Miracle-dz/UniFAR-FTUs huggingface dataset:
RADIO BASED ON THE IPAQ PDA : SOFTWARE

Vanu, Inc. has demonstrated analog FM two way radio and digital APCO Project 25 waveforms on an iPAQ-based handheld software radio. The iPAQ contains a low-power 206 MHz StrongARM processor that is used for all signal processing. This paper explains the software approaches used and lessons learned from implementing the waveforms on this platform. Commercial and public safety applications of the handheld are also described.
FPGA Based Design and Implementation of DUC/DDC Based OFDM for Data/Image Transmission

—The tremendous growth in the wireless communication system demands a very high-speed data transmission with better quality of service. The Orthogonal Frequency Division Multiplexing (OFDM) provides high-speed data communications by utilizing the spectrum more significantly than other approaches including Frequency Division Multiple Access (FDMA). Most of the OFDM transceiver architectures with different algorithms for wireless communication are conventionally used along with software-based approaches which are not suitable for real-time scenarios in Radio Frequency (RF) systems. There is no complete standard benchmark or prototyped hardware architecture for OFDM based RF systems. Very few existing designs are available with hardware overhead issues. In this paper, the proposed OFDM system offers low cost hardware architecture which includes Quadrature Amplitude Modulation (QAM) modulation-demodulation, highly pipelined Inverse Fast Fourier Transform (IFFT)- Fast Fourier Transform (FFT) modeling along with digital conversion systems like Direct Up-Conversion (DUC) and Direct-Down-Conversion (DDC), which supports the RF systems for real-time requirements. The proposed OFDM systems support both data and image for transmission. The design is synthesized in Xilinx platform and simulated using Model-sim and prototyped on Artix 7 FPGA board. The proposed OFDM system is compared with existing similar architecture on the same FPGA device with hardware constraints improvements. 
Choices for Semantic Analysis in Cognitive Systems

Over the past couple of decades, fundamental semantic analysis has been outside of the purview of mainstream natural language processing, but the recent surge of interest in cognitive computing has returned the notion to center stage. However, what exactly is fundamental semantic analysis? What methods can be used to achieve it? What counts as a useful result? How does one measure progress? All of these issues, and many more, define the choice space for building semantic analysis systems. This paper describes key aspects of this choice space and suggests that published descriptions of systems should explicitly state both the choices made and the positive and negative consequences of those choices. This will counter the current tendency for system descriptions to tacitly reflect choices understood only by insiders without overtly motivating or justifying them.
Association Between Dietary Diversity Score and Nutritional Status of Filipino Children Aged 6-23 Months

Starting at six months, the quality of diet already plays a vital role in the nutritional adequacy and nutritional status of children 6-23 months old. This cross-sectional study aimed to test the association between food intake quality, as measured by dietary diversity score, and nutritional status of a child based on a one-day food recall. Data on 4,276 children aged 6-23 months were obtained from the June-December 2011 Updating of Nutritional Status of Filipino Children and Other Population Groups surveyed by the Food and Nutrition Research Institute of the Department of Science and Technology (FNRI-DOST). Children with four or more dietary diversity scores were classified as “meeting” the minimum dietary diversity (MDD) while those with less than four as “not meeting” the MDD. Bivariate analysis using Chi-square test was performed on selected child, maternal, and household characteristics to determine the associated predictors of MDD while multiple regression analyses were conducted to test the association between nutritional status and MDD and other predictors. Results showed that MDD was associated with underweight and wasting/thinness but not with stunting. Meeting the MDD was protective against underweight (Odds Ratio (OR)=0.80, 95% Confidence Interval (CI) 0.64-1.00) and wasting/thinness (OR= 0.62, 95% CI 0.46-0.82). Aside from not meeting the MDD, factors that increased the child’s odds of becoming underweight were: child’s age at 9-11months (OR=1.83) and 12-23 months (OR=2.17); household food insecurity (OR=1.89); and the mother being the primary caregiver (OR 1.30). Meanwhile, household food insecurity (OR=1.44) and child’s age at 9-11 months (OR 1.35) increased the probability of the child being wasted/thin. MDD, as a measure of the quality of complementary food, warrants further investigation as a potential assessment tool that can be used to evaluate the dietary intake of children aged 6-23 months.
Finite element analysis for a diffusion equation on a harmonically evolving domain

