Miracle-dz/UniFAR-FTUs huggingface dataset:
treebanks through semi-automatic conversion of annotated corpora

Introduction. Wide empirical coverage is an important issue for any grammatical theory. A strongly data-driven approach toward achieving this goal is the analysis and annotation of a sufficiently large collection of sentences which, ideally, captures all grammatical phenomena of a given language. An annotated corpus of this kind could then be used for testing the validity and the degree of coverage of hand-written grammar fragments as well as for the data-driven extension of such fragments. In this paper, we present ongoing work on developing treebanks for RRG, that is, corpora annotated with RRG compliant syntactic structures. Since large-scale syntactic annotation is a highly time-consuming task, our approach builds on existing annotations, which are transformed automatically into RRG structures. Our automatic conversion is developed on a small set of manually annotated sentences and combined with an additional manual correction cycle. We present two conversion algorithms: the first takes as input constituent structure annotations as used in the Penn Treebank (PTB) (Marcus, Marcinkiewicz, & Santorini, 1993), the second starts with dependency annotations in accordance with the Universal Dependency framework (UD) (Nivre et al., 2016). Conversion procedure and annotation format. Our tree conversion process is iterative and error-driven, alternating between improving the conversion algorithm and comparing its output to manually validated RRG trees. We apply the conversion algorithm to bootstrap samples of new RRG trees, which are then checked and corrected by the annotators using the click/drag/drop-based web-interface we developed for the RRGbank (https://rrgbank.phil.hhu.de). The usual notation of the RRG structures differs from the tree notation format typically used in treebanks, in that the RRG structures use an operator projection and represent periphery nodes and clause-linkage markers disconnected from the main constituency structure [cf. van Valin, 2005]. To avoid the discrepancy between the annotation formats, we adopted a notational variant for the RRGbank in which every RRG structure is represented as a single connected tree. We merge the operator projection (which is usually represented in the lower part of the
FITTS’ LAW AS AN EDUCATION RESOURCE FOR HUMAN-COMPUTER INTERACTION IN COMPUTER SCIENCE CURRICULA

Fitts’ Law is, more often than not, thought of as standard knowledge in the field of Human-Computer Interaction. However, in many occasions, interface components are being built by professionals with little or no knowledge of HCI principles (e.g., software menus are often being built by software developers with no designer input). How much appreciation of Fitts’ Law exists among developers, and how does it affect our collaboration with them and the software they build and we use? To help answer this question, a survey among 65 designers and developers was conducted, as well as an analysis of the Computer Science undergraduate curricula from 94 internationally high-ranked universities. The contribution of this paper is twofold: firstly, treating Fitts’ Law as an Open Educational Resource and, secondly, the analysis identified gaps that extend beyond HCI Education and fall in the sphere of Epistemology. Keywords: Fitts’ law; HCI; education; epistemology.
A Survey on Attribute Based Encryption Schemes for Data Sharing

As sensitive data is stored and shared by third party sites on the Internet, there will be a need to encrypt data stored at these sites. Attribute Based Encryption (ABE) schemes is a vision of public key encryption mechanism that allows users to encrypt and decrypt messages based on user attributes. ABE takes attributes as public key and associates them with the ciphertext and user’s secret key. It is an efficient way to solve open problems in access control scenarios. In this paper, we survey the basic Attribute Based Encryption (ABE) scheme and its two varients: Keypolicy ABE (KP-ABE) scheme and the Ciphertext-policy ABE (CP-ABE) scheme.
Investigation Of Turbulent Mixing Layer With Compressibiliity Corrections For RANS Models

Turbulent mixing is highly a ected by uid compressibilty. The current work aims to study the e ect of compressibility corrections for 3 di erent Reynold Averaged Navier Stokes (RANS) turbulence models namely the standard k-epsilon, RNG and Spalart Allmaras models using an in-house parallel three dimensional unstructued CFD solver to compute a high speed mixing layer. The experimental study done by Goebel and Dutton has been used as the benchmark for investigation. The standard kis compared with the RNG model to see the e ect of the change in model coe cients on the predicted ow physics. The one equation Spalart Allmaras model is compared with the aforementioned two equation model to make the performance comparison complete. Turbulent quantities like rate of mixing layer growth, turbulence intensity and normalized Reynold's stress have been compared with benchmark results along with mean ow quantities like the self similar velocity pro les and their results have been presented.
Regional and global benthic  18 O stacks for the last glacial cycle

