Miracle-dz/UniFAR-FTUs huggingface dataset:
Tolmeldajate liigiline mitmekesisus ja arvukus põllumajandusmaastiku erinevatel elementidel

Veromann, E. , Kovacs, G. , Kaasik, R. , Vaino, L. , Karise, R. , Päädam, R. , Jõgar, K. , Veromann, L-L. , Jürgenson, M. , Mänd, M. 2015. The abundance and species diversity of pollinators in agricultural landscape elements. – Agronomy 2015. Insect pollination is an important ecosystem service that benefits many food crops. However, the loss and fragmentation of semi-natural and non-crop habitats have drastically diminished the number and species richness of pollinators i.e. the providers of this ecosystem service. Semi-natural habitats such as field margins, grasslands, hedgerows, and woodlands can offer habitats, food resource, shelter, hibernation places etc. for different pollinators. In our study, the impact of different landscape elements on the abundance and species richness of pollinators was measured. Specifically, we compared the abundance and species diversity of pollinators in five landscape elements – two linear elements: herbaceous and woody, and three areal elements: fallow, herbaceous and woody. Generally, the number of pollinators was low and the most abundant species was honeybee. The number of bumblebees was 1.61 times lower than honeybees. However, the richness of bumblebee species was relatively high – 14 different species out of the 28 occurring in Estonia were found. The type of landscape element had a significant impact on the pollinators’ abundance. The greatest number of pollinators was found on fallows, herbaceous and woody linear elements, while the smallest number of pollinators was found in the woody areal elements. There was also a difference between landscape elements on the support of different pollinators. Syrphids were most numerous on herbaceous linear elements whereas honeybees and bumblebees were most abundant on fallows. The attractiveness of fallows to the bees can be explained by the richness of their flowers – mass-flowering leguminous cultures were mostly grown there. However, the most diverse bumblebee community was found on the woody areal elements. In conclusion, our study showed that different landscape elements support different groups of pollinators. Use of leguminous catch crops in crop rotation offers long-lasting stable food resource for bees that guarantees the preservation of their population also in agricultural landscapes. However, since syphids preferred narrow linear elements, heterogenic landscape that consists of several elements is best to ensure the pollination service and hence, greater and more quality crop yields.
Geometric Priors from Robot Vision in Deep Networks for 3 D Object Classification

Handcrafted geometric features for object classification are heavily relied on in robot vision because of their demonstrated robustness. While modern deep learning approaches typically outperform classical methods, transferring this success to 3D data in a robust manner is still an open question because of the challenges introduced by the additional dimension and the relative lack of non-artificial large 3D datasets for classification. In this work, we demonstrate the benefits of using a deep network to improve on classical histogram-based descriptors. Our network uses shape features inspired by 3D object classification based on local and global geometry. Due to the geometric priors, our network does not require aligned data and is directly applicable to point clouds. Performance is evaluated on the ModelNet dataset and results show competitive accuracy and robustness, while being rotation invariant and using 10-100x less parameters than some competing methods.
Modeling of Laser-Based Direct Metal Deposition

Central to the success of the metal part fabrication is how well the issues related to process complexity, time, and cost are addressed. Integrating various metal deposition methods in the framework of solid freeform fabrication (SFF) for the varying size and volume of geometrical features along with machining has demonstrated a feasible and economical solution. A number of issues related to laser-based direct metal deposition using the multi-fabrication (MultiFab) system, such as simulation of gas-powder flow, and heat transfer and evolution of residual stresses have been addressed.
Fermi-surface nesting and the origin of the charge-density wave inNbSe2

