Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation and Enhancement of Port Security and Efficiency using Mathematical Techniques

In this paper, progress and challenges in US homeland security are discussed, and security and efficiency, two important aspects of the operation of maritime ports, are addressed. Specifically, this paper describes the application of Data Envelopment Analysis to assess port efficiency and the application of Fault-Tree Analysis and Risk Analysis to enhance port security. Use of high technology and marine animals to enhance port security are also discussed.
Exploring Summary-Expanded Entity Embeddings for Entity Retrieval

Entity retrieval is an important part of any modern retrieval system and often satisfies user information needs directly. Word and entity embeddings are a promising opportunity for new improvements in retrieval, especially in the presence of vocabulary mismatch problems. We present an approach to entity embedding that leverages the summary of entity articles from Wikipedia in order to form a richer representation of entities. We present a brief evaluation using the DBPedia-Entity-v2 dataset. Our evaluation shows that our new, summary-inspired representation provides improvements over both standard retrieval and pseudo-relevance feedback baselines as well as over a straightforward word-embedding model. We observe that this representation is particularly helpful for the verbose queries in the INEX-LD and QALD-2 subsets of our test collection.
Entity Annotation WordPress Plugin using TAGME Technology

The development of internet technology makes more information can be accessed. It makes information need to be organized in order to be easily managed. One solution can be used is by using the entity annotation approach which generates tags to represent that document. In this study, TAGME technology is implemented on a WordPress plugin, which is used to manage a blog. Moreover, information on Wikipedia ‘Bahasa Indonesia’ is processed to generate an anchor dictionary which is required by the technology that is implemented. This plugin performs entity annotation by giving tag suggestion for posts in a blog. Testing is carried out by measuring the precision, recall, and of tag suggestions given by the plugin. The result shows that the plugin can give tag suggestions with precision 0.7638, recall 0.5508, and 0.59.
Low-Frequency Noise in Electric Double Layer InGaZnO Thin-Film Transistors Gated with Sputtered SiO2-Based Electrolyte

Using electrolyte as the gate dielectric to form an electric double layer (EDL) is an effective method to reduce the operating voltage of thin-film transistors (TFTs). Such TFTs are typically able to work at a low voltage of 1 V. However, there has been very limited work on the low-frequency noise (LFN) properties of EDL TFTs despite that the nature of EDL means an accumulation of a large number of ions at the channel interface which may well play an important role in device electronic noise. Here, the LFN properties of amorphous indium–gallium–zinc oxide (a-IGZO) EDL TFTs gated with sputtered SiO2-based electrolyte are characterized. The LFN in the EDL TFTs shows two distinctively different dependencies on frequency in different gate bias ranges, i.e., 1/f noise and 1/f2 noise. The 1/f noise generated at low gate voltages VG 1 V, on the other hand, is found to .
Dynamic Integrated Platform for Multi-Dimensional Propagation Data Analysis

In order to evaluate the performance of Multi-Input Multi-Output (MIMO) communication systems accurately, MIMO channel sounding is necessary. In this paper, a Dynamic Integrated platform for multi-DimensiOnal data analysis (DINO) is proposed for the systematic analysis of the data from a MIMO channel sounder. In DINO, through the visualization of the obtained data by recreating the propagation channel virtually in a computer, a fundamental link between the measured data and the physical environment is established.
Stochastic Blockmodels meet Graph Neural Networks Supplemental Material 1

The framework proposed uses a stick-breaking IBP prior which has two parameters: α and K. The parameter α is the initial guess of the number of non-zero entries in the binary vector bn and K is the truncation parameter. In the experiments, α ∈ {5, 10, 20, 50, 100}. In general, a higher value of the α parameter worked better for DGLFRM-B and LFRM, as compared to the α value in the DGLFRM model. This difference in α reflects the inherent capacity of the latent space of these models. The embedding learned by DGLFRM, while being highly sparse, are in real space resulting in more capacity to represent data as compared to the binary latent space in DGLFRM-B and LFRM.
Text Feature Selection Method Based on Improved TFIDF

