Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Learning-Based Maritime Environment Segmentation for Unmanned Surface Vehicles Using Superpixel Algorithms

Unmanned surface vehicles (USVs) are receiving increasing attention in recent years from both academia and industry. To make a high-level autonomy for USVs, the environment situational awareness is a key capability. However, due to the richness of the features in marine environments, as well as the complexity of the environment influenced by sun glare and sea fog, the development of a reliable situational awareness system remains a challenging problem that requires further studies. This paper, therefore, proposes a new deep semantic segmentation model together with a Simple Linear Iterative Clustering (SLIC) algorithm, for an accurate perception for various maritime environments. More specifically, powered by the SLIC algorithm, the new segmentation model can achieve refined results around obstacle edges and improved accuracy for water surface obstacle segmentation. The overall structure of the new model employs an encoder–decoder layout, and a superpixel refinement is embedded before final outputs. Three publicly available maritime image datasets are used in this paper to train and validate the segmentation model. The final output demonstrates that the proposed model can provide accurate results for obstacle segmentation.
Active vibration control system of smart structures based on FOS and ER actuator

An active vibration control system based on fiber optic sensor (FOS) and electrorheological (ER) actuator is established in this paper. A new intensity modulated fiber optic vibration sensor is developed following the face coupling theory. The experimental results show that this new type of intensity modulated fiber optic vibration sensor has higher sensitivity in measuring the vibration frequency. At the same time, experimental investigations are focused on evaluating the dynamic response characteristics of a beam fabricated with ER fluid. It is noted that the most significant change in the material properties of ER fluid is the change of material stiffness and damping which varies with the electric field intensity imposed upon the ER fluid. Finally, the structural vibration of the smart composite beam based on ER fluid, fiber optic sensor and piezoelectric transducer has been monitored and controlled actively utilizing a fuzzy-logic algorithm.
THE RASSP INTEGRATED SYSTEMS TOOL SET PROVIDES BETTER SYSTEM TRADE-OFF STUDIES

The goal of the ARPA/Tri-Service-sponsored Rapid Prototyping of Application Specific Signal Processors (RASSP) program is to reduce development and manufacturing time and cost of signal processors by a factor of four. Lockheed Martin's Advanced Technology Laboratories (ATL) RASSP team has developed an integrated systems engineering tool set. This tool set integrates Ascent Logic's RDD-100, PRICE Systems parametric cost estimation models, and Management Sciences RAM-ILS tools. This tool set provides systems engineers with cost and reliability estimation data within a systems engineering tool. This tool set is described and an example of the tool usage provided. The example demonstrates the value of the tool integration. This tool set enables systems engineers to estimate the life-cycle costs and reliability early in the design process.
A New Genus and Species of Lophocateridae from Mid-Cretaceous Amber of Myanmar (Coleoptera)

Simple Summary Lophocateridae are a small family of Cleroidea and their taxonomic rank has changed several times. The fossil record of Lophocateridae from Mesozoic deposits is sparse. Here, we figure and describe a new lophocaterid fossil, Gracilenticrus burmiticus, from the mid-Cretaceous amber of Myanmar. The new taxa broaden the generic and species diversity of lophocaterids and provide additional information for understanding the early evolution of Cleroidea. Abstract A new genus and species of the cleroid family Lophocateridae are described and illustrated from the mid-Cretaceous amber of northern Myanmar. Gracilenticrus burmiticus Yu, Kolibáč & Ślipiński gen. et sp. nov. is unique among Lophocateridae in the tiny body size, frontoclypeal suture and antennal grooves absent, symmetrical antennal clubs, protrochantin reduced, tarsal claws small and widened at base. A key to the species of Mesozoic Lophocateridae is also provided. Morphological characters of the newly discovered Gracilenticrus were analyzed together with representatives of 43 extant genera of Cleroidea (broadly defined Trogossitidae) in a matrix of 91 characters. Gracilenticrus burmiticus was resolved as a member of Lophocateridae. The discovery of a diverse fauna of Lophocateridae in the mid-Cretaceous sheds a new light on the early evolution of superfamily Cleroidea.
Three‐dimensional analysis of spatially varying ground motions around a uniform canyon in a homogeneous half‐space

Department of Civil Engineering, University of California, Berkeley, CA 94720, U.S.A. A direct boundary element method to determine the three-dimensional seismic response of an infinitely-long canyon of arbitrary but uniform cross-section cut in a homogeneous viscoelastic half-space is presented. The seismic excitation is represented by P, SV, SH or Rayleigh waves at arbitrary angles with respect to the axis of the canyon. The accuracy of the procedure and implementing computer program is demonstrated by comparison with previous solutions for the limiting case of two-dimensional response, recently obtained three-dimensional response results for infinitely-long canyons, and three-dimensional boundary method solutions presented in this paper for finite canyons.
A CMOS Time-of-Flight Image Sensor with High Dynamic Range Digital Pixel