We study convergence of the evolving finite element semidiscretization of a parabolic partial differential equation on an evolving bulk domain. The boundary of the domain evolves with a given velocity, which is then extended to the bulk by solving a Poisson equation. The numerical solution to the parabolic equation depends on the numerical evolution of the bulk, which yields the time-dependent mesh for the finite element method. The stability analysis works with the matrix–vector formulation of the semidiscretization only and does not require geometric arguments, which are then required in the proof of consistency estimates. We present various numerical experiments that illustrate the proven convergence rates.
Annotation projection for coreference resolution

The goal of this short-term scientific mission was to investigate how linguistic annotations of discourse coherence can be used for annotation projection and development of linguistically annotated resources for multiple languages. In particular, we were dealing with annotations of coreference (which is necessary to maintain coherence in discourse). Repeated references to entities are common for all languages, but they can vary considerably in their structure and usage. The emergence of parallel corpora made it possible to compare referring expressions in different languages based on the annotated data. However, linguistically annotated resources are unevenly distributed across the languages, and there are only few parallel coreference corpora available, mostly for major European languages. Our idea was to apply automatic annotation projection techniques, in order to alleviate the problem of resource scarcity. Our work proposal was based on our earlier research where we applied a direct projection algorithm on a multilingual and multi-genre coreference corpus (Grishina and Stede, 2015), in order to see how well a projection algorithm works for a) different languages, b) different text genres. Therefore, we experimented with relatively similar languages (English-German) and less similar languages (English-Russian) and used three different genres of text (newswire, stories, medical instructions). At the same time, Agic and colleagues (2015) applied a projection algorithm to transfer POS annotations for 100 languages and used all possible combinations of them in order to implement a multi-sourced annotation transfer. The purpose of the proposed STSM was to collaborate on the implementation of a similar algorithm for coreference annotations and make it applicable to a wide range of languages. Work carried out and results obtained were driven by the idea to explore the boundaries of large-scale annotation projection for coreference resolution. We collected the data that contains gold coreference annotations for multiple language from the recently published sources. We used the data with coreference annotations for as many languages as possible, in particular, from SemEval20101 and CoNLL-20122 Shared Tasks. We used the data for the following languages: English, German, Italian, Spanish, Catalan, Dutch, Arabic and Chinese.
University of Dundee Cannabidiol induces antioxidant pathways in keratinocytes by targeting BACH 1

Cannabidiol (CBD) is a major non-psychotropic phytocannabinoid that attracted a great attention for its therapeutic potential against different pathologies including skin diseases. However, although the efficacy in preclinical models and the clinical benefits of CBD in humans have been extensively demonstrated, the molecular mechanism(s) and targets responsible for these effects are as yet unknown. Herein we characterized at the molecular level the effects of CBD on primary human keratinocytes using a combination of RNA sequencing (RNA-Seq) and sequential window acquisition of all theoretical mass spectrometry (SWATH-MS). Functional analysis revealed that CBD regulated pathways involved in keratinocyte differentiation, skin development and epidermal cell differentiation among other processes. In addition, CBD induced the expression of several NRF2 target genes, with heme oxygenase 1 (HMOX1) being the gene and the protein most upregulated by CBD. CRISPR/Cas9-mediated genome editing, RNA interference and biochemical studies demonstrated that the induction of HMOX1 mediated by CBD, involved nuclear export and proteasomal degradation of the transcriptional repressor BACH1. Notably, we showed that the effect of BACH1 on HMOX1 expression in keratinocytes is independent of NRF2. In vivo studies showed that topical CBD increased the levels of HMOX1 and of the proliferation and wound-repair associated keratins 16 and 17 in the skin of mice. Altogether, our study identifies BACH1 as a molecular target for CBD in keratinocytes and sets the basis for the use of topical CBD for the treatment of different skin diseases including atopic dermatitis and keratin disorders.
Control method for EV charging and discharging in V2G/V2H scenario based on the synchronvter technology and
 H
 ∞
 repetitive control

