Miracle-dz/UniFAR-FTUs huggingface dataset:
Colony-specific foraging behaviour and co-ordinated divergence of chick development in the wedge-tailed shearwater Puffinus pacificus

We examined divergence in foraging, provisioning and chick developmental patterns between wedge-tailed shearwaters Puffinus pacificus breeding at a temperate (Lord Howe Island) and sub-tropical (Heron Island) location. We aimed to evaluate the potential for different foraging environments to cause co-ordinated adaptive divergence in these characteristics. Adult foraging and provisioning behaviour differed significantly between locations, reflecting lower near-colony resource availability at Heron Island. Chick developmental patterns also differed significantly between locations. Overall, chicks at Lord Howe Island grew faster and had greater skeletal growth per gram of food delivered. In contrast, chicks at Heron Island exhibited greater body mass gains per gram of food delivered. Based on previously observed physiological or facultative responses to changes in provisioning rates in seabirds and long-term patterns of primary productivity at each location, we propose these developmental differences reflect colony-specific physiological adaptations to differences in long-term provisioning rates. If so, our results suggest co-ordinated environmentally determined divergent coevolution of chick and adult life-history parameters between these 2 locations.
ESTIMATED AND ANALYSIS OF THE RELATIONSHIP BETWEEN THE ENDOGENOUS AND EXOGENOUS VARIABLES USING FUZZY SEMI-PARAMETRIC SAMPLE SELECTION MODEL

An important progress within the last decade in the development of the selectivity model approach to overcome the inconsistent results if the distributi onal assumptions of the errors terms are made this problem is through the use of semi-parametric method. However, the uncertainties and ambiguities exist in the mod els, particularly the relationship between the endogenou s and exogenous variables. A new framework of the relationship between the endogenous and exogenous variables of semi-parametric sample selection model using the concept of fuzzy modelling is introduced. Through this approach, a flexible fuzzy concept hy brid with the semi-parametric sample selection models known as Fuzzy Semi-Parametric Sample Selection Model (FSPSSM). The elements of vagueness and uncertainty in the models are represented in the model construction, as a way of increasing the available information to produce a more accurate model. This led to the development of the convergence theorem presented in the form of triangular fuzzy numbers to be use d in the model. Besides that, proofs of the theorems are presented. An algorithm using the concept of fuzzy modelling is developed. The effectiveness of the es timators for this model is investigated. Monte Carl o simulation revealed that consistency depends on ban dwidth parameter. When bandwidth parameters, c are increased from 0.1, 0.5, 0.75 and 1 as the numbers of N increased (from 100 to 200 and increased to 50 0), the values of mean approaches (closed to) the real para meter. Through the bandwidth parameter also reveals that the estimated parameter is efficient, i.e., the S.D , MSE and RMSE values become smaller as N increased. In particular, the estimated parameter becomes consist ent and efficient as the bandwidth parameters appro aches to infinity, c→∞ as the number of observations, n tend to infinity, n→∞.
Multi-Level Seismic Performance Assessment of a Damage-Protected Beam-Column Joint With Internal Lead Dampers

A multi-level seismic performance assessment is performed on a near full scale beam-column subassembly. The physical model is taken from a 3D exterior connection of a jointed precast concrete frame structure that is designed for damage avoidance. Unbonded post-tensioned prestress is provided by high-alloy high-strength thread-bars. Draped and straight tendon profiles are used in the transverse and orthogonal directions, respectively. The joint region is armoured to avoid damage by providing steel plates at the beam-column contact points. Supplemental energy dissipation is provided by high-performance lead-damping devices cast internally in each beam. Bi-directional quasi-earthquake displacement profiles are applied meaning the input displacement profiles are taken directly from the results of inelastic dynamic analysis. Three input earthquakes are selected probabilistically to represent multiple levels of seismic demand. Results from physical testing are critically discussed.
Developing Machine-Assisted Analysis of Engineering Students' Ethics Course Assignments

