Miracle-dz/UniFAR-FTUs huggingface dataset:
Selection of the Key Earth Observation Sensors and Platforms Focusing on Applications for Polar Regions in the Scope of Copernicus System 2020-2030

An optimal payload selection conducted in the frame of the H2020 ONION project (id 687490) is presented based on the ability to cover the observation needs of the Copernicus system in the time period 2020–2030. Payload selection is constrained by the variables that can be measured, the power consumption, and weight of the instrument, and the required accuracy and spatial resolution (horizontal or vertical). It involved 20 measurements with observation gaps according to the user requirements that were detected in the top 10 use cases in the scope of Copernicus space infrastructure, 9 potential applied technologies, and 39 available commercial platforms. Additional Earth Observation (EO) infrastructures are proposed to reduce measurements gaps, based on a weighting system that assigned high relevance for measurements associated to Marine for Weather Forecast over Polar Regions. This study concludes with a rank and mapping of the potential technologies and the suitable commercial platforms to cover most of the requirements of the top ten use cases, analyzing the Marine for Weather Forecast, Sea Ice Monitoring, Fishing Pressure, and Agriculture and Forestry: Hydric stress as the priority use cases.
Hyperspectral Images Classification Based on Dense Convolutional Networks with Spectral-Wise Attention Mechanism

Hyperspectral images (HSIs) data that is typically presented in 3-D format offers an opportunity for 3-D networks to extract spectral and spatial features simultaneously. In this paper, we propose a novel end-to-end 3-D dense convolutional network with spectral-wise attention mechanism (MSDN-SA) for HSI classification. The proposed MSDN-SA exploits 3-D dilated convolutions to simultaneously capture the spectral and spatial features at different scales, and densely connects all 3-D feature maps with each other. In addition, a spectral-wise attention mechanism is introduced to enhance the distinguishability of spectral features, which improves the classification performance of the trained models. Experimental results on three HSI datasets demonstrate that our MSDN-SA achieves competitive performance for HSI classification.
A Pose Awareness Solution for Estimating Pedestrian Walking Speed

Pedestrian walking speeds (PWS) can be used as a “body speedometer” to reveal health status information of pedestrians and positioning indoors with other locating methods. This paper proposes a pose awareness solution for estimating pedestrian walking speeds using the sensors built in smartphones. The smartphone usage pose is identified by using a machine learning approach based on data from multiple sensors. The data are then coupled tightly with an adaptive step detection solution to estimate the pedestrian walking speed. Field tests were carried out to verify the advantages of the proposed algorithms compared to existing solutions. The test results demonstrated that the features extracted from the data of the smartphone built-in sensors clearly reveal the characteristics of the pose pattern, with overall accuracy of 98.85% and a kappa statistic of 98.46%. The proposed walking speed estimation solution, running in real-time on a commercial smartphone, performed well, with a mean absolute error of 0.061 m/s, under a challenging walking process combining various usage poses including texting, calling, swinging, and in-pocket modes.
NIST Post-Quantum Cryptography- A Hardware Evaluation Study

—Experts forecast that quantum computers can break classical cryptographic algorithms. Scientists are developing post-quantum cryptographic (PQC) algorithms, that are invulnerable to quantum computer attacks. The National Institute of Standards and Technology (NIST) started a public evaluation process to standardize quantum-resistant public key algorithms. The objective of our study is to provide a hardware-based comparison of the NIST PQC candidates. For this, we use a High-Level Synthesis (HLS)-based hardware design methodology to map high-level C speciﬁcations of round 2 PQC candidates into both FPGA and ASIC implementations.
Nonintrusive Depth Estimation of Buried Radioactive Wastes Using Ground Penetrating Radar and a Gamma Ray Detector

This study reports on the combination of data from a ground penetrating radar (GPR) and a gamma ray detector for nonintrusive depth estimation of buried radioactive sources. The use of the GPR was to enable the estimation of the material density required for the calculation of the depth of the source from the radiation data. Four different models for bulk density estimation were analysed using three materials, namely: sand, gravel and soil. The results showed that the GPR was able to estimate the bulk density of the three materials with an average error of 4.5%. The density estimates were then used together with gamma ray measurements to successfully estimate the depth of a 658 kBq ceasium-137 radioactive source buried in each of the three materials investigated. However, a linear correction factor needs to be applied to the depth estimates due to the deviation of the estimated depth from the measured depth as the depth increases. This new application of GPR will further extend the possible fields of application of this ubiquitous geophysical tool.
Spatio-Temporal Patterns of Smallholder Irrigated Agriculture in the Horn of Africa Using GEOBIA and Sentinel-2 Imagery

