Miracle-dz/UniFAR-FTUs huggingface dataset:
BioNLP Shared Task 2011: Supporting Resources

This paper describes the supporting resources provided for the BioNLP Shared Task 2011. These resources were constructed with the goal to alleviate some of the burden of system development from the participants and allow them to focus on the novel aspects of constructing their event extraction systems. With the availability of these resources we also seek to enable the evaluation of the applicability of specific tools and representations towards improving the performance of event extraction systems. Additionally we supplied evaluation software and services and constructed a visualisation tool, stav, which visualises event extraction results and annotations. These resources helped the participants make sure that their final submissions and research efforts were on track during the development stages and evaluate their progress throughout the duration of the shared task. The visualisation software was also employed to show the differences between the gold annotations and those of the submitted results, allowing the participants to better understand the performance of their system. The resources, evaluation tools and visualisation tool are provided freely for research purposes and can be found at http://sites.google. com/site/bionlpst/
ANALYSIS OF THE SLAG AND METAL INFLUENCE ON THE LIF E OF ELECTRIC ARC FURNACE HEARTH REFRACTORY

MgO-based refractory linings for electric arc furn ace (in further EAF) hearth are most preferred worldwide. Potential for elimination and knowledge of causes, mechanisms of refractory wear coupled with continuous correction of plant parameters is needed in order to prolong refractory life. Wear process can be signif cantly modified by changes in technology. The most critical location in the EAF hearth is a s lag line. Slag compatibility (i.e. dual saturation of slag both with CaO and MgO) with refractory lini ng using dolomitic lime, MgObriquettes or refractory wastes is an effort of slag management. Slag foaming is very beneficial against wear. Governing of FeO content in the slag is a critical aspect of both slag foaming and refractory wear point of view. This study deals about analysis of slag and metal composition influence on the EAF hearth refractory lining wear level based on the st atistical evaluation of plant data. Influence of specific slag (CaO, MgO, FeO, Al 2O3, SiO2, basicity) and metal (C, Mn) constituents on the extent of EAF hearth lining wear was analysed at se lect d number of 24 campaigns. Average values of slag composition of mentioned campaigns t ogether with wear data were plotted to the pseudoternary diagram which expresses the relation between basic, acidic oxides and oxides with oxidation potential. Results were affected by scattering factor of used EAF shop statistical data reinforced with human factor (manual slag and metal sampling, non-ideal method of wear extent measurement), factor of oxygen lance use jus t before sampling in the same location as well as contribution of other various (except of sl ag and metal) non-constant factors acted in
Impact of Multi-Packet Transmission and Reception on Throughput Capacity of Wireless Ad Hoc Networks

We study the capacity of random wireless ad hoc networks when nodes are capable multi-packet transmissionand reception (MPTR). This paper extends the unified framework of (n, m, k)-cast by Wang et al. [9] with single-packet reception (SPR) capability for each node to MPTR. (n, m, k)-cast considers all types of information dissemination including unicast routing, multicast routing, broadcasting and anycasting. In this context, n, m, and k represent total number of nodes in the network, number of destinations for each communication group and act ual number of destinations that receive the packets respective ly. We show that the capacity of an(n,m,k)-cast wireless ad hoc network scales asΘ `
Device for adhesion tests of lubricants

The article presents a device for adhesion tests of lubricants with different chemical compositions to steel substrates. The cont rol system of the device and technical parameters of the actuator and the measur ing nit are described. The authors also present an algorithm method for adhesi on tests of lubricants. Additionally, the data acquisition subsystem of adh esion forces cooperating with the device is presented. The examples of the o btained results from the verification tests for grease and oil compositions are given.
A COMPROMISE RATIO RANKING METHOD OF TRIANGULAR INTUITIONISTIC FUZZY NUMBERS AND ITS APPLICATION TO MADM PROBLEMS