: Although detailed age models exist for some marine sediment records of the last glacial cycle (0-150 ka), age models for many cores rely on the stratigraphic correlation of benthic δ 18 O, which measures ice volume and deep ocean temperature change. The large amount of data available for the last glacial cycle offers the opportunity to improve upon previous benthic δ 18 O compilations, such as the “LR04” global stack [ Lisiecki and Raymo , 2005]. Not only are the age constraints for the LR04 stack now outdated, but a single global alignment target neglects regional differences of several thousand years in the timing of benthic δ 18 O change during glacial terminations. Here we present regional stacks that characterize mean benthic δ 18 O change for eight ocean regions and a volume-weighted global stack of data from 263 cores. Age models for these stacks are based on radiocarbon data from 0-40 ka, correlation to a layer-counted Greenland ice core from 40-56 ka, and correlation to radiometrically dated speleothems from 56-150 ka. The regional δ 18 O stacks offer better stratigraphic alignment targets than the LR04 global stack and, furthermore, suggest that the LR04 stack is biased 1-2
GENETIC RELATIONSHIPS AMONG PLANTAGO SPP . GROWING IN IRAQ USING RANDOM AMPLIFIED POLYMORPHIC DNA ( RAPD ) MARKERS

The study dealt with the genetic relationships among 13 species of Plantago L. genus. Field surveys were conducted for Iraqi districts to species collection. Leaves collected and DNA extracted. RAPD marker used to detect different relations among species. Through similarity coefficient cluster; the species divided into five groups depending on the relationships between species, the highest related were observed among P.lanceolata L. and P. major L. , at 91% similarity coefficient, while P. cretica L. and P. crypsoides Bois. , at 73% similarity coefficient. More distantly between some species in genetic diversity considered very useful in programs of genetic improvement and the linking of useful germplasm, especially for species of economic importance.
Preparing School Evaluators: Hiroshima Pilot Test of the Japan Evaluation Society’s Accreditation Project

Abstract: This article reports on the efforts of the Japan Evaluation Society (JES), in collaboration with the Canadian Evaluation Society, to develop and pilot test an accreditation and certification scheme for school evaluators. The purpose of the JES accreditation model is to support evaluation capacity building and promote high quality evaluation by developing functional evaluation competencies. The article describes the theory and practice of the JES approach to evaluation training and accreditation, including its overall rationale, the influence of Japan’s socio-political context, the content of the school evaluator training program, and the findings of the initial “test of concept” pilot test in Hiroshima. Based on a six-month follow-up evaluation, the article also provides an assessment of the acceptance, early results, and potential sustainability of the evaluator training program. These findings have encouraged the JES to establish the accreditation scheme for school evaluation, followed by a similar system for the evaluation of international development assistance programs and government policy evaluation. The development of the JES accreditation scheme should be of interest to other evaluation societies and also to public/nonprofit organizations that must use brief training courses or evaluation “toolkits” for building evaluation competencies quickly among staff.
What's in the Adaptive Toolbox and How Do People Choose From It? Rational Models of Strategy Selection in Risky Choice

Although process data indicate that people often rely on simplifying processes when choosing between risky options, current models of heuristics cannot predict people’s choices very accurately. To address this apparent paradox, it has been proposed that people might adaptively choose from a toolbox of simple strategies. But which strategies are contained in this toolbox? And how do people decide when to use which decision strategy? Here, we develop a model according to which the decision maker selects a decision strategy for a given choice problem rationally from a toolbox of strategies; the content of the toolbox is estimated for each individual decision maker. Using cross-validation on an empirical data set, we find that this model of strategy selection from a personal adaptive toolbox predicts people’s choices better than any single strategy (even when it is allowed to vary across participants) and better than previously proposed toolbox models. Our model comparisons show that both inferring the content of the toolbox and rational strategy selection are critical for accurately predicting people’s risky choices. Furthermore, our analysis reveals considerable individual differences in the set of strategies people are equipped with and how they choose among them; these individual differences could partly explain why some people make better choices than others. These findings represent an important step towards a complete formalization of the notion that people select their cognitive strategies from a personal adaptive toolbox.
A Novel Security Protocol for Wireless Sensor Networks Based on Elliptic Curve Signcryption

With the growing usage of wireless sensors in a variety of applications including Internet of Things, the security aspects of wireless sensor networks have been on priority for the researchers. Due to the constraints of resources in wireless sensor networks, it has been always a challenge to design efficient security protocols for wireless sensor networks. An novel elliptic curve signcryption based security protocol for wireless sensor networks has been presented in this paper, which provides anonymity, confidentiality, mutual authentication, forward security, secure key establishment, and key privacy at the same time providing resistance from replay attack, impersonation attack, insider attack, offline dictionary attack, and stolen-verifier attack. Results have revealed that the proposed elliptic curve signcryption based protocol consumes the least time in comparison to other protocols while providing the highest level of security.
High-order computation of incompressible flow on arbitrarily moving unstructured meshes using direct discontinuous Galerkin formulation