Electric vehicles (EVs) will play a vital role in the future's transportation systems since this technology is promising for environment, energy security, and improved fuel economy. EVs have huge potential of serving as the energy storage for the power grid as well as inhabitants in vehicle-to-grid (V2G) or vehicle-to-house (V2H) scenario. In this study, a control method is proposed for EV charging and discharging by using the synchronverter technology and H ∞ repetitive controller, where synchronverter technology is used to generate the reference voltage to decide the power angle and amplitude of the AC side voltage of the charging/discharging port, so that the power flow between EV and the grid is controlled. In order to ensure the power quality of EVs provided for the grid and the load while EVs are with local loads, a H ∞ repetitive controller is designed to control the voltage between EVs and the grid to follow the reference voltage. Simulation results have shown that the proposed controller is not only able to realise bi-directional real power and reactive power control, but also keep the output voltage of EVs in V2G or V2H scenario stable and clear while they are with different kinds of local loads.
Near-Field IR Orientational Spectroscopy of Silk

Orientational dependence of the IR absorbing amide bands of silk is demonstrated from two orthogonal longitudinal and transverse microtome slices with a thickness of only ∼100 nm. Scanning near-field optical microscopy (SNOM) which preferentially probes orientation perpendicular to the sample’s surface was used. Spatial resolution of the silk–epoxy boundary was ∼100 nm resolution, while the spectra were collected by a ∼10 nm tip. Ratio of the absorbance of the amide-II C-N at 1512 cm − 1 and amide-I C=O β -sheets at 1628 cm − 1 showed sensitivity of SNOM to the molecular orientation. SNOM characterisation is complimentary to the far-field absorbance which is sensitive to the in-plane polarisation. Volumes with cross sections smaller than 100 nm can be characterised for molecular orientation. A method of absorbance measurements at four angles of the slice cut orientation, which is equivalent to the four polarisation angles absorbance measurement, is proposed.
Exploiting subspace distance equalities in high-dimensional data for knn queries

Efficient k-nearest neighbor computation for high-dimensional data is an important, yet challenging task. The response times of stateof-the-art indexing approaches highly depend on factors like distribution of the data. For clustered data, such approaches are several factors faster than a sequential scan. However, if various dimensions contain uniform or Gaussian data they tend to be clearly outperformed by a simple sequential scan. Hence, we require for an approach generally delivering good response times, independent of the data distribution. As solution, we propose to exploit a novel concept to efficiently compute nearest neighbors. We name it sub-space distance equality, which aims at reducing the number of distance computations independent of the data distribution. We integrate knn computing algorithms into the Elf index structure allowing to study the sub-space distance equality concept in isolation and in combination with a main-memory optimized storage layout. In a large comparative study with twelve data sets, our results indicate that indexes based on sub-space distance equalities compute the least amount of distances. For clustered data, our Elf knn algorithm delivers at least a performance increase of factor two up to an increase of two magnitudes without losing the performance gain compared to sequential scans for uniform or Gaussian data.
Prototypes on IPFS : A Realization of globally distributed reusable Knowledge Prototypen im Interplanetary File System-Wiederverwendbares Wissen global verteilt