Analyzes several common evaluation functions for feature selection,then applies the terms weight function in feature selection,proposes a new evaluation function based on improved TFIDF method called TFIDF-Dac.In order to show the ability of separating from categories,introduces the distribution information between categories of feature item in this new method and it made up the disadvantages of the traditional TFIDF.Experiments have proved that the improved feature selection method can effectively improve the precision of the text categorization result.
Big data analysis of power grid from random matrix theory

Data will become a strategic resource and even prime driving force for future grid. Essentially, rather than massive data themselves, we are much more interested in the potential contained in the data. In other words, how to mine the value from the 4Vs data (data with features of volume, variety, velocity, and veracity) within tolerant resources (time, hardware, human, etc.) is the key challenge. This chapter studies the methodology of applying big data analytics to power grids. First, the definition of big data and random matrix theories (RMTs), as well as related system mapping framework and data processing methods are introduced as foundations. Especially, some mathematical contents, such as random matrix models (RMMs), probability in high dimension, and linear eigenvalue statistics (LES), are discussed in detail. Then, a series of functions related to situation awareness (SA) of power grids, including early event detection (EED), fault diagnosis and location, correlation analysis, high-dimensional indicator system and its visualization (i.e., auxiliary 3D power-map), are developed as concrete applications. In this way, a typical data-driven methodology, mainly based on RMT, is proposed to cognize power grids. Three main procedures are essential: (1) big data model-to build the RMMs with raw data; (2) big data analysis-to conduct high-dimensional analyses to construct the indicator system via statistical transformations; and (3) engineering interpretation-to visualize and interpret the statistical results to human beings. This methodology is a more precise and natural way to gain insight into the large-scale interconnected systems. Furthermore, the indicator system will build a new epistemology to reveal the physical systems; it will open a new ear for the SA.
Helium ion beam lithography

As nanoelectronic device design pushes towards ever smaller feature sizes, there is an increasing need for new lithographic patterning techniques and resists. Helium ion beam lithography (HIBL), an emerging technique that uses a high-intensity, sub-nanometer focused beam of helium ions generated in the helium ion microscope (HIM) to expose resist, promises to drive nano-patterning beyond the capabilities of conventional electron beam lithography (EBL). In this work, an investigation on HIBL in direct comparison with EBL using both conventional EBL resist PMMA and a novel fullerene-based molecular resist is described. Analysis of large area exposures reveals a sensitivity of 2 μC/cm2 on PMMA and 40 μC/cm2 on fullerene derivative resist with 30-keV helium ion beam, which are 60 times and 500 times higher than those with an electron beam for the same resists respectively. This improved resist sensitivity in HIBL demonstrates the potential for faster pattern definition and therefore high throughput. The proximity effect, caused by the backscattered primary particles and known to limit the performance of EBL, was then quantitatively studied using a “doughnut” method on 20-nm-thick PMMA resist on silicon with 30 keV HIBL and EBL. The lithographic results were fitted to the proximity function and the backscattered electrons/ions range were found out to be ~3.26 μm and ~0.067 μm, revealing a 60 times proximity effect reduction in HIBL compared to EBL. This suggests that the negligible proximity effect in HIBL enables high-density pattern definition, whilst avoiding the inadvertent exposure of surrounding material. Finally, to demonstrate the benefit of the smaller spot size and the reduced proximity effect in HIBL, line dose optimisation was carried out with high-resolution single-pixel line arrays on both resists. Linewidth of ~11.7 nm was achieved in 20-nm PMMA with pitches down to 30 nm. In 10-nm fullerene resist, line widths of 7.2 nm were achieved in sparse line arrays. The fabrication of 8.5 nm half-pitched lines with good feature separation and 6 nm half-pitched lines with inferior but still resolvable separation is also shown in this resist. Thus, sub-10 nm patterning with high resist sensitivity and small proximity effect is demonstrated using HIBL with standard processing conditions, establishing its potential as an alternative to EBL for rapid prototyping of beyond CMOS devices.
Development of a Steady-State Fluorescence Spectroscopy System and a Time-Resolved Fluorescence Spectroscopy System