Our research concerns engineering ethics education. We were drawn to this topic by a recent paper titled “Do Ethics Classes Teach Ethics? ”, but more so by ABET criteria 3f and 3h regarding the development of ethical responsibility in engineering students. The purpose of the present project is to use the learning and analytical capabilities of IBM Watson Natural Language Classifier to analyze capstone papers submitted by undergraduates in a course on engineering ethics. The capstone papers that we analyzed required students to identify and discuss a contemporary engineering technology (e.g., autonomous tractor trailers) and to explicitly discuss the ethical issues involved. In the two tests described here we assessed whether Watson-NLC could classify sentences from students’ papers as either related to ethics or not related to ethics. Additionally, we consider the utility of these simple machine-based classifications. Our longer-term goals are to use Watson-NLC to identify the ethical theory or theories from the course that students adopt to frame their ethical positions, to assess the effectiveness of students’ ethical arguments, and to assess changes in ethical thinking across the semester.
PMSG based residential wind turbines: possibilities and challenges

This paper presents an overview of technologies for wind energy conversion into electrical energy with the help of residential wind turbines. The theory of wind energy conversion into mechanical energy is shown. Wind velocity distribution and normalised energy yield examples are given to improve understanding of wind energy availability and converter operation modes. Additionally the wind velocity dependency of the height above ground is explained. The pros and cons of wind turbine generators are analysed. Converter topologies galvanically isolated for interfacing a permanent magnet synchronous generator based variable speed wind turbine with a residential power network is analysed. Main emphasis is on the combination of a rectifier and an isolated quasi-Z-source (qZS) based DC/DC converter topology proposed by the authors. The topology (rectifier coupled with a qZS based galvanically isolated step-up DC/DC converter) is essential to generate regulated DC voltage (400 V DC typical for 230 V AC output) despite wide variations in the output voltage of a wind generator. The operation principle of the proposed topology is described. Experimental and simulation results are presented and analysed.
Detection and Classification of Malware Data in Android Based Smart Device

: The detection and classification of malware data in android based smart device is very serious challenge due to self-propagation nature of malware. Most of the malware nature is dynamic and self-propagated and infected automatically files and consume more energy and switch off the smart devices. The infected files also decrease the performance of smart devices. In this paper proposed novel methods for the detection and classification of malware data in android based smart devices. The proposed algorithm is combination of support vector machine and wrapper feature extraction of malware data. the wrapper feature extractor extracts the malware features in three level, application, network and processing of file. The proposed algorithm implemented in android visual studio and used SSMD malware dataset. The proposed algorithm is better in comparison of SVM.
Ice-penetrating radar profiles across the grounding line of a small ice-rise promontory located within the Roi Baudouin Ice Shelf in the Dronning Maud

[1] Ice-penetrating radar profiles across the grounding line of a small ice-rise promontory located within the Roi Baudouin Ice Shelf in the Dronning Maud Land sector of East Antarctica show downward dipping englacial radar-detected reflectors. Model results indicate that this reflector pattern is best fit by including basal melting of at least 15 cm a . This rate of melting is low compared with rates observed on larger ice shelves in both West and East Antarctica. Ice cores extracted from a rift system close to the ice-rise promontory show several meters of marine ice accreted beneath the shelf. These observations of low rates of basal melting, and limited distribution of accreted marine ice suggest that either Antarctic surface water may reach the ice shelf base or that circulation beneath the shelf is likely dominated by the production of high salinity shelf water rather than the incursion of circumpolar deep water, implying a weak sub-shelf circulation system here. Many of the ice shelves located along the coast of Dronning Maud Land are, like Roi Baudouin Ice Shelf, characterized by frequent ice rises and promontories. Therefore, it is highly likely that these are also of shallow bathymetry and are subject to similarly weak side-shelf basal melting and refreezing.
Magnetic turbulence in clusters of galaxies