This bachelor thesis combines the Prototype Knowledge Representation with the InterPlanetary File System (IPFS). After introducing both systems, we give an overview of existing Prototype systems and comparable distributed knowledge representation approaches. Then, the thesis will focus on a mapping from the formal Prototype definition by Cochez, Decker and Prud’hommeaux to the specifications of IPFS. The main part of the thesis deals with the implementation of this mapping, including important design decisions and several benchmarks in a controlled system as well as in a real world environment. As a result, we created a system allowing the deployment of immutable and mutable prototype expressions on a globally distributed, peer-to-peer system. Prototype knowledge base’s consistency can be checked and its fixpoint can be computed, right after. Strong reuse of prototype expressions is enabled due to IPFS’ content based addressing as well as the way of how the presented implementation allows to reuse expressions from other users. Nevertheless, we will observe that the used peer-to-peer system is not suiting the created mapping for prototype knowledge representation on a large scale. Therefore, the thesis is rounded up with an outlook into possible improvements of the underlying peer-to-peer system, as well as alternative mappings.
A multi‐vehicle covering tour problem with speed optimization

In the multi‐vehicle covering tour problem with speed optimization, we aim to construct a set of maximal coverage routes for a fleet of vehicles that serve (observe) a set of secondary sites, given a fixed time schedule and coverage requirements. We develop an exact solution approach using a branch‐and‐price framework with a label‐correcting algorithm and a set of innovative dominance rules to solve the resulting pricing problem. We also develop a two‐stage heuristic capable of finding effective initial solutions. In addition, we consider practical extensions to the model by incorporating risk thresholds, energy capacities, and time windows. To validate our proposed solution approaches, we perform an extensive set of numerical experiments. Numerical results show the computational advantage of our proposed solution approaches compared with a state‐of‐the‐art commercial solver.
Deep Gated Multi-modal Learning: In-hand Object Pose Estimation with Tactile and Image

In robot manipulation tasks, especially in-hand manipulation, estimation of the position and orientation of an object is an essential skill to manipulate objects freely. However, since in-hand manipulation tends to cause occlusion by the hand itself, image information only is not sufficient. For the challenge, combining tactile sensors is one of the approaches. The advantage of using multiple sensors (modals) is that the other modals can compensate for occlusion, noise, and sensor malfunctions. Even though the decision making of each modal reliability corresponding to the situations is important, the manual design of the model is difficult to deal with various situations. Therefore, in this study, we propose deep gated multi-modal learning using end-to-end deep learning in which the network self-determines the reliability of each modal. As experiments, an RGB camera and a GelSight tactile sensor were attached to the gripper of the Sawyer robot, and the poses were estimated during grasping. A total of 15 objects were used in the experiments. In the proposed model, the reliability of the modal was determined according to the noise and failure of each modal, and it was confirmed that the pose was estimated even for unknown objects.
Optimal Charging of an Electric Vehicle Battery Pack: A Real-Time Sensitivity-Based MPC approach

Lithium-ion battery packs are usually composed of hundreds of cells arranged in series and parallel connections. The proper functioning of these complex devices requires suitable Battery Management Systems (BMSs). Advanced BMSs rely on mathematical models to assure safety and high performance. While many approaches have been proposed for the management of single cells, the control of multiple cells has been less investigated and usually relies on simplified models such as equivalent circuit models. This paper addresses the management of a battery pack in which each cell is explicitly modelled as the Single Particle Model with electrolyte and thermal dynamics. A nonlinear Model Predictive Control (MPC) is presented for optimally charging the battery pack while taking voltage and temperature limits on each cell into account. Since the computational cost of nonlinear MPC grows significantly with the complexity of the underlying model, a sensitivity-based MPC (sMPC) is proposed, in which the model adopted is obtained by linearizing the dynamics along a nominal trajectory that is updated over time. The resulting sMPC optimizations are quadratic programs which can be solved in real-time even for large battery packs (e.g. fully electric motorbike with 156 cells) while achieving the same performance of the nonlinear MPC.
Dynamic Search - Optimizing the Game of Information Seeking