To widen measuring range and suppress background light, a CMOS time-of-flight image sensor with high dynamic range digital pixel is proposed. The sensing charge is quantized by extended-counting analogue-to-digital converter (ADC) which consists of pixel coarse quantization and column fine quantization. To maximize dynamic range in limited pixel area, the coarse quantization circuit is shared by 2×2 pixels, in which a novel up/down counter with a small number of transistors is proposed. Based on the pixel circuit, a 32×32 prototype TOF imager with 12μm-pitch digital pixel is designed in 0. 11μm 1P4M CMOS image sensor technology. Simulation results show that a 104.6dB dynamic range of this ADC for wide measuring range is achieved at a frame rate of 50Hz.
ECG Signal Analysis Using Wavelet Transforms

This paper deals with the study of ECG signals using wavelet trans- form analysis. In the first step an attempt was made to generate ECG wave- forms by developing a suitable MATLAB simulator and in the second step, using wavelet transform, the ECG signal was denoised by removing the corresponding wavelet coefficients at higher scales. Then QRS complexes were detected and each complex was used to find the peaks of the individual waves like P and T, and also their deviations.
Monitoring Fine-Scale Forest Health Using Unmanned Aerial Systems (UAS) Multispectral Models

Forest disturbances—driven by pests, pathogens, and discrete events—have led to billions of dollars in lost ecosystem services and management costs. To understand the patterns and severity of these stressors across complex landscapes, there must be an increase in reliable data at scales compatible with management actions. Unmanned aerial systems (UAS or UAV) offer a capable platform for collecting local scale (e.g., individual tree) forestry data. In this study, we evaluate the capability of UAS multispectral imagery and freely available National Agricultural Imagery Program (NAIP) imagery for differentiating coniferous healthy, coniferous stressed, deciduous healthy, deciduous stressed, and degraded individual trees throughout a complex, mixed-species forests. These methods are first compared to assessments of crown vigor in the field, to evaluate the potential in supplementing this resource intensive practice. This investigation uses the random forest and support vector machine (SVM) machine learning algorithms to classify the imagery into the five forest health classes. Using the random forest classifier, the UAS imagery correctly classified five forest Health classes with an overall accuracy of 65.43%. Using similar methods, the high-resolution airborne NAIP imagery achieved an overall accuracy of 50.50% for the five health classes, a reduction of 14.93%. When these classes were generalized to healthy, stressed, and degraded trees, the accuracy improved to 71.19%, using UAS imagery, and 70.62%, using airborne imagery. Further analysis into the precise calibration of UAS multispectral imagery, a refinement of image segmentation methods, and the fusion of these data with more widely distributed remotely sensed imagery would further enhance the potential of these methods to more effectively and efficiently collect forest health information from the UAS instead of using field methods.
Inter- and intra-rater reliability of carpal tunnel volume measurement

ABSTRACT The reliability of carpal tunnel volume (CTV) measurement has not been previously reported. This study evaluated inter- and intra-rater reliability and assessed the variability of image segmentation and anatomical landmark selection. Analysis was performed by two raters on computed tomography images collected on two cadaveric specimens in neutral wrist posture. The variability of landmark selections was less than 0.3 mm. Intra-class correlation coefficients (ICC) for segmentation surpassed 0.88. The carpal tunnel volume calculations had ICC values greater than 0.98. These results suggest carpal tunnel volume can be reliably measured using the methods outlined in this study.
The Efficacy of a Diode Laser on Titanium Implants for the Reduction of Microorganisms That Cause Periimplantitis

The paper presents the optimisation of a safe diode laser irradiation process applied to the surface of titanium implants in order to reduce microbial numbers in the treatment of inflammation classified as periimplantitis. The study comprised isolation and identification of microorganisms inhabiting surfaces of dental implants, crowns, teeth and saliva from patients with fully symptomatic periimplantitis. Microorganisms were detected by a culture-dependent method and identified with the use of MALDI-TOF mass spectrometry. The isolated microorganisms were inoculated on the surface of a new implant and then irradiated by a diode laser (wavelength of 810 ± 10 nm) in one, two or three repetitions and biocidal efficacy was assessed. To evaluate impact of laser irradiation on roughness, morphology and structure of the implant surface, optical profilometry, scanning electron microscopy and optical microscopy were used. Examination of the tested surfaces and saliva revealed the presence of Gram-positive and Gram-negative bacteria and one fungal species. In all patients, cultures from the endosseous part of the implant revealed the presence of the pathogenic and pyogenic bacterium Streptococcus constellatus. In 13 out of 20 samples laser-irradiated in duplicate and triplicate, all microorganisms were eliminated. The irradiation used did not cause any changes in the properties of the implant surface.
Extracting Creativity from Narratives using Distributional Semantic Modeling