Triangular intuitionistic fuzzy numbers (TIFNs) is a special case of intuitionistic fuzzy (IF) set and the ranking of TIFNs is an important problem. The aim of this paper is to develop a new methodology for ranking TIFNs by using multiattribute decision making methods (MADM). In this methodology, the value and ambiguity indices of TIFNs may be considered as the attributes and the TIFNs in comparison are seen as the alternatives. A compromise ratio method for fuzzy MADM is developed based on the concept that larger TIFN should close to the maximum value index and is far away from the minimum ambiguity index simultaneously. The proposed ranking method is applied to solve multiattribute decision making problems in which the ratings of alter- natives on attributes are expressed by using TIFNs. Numerical examples are examined to demonstrate the implementation process and applicability of the proposed method in this paper. Furthermore, a comparison analysis of the proposed method is conducted to show its advantages over other methods.
FUZZY AHP METHOD FOR PLANT SPECIES SELECTION IN MINE RECLAMATION PLANS: CASE STUDY SUNGUN COPPER MINE

All steps of a mining project generally disturb the environment's original condition during construction. Therefore, it is crucial to implement an appropriate mine reclamation plan throughout all mine planning stages from sustainable and environmental point of view. Planting the suitable plant species in each step of any reclamation plan and each area is one of the ne- cessities in this respect. Selecting of plant species is carried out on the basis of the primary factors. After that priorities between the selected species are dened on account of the secondary factors by a MCDM model. In this regard, a Fuzzy AHP approach was used. This method was applied to Sungun open pit copper mine in Iran as a case study. Decision making was conducted on the basis of oral judgments and group expertise in the case study. The results achieved from the analyses showed that the priorities of alternatives are as Maple, Ash, Oak, Barberry, Paliurus spina -Christi, Sloe, respectively.
3 D Surface Approximation from Point Clouds

3D Visual perception has recently become very popular because of the advancements in 3D sensor hardware and development of powerful computational devices. Today, 3D sensory information is being extensively used to automate navigation and motion planning in autonomous systems like self-driving cars. Visual perception can be very useful for locomotion in robots. More specifically, a 3-dimensional representation of the surfaces present in a robot’s environment can be helpful in motion planning tasks such as foot step planning for legged robots. However, since the information produced by 3D sensors can be very large, it is required to create models that can efficiently represent this information and derive useful features from it. In this project, various models for representing 3D sensory information in the form of surfaces were analysed. Based on the analysis, a representation model was chosen. Later, using the chosen model a system was designed, implemented and tested. More specifically, the designed system uses B-spline surfaces for point cloud approximation. The surfaces generated are C2 continuous and therefore can be used to apply optimisation algorithms to find optimal locomotion trajectories and patterns. The system provides an easy way to extract the information needed by such algorithms. The surface approximations produced by the system are accurate and meet all the criteria for evaluation.
qu an tph ] 3 0 M ar 2 01 7 Conditional steering under von-Neumann scenario

Kaushiki Mukherjee,1, ∗ Biswajit Paul,2, † Sumana Karmakar,3, ‡ Debasis Sarkar,3, § Amit Mukherjee,4, ¶ Some Sankar Bhattacharya,4, ∗∗ and Arup Roy4, †† Department of Mathematics, Government Girls’ General Degree College, Ekbalpore, Kolkata-700023, India. Department of Mathematics, South Malda College, Malda, West Bengal, India Department of Applied Mathematics, University of Calcutta, 92, A.P.C. Road, Kolkata-700009, India. Physics and Applied Mathematics Unit, Indian Statistical Institute, 203,B. T. Road, Kolkata 700108 , India.
Design patterns for object-oriented hypermedia applications

This chapter proposes design patterns for object-oriented applications enhanced with hypermedia functionality. We briefly discuss our problem: building a software architecture for seamlessly extending object-oriented applications with hypermedia interface and navigational styles. Two new design patterns named ‘Navigation Strategy’ and ‘Navigation Observer’ are presented, showing how they are used to design flexible and extensible navigational structures.
Measurement of complex-valued spatial coherence and its application to diﬀractive imaging