The direct discontinuous Galerkin method is used to calculate the viscous flux and the Arbitrary Lagrangian-Eulerian method is adopted so that the fluid analysis domain changes over time. To calculate the higher order numerical flux, we reconstructed the solution using the solution information. First, the TaylorGreen vortex problem is analyzed to confirm the performance of the fluid solver without Arbitrary Lagrangian Eulerian. Second, the flow past a circular cylinder problem is analyzed to confirm the performance of Arbitrary Lagrangian Eulerian solver.
COMPARATIVE ANALYSIS OF MULTIPLE FUSION APPROACHES FOR MULTIMODAL BIOMETRIC SYSTEMS

This paper presents comparative analysis of different fusion approaches which are widely used in multimodal biometric systems. Fusion of multiple biometric traits i.e. multimodal biometric system and information fusion at the match score level are the most commonly used approaches in multibiometric systems. Fusion at sensor level suffer from sensor interoperability problem, fusion at feature level suffer from feature set incompatibility problem, and fusion at decision level contains least amount of information i.e. the decisions output by the individual biometric matchers to be fused. Among the type of biometric information fused i.e. multi-sensor, multi-algorithm, multi-instance, multi-sample, and multimodal, the fifth multibiometric system i.e. multimodal seems better choice because it is more robust to noise, addresses the problem of nonuniversality, involves more than one biometric trait, improves the matching accuracy, and provides protection against spoof attacks. Fusion methodologies depend upon the type of biometric information fused and level of fusion.
Math Model and Calculation Analysis of Inter-harmonic of Double PWM Speed Control System in Distribution Network

Aiming at the problem that the distribution network voltage will fluctuate because of the interharmonic currents injected into the network by double PWM speed control system when regulating the speed of the asynchronous motor, we established the inter-harmonic current math model of double PWM speed control system according to switching function based on a real bridge crane. The distribution law of the inter-harmonic is got by calculating the grid-side currents and their spectrum while letting the motor run at different quadrants and frequencies. The result which is verified by simulation and experiment shows that the content of the inter harmonic currents is more than that of harmonic currents in double PWM speed control system, the frequency of the inter harmonics of the grid-side current mainly focus on the scope lower than the fundamental frequency, and when the motor runs at low frequencies, the THD of the grid-side current is high. The result has verified the reason why the voltage of a bridge crane distribution system of a deepwater port in Shanghai flickers. Copyright © 2014 IFSA Publishing, S. L.
Memory Training Interface for Elderly based on Mobile APP

Currently, the world population is aging rapidly and one of the characteristics that will accompany this new generation of elderly people is the concept of “aging in place”, which means aging at home. The quality of life of the elderly in their home depends on the maintenance of their cognitive and motor skills and, therefore, the way to encourage them to remain autonomous and reduce institutionalization is by training their memory. To help on solving problems like cognitive decline in elderly population it was developed a memory training mobile application based on life story work. The APP has the contribution of many professionals and was validated with a small group of elderly users. Analysis of the collected data is presented in the work to underline the effectiveness of developed APP on cognitive training.
Feature Selection and Machine Learning Classification for Live P 2 P Traffic

Classification of bandwidth-heavy Internet traffic is important for network administrators to throttle network of heavy bandwidth traffic applications. Statistical methods have been previously proposed as promising method to identify Internet traffic based on their statistical features. The selection of statistical features still plays an important role in accurate and timely classification although most feature selection algorithms consider the correlation between features. In this work, we propose a technique based on features characters and Principal Components Analysis (PCA) feature selection algorithms for online Peer-to-Peer (P2P) traffic detection. Using Naïve Bayes and J48 machine learning techniques for available traces from University of Brescia and University of Cambridge, experimental results show that the proposed method is able to achieve up to 99.5% accuracy for 0.007 second testing time. These results are superior to other existing approaches in term of accuracy and testing time.
On Secure Cloud Computing for Genomic Data: From Storage to Analysis