We use highly accurate density functional calculations to study the band structure and Fermi surfaces of $\mathrm{Nb}{\mathrm{Se}}_{2}$. We calculate the real part of the noninteracting susceptibility, $\mathrm{Re}{\ensuremath{\chi}}_{0}(\mathbf{q})$, which is the relevant quantity for a charge density wave (CDW) instability and the imaginary part, $\mathrm{Im}{\ensuremath{\chi}}_{0}(\mathbf{q})$, which directly shows Fermi surface (FS) nesting. We show that there are very weak peaks in $\mathrm{Re}{\ensuremath{\chi}}_{0}(\mathbf{q})$ near the CDW wave vector, but that no such peaks are visible in $\mathrm{Im}{\ensuremath{\chi}}_{0}(\mathbf{q})$, definitively eliminating FS nesting as a factor in CDW formation. Because the peak in $\mathrm{Re}{\ensuremath{\chi}}_{0}(\mathbf{q})$ is broad and shallow, it is unlikely to be the direct cause of the CDW instability. We briefly address the possibility that electron-electron interactions (local field effects) produce additional structure in the total (renormalized) susceptibility, and we discuss the role of electron-ion matrix elements.
Knowledge mining tools and strategies for hypertemporal remote sensing data sets

This study focuses on data exploration and knowledge mining using remote sensing data archives with high temporal resolution to study surface conditions in Mediterranean drylands, which are controlled by a complex interaction of climate, soil, vegetation, water resources, stocking rates and human impacts. Major objectives of this study were (a) to develop a software tool to reveal temporal patterns in the seasonal and long-term characteristics of the almost exclusively vegetation-related signal archived in global environmental satellite data and (b) to describe changes in surface reflectance by archetypical, dynamic, co-evolutionary patterns of civilisation-nature interactions, so-called syndromes. For time-series analysis the proprietary software tools TimeStats was developed, which constitutes an image-processing package with advanced tools in the field of time-series analysis. An adaptation of the syndrome approach was applied for the Iberian Peninsula, with a focus on the syndromes “Overexploitation”, “Rural Exodus” and the “Disaster”, which are relevant to dryland degradation in the Mediterranean. The mapping approach is based on time-series analysis results derived from the Mediterranean Extended Daily One Km AVHRR Data Set (MEDOKADS) (1989 to 2004).
Toward Safe Perception in Human-Robot Interaction

Perception is a major component of a system when it comes to the concept of safety in human-robot interaction. Although designing a mechanically safe robot may reduce lots of potential hazards, it is still beneficiary or even required to have detailed knowledge of the current status of the robot, human, and other environmental entities. We refer to this knowledge as perceptional awareness, or simply perception, that subsumes: (i) what our system perceives from robot state and its environment, (ii) what our system perceives from human state, and (iii) what a human perceives from the robot state. In this paper we provide requirements for a holistic architecture to construct safe perception using multiple heterogeneous and independent sensors and processing units in any environment that includes both robots and humans. We also illustrate our concepts on the basis of particular instances of this scheme realized in the robotic lab.
Multi-objective Evolutionary Algorithms for Decision-Making in Reconfiguration Problems Applied to the Electric Distribution Networks

In this work the performance of three multiobjective optimization techniques based on evolutionary programming, applied to distribution network reconfiguration problems, are evaluated. The proposed model takes into account the power losses and the reliability index as minimization objectives. Due to their proven ability to find the commitment solution sets in multi-objective problems and due to the adaptability of techniques based on the Genetic Algorithms applied to reconfiguration processes the following algorithms were chosen: Microgenetic Algorithms, Non-Dominated Sorting Genetic Algorithm 2 and Strength Pareto Evolutionary Algorithm 2. The results of this research show the effectiveness of the SPEA 2 to solve this problem.
Real-World Robotic Perception and Control Using Synthetic Data