Irrigated agriculture practiced by smallholders is essential for food security in East Africa. Insight in the spatio-temporal distribution of irrigated agriculture is required to optimize irrigation water use. Irrigation-mapping efforts in the complex smallholder-dominated agricultural landscape in the Horn of Africa so far are generally too coarse and often the extent of smallholder irrigated agriculture is underestimated. The arrival of Sentinel-2 (10-m resolution) considerably enhanced the prospect of analyzing agriculture at field level. The objective of this study is to demonstrate the feasibility to map spatio-temporal patterns of smallholder irrigated agriculture in the Horn of Africa using a novel method based on object-based image analysis and Sentinel-2 imagery. The method includes segmentation at field level and smart process-based rules on neighbouring objects and NDVI time series to distinguish irrigated agriculture from rainfed agriculture. The assumption is that irrigation is applied at field level, while a rainfall event is not restricted to field borders and that this information on the local context of irrigated agriculture can be exploited in an object-based approach. Monthly land-use maps on irrigated agriculture were produced for September 2016 to August 2017 at 10-m resolution field level (objects). Three different spatial-heterogeneity thresholds were used to describe the vegetation development of neighbouring objects and to assign crop growth to either rainfall or irrigation. This method is unique as it can discriminate irrigation- and rainfall-induced crop growth, even in the rainy season. The estimates of irrigated agriculture in the Horn of Africa range from 27.96 Mha to 37.13 Mha. This is 2.8 to 3.7 times higher than the current highest estimate, the Global Irrigated Area Map at 1000 m resolution, and 1.2 to 1.7 times higher than the Irrigated Area Map Asia (2000–2010) and Africa (2010) when including water-managed non-irrigated croplands. For the dry season (October–March), the estimates of irrigated agriculture range from 17.67 Mha to 23.72 Mha. The irrigation frequency, the number of time steps (months) with irrigation events in the studied year, varies strongly. Irrigated area with an irrigation frequency of 1 to 2 events has a mapped surface area of 22.57 Mha to 23.13 Mha. Irrigated area with an irrigation frequency of 3 or more events has a mapped surface area of 4.83 Mha to 14.56 Mha. The produced maps will provide valuable information for the development of irrigated agriculture and optimization of irrigation water use in the Horn of Africa. In addition, the portability of this method to other (semi-)arid regions seems feasible as the local context of irrigated agriculture, used in this study for irrigation classification, describes universal characteristics regarding irrigated agriculture. This is especially valuable in the context of food security and water availability for other large data-poor regions in low- and middle-income countries.
The Global Spatiotemporal Distribution of the Mid-Tropospheric CO2 Concentration and Analysis of the Controlling Factors

The atmospheric infrared sounder (AIRS) provides a robust and accurate data source to investigate the variability of mid-tropospheric CO2 globally. In this paper, we use the AIRS CO2 product and other auxiliary data to survey the spatiotemporal distribution characteristics of mid-tropospheric CO2 and the controlling factors using linear regression, empirical orthogonal functions (EOFs), geostatistical analysis, and correlation analysis. The results show that areas with low mid-tropospheric CO2 concentrations (20°S–5°N) (384.2 ppm) are formed as a result of subsidence in the atmosphere, the presence of the Amazon rainforest, and the lack of high CO2 emission areas. The areas with high mid-tropospheric CO2 concentrations (30°N–70°N) (382.1 ppm) are formed due to high CO2 emissions. The global mid-tropospheric CO2 concentrations increased gradually (the annual average rate of increase in CO2 concentration is 2.11 ppm/a), with the highest concentration occurring in spring (384.0 ppm) and the lowest value in winter (382.5 ppm). The amplitude of the seasonal variation retrieved from AIRS (average: 1.38 ppm) is consistent with that of comprehensive observation network for trace gases (CONTRAIL), but smaller than the surface ground stations, which is related to altitude and coverage. These results contribute to a comprehensive understanding of the spatiotemporal distribution of mid-tropospheric CO2 and related mechanisms.
Neural coding of speech and language : fMRI and EEG studies

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Strata: High-Performance Scalable Storage on Virtualized Non-volatile Memory

Strata is a commercial storage system designed around the high performance density of PCIe flash storage. We observe a parallel between the challenges introduced by this emerging flash hardware and the problems that were faced with underutilized server hardware about a decade ago. Borrowing ideas from hardware virtualization, we present a novel storage system design that partitions functionality into an address virtualization layer for high performance network-attached flash, and a hosted environment for implementing scalable protocol implementations. Our system targets the storage of virtual machine images for enterprise environments, and we demonstrate dynamic scale to over a million IO operations per second using NFSv3 in 13u of rack space, including switching.
On-line adaptive learning rate BP algorithm for MLP and application to an identification problem