Narrative text permeates our lives from job applications to journalistic stories to works of fiction. Developing automated metrics that capture creativity in narrative text has potentially far reaching implications. Human ratings of creativity in narrative text are labor-intensive, subjective, and difficult to replicate. Across 27 different story prompts and over 3,500 short stories, we used distributional semantic modeling to automate the assessment of creativity in narrative texts. We tested a new metric to capture one key component of creativity in writing – a writer’s ability to connect divergent ideas. We termed this metric, word-to-word semantic diversity (w2w SemDiv). We compared six models of w2w SemDiv that varied in their computational architecture. The best performing model employed Bidirectional Encoder Representations Transformer (BERT), which generates context-dependent numerical representations of words (i.e., embeddings). The BERT w2w SemDiv scores demonstrated impressive predictive power, explaining up to 72% of the variance in human creativity ratings, even exceeding human inter-rater reliability for some tasks. In addition, w2w SemDiv scores generalized across Ethnicity and English language proficiency, including individuals identifying as Hispanic and L2 English speakers. We provide a tutorial with R code (osf.io/ath2s) on how to compute w2w SemDiv. This code is incorporated into an online web app (semdis.wlu.psu.edu) where researchers and educators can upload a data file with stories and freely retrieve w2w SemDiv scores.
Embedded Data Imputation for Environmental Intelligent Sensing: A Case Study

Recent developments in cloud computing and the Internet of Things have enabled smart environments, in terms of both monitoring and actuation. Unfortunately, this often results in unsustainable cloud-based solutions, whereby, in the interest of simplicity, a wealth of raw (unprocessed) data are pushed from sensor nodes to the cloud. Herein, we advocate the use of machine learning at sensor nodes to perform essential data-cleaning operations, to avoid the transmission of corrupted (often unusable) data to the cloud. Starting from a public pollution dataset, we investigate how two machine learning techniques (kNN and missForest) may be embedded on Raspberry Pi to perform data imputation, without impacting the data collection process. Our experimental results demonstrate the accuracy and computational efficiency of edge-learning methods for filling in missing data values in corrupted data series. We find that kNN and missForest correctly impute up to 40% of randomly distributed missing values, with a density distribution of values that is indistinguishable from the benchmark. We also show a trade-off analysis for the case of bursty missing values, with recoverable blocks of up to 100 samples. Computation times are shorter than sampling periods, allowing for data imputation at the edge in a timely manner.
Characteristics of Chinese Driver Behavior

The high growth rate of vehicle ownership and many novel drivers in China determine the special features of Chinese driver behavior. This thesis introduces a comparative study on driver behavior by the analysis of saturation flow at urban intersections, Driver Behavior Questionnaire surveys, focus group discussion, and in-car tests. The main characteristics of Chinese driver behavior have been identified. A new method is developed for a simulation model calibration based on the study results.
High Dynamic Range imaging in design education

High Dynamic Range (HDR) imaging is a popular photographic technique that accurately captures the lighting conditions of the scene from which they are created. HDR images can subsequently be used to illuminate 3D virtual scenes realistically, or be a source for numerical lighting simulations. This paper discusses two workflows that have been developed using inexpensive digital cameras and open source software, supporting the interactive exploration of realistic lighting conditions, both qualitatively and quantitatively, in a digital environment. The paper first details the suitability of the qualitative workflow as a vehicle for teaching the technical aspects of lighting to architecture students, due to its relative ease of implementation, close relationship to existing design tools, and application to visual design work. Finally, the extension of this technique to enable simplified numerical analysis is discussed.
Analysis of the use of digital road maps in vehicle navigation

Digital road maps are being used increasingly throughout the world as they become more available. Five major digital road map suppliers are focusing their efforts on producing databases that support vehicle navigation functions. Of a total of 147 vehicle navigation systems in the world, 89 use in-vehicle maps, of which, 35 employ map matching, and 31 offer real-time route guidance. Vehicle navigation systems are limited by the maps they use, so the availability of inexpensive, complete and seamless navigable digital road maps remains as an impediment to the wider use of vehicle navigation systems. <<ETX>>
Structural and Dynamic Properties of Hydrophobic Eutectic Solvents Based on Menthol and Fatty Acids: a Molecular Dynamics Simulation Study