Abstract Galaxy clusters are large laboratories for magnetic plasma turbulence and therefore permit us to confront our theoretical concepts of magnetogenesis with detailed observations. Magnetic turbulence in clusters can be studied via the radio-synchrotron emission from the intra-cluster medium in the form of cluster radio relics and halos. The power spectrum of turbulent magnetic fields can be examined via Faraday rotation analysis of extended radio sources. In case of the Hydra A cool core, the observed magnetic spectrum can be understood in terms of a turbulence-mediated feedback loop between gas cooling and the jet activity of the central galaxy. Finally, methods to measure higher-order statistics of the magnetic field using Stokes-parameter correlations are discussed, which permit us to determine the power spectrum of the magnetic tension force. This fourth-order statistical quantity offers a way to discriminate between different magnetic turbulence scenarios and different field structures using radio polarimetric observations.
Aconitase and Developmental EndPointsasEarly IndicatorsofCellularToxicity Induced by Xenobiotics in Drosophila Melanogaster

Background: In this study, the toxicity of the different xenobiotics was tested on the fruit fly Drosophila melanogaster model system. Methods: Fly larvae were raised on food supplemented with xenobiotics at different concentrations (sodium nitroprusside (0.1-1.5 mM), S-nitrosoglutathione (0.5-4 mM), and potassium ferrocyanide (1 mM)). Emergence of flies, food intake by larvae, and pupation height preference as well as aconitase activity (in 2-day old flies) were measured. Results: Food supplementation with xenobiotics caused a developmental delay in the flies and decreased pupation height. Biochemical analyses of oxidative stress markers and activities of antioxidants and their associated enzymes were carried out on 2-day-old flies emerged from control larvae and larvae fed on food supplemented with chemicals. Larval exposure to chemicals resulted in lower activities of aconitase in flies of both sexes and perturbation in activities of antioxidant enzymes. Conclusions: The results of this study showed that among a variety of parameters tested, aconitase activity, developmental endpoints, and pupation height may be used as reliable early indicators of toxicity caused by different chemicals.
Exploring Teacher Effectiveness As Measured By The Danielson Framework For Teaching and Student Achievement Outcomes: Pursuing An Understanding of Leading Students to Excellence-PULSE Study

i PREFACE.ii TABLE OF CONTENTS.iii LIST OF TABLES . iv LIST OF FIGURES . v SECTION ONE: INTRODUCTION . 1 Purpose . 1 Program Details . 3 Rationale . 7 Goals . 8 Research Questions . 9 SECTION TWO: LITERATURE REVIEW . 1
An improved adaptive policy Based on Recency and Frequecy

Cache replacement policy is one of the caching techniques, including the recency based algorithms and the freqency based algorithms etc. Although combining the recency and frequency, the LRFU algorithm could not dynamically adjust itself to adapt to the practical circumstance. This paper proposes an improved LRFU algorithm, which can dynamically modify the λ value of the LRFU to choice the appropriate replacement policy according to the practical case. Adopted the trace simulations with three common access patterns, the experiment shows that the improved LRFU algorithm can improve the hit ratio compared the LRFU, LRU and LFU algorithms.
Improvement of the critical temperature of superconducting NbTiN and NbN thin films using the AlN buffer layer

Thin superconducting NbTiN and NbN films with a few nm thickness are used in various device applications including in hot electron bolometer mixers. Such thin films have lower critical temperature (Tc) and higher resistivity than corresponding bulk materials. In an effort to improve them, we have investigated an effect of the AlN buffer layer between the film and the substrate (quartz or soda lime glass). The AlN film is deposited by DC magnetron sputtering, and the process condition is optimized so that the x-ray diffraction intensity from the 002 surface of wurtzite AlN becomes the highest. By use of this well-characterized buffer layer, Tc and the resistivity of the NbTiN film with a few nm thickness are remarkably increased and decreased, respectively, in comparison with those without the buffer layer. More importantly, the AlN buffer layer is found to be effective for NbN. With the AlN buffer layer, Tc is increased from 7.3 to 10.5 K for the 8 nm NbN film. The improvement of Tc and the resistivity originates from the good lattice matching between the 002 surface of AlN and the 111 surface of NbTiN or NbN, which results in better crystallization of the NbTiN or NbN film. This is further confirmed by the x-ray diffraction measurement.
Quality Management System: A Tool to Effect Operational Performance