Author(s): Tobin, Joshua P | Advisor(s): Abbeel, Pieter | Abstract: Modern deep learning techniques are data-hungry, which presents a problem in robotics because real-world robotic data is difficult to collect. Simulated data is cheap and scalable, but jumping the "reality gap" to use simulated data for real-world tasks is challenging. In this thesis, we discuss using synthetic data to learn visual models that allow robots to perform manipulation tasks in the real world. We begin by discussing domain randomization, a technique for bridging the reality gap by massively randomizing the visual properties of the simulator. We demonstrate that, using domain randomization, synthetic data alone can be used to train a deep neural network to localize objects accurately enough for a robot to grasp them in the real world. The remainder of the thesis discusses extensions of this approach to a broader range of objects and scenes. First, we introduce a data generation pipeline inspired by the success of domain randomization for visual data that creates millions of unrealistic procedurally generated random objects, removing the assumption that 3D models of the objects are present at training time. Second, we reformulate the problem from pose prediction to grasp prediction and introduce a generative model architecture that learns a distribution over grasps, allowing our models to handle pose ambiguity and grasp a wide range of objects with a single neural network. Third, we introduce an attention mechanism for 3-dimensional data. We demonstrate that this attention mechanism can be used to perform higher fidelity neural rendering, and that models learned this way can be fine-tuned to perform accurate pose estimation when the camera intrinsics are unknown at training time.We conclude by surveying recent applications and extensions of domain randomization in the literature and suggesting several promising directions for research in sim-to-real transfer for robotics.
' s response to reviews Title : Early microstructural white matter changes in patients with HIV : a diffusion tensor imaging study

Bianca Stubbe-Dräger MD (dragerb@uni-muenster.de) Michael Deppe PhD (deppe@uni-muenster.de) Siawoosh Mohammadia PhD (siawoosh@gmx.de) Simon S Keller PhD (s.s.keller@uni-muenster.de) Harald Kugel PhD (kugel@uni-muenster.de) Nora Gregor MD (gregor@uni-muenster.de) Stefan Evers MD (everss@uni-muenster.de) Peter Young MD (young@uni-muenster.de) E-Bernd Ringelstein MD (ringels@uni-muenster.de) Gabriele Arendt MD (gabriele.arendt@uni-duesseldorf.de) Stefan Knecht MD (knecht@uni-muenster.de) Ingo W Husstedt MD (husstedt@uni-muenster.de)
Supplementary Material for DLOW : Domain Flow for Adaptation and Generalization

In Section 4.1 of the main paper, we show the examples of intermediate domain images between the source domain GTA5 and the target domain Cityscapes. The main change in those images at the first glance might be the image brightness. Here we provide an enlarged version of intermediate images to show that not only the brightness but also the subtle texture are adjusted to mimic the Cityscapes style. For comparison, we adjust the brightness of the translated image with z = 0 to match it with the brightness of the corresponding translated image with z = 1. The enlarged translated image with z = 1 and the corresponding the brightness adjusted image(z = 0) are shown in Fig 2, from which we observe that the brightness adjusted image still exhibits obvious features of the game style such as the high contrast textures of the road and the red curb, while our DLOW translated image well mimics the texture of Cityscapes style.
Analysis of a Spatially Discrete Sound Field Synthesis Array in a Reflective Environment

While the foundations of sound field synthesis demand an anechoic environment, this requirement cannot be met in real-world installations. Reflections at the walls of the listening room modify the synthesised sound field. Moreover, the synthesised sound field in a reflective environment, of e.g. a virtual point source, differs from the one of a real point source in the same environment. Filtered copies of the direct sound from each loudspeaker are mingled with spatial aliasing artefacts due to room reflections and a finite distance between loudspeakers, respectively. In a setup with typical loudspeaker spacings, the additional wave fronts that constitute spatial aliasing artefacts occur in a shorter timeframe than the early reflections of the listening room. This paper investigates how early reflections are filled in by these additional wave fronts produced by spatially discrete secondary source distributions. Different scenarios with real and virtual point sources in the free field and in a reflective environment are simulated. The reflective environment is simulated by an image source model. The spacing of the secondary sources is varied to generate different sequences of additional wave fronts. The resulting (room) impulse responses are analysed with respect to the structure and density of reflections and/or aliasing. Room acoustic measures like the reverberation time and early decay time of the system are considered. Finally, findings in the literature concerned with the perception of early reflections and diffuse reverberation allow for concluding on the perceptive impact of the listening room.
Research of RPL Protocol of Wireless Sensor Network