The complete characterization of spatial coherence is diﬃcult because the mutual coherence function is a complex-valued function of four independent variables. This diﬃculty limits the ability of controlling and optimizing spatial coherence in a broad range of key applications. Here we propose a method for measuring the complex-valued mutual coherence function, which does not require any prior knowledge and can be scaled to measure arbitrary coherence properties for any wavelength. We apply our method to retrieve a phase object illuminated by a partially coherent beam. This application is particularly useful for diﬀractive imaging of nanoscale structures in the X-ray or electron regime, where the illumination sources lack of spatial coherence.
Recommended Algorithm of Latent Factor Model Fused with User Clustering

To solve the problems of partial implicit feature information loss and long-time model training caused by matrix factorization on recommended algorithm of latent factor model (LFM), a recommended algorithm of user clustering fused with latent factor model is put forward. Firstly, the users’ preference information is used to cluster them, and then the similarity calculation method is used to find the cluster and the nearest neighbor users that are most similar to the target user. Next, training similar clusters with the improved LFM to obtain the user’s implicit features Matrix p and item’s implicit feature Matrix q, and then generating the predictive score matrix of similar clusters. Finally, the predictive score of similar clusters are weighted and summed to gain the final user score. Compared with the traditional collaborative filtering and LFM, the improved model effectively reduces the training time and the root-mean-square error of predictive score, also improves the accuracy of predictive recommendation based on the experiments on Movielens datasets.
Noncoherent Integration Gain

1 Noncoherent Integration Gain Consider threshold detection of a radar target in additive complex Gaussian noise. To achieve a certain probability of detection and false alarm (PD and PFA, respectively) with a single measurement (N = 1), a certain signal-to-noise ratio (SNR1) is required. The required value depends on the target radar cross section (RCS) statistics. Equations for PD given PFA and N and a square-law detector are given in [1] for a nonfluctuating target and for targets with RCS fluctuations modeled by one of the four Swerling models, also described in [1].
Optimization of Intake Manifold of Dual Fuel Gasoline Engine-A Review

An inlet manifold or intake manifold is the part of an engine that supplies the fuel/air mixture to the cylinder. The primary function of the intake manifold is to evenly distribute the combustion mixture to each intake port in the cylinder head(s). Even distribution is important to optimize the efficiency and performance of the engine. An uneven air distribution leads to less volumetric efficiency, power loss and increased fuel consumption. There is some scope to increase the velocity of air and volumetric efficiency. The study of various researchers works indicating to increase the volumetric efficiency with different methods. There is scope to change the geometry of intake manifold and increase its volumetric efficiency. The trend has motivated to carry out a review on such research work. Such review will help in forming the basis for an intended research work in the similar direction. Keywords-CNG, intake manifold, volumetric efficiency
Speaker Recognition for Wire/Wireless Communication Systems

Recently data communication spread to the mobile wireless world. The complexity of medium and large speech & speaker recognition systems are beyond the memory and computational resources of the small portable devices. Moreover, the most common approach to speaker recognition today is the use of global Gaussian Mixture Models (GMM) which ignores knowledge of the underlying phonetic content of the speech, so it does not take advantage of all available information. In this paper we address the solution of these two problems by investigating the phoneme effect on speaker recognition system. We used YOHO database for speaker identification task. We found that some phonemes have strong effect on speaker identification. Segmenting the most effective phoneme for speaker recognition task from a speaker utterance and send this phoneme only through the wireless communication system will decrease the complexity of medium and speed up the authentication process though mobile communication system. We have applied different approaches on YOHO corpus, several of these approaches were able outperform previously published results on the speaker ID task. One of our approaches could achieve 0.7% error rate by using only an average segment of 4.45% of the testing utterance for recognition.
Innovation Generation and Innovation Adoption