Abstract An on-line algorithm that uses an adaptive learning rate is proposed. Its development isbased on the analysis of the convergence of the conventional gradient descent method for three-layer BP neural networks. The effectiveness of the proposed algorithm applied to theidentification and prediction of behavior of non-linear dynamic systems is demonstrated bysimulation experiments. Keywords: Neural networks, learning algorithms, adaptive behavior, Gradient descent method,Input/output modelling 1 Introduction Current state of technology is strongly influenced by capabilities of modern computing systems. Theavailability of cheap and powerful computing machinery today enables many real-time applications ofnumerous control algorithms that were not possible a number of years ago. One group of such,algorithms that received increased attention during the past years are those based on artificial neuralnetworks (ANNs). Unless the learning algorithm has a built-in capability to cater for an adaptive on-lineadjustment of the learning rate during the on-line operation of adaptive ANN based control systems, itappears to be critical to determine a proper fixed learning rate for the real-time mode. This is particularlyimportant if the popular back-propagation (BP) algorithm for ANNs is used. If the learning rate is large,learning may occur quickly, but it may also become unstable. Thus, to ensure stable learning, thelearning rate must be sufficiently small. However, having a small learning rate, an ANN, for example amultilayer perceptron (MLP), may adapt reliably, but it may take a long time and thus, it can invalidatethe purpose of real-time operation. These problems characterize the basic learning rule of ANNs thatrelies on the gradient descent (GD) method and the chain rule [1]. The convergence properties of suchalgorithms are discussed in [2] and [3]. An additional problem associated with the GD method is itsknown slowness and tendency to become trapped in local minima. It is thus difficult to select a suitablefixed learning rate for different initial values of ANN parameters and for different structures of ANNs.To reduce these shortcomings, a number of faster training algorithms have been developed for ANNtraining, including the conjugate gradient algorithm (see [4]), the Levenberg-Marquardt method (see[5]), adaptive learning algorithms (see [6] and [7], and other modified algorithms (see [8]-[17]). Most ofthese algorithms are developed only for off-line training of ANNs.
Parsimonious or Profligate: How Many and Which Discourse Structure Relations?

Abstract : Over the past ten years, researchers studying the structure of discourse have consistently had to face questions such as the following: Given that discourses consist of segments, how do the segments relate? What intersegment relations are there? How many are needed? A fair amount of controversy exists, ranging from the parsimonious position (that two basic relations suffice) to the profligate position (that an open-ended set of semantic/rhetorical relations is required). This paper outlines the arguments and then summarizes a survey of the conclusions of approximately 30 researchers -- from linguists to computational linguists to philosophers to Artificial Intelligence workers. It fuses and taxonomizes the more than 400 relations they have proposed into a hierarchy of approximately 70 increasingly semantic relations, and argues that though the taxonomy is open-ended in one dimension, it is bounded in the other and therefore does not give rise to anarchy. Some evidence is provided for the organization of the taxonomy, as well as a full listing of the sources. Discourse structure, Rhetorical structure theory, Computational linguistics and discourse and text.
Audio Watermarking for Automatic Identification of Radiotelephone Transmissions in VHF Maritime Communication

Audio watermarking (AW) corresponds to digital information imperceptibly embedded into the audio signal. AW for maritime VHF (Very High Frequency) communication is inspired first of all by the ability of implementation an automatic identification of radiotelephone transmissions in the channels of maritime (156.174) MHz mobile radio communication service. Applied to VHF radiotelephony, a watermarking system could overcome existing limitations, and ultimately increase safety and efficiency of maritime communication. The same application of AW may be implemented in the aeronautical (118.136) MHz mobile service. In the mentioned services analogue broadcasting channels with frequency/phase and amplitude modulation correspondingly are utilized.
SPIHT: Highly Efficient Technique for Image Transmission and Coding

Abstract Uncompressed multimedia data (graphics, audio and video) requires considerable storage and transmission bandwidth. A fundamental goal of data compression is to reduce the bit rate for transmission or storage while maintaining acceptable quality. Image coding and compression technique, converts an image that requires low memory storages space, smaller bandwidth for transmission, high PSNR with acceptable image quality. This paper presents wavelet based coding algorithm SPIHT to encode and compress an image data. The coding and decoding process is comparatively fast. The numerical results obtained using MATLAB shows that the output image has high value of PSNR with good compression ratio for low bit rate.
A Concurrency Oriented Real-Time Language