This article presents the emerging topic of dynamic search (DS). To position dynamic search in a larger research landscape, the article discusses in detail its relationship to related research topics and disciplines. The article reviews approaches to modeling dynamics during information seeking, with an emphasis on Reinforcement Learning (RL)-enabled methods. Details are given for how different approaches are used to model interactions among the human user, the search system, and the environment. The paper ends with a review of evaluations of dynamic search systems.
Learning Generalizable Locomotion Skills with Hierarchical Reinforcement Learning

Learning to locomote to arbitrary goals on hardware remains a challenging problem for reinforcement learning. In this paper, we present a hierarchical framework that improves sample-efficiency and generalizability of learned locomotion skills on real-world robots. Our approach divides the problem of goal-oriented locomotion into two sub-problems: learning diverse primitives skills, and using model-based planning to sequence these skills. We parametrize our primitives as cyclic movements, improving sample-efficiency of learning from scratch on a 18 degrees of freedom robot. Then, we learn coarse dynamics models over primitive cycles and use them in a model predictive control framework. This allows us to learn to walk to arbitrary goals up to 12m away, after about two hours of training from scratch on hardware. Our results on a Daisy hexapod hardware and simulation demonstrate the efficacy of our approach at reaching distant targets, in different environments, and with sensory noise.
Molecular Characterization of Azotobacter chroococcum Strains Isolated from Different Agro-climatic Zones of Karnataka , India

Azotobacter chroococcum is an aerobic, free-living bacterium capable of synthesizing various plant growth-promoting substances and is useful in crop improvement for biological nitrogen-fixing activity. Ten A. chroococcum strains were isolated and purified from different agro-climatic zones of Karnataka, India by Waksman No. 77 N-free agar by a serial dilution plate technique. Molecular diversity of the isolates was estimated by using ten selected RAPD primers. A total of 103 bands were scored out of which 87 were found to be polymorphic (84.97%). A dendrogram divided the isolates into two groups separated by 37 linkage distances and the dissimilarity matrix showed a maximum difference of 64% between the isolates of the North eastern transition zone and the Central dry zone and a minimum difference of 18% between the isolates of the Eastern dry zone and the Hilly zone. The isolate from zone 4 was clustered separately from the group. Thus, RAPD markers analysis proved to be a quick, simple and significant testing method to assess genetic diversity among A. chroococcum isolates. _____________________________________________________________________________________________________________
The effects of irradiance on the production of phenolic compounds and condensed tannins in Larix gmelinii needles

Needles of Larix gmelinii seedlings grown under different irradiances (100, 52, and 26 % of natural sunlight) were collected from June to August 2009. The content of phenolic compounds and condensed tannins in needles were strongly affected by different irradiances. The highest content of phenolic acids occurred under the lowest irradiance. Chlorogenic acid and syringic acid were detected only under the shade. In contrast, the needles under full irradiance showed the highest content of condensed tannins. Additional key words: chlorogenic acid, phenolic acid, larch, syringic acid.
Cell-Free Massive MIMO for Wireless Federated Learning

This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO) networks to support any federated learning (FL) framework. This scheme allows each instead of all the iterations of the FL framework to happen in a large-scale coherence time to guarantee a stable operation of an FL process. To show how to optimize the FL performance using this proposed scheme, we consider an existing FL framework as an example and target FL training time minimization for this framework. An optimization problem is then formulated to jointly optimize the local accuracy, transmit power, data rate, and users’ processing frequency. This mixed-timescale stochastic nonconvex problem captures the complex interactions among the training time, and transmission and computation of training updates of one FL process. By employing the online successive convex approximation approach, we develop a new algorithm to solve the formulated problem with proven convergence to the neighbourhood of its stationary points. Our numerical results confirm that the presented joint design reduces the training time by up to 55% over baseline approaches. They also show that CFmMIMO here requires the lowest training time for FL processes compared with cell-free time-division multiple access massive MIMO and collocated massive MIMO.