The structural and dynamical properties of the binary mixture of Menthol (MEN) and Fatty acids (FAs) were investigated using molecular dynamics simulations. We focused on the relationship between the structural and dynamical properties of the eutectic mixtures of MEN and FAs with different molar percentages of FAs. Structural properties of the eutectic mixtures were characterized by calculating the combined distribution functions(CDFs), the radial distribution functions (RDFs), and the angular distribution functions (ADFs), and the Hydrogen bonding network between species and Spatial distribution functions (SDF). Further interaction between menthol and Caprylic acid molecules was confirmed by the results of these analyzes. Also, the transport properties of the mixtures were investigated by using the mean square displacement (MSD) of the centers of mass of the species, self-diffusion coefficients and vector reorientation dynamics (VRD) of bonds. The simulation results indicated that intermolecular interactions have a significant effect on the dynamic properties of species.
Impact of Climate Change on Water Resources in the Shiyang River Basin and the Adaptive Measures for Energy Conservation and Emission Reduction

Climate is an important factor which formed and affected surface water resources. Through sensitivity analysis of natural runoff towards climate change, assuming the main factors effect runoff are precipitation and temperature, then according to the possible tendency of climate changes in the future, set climate scenarios, and use the hydrological model simulate the changes trend of runoff under different climate scenarios, thereby analyze the climate change impacts on surface water resources. The results show that annual runoff will be increased with the increasing annual precipitation, and it will be reduced with rise of annual temperature, the sensitivity that annual runoff towards the change of precipitation and temperature are equally notable, both of them are two major factors impact on the change of runoff and the precipitation change impacts on annual runoff will be even more obvious in flood season. Last, with the global warming trend, put forward the corresponding adaptive measures of energy conservation and emissions reduction。
Finite Element Static Analysis on Heavy-Duty Truck Gearbox Housing

The heavy-duty truck’s gearbox housing is studied in this paper. The analysis model is built with finite element software. MPC (multipoint constraint) contact algorithm is used to simulate the connections between different gearbox housings. The strength and stiffness of gearbox housing is calculated at its low-speed load case in the first gear. The contour of the stress and displacement is obtained through the calculation results. The results show that the housing meets the design requirements and it provides a reference for optimization and improvement of the gearbox housing.
Synthesis and Characterization of Nanoporous Carbon Carriers for Losartan Potassium Delivery

Losartan potassium is most commonly used for the treatment of hypertension. In recent years, new applications of this drug have emerged, encouraging the design of novel nanoporous carriers for its adsorption and release. The purpose of this study was to synthesize ordered mesoporous carbon vehicles via a soft-templating method altered with the use of nitrogen precursors and via a hard-templating method followed by chitosan functionalization. As a result, the materials obtained differed in nitrogen content as well as in the number of total surface functional groups. The impact of the modification on the physicochemical properties of carbon carriers and their interaction with losartan potassium during adsorption and release processes was examined. The materials were characterized by various morphologies, specific surface areas (101–1180 m2 g−1), and the amount of acidic/basic oxygen-containing functional groups (1.26–4.27 mmol g−1). These features, along with pore sizes and volumes, had a key effect on the sorption capacity of carbon carriers towards losartan potassium (59–161 mg g−1). Moreover, they contributed to the differential release of the drug (18.56–90.46%). Losartan potassium adsorption onto the surface of carbonaceous materials was mainly based on the formation of hydrogen bonds and π–π interactions and followed the Langmuir type isotherm. It has been shown that the choice of the method of carbon carriers’ synthesis and their modification allows for the precise control of the kinetics of the losartan potassium release from their surface, resulting in rapid or sustained drug liberation.
Improving stability of EKF filter used by the symmetrical measurement equation approach to multiple-target tracking

Multiple Target Tracking (MTT) requires the proper association of measurement data with individual targets before the data is filtered and target positions estimated. Because data association is computationally intensive, there has been interest in the Symmetrical Measurement Equation (SME) approach to MTT. An SME tracker subsumes the data association step by defining a measurement equation where the ordering of measurements is no longer required. However, the acceptance of the SME approach has been curtailed by a lack of stability in the Extended Kalman Filter (EKF) and the ability of the SME track to properly maintain tracks during track crossings. Tweaking the EKF parameter can improve stability and track maintenance, but we show that an extension to the EKF filter, the Proportional-integral EKF, produces superior results. Integral action improved track maintenance at crossings, reducing the incidence of track switching by more than an order of magnitude. The SME tracker now shows promise of providing superior stability and reduced estimation error while tracking multiple, crossing, and maneuvering targets.