This document describes thoroughly the construction of two spectroscopic systems: One system for obtaining fluorescence spectra and another system for obtaining the fluorescence lifetime. The first system consists of obtaining the fluorescence spectrum and is constituted by a Czerny-Turner type monochromator, a photomultiplier tube (PMT), a system for modulating the excitation signal and a system for treating and filtering the fluorescent signal constituted by an electromechanical chopper, a lock-in amplifier and a fast response PMT; plus a set of lenses and a samples holder. The fluorescein dissolved in ethanol was used as a calibration standard, and an Nd:YAG laser source was used as a source of excitation, which emits in 532 nm, of continuous wave and stable power in time adjustable by current. On the other hand, a fluorescence time-resolved system was developed. This system consists of obtaining the fluorescence lifetime of different samples under study from a Voltage curve Vs Time obtained from the system and showing the decay behavior of the phenomenon. This has a pulsed laser unit as a source of excitation, emitting at 532 nm, 80 mJ of energy and with a pulse width of 4 ns. For this system, two semiconductor photodiode detectors with fast response have been built; both with a response of temporary uptake above 1 ns, thus providing obtaining fluorescence lifetime up to this value. Fluorescein was also used in this system as a standard sample, but in this case dissolved in a buffer-like solution; accompanied also by a brief study of the change in the average lifespan of fluorescence in function of the pH of the solution. The results obtained show that two automated systems, reproducible, accurate and of very low cost compared to the current ones, have been successfully implemented for the study of steady-state and time-resolved fluorescence spectroscopy.
Fibrinolysis Using Monotherapy is Inadequate and Risky

Affiliation: Director, Vascular Research Laboratory, Harvard Medical School, Mt Auburn Hospital, Cambridge, Massachusetts, United States Corresponding author: Gurewich V, Director, Vascular Research Laboratory, Harvard Medical School, Mt Auburn Hospital, Cambridge, Massachusetts, United States, E-mail: vgurewich@tsillc.net Citation: Gurewich V. Fibrinolysis using monotherapy is inadequate and risky (2019) Neurophysio and Rehab 2: 26-28 Received: Apr 19, 2019 Accepted: May 24, 2019 Published: May 28, 2019 Copyright: © 2019 Gurewich V. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The use of doppelgangers in virtual reality to treat public speaking anxiety: a gender comparison

The present study explores the potential of using doppelgangers—virtual humans that highly resemble the real self but behave independently—in conjunction with a visualization technique to reduce public speaking anxiety and compares it to the traditional form of visualization through imagination. Moreover, it explores gender differences in the efficacy of the techniques. Forty-one participants were assigned to one of two conditions (visualization with a doppelganger or visualization through imagination) in which they went through a relaxation process before giving a speech. In the condition of visualization through imagination, participants listened to a script that encouraged them to imagine themselves giving a successful speech. In the doppelganger condition, participants listened to the same script but were in virtual reality at the same time, where they watched a doppelganger, whose face was modeled from their face, performing a successful speech. There was an interaction between condition and gender for state anxiety and self-perceived communication competence, such that the doppelganger technique worked better in males than in females whereas the imagination technique worked better in females than in males.
A More Accurate and Precise Method to Calibrate Atomic Force Microscope (AFM) Cantilevers