Routing protocol implements the description of network topology,routing path selection and data packets forwarding,which influences the performance and alive time of the entire network.Existing routing protocols require a large amount of messages to maintain network topology,as well as large storage space to keep routing entries.Due to the constraints of hardware,the energy and the ability of processing,also the storing of wireless sensor network nodes has been dramatically limited.Hence,the IETF routing over low-power and lossy networks(RoLL) working group has recently proposed the IPv6 routing protocol for low power and lossy networks,i.e.,the RPL protocol.In this paper,the topology building process and data packets routing process,also the Trickle timer algorithm of RPL routing protocol is analyzed.It has been simulated by COOJA,which clearly shows that RPL routing protocol plays a beneficial and rewarding role in low-power and lossy networks.
How Mobile Devices are Changing the Classic Computing Paradigm

This paper will illustrate how mobile computers and technology is changing and evolving. Slowly the classic computing paradigm of a main unit for processing, a keyboard and mouse for input, and monitor for output is changing. This is a change that faces many hurdles but is an inevitable part of evolution. Mobile computing faces both technological obstacles and consumer acceptance obstacles. I will demonstrate several ways that the technological hurdles are being confronted, including the Future Internet Architecture Program, mobile cloud computing, CogMAC, femtocells, battery alternatives, and carbon based nanotubes. I will then present current technologies that may someday replace modern computers such as new output interfaces and wearable computers, presenting one wearable computer in development, Google Glass, and one that is now in production, the Pebble. Even wearable computers depend on consumer acceptance to be successful. I present the Microsoft Surface RT tablet as an example of a product that has not gained consumer acceptance. Finally, I illustrate how volatile the industry is and how successful a product can be by looking at the iPhone quarterly sales.
Perceptual evaluation of the effect of mismatched Fujisaki model commands and surface tone in Sesotho

Sesotho is a tonal Southern Bantu language which has so far received extremely little attention by the speech research community. We consider tone modelling for Sesotho using the Fujisaki model- based analysis with a view to the development of a text-to-speech (TTS) system. Fujisaki analysis can be used to indicate the tone associated with a syllable, but it often differs from the surface tone that would be available for TTS synthesis. We investigate instances in which the surface tone differs from the tone indicated by Fujisaki analysis, and determine the effect of these discrepancies on speech quality. The amplitude of Fujisaki tone commands is manipulated to match the surface tones, and the resulting resynthesized speech subsequently analysed by perceptual tests. We find that the effect of inserting tone commands at high surface tone syllables is more severe than matching the Fujisaki tone commands with low surface tone syllables, in terms of naturalness. Furthermore, some discrepancies can be attributed to errors in the surface tonal transcription. However, on average, all manipulations lead only to a mild degradation in speech quality. We conclude that the Fujisaki model is a feasible way to model tone in Sesotho even in the presence of limited and under- developed linguistic resources.
Cybersecurity Information Exchange Techniques : Cybersecurity Information Ontology and CYBEX 高橋健志 門林雄基

Cyber threats cross country borders, but most organizations are currently coping with them individually without global collaboration mainly due to the lack of global standard for cybersecurity information exchange format and framework. Though some countries possess their local standards to solve this problem, these standards are not orchestrated in order for each organization to fully collaborate each other. To build the basis of cybersecurity information exchange framework, this paper proposes an ontology of cybersecurity operational information. It also discusses the standardization activity on cybersecurity information exchange, such as X.1500/CYBEX and its ensembles, and its effectiveness from the standpoint of advancing and expediting cybersecurity information exchange.
Gender differences in technologies courses at ICT-UNIFESP Brazil

This article reports a case study carried out at the Institute of Sciences and Technology (ICT) Federal University of São Paulo (UNIFESP) in Brazil. To investigate the gender differences among students of technology courses, a questionnaire was made available in order to analyze the main differences in the use of technologies, difficulties in the courses and vision of the labor market. The results pointed out that both genders use various computing devices, spent some time in front of computers and women make more use of social networks while men play more online games. Women have more difficulties in the disciplines, mainly physics and programming. The students like the area and are interested in working in different fields. Also, women are more aware of gender inequality (80%) in the labor market than men (59%). Finally, we present some discussion about the questions addressed in the questionnaire and present some gender equality programs that could be adapted to our university.
Visioning with Displaced Academics A strategy for sustainable reconstruction?