In this report we will present a concurrency oriented real-time language we have created. We will present the parallelization patterns applied, and the structure of the compiler. The language is based on a sub-set of occam’s grammar, it includes features such as fine grained parallelism and message passing between processes. During compilation the compiler generates processes, and maps how they depend how they depend on each other. This is made possible by limiting the ways processes can communication with each other. The language runs on a multiprocessor run-time system. It has one worker thread pr. processor, which executes processes created by the compiler. The processes are scheduled with a multiprocessor earliest deadline first (EDF) scheduler. Two different versions of the EDF scheduler were implemented: One pure EDF scheduler and one modified EDF scheduler that utilize the dependency analysis performed by the compiler. The dependency analysis based scheduler runs the process with the earliest deadline concurrently with the processes it depends on. This enables the workers to work together towards the deadline of the process with the earliest deadline. This is an implementation that enables real-time application to utilize the power of multiprocessor systems. Performance data and examples is also presented. The examples demonstrate how scheduling based on dependency analysis is able to reach deadlines, which the pure EDF scheduler does not reach. Standard performance tests was performed on our language and several other languages, it showed surprisingly that our system performed as well and even better than some of the other languages. This is likely due to the simple and light structure of our system.
Performance of a DFE modem evaluated from measured indoor radio multipath profiles

Measured multipath profiles from five different indoor areas are used for the performance analysis of a binary phase-shift-keying modem, with and without a decision feedback equalizer. Both the average bit error rate and outage probability are calculated as the performance criteria. The average probability of error from the measured multipath profiles is compared with the performance predictions based on theoretical and computer-simulated channel models. For all five areas, it was observed that data rates on the order of 10 Mb/s are obtainable with a DFE having three forward and three feedback taps. Equivalent performance without equalization requires data rates of less than 1 Mb/s. <<ETX>>
Asynchronous Signals is Standard ML

We describe the design, implementation and use of a mechanism for handling asynchronous signals, such as user interrupts, in the New Jersey implementation of standard ML. Providing this kind of mechanism is a necessary requirement for the development of real-world application programs. Our mechanism uses first-class continuations to represent the execution state at the time at which a signal occurs. It has been used to support pre-emptive scheduling in concurrency packages and for forcing break-points in debuggers, as well as for handling user interrupts in the SML/NJ interactive environment.
Distributed Computation of Fixed Points.

Abstract : We present an algorithmic model for distributed computation of fixed points whereby several processors participate simultaneously in the calculations while exchanging information via communication links. We place essentially no assumptions on the ordering of computation and communication between processors thereby allowing for completely uncoordinated execution. We provide a general convergence theorem for algorithms of this type, and demonstrate its applicability to several classes of problems including the calculation of fixed points of contraction and monotone mappings arising in linear and nonlinear systems of equations, shortest path problems, and dynamic programming. (Author)
GENRE ANALYSIS OF STANFORD UNIVERSITY BROCHURES

This thesis presents Genre Analysis of Stanford University Brochure. It has three objectives. First, it is aimed at finding out the social function, the second finding out the schematic structure and the last finding out the linguistic features on the brochure of Stanford University. The data were analyzed using descriptive method. The researcher followed some steps to analyze the data, namely: reading all the texts of the brochures, segmenting sentences into clauses, describing the social function, schematic structure, and linguistic features, and the last one is drawing the conclusion. The results of the analysis on Stanford University Brochure show that the two brochures, the social function is to inform and promote the program of Stanford University. The dominant schematic structures in the brochures made by Stanford University are Headlines ^ Supplementary information ^ Introduction the product ^ Justifying the product ^ Establishing credentials ^ Reader Attraction ^ Targeting the market ^ Describing the product ^ User endorsement ^ Additional Information ^ Value of the product ^ Soliciting response. Relational and Material process become the dominant process because the process describes processes of being and doing. Relational process has function to give information about the program, and it gives appeal for participant to take this program. Material process has function to persuade and attract people to join this program. The researcher covers that simple present tense is the most dominant tense. The declarative and imperative mood types are used in each brochure.
Extracting functionally equivalent object-oriented designs from legacy imperative code

Abstract : This research defines a methodology for automatically extracting functionally equivalent object-oriented designs from legacy imperative programs. The Parameter-Based Object Identification (PBOI) methodology is based on fundamental ideas that relate programs written in imperative languages such as C or COBOL to objects and classes written in object-oriented languages such as Ada 95 or C ++. Transformations have been developed that formalize the PBOI methodology and a formal proof is provided showing the extracted object-oriented design is functionally equivalent to the legacy imperative system. To focus the task of re-engineering, generic models of imperative programming languages and object-oriented programming languages have been developed. The formal transformations convert imperative subprograms represented in the Generic Imperative Model (GIM) into classes and objects represented in the Generic Object-Oriented Design Model (GOM). A taxonomy of imperative subprograms has also been developed which classifies all imperative subprograms into one of six categories. A proof-of-concept prototype has been developed and a 3000-line FORTRAN-77 system has been converted to an object-oriented design as a feasibility demonstration.