This paper presents a method for using a calibrated microelectromechanical system (MEMS) device to calibrate an atomic force microscope (AFM) cantilever. Measurements of stiffness and deflection can be made with quantifiable uncertainty. The popular AFM is responsible for initiating the field of nanotechnology; however, the AFM has been quite inaccurate, with measurements yielding only about one significant digit. Traditional AFM calibration methods are about 10% uncertain with unknown accuracy. The present calibration method appears to have superior accuracy, precision, repeatability, and reliability. Accuracy is from using electro-micro metrology (EMM), precision is based on eliminating unknown or coarsely-known dependencies, repeatability is through well-defined gapstops, and reliability is achieved through the method’s independence of parasitics. In this paper we present a packageable, practical, stiffness and deflection calibration method for microscale cantilevers.
An English Text to Speech Conversion System

-This paper is demonstrating to convert the international language English text into speech sign. The exchange of text to speech is made by the speech synthesizer. Speech synthesis is the imitation technique of human speech. Text handling and speech generation are two main mechanisms of text to speech system. In a text to speech system, spoken words are automatically formed from text. The extreme vital talents of a synthesized speech are genuineness and fluency.Text to speech system will support in saving the information from websites and documents that contain information in different languages. Database formation, character recognition and text to speech conversion are the essential phases in text to speech analysis.
Triple Energy Saving by Use of Contra Rotating, Tip Loaded and Podded Propulsion Technology

TRIPOD deals with energy saving in waterborne transport. It explores the feasibility of a novel propulsion concept resulting from the integration of two promising technologies (podded propulsion and tip loaded endplate propellers) in combination with energy recovery based on counter rotating propeller (CRP) principle. New ways of saving energy are studied to improve ship operational costs. The paper describes the main objectives and the different phases of the project, including the design activities, validation of the concept by model testing and numerical computations, and the economic analysis of main results. The main focus is on the development of a tool for the assessment of the overall energy balance in the ship design phase and on the application of the new propulsion concept to several ship fleets. Energy savings and consequently emission reductions are derived from the use of the analysis tool.
Experimental Study on Acoustic Emission Characteristics of Intermittent Jointed Rock Mass Under Uniaxial Compression

Using large size of intact and intermittent jointed rocks made with equivalent materials, the stress-stain curves, ringing counts and energy accumulation of acoustic emission (AE) were obtained by AE monitoring in real time under uniaxial compression. The strength, deformation, progressive failure evolution and AE properties of two kinds of rock samples were compared. Through the analysis of AE parameters, the results indicate that the sudden increase of AE ringing counts and AE energy may be utilized as precursor information for the failure of rocks. AE location may directly reflect the dynamic evolvement process of rock cracks. Unlike the failure of intact rock sample, the AE ringing counts and energy curves of jointed rock sample show obvious multi-peaks, and the final peak appears behind the stress peak. The failure mode of intact rock is mainly vertical tensile breakage, whereas the tensile wing crack propagates through the joint surface, resulting in the failure of jointed rock sample.
Optimal Design of Laminated Composite Plates by Using Advanced Genetic Algorithm

: Composite laminate design and optimization requires discrete programming in order to find the correct number of plies with thicknesses, orientation angles, and material types which are usually restricted to a discrete set of values. Genetic algorithms are one of the few optimization tools available that are well suited to such discrete problem solving environments. The main goal of this work was to try and improve the computational efficiency of the GA (its most serious drawback), and demonstrate the GA's ability to be easily adapted to different types of composite laminate design optimization problems. Two different versions of a genetic algorithm, GA-I and GA-II, were developed specifically to accomplish these tasks. To demonstrate the flexibility of the GA structure, the GA-II algorithm was devised to handle more complex composite laminate configurations constructed from multiple materials. The modified GA utilized two chromosome strings to represent the composite laminate. The first string defined the orientation angle of each ply, and the second string defined a ply's material type. By using two different chromosome strings, only small modifications to the various genetic operators were required. The two chromosome string concept was tested on a multi-objective optimization problem which involved minimizing laminate cost and weight of a simply supported composite plate subjected to various in-plane loading conditions, and numerous constraints. The cost of the laminate was based on the required lay up time and by its material make-up. To achieve high performance laminates at the lowest cost, two materials were allowed in the stacking sequence, one with high strength and cost, the other with lower strength and cost. The optimization formulation was carried out by determining separate cost and weight objective functions. A convex combination of these two objectives was used for
Automatic detection of relation assertion errors and induction of relation constraints