Post Conflict Futures is an ongoing project, where displaced Syrian academics meet in Visioning Labs and a global scenario group to jointly reflect on possible future developments and to look for actionable leverage points to work proactively for sustainable transitions. The collective visioning aims to identify aspects that may be critical in strategies for sustainable post conflict reconstruction, notably in the socio-technical implications of different infrastructure options. A crisis such as that in Syria creates shocks to infrastructure and people. These shocks generate emergencies and responses. But the collapse of existing structures can also open opportunities for a paradigm shift. In several cases, infrastructure shocks have opened opportunities that enable higher order learning with the potential to catalyse a transition towards sustainable and resilient structures (Broto et al., 2014). This has implications to the design of processes and practices to rebuild communities. Importantly, and considering the complexity of the challenges, holistic reflection is supported by the compression that results from fitting highly complex issues into an ongoing conversation in a small group of people, with diverse backgrounds. The format makes it possible to draw on tacit and cultural knowledge, as well as the differing professional experiences of participants.
Full-Wave Analysis of Planar Reflectarrays with Spherical Phase Distribution for 2-D Beam-Scanning using FEKO Electromagnetic Software

This paper presents a novel reflectarray antenna design for two-dimensional beam-scanning based on the concept of a planar array with spherical phase distribution. The restricted aperture approach is used to minimize the effects of spherical aberration on the reflectarray aperture and a Ka-band beamscanning reflectarray antenna with 20 dB gain and 30 degrees elevation coverage is designed and analyzed using the commercial electromagnetic software FEKO. The simulation results show that a good 2D beam-scanning performance is obtained with this passive reflectarray antenna designed with spherical phase distribution.
Application of a Selective Desensitization Neural Network to Concept Drift Problems

Previous studies have shown that a selective desensitization neural network (SDNN) has a high function approximation ability, low hyper-parameter dependency, and suitability for online incremental learning. These properties suggest that an SDNN can deal well with temporal changes in the characteristics of data, or concept drift, although this has not been verified. In this study, we conducted experiments on online learning using an artificial dataset generated using a timevarying function and a real-world dataset on a stock prices index, and evaluated the effectiveness of an SDNN for concept drift problems. The results show that an SDNN exhibited a superior performance than existing methods for both datasets, suggesting that an SDNN is highly suitable for certain types of concept drift problems.
Near-Linear Time Edit Distance for Indel Channels

We consider the following model for sampling pairs of strings: $s_1$ is a uniformly random bitstring of length $n$, and $s_2$ is the bitstring arrived at by applying substitutions, insertions, and deletions to each bit of $s_1$ with some probability. We show that the edit distance between $s_1$ and $s_2$ can be computed in $O(n \ln n)$ time with high probability, as long as each bit of $s_1$ has a mutation applied to it with probability at most a small constant. The algorithm is simple and only uses the textbook dynamic programming algorithm as a primitive, first computing an approximate alignment between the two strings, and then running the dynamic programming algorithm restricted to entries close to the approximate alignment. The analysis of our algorithm provides theoretical justification for alignment heuristics used in practice such as BLAST, FASTA, and MAFFT, which also start by computing approximate alignments quickly and then find the best alignment near the approximate alignment. Our main technical contribution is a partitioning of alignments such that the number of the subsets in the partition is not too large and every alignment in one subset is worse than an alignment considered by our algorithm with high probability. Similar techniques may be of interest in the average-case analysis of other problems commonly solved via dynamic programming.