these sources can be used not to replace the fossil fuels, but to supply energy requirement in the country. Renewable energy is being pointed as a potentially significant new source of jobs and climate change mitigation. This paper discusses the status, features, and trends, as well as technical potentials of renewable energy for rural development in Turkey. The present study also shows that there is enough renewable potential for meeting the country energy and electricity demand.
ICT and the Changing Landscape of Global Tourism Distribution

The travel and tourism sector has emerged as one of the most important sectors for developing as well as developed countries. Tourism incorporates many of the features of the information society such as globalization, mobility and information richness. People from all nations, social rank, professions are potential tourists. Tourism links a worldwide supplier community with consumers, equally distributed worldwide. Its physical and virtual networks enable worldwide travelling, bringing together very distant cultures and habits. The industry is diverse, the size of tourism principals varies from micro to global enterprises. While some are fragmented, other parts, like the airlines, are concentrated into an oligopoly of global alliances. Information systems (IS) in tourism have been among the pioneers of leading edge technology applications: Computer Reservation Systems (CRS) or Global Distribution Systems (GDS) have been among the first international inter-organizational systems. Yield management systems are among the most advanced data mining applications. Tourism marketing systems typically represent the forefront of multimedia and virtual-reality applications. The World Wide Web is profoundly changing the production, distribution and consumption of touristic products. Information and communication technology (ICT) is probably the strongest driving force for changes within the tourism industry. Both industries are not only growing above average, they will also be among the most important industries in the next century. Being closely interrelated
Variational Bayesian Inference for Mixed Logit Models with Unobserved Inter- and Intra-Individual Heterogeneity

Variational Bayes (VB) methods have emerged as a fast and computationally-efficient alternative to Markov chain Monte Carlo (MCMC) methods for Bayesian estimation of mixed logit models. In this paper, we derive a VB method for posterior inference in mixed multinomial logit models with unobserved interand intra-individual heterogeneity. The proposed VB method is benchmarked against MCMC in a simulation study. The results suggest that VB is substantially faster than MCMC but also noticeably less accurate, because the mean-field assumption of VB is too restrictive. Future research should thus focus on enhancing the expressiveness and flexibility of the variational approximation.
Taxonomies of Visual Programming P and rogram Visualization

here has been a great interest recently in systems that use graphics to aid in the programming, ‘ debugging, and understanding of computer systems. The terms ‘‘Visual Programming’’ and ‘Program Visualization’’ have been applied to these systems. This paper attempts to provide - t more meaning to these terms by giving precise deﬁnitions, and then surveys a number of sys ems that can be classiﬁed as providing Visual Programming or Program Visualization. These systems are organized by classifying them into three different taxonomies.
Multiple Agent Formalisms for Coordination in Organizational Problems

Many organizational problems are ill-structured where the structure of a problemis not apparent at the outset of the problem solving process. Agents responsiblefor these problems often decompose them into subproblems the solution ofwhich is the responsibility of other agents. These problems are only nearly independentin the sense that temporal and technical dependencies exist betweenthe different subproblems. Since the problems are interdependent, coordinatingthe activities of the different agents is important for ensuring that the partial solutionsdiscovered by these different agents are not conflicting in terms of globalconsistency. Usual mechanisms for coordination include communication and negotiationbetween agents of interrelated problems. In this paper we describe aformalism for coordination in multiple agent ill-structured problems based onfour properties of tasks, atomicity, serializability, completeness and soundness.We examine how these properties are essential for handling conflict resolution.We also outline some requirements for control.
Database Compression for Intelligent On-board Vehicle Controllers

often equipped with intelligent on-board passenger information systems. A frequently used but time and labor-intensive way for keeping the on-board controllers up-to-date is the manual update using different memory cards (e.g. flash cards) or portable computers. This paper describes a compression algorithm that enables data transmission using low bandwidth wireless radio networks (e.g. GPRS) by minimizing the amount of data traffic. In typical cases it reaches a compression rate of an order of magnitude better than that of the general purpose compressors. Compressed data can be easily expanded by the low-performance controllers, too.
High-fidelity haptic synthesis of contact with deformable bodies

A method for synthesizing the haptic response of nonlinear deformable objects from data obtained by offline simulation helps create surgical simulators with high-fidelity haptic feedback. Haptic displays provide users with artificially created tactile sensations. One important use of these displays is to recreate the experience caused by contact between a tool and an object. This capability can be useful in several applications, such as surgical simulators, because users experience an enhanced sense of realism when a haptic simulation is combined with a graphic simulation. Haptic displays require two essential subsystems: a haptic device, which typically has a handle connected to sensors and actuators, and a computational system that interfaces with the device.
Partial-Observation Stochastic Games: How to Win when Belief Fails

In two-player finite-state stochastic games of partial observation on graphs, in every state of the graph, the players simultaneously choose an action, and their joint actions determine a probability distribution over the successor states. The game is played for infinitely many rounds and thus the players construct an infinite path in the graph. We consider reachability objectives where the first player tries to ensure a target state to be visited almost-surely (i.e., with probability 1) or positively (i.e., with positive probability), no matter the strategy of the second player. We classify such games according to the information and to the power of randomization available to the players. On the basis of information, the game can be one-sided with either (a) player 1, or (b) player 2 having partial observation (and the other player has perfect observation), or two-sided with (c) both players having partial observation. On the basis of randomization, (a) the players may not be allowed to use randomization (pure strategies), or (b) they may choose a probability distribution over actions but the actual random choice is external and not visible to the player (actions invisible), or (c) they may use full randomization. Our main results for pure strategies are as follows: (1) For one-sided games with player 2 having perfect observation we show that (in contrast to full randomized strategies) belief-based (subset-construction based) strategies are not sufficient, and we present an exponential upper bound on memory both for almost-sure and positive winning strategies; we show that the problem of deciding the existence of almost-sure and positive winning strategies for player 1 is EXPTIME-complete and present symbolic algorithms that avoid the explicit exponential construction. (2) For one-sided games with player 1 having perfect observation we show that nonelementary memory is both necessary and sufficient for both almost-sure and positive winning strategies. (3) We show that for the general (two-sided) case finite-memory strategies are sufficient for both positive and almost-sure winning, and at least nonelementary memory is required. We establish the equivalence of the almost-sure winning problems for pure strategies and for randomized strategies with actions invisible. Our equivalence result exhibit serious flaws in previous results of the literature: we show a nonelementary memory lower bound for almost-sure winning whereas an exponential upper bound was previously claimed.
Single Network Adaptive Critic aided nonlinear dynamic inversion for suboptimal command tracking

Using the Approximate Dynamic Programming (ADP) approach, nonlinear optimal control problems can be solved by using a dual neural network architecture called the Adaptive Critic (AC). A Single Network Adaptive Critic (SNAC) architecture has been shown to have much faster convergence than AC. Even though the SNAC offers a systematic optimal control design method for optimal state regulation for a class of nonlinear control systems, it lacks the generality necessary for command tracking as it is practically difficult to anticipate a proper training domain in state space when the command sequence is not known a priori. Dynamic Inversion (DI), on the other hand, is a very popular nonlinear control design method for both output regulation and command tracking that offers a closed form expression for control. However, it lacks the interpretation and advantages of optimal control design. In this paper we propose a systematic technique for selecting the DI gains with the help of a pre-synthesized SNAC network in order that the resulting DI solution closely mimics the SNAC solution for output regulation and can be extended to command tracking problems. Moreover, it retains all the benefits of DI design. The potential of this new methodology of near-optimal dynamic inversion design is demonstrated in this paper by considering a benchmark nonlinear system.