Although the link prediction problem, where missing relation assertions are predicted, has been widely researched, error detection did not receive as much attention. In this paper, we investigate the problem of error detection in relation assertions of knowledge graphs, and we propose an error detection method which relies on path and type features used by a classiﬁer for every relation in the graph exploiting local feature selection. Furthermore, we propose an approach for automatically correcting detected errors originated from confusions between entities. Moreover, we present an approach that translates decision trees trained for relation assertion error detection into SHACL-SPARQL relation constraints. We perform an extensive evaluation on a variety of datasets comparing our error detection approach with state-of-the-art error detection and knowledge completion methods, backed by a manual evaluation on DBpedia and NELL. We evaluate our error correction approach results on DBpedia and NELL and show that the relation constraint induction approach beneﬁts from the higher expressiveness of SHACL and can detect errors which could not be found by automatically learned OWL constraints.
Zinc oxide ultraviolet photodetectors: rapid progress from conventional to self-powered photodetectors

Currently, the development of ultraviolet (UV) photodetectors (PDs) has attracted the attention of the research community because of the vast range of applications of photodetectors in modern society. A variety of wide-band gap nanomaterials have been utilized for UV detection to achieve higher photosensitivity. Specifically, zinc oxide (ZnO) nanomaterials have attracted significant attention primarily due to their additional properties such as piezo-phototronic and pyro-phototronic effects, which allow the fabrication of high-performance and low power consumption-based UV PDs. This article primarily focuses on the recent development of ZnO nanostructure-based UV PDs ranging from nanomaterials to architectural device design. A brief overview of the photoresponse characteristics of UV PDs and potential ZnO nanostructures is presented. Moreover, the recent development in self-powered PDs and implementation of the piezo-phototronic effect, plasmonic effect and pyro-phototronic effect for performance enhancement is highlighted. Finally, the research perspectives and future research direction related to ZnO nanostructures for next-generation UV PDs are summarized.
Integrated optimization of Distributed Network Reconfiguration Considering Distributed Generation

Distributed Generation(DG) brings lots of difficulty to network reconfiguration,making it hard to describe the problem while using the traditional model.In order to make use of the beneficial effect of DG,this paper establishes a integrated optimization configuration model regarding network switches、DG power、DG location as variables,and takes network loss as the objection,using quantum evolutionary algorithm(QEA) to solve the model.The effectiveness and correctness of the method proposed in this paper is verified through the simulation results of IEEE 33-node system.
MODELLING AND SIMULATION WITH MSC ADAMS OF A 5-FINGER AND 3-PHALANX / FINGER UNDER-ACTUATED MECHANICAL HAND

This paper studies the modelling and simulation with MSC ADAMS of a 5-fingered and 3phalanx/finger under-actuated mechanical hand, designed by the author to work on industrial robots. Moreover, in order to increase grasping safety in the automated handling process, the author has fitted each finger with a locking sequence in the final phase of grasping. Thus, the mechanism of mechanical hand is considered to be a mechanical system and is treated like a set of rigid bodies connected by mechanical linkages and elastic elements. To model and simulate this mechanism with MSC ADAMS programme, the author covered the following stages: construction of the model, testing-simulation, validation, finishing, parameterization, and optimization
Research on Speech Cepstral Features

The speech cepstral features are very important parameter in ASR, which symbolizes the property of HAS(human auditory system). The paper discusses cepstral features based on linear predictive and non-linear MEL scale, and presents LPCC and MFCC's extraction algorithm and differential coefficient and accelerated coefficient are also presented. The recognition experiment results show that MFCC's robustness is prior to LPCCs.