The growing level of global competition is forcing organizations to make dramatic change and improvements in order to compete, prosper, and survive (Kotter, 1996). During the past three decades, the world has witnessed some spectacular changes that have provided a totally new environment for organizations. These changes include technological and administrative innovations that organizations are dealing with in different areas of their operations such as manufacturing process, operation technologies, and information systems (Shields, 1997). It can be argued that the growing level of global competition has lead to the adoption of technological evolution, which may also require the adoption of complementary administrative innovation (e.g., Baines & Langfield-Smith 2003). Given this information, to keep pace with other competitors in the global market, the adoption and the diffusion of latest ideas, techniques, practices, and processes has become a key factor for success in organizations. Therefore, this places a greater emphasis on the innovation generation and innovation adoption in organizations in order to compete, prosper, and survive.
Hovering Quad-Rotor Control: A Comparison of Nonlinear Controllers using Visual Feedback

This article presents a comparison of three control techniques: nested saturations, backstepping, and sliding modes. The control objective consists of obtaining the best control strategy to stabilize the position of a quad-rotor unmanned aerial vehicle (UAV) when using visual feedback. We propose a vision-based method to measure translational speed as well as the UAV 3D position in a local frame. The three selected controllers were implemented and tested in real-time experiments. The obtained results demonstrate the performance of such methodologies applied to the quad-rotor system.
Artiﬁcial Intelligence for Engineering Design, Analysis and Manufacturing

Although many approaches to digital ink recognition have been proposed, most lack the flexibility and adaptability to provide acceptable recognition rates across a varietyof problem spaces. This project uses a systematic approach of data mining analysis tobuilda gesture recognizerforsketched diagrams.Awide rangeof algorithms wastested,andthosewith the bestperformance were chosen for further tuning and analysis. Our resulting recognizer, RATA.Gesture, is an ensemble of four algorithms. We evaluated it against four popular gesture recognizers with three data sets; one of our own and two from other projects. Exceptfor recognizer–datasetpairs (e.g.,PaleoSketch recognizerandPaleoSketchdataset)theresults show thatitoutperforms the other recognizers. This demonstrates the potential of this approach to produce flexible and accurate recognizers.
Sensor Based Navigation for Car-like Mobile Robots Based on Generalized Voronoi Graph-Implementation and Experiment-Keiji Nagatani

Our research objective is to realize a sensor-based navigation by a car-like mobile robot in unknown environment. Generalized Voronoi Graph (GVG) is used for the navigation in this research. The GVG is a good tool for representing a topological map of environment, and it can be constructed by range sensor data incrementally. However, GVG is not suitable for a path of car-like mobile robots, because it is not always smooth. Therefore, the GVG should be modi ed for car-like robots. In this paper, we represent implementation issues for path representation to enable a sensor based navigation for car-like robots. Experimental results support this method. Keyword: Sensor based navigation, Generalized Voronoi Graph, Bezier curve
Statistical Methods for Reliability Data

Partial table of contents: Reliability Concepts and Reliability Data. Nonparametric Estimation. Other Parametric Distributions. Probability Plotting. Bootstrap Confidence Intervals. Planning Life Tests. Degradation Data, Models, and Data Analysis. Introduction to the Use of Bayesian Methods for Reliability Data. Failure--Time Regression Analysis. Accelerated Test Models. Accelerated Life Tests. Case Studies and Further Applications. Epilogue. Appendices. References. Indexes.
Abstract Non-Interference

Non-Interference Roberto Giacobazzi Isabella Mastroeni Dipartimento di Informatica Università di Verona (roberto.giacobazzi|isabella.mastroeni)@univr.it Questo rapporto è disponibile su Web all’indirizzo: This report is available on the web at the address: http://www.di. univr.it/report
Deep End-to-end Network for 3 D Object Detection in the Context of Autonomous Driving