Although privacy is generally considered to be the right of an individual or group to control information about themselves, such a right has become challenging to protect in the digital era, this is exemplified by the case of cloud-based genomic computing. Despite the rapid progress in understanding, producing, and using genomic information, the practice of genomic data protection remains a fairly underdeveloped area. One of the indisputable reasons is that most nonexpert individuals do not realize the sensitive nature of their genomic data, unless it has been used against them. Many commercial organizations take advantage of their customers by taking control of personal genomic information, if customers want to benefit from services such as genetic analysis; even worse, these organizations often do not enforce proper protection, which could result in embarrassing data breaches. In this thesis, we investigate the potential threats of cloudbased genomic computing systems and propose various countermeasures by taking into account the functionality requirement. We begin with the most basic system where only symmetric encryption is needed for the cloud storage of genomic data, and we propose a new solution that protects the data against brute-force attacks that threaten the security of password-based encryption in direct-to-consumer companies. The solution employs honey encryption, where plaintext messages need to be transformed to a different space with uniform distribution on elements. We present a novel distribution-transformation encoder. We provide formal security proof of our solution. We analyze the scenario where efficient searching on encrypted data is necessary. We propose a system that provides fast retrieval on encrypted compressed data and that enables individuals to authorize access to fine-grained regions during data retrieval. Our solution addresses three critical dimensions in platforms that use large genomic data: encryption, compression, and efficient data retrieval. Compared with a previous de facto standard solution for storing aligned genomic data, our solution uses 18% less storage. To enable complicated data analysis, we focus on a proposal for secure quality-control of genomic data by using secure multi-party computation based on garbled circuits. Our proposal is for aggregated genomic data sharing, where researchers want to collaborate to perform large-scale genome-wide association studies in order to identify significant genetic variants for certain diseases. Data quality control is the very first stage of such a collaboration and remains a driving factor for further steps. We investigate the feasibility of advanced cryptographic techniques in the data protection of this phase. We demonstrate that for certain protocols, our solution is efficient and scalable. With the advent of precision medicine based on genomic data, the future of big data
Analysis and Novel Performance of Long and Short Shunt Self Excited Generators with Natural Energy Generation

Analysis and Novel Performance of Long and Short Shunt Self Excited Generators with natural Energy generation is presented. An outwardly ambitious induction machine can function as induction generator with unremitting self excitation when a suitable value of a capacitor bank is appropriately associated transversely at the stator terminal of the machine. Such a machine is said to be Self-Excited Induction Generator (SEIG). We proposed the series capacitor bank which really improves the voltage profile and also increases the maximum power delivery capability. The main significant of the projected work is that the effects of both long-shunt and short-shunt connections on the dynamic performance of an SEIG feeding and Induction Motor load is compared. We also examined the analysis of the reactive power prerequisite of self excited induction generator at different load conditions. Finally we originate that the short shunt self-excited induction generator is the attractive option for improved better voltage regulation and also maintain the good power quality. Wind turbine act as the prime mover of the projected work. The simulation work is carried out by the MATLAB and the result of the proposed work promises better voltage profile with grid connected system. [V. Karthikeyan,V.J. Vijayalakshmi. Analysis and Novel Performance of Long and Short Shunt Self Excited Generators with Natural Energy Generation. Life Sci J 2016;13(12):64-73]. ISSN: 1097-8135 (Print) / ISSN: 2372-613X (Online). http://www.lifesciencesite. com. 10. doi:10.7537/marslsj131216.10.
Increasing the Stability and Expression of Green Fluorescent Protein in Pancreatic Cancer Cells for Metastasis Assays

Pancreatic cancer is the fourth leading cause of cancer death in the United States, with only 11% of patients diagnosed with metastatic disease surviving the first year. Even so, few studies exist to characterize the mechanism of metastasis in this highly aggressive form of cancer. Consequently, it is imperative that techniques, such as tagging cells with green fluorescent protein (GFP), are developed to track cancerous cells over the course of their spread. Unfortunately, the existing GFP vector contains a cytomegalovirus promotor, which is readily silenced by cells and decreases the vector’s usefulness for long-term studies in vivo. It was hypothesized that the insertion of the enhanced GFP gene downstream from a beta-actin promotor with CMV enhancers would increase expression and long-term stability of GFP in pancreatic cancer cells. The enhanced GFP gene was removed from the pEGFP-N1 vector and then ligated into pCAGEN.puro. Murine pancreatic cancer cells were transfected with either pCAGEN.puro-EGFP or pEGFP-N1. Fluorescence intensity and stability were assessed through flow cytometry, revealing that the beta-actin promoter resulted in a greater percentage of cells fluorescing after two months of culture than the cells with GFP expressed under a CMV promoter. Assessment of tumorigenicity of two novel clones in mouse models reveals that one clone in particular shows promise for use in metastasis assays due to its stable fluorescence, high growth rate, and ability to report the presence of metastases and single cells or micrometastases disseminated in the lungs. Ongoing studies are confirming the increase in intensity and stability in human pancreatic cancer lines.