The aim of the research is to find out the impact of QMS on firm’s operational performance. The focus of study is to identify the factors of QMS implementation and operational performance, and their mutual relationship. In modern business world the business has shifted from hard techniques of quality management to soft techniques of quality. They involve ISO Certifications and quality models. Among all these standards ISO 9001 or QMS is the most significant. It involves set of practices that have significant impact on the performance of the firm. The impact of ISO 9001 certification of firm’s financial performance is established, but the study investigates its impact on firm’s operational performance. Different companies that are QMS certified were taken under the scope of study and questions were asked as per QMS implementation and operational performance, later on test were performed to confirm and validate the hypothesis.
ScienceDirect The Manufacturing Engineering Society International Conference , MESIC 2013 Defining a Methodology to Design and Implement Business Process Models in BPMN according to the Standard ANSI / ISA-95 in a Manufacturing Enterprise

Nowadays, extended enterprise requires flexible and adaptable platforms which enable technology and internal integration between ERP and MES levels of manufacturing industry. Under the EAI perspective, it is proposed the use of ESB and BPMS technologies to improve integration between business and manufacturing layers. In order to enable this integration, it should be considered standard ANSI/ISA-95 Enterprise/Control System Integration due to it defines an effective model for business integration/manufacturing. In this paper, in order to develop applications that allow the orchestration of information exchanges between ERP/MES, a methodology is defined to design BPMN process models according to the standard ANSI/ISA-95 because it enables B2M integration projects development. © 2013 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of Universidad de Zaragoza, Dpto Ing Diseño y Fabricacion.
Extraction of Information From Public Health Emergency Web Documents

Globalization and economic growth have brought more and more uncertain factors that would lead to the occurrence of public health emergencies, which greatly threaten people’s lives and properties. The occurrence of a public health emergency is often accompanied by the appearance of a huge amount of related documents on the Internet, and these documents carry a lot of important information. To extract such information, which are usually stored in the form of plain texts (unstructured documents) and cannot be reused directly, it is crucial to automate the extraction process. This work proposed a method for the recognition of named entities with H7N9 public health emergency-related web documents as the research subject, using Hidden Markov Models. The experimental results showed that the proposed method could effectively extract time, location and symptom information.
Smartphone based automatic incident detection algorithm and crash notification system for all-terrain vehicle drivers