Nowadays, autonomous driving is a trending topic in the automotive ﬁeld. One of the most crucial challenges of autonomous driving research is environment perception. Currently, many techniques achieve satisfactory performance in 2D object detection using camera images. Nevertheless, such 2D object detection might be not suﬃcient for autonomous driving applications as the vehicle is operating in a 3D world where all the dimensions have to be considered. In this thesis a new method for 3D object detection, using deep learning approach is presented. The proposed architecture is able to detect cars using data from images and point clouds. The proposed network does not use any hand-crafted features and is trained in an end-to-end manner. The network is trained and evaluated with the widely used KITTI dataset. The proposed method achieves an average precision of 81.38%, 67.02%, and 65.30% on the easy, moderate, and hard subsets of the KITTI validation dataset, respectively. The average inference time per scene is 0.2 seconds.
A Computational Model for a Multi-Goal Spatial Navigation Task inspired by Rodent Studies

We present a biologically-inspired computational model of the rodent hippocampus based on recent studies of the hippocampus showing that its longitudinal axis is involved in complex spatial navigation. While both poles of the hippocampus, i.e. septal (dorsal) and temporal (ventral), encode spatial information; the septal area has traditionally been attributed more to navigation and action selection; whereas the temporal pole has been more involved with learning and motivation. In this work we hypothesize that the septal-temporal organization of the hippocampus axis also provides a multi-scale spatial representation that may be exploited during complex rodent navigation. To test this hypothesis, we developed a multi-scale model of the hippocampus evaluated it with a simulated rat on a multi-goal task, initially in a simplified environment, and then on a more complex environment where multiple obstacles are introduced. In addition to the hippocampus providing a spatial representation of the environment, the model includes an actor-critic framework for the motivated learning of the different tasks.
InterBase-KB: Integrating a Knowledge Base System with a Multidatabase System for Data Warehousing

This paper describes the integration of a multidatabase system and a knowledge-base system to support the data-integration component of a data warehouse. The multidatabase system integrates various component databases with a common query language; however, it does not provide capability for schema integration and other utilities necessary for data warehousing. In addition, the knowledge base system offers a declarative logic language with second-order syntax but first-order semantics for integrating the schemes of the data sources into the warehouse and for defining complex, recursively defined materialized views. Furthermore, deductive rules are also used for cleaning, checking the integrity and summarizing the data imported into the data warehouse. The knowledge base system features an efficient incremental view maintenance mechanism that is used for refreshing the data warehouse, without querying the data sources.
Numerical study of rotating turbulence with external forcing

Direct numerical simulations at 2563 resolution have been carried out to study the response of isotropic turbulence to the concurrent effects of solid-body rotation and stochastic, isotropic forcing at the large scales. Because spectral transfer to the smaller scales is weakened by rotation, energy input from forcing gradually builds up at the large scales, causing the overall kinetic energy to increase. At intermediate wave numbers the energy spectrum undergoes a transition from a limited k−5/3 inertial range to k−2 scaling recently predicted in the literature. Although the Reynolds stress tensor remains approximately isotropic and three-component, evidence for anisotropy and quasi-two-dimensionality in length scales and spectra in different velocity components and directions is strong. The small scales are found to deviate from local isotropy, primarily as a result of anisotropic transfer from the large scales. To understand the spectral dynamics of this flow, we study the detailed behavior of nonlinear.
Grid Supporting VSCs in Power Systems with Varying Inertia and Short-Circuit Capacity

Voltage Source Converters (VSCs) can offer various control strategies to enable realization of the vision of a “Global Grid With the increasing penetration of renewable energy sources, it is becoming more frequent for VSCs to be required to provide active and reactive power regulation. In this paper, a model of a grid-supporting VSC connected to a weak AC grid with low Short Circuit Capacity (SCC) and low inertia is presented. The impact of SCC and inertia is then illustrated by means of small-signal stability, $H_{2}$ norm and large-disturbance analysis.