All-Terrain Vehicle (ATV ) drivers face a different sort of danger than posed by most other means of travel. An ATV is mainly designed to travel forests and unpaved areas. It is a versatile vehicle often used only by one person at a time; thus, if an accident occurs far out in the wilderness help is hard to come by, especially if the driver is incapacitated. As a result of the prevalence of GPS-enabled smartphones, an application for them implementing an accurate Incident Detection Algorithm (IDA) could save even an unconscious driver, via an automatic message to an In Case of Emergency (ICE ) contact. This thesis investigates the possibility of designing such an application, as well as the feasibility of running it in real time on a smartphone. A dataset containing 55 hours of logged normal ATV driving motion data was available, of which approximately 21 hours were of high quality. Two logs were omitted due to their content of abnormally erratic motion data. Machine learning methods (specifically One Class Support Vector Machines (OC-SVM )) were used in order to create an IDA that can satisfactorily identify several types of accidents. Motion data was collected containing 20 abnormalities in the form of a test person falling and rolling in several directions, in order to simulate a number of crash scenarios. Together with Accident Confirmation Criteria (ACC ) to cancel false positives, and a decision tree within the IDA, few false alarms are raised while alarms do occur for all incidents simulated in the crash dataset. Overall, the trained OC-SVM classified normal driving with a precision of 99.39%, and correctly identified all 20 simulated accidents; thus, the OC-SVM obtained an estimated F1-score of 99.69%. A design for a smartphone application to enable this automatic alarm is proposed in the form of a flow chart. Investigations of required functionality support the claim that a smartphone is capable of running the IDA in real time and with low battery consumption. With the limited amount of normal driving data, and only simulated crash data, further investigations must be performed in order to ensure no overfitting has taken place. The next step in the development would be for a test group consisting of regular ATV drivers to evaluate the performance of the IDA in real life situations. It is the authors’ opinion that with additional trials and tweaking of parameters, a well-functioning smartphone application could be released to the public and potentially serve as a life saver, perhaps even for other vehicles, in cases where the driver is otherwise helpless.
Physical forcing of distributions of bryozoan cyphonautes larvae in a coastal embayment

In shallow rocky subtidal ecosystems in the western North Atlantic, outbreaks of the nonindigenous encrusting epiphytic bryozoan Membranipora membranacea cause defoliation of laminarian algae, facilitating a phase transition from native kelp beds to meadows of invasive algae. We quantified spatial (m [depth] to km [sites]) and temporal (hourly to monthly) patterns in the abundance of larvae of M. membranacea, and a morphologically similar native species, Electra pilosa, in relation to physical structure (temperature, salinity, density) of the water column in St. Margarets Bay, Nova Scotia, Canada, on 8 dates from September to November 2007. During the study period, the water column ranged from strongly stratified to well mixed, and cross-shore movements of water masses (wind-driven upwelling and downwelling) were indicated by shoaling of the isoclines. When a strong pycnocline was located between the 2 sampled depths (4 and 12 m), larvae of both species were more abundant in the shallower, warmer, fresher layer. The linear relationship between strength of stratification and the relative abundance of larvae between depths was significant over 2 temporal (hourly, weekly) and 1 spatial (km) scale examined for M. membranacea, but not for E. pilosa. Highest abundance of larvae of both species in the warm fresh surface layer suggests onshore transport during wind-driven downwelling events. Dissimilar patterns in size-frequency distributions between the indigenous and nonindigenous bryozoan larvae suggest that species-specific characteristics of larvae of M. membranacea may be a contributing factor to its success as an invader in the western North Atlantic.
Bayesian Networks: Performance Analysis of Loopy Belief Propagation

Loopy belief propagation (LBP) is a probability inference algorithm on Graphical Models. It has been successfully applied in low-density parity-check codes, turbo codes, computer vision problems such as stereo matching, image segmentation and image impainting. Belief propagation was first proposed by Judea Pearl in 1982 for tree-structured graphs, and was extended to poly-trees in 1983, and later applied to general graphs with empirical success. Since LBP ignores the loopy structure of graphs and blindly propagates messages, many researchers have focused in analyzing its performance of convergence and accuracy, and presented variations of message passing algorithm. In this thesis, we focus on the performance analysis of LBP with respect to error bound and convergence. We present novel results that show the relationship between the performance of LBP and the strength of potential functions as well as topology structure of graphical models. Specifically, we first present lower-bound and upper-bound on multiplicative message errors. Then we present uniform and non-uniform distance bound on beliefs, which can improve an existing accuracy bound between beliefs and true marginals. Thereafter, we present our non-uniform sufficient convergence condition for LBP, which is shown to be better than existing conditions. We also show our error bound is related with the rate of convergence of LBP. Furthermore, we analyze fixed points of completely uniform binary graph, and present tight distance bound between beliefs. Finally, we implement LBP algorithm for an image segmentation application, and show how the segmentation performance is affected by some parameters in potential functions.