Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Resolution Operational Coastal Modeling System for the Prediction of Hydrodynamics in Korea Using a Wave-Current Coupled Model

ABSTRACT Lim, H.S. , Chun, I.S. , Kim, C.S. , Park, K.S. , Shim, J.S. and Yoon, J.J, 2013. High-Resolution Operational Coastal Modeling System for the Prediction of Hydrodynamics in Korea Using a Wave-Current Coupled Model We have developed a high-resolution operational coastal modeling system for the coastal waters of Korea using a wave-current coupled model ROMS. The operational oceanographic system consists of operational modeling and monitoring modules. The modeling system comprises atmospheric and hydrodynamic models coupled with three-dimensional hydrodynamics, wave, sediment transport, and water quality model. The hydrodynamic variables are forecasted on a 72-hour basis. The real-time monitoring system is comprised of buoy, HF-radar and geostationary Communication Ocean Meteorological Satellite (COMS). The web-GIS-based coastal information system provides predicted results with real-time monitoring data for dissemination to the public and validation of the predicted results. The operational coastal modeling system uses the ROMS hydrodynamic model coupled with SWAN, a wave model. WRF is used for meteorological modeling of atmospheric forcing, NAO.99jb is a regional tide model used for the tides, and CE-QUAL-ICM is an eutrophication model that is used for simulating the water quality. The atmospheric forcing is derived from the predicted results of the WRF atmospheric model, which has been operated for forecasting in the East China Sea and East Sea. The ocean boundary condition is derived from data-assimilative ROMS, which has been in operation for the Yellow Sea. The hydrodynamic variables were calibrated with tidal surface elevation and verified with current data observed by a bottom-mounted ADCP and AWAC. To validate the predicted results, we use real-time monitoring data from hydrodynamic measurements observed by the operational AWAC and buoy, 1-h averaged surface currents measured by HF-radar, and suspended sediment concentration (SSC) obtained hourly and derived from the Geostationary Ocean Color Imager (GOCI) of COMS. The wave-current coupled ROMS-SWAN modeling system shows enhanced wave-current interaction for the coastal waters of Korea, especially for the prediction of storm surge height and variation of suspended sediment transport. This operational coastal modeling system has been originally developed for the prediction system of coastal waters of Korea and used for the development of an Integrated-Maritime Prediction System (I-MAPS) supporting the operation of the major ports system of Korea such as Incheon and Gunsan on the western coast of Korea, and Yeosu, Masan and Busan on the southern coast of Korea. I-MAPS will also provide monitoring and predicted data to governmental agencies and to the public to support ship navigation and marine activity and to solve problems associated with coastal accidents, such as storm surge, inundation, search and rescue, and oil-spills, as a part of the Korea Operational Oceanographic System (KOOS) which will be in operation by the end of 2013.
Group Authentication Using The Naccache-Stern Public-Key Cryptosystem

A group authentication protocol authenticates pre-defined groups of individuals such that: - No individual is identified - No knowledge of which groups can be successfully authenticated is known to the verifier - No sensitive data is exposed The paper presents a group authentication protocol based on splitting the private keys of the Naccache-Stern public-key cryptosystem in such a way that the Boolean expression defining the authenticable groups is implicit in the split.
Trajectory compression-guided visualization of spatio-temporal AIS vessel density

As an automatic tracking system, the shipboard Automatic Identification System (AIS) has been widely adopted to identify and locate the vessels by electronically exchanging data with other nearby ships. With the development of computer technology, AIS-based visualization of vessel traffic has attracted increasing attention during the past several years. The vessel density visualization can be used as an appropriate computer-aided method to better understand the maritime traffic situation and (abnormal) vessel behaviors. However, it often suffers from high computational cost due to the massive sample size of spatio-temporal AIS trajectories datasets. To handle the problem of high computational cost, the Douglas-Peucker (DP) algorithm was firstly introduced to simplify the massive AIS trajectories. The final Kernel Density Estimation (KDE)-based vessel density visualization was implemented based on the simplified trajectory datasets to shorten the visualization time. To guarantee a good balance between AIS trajectory simplification and visualization performance, numerous experiments haven been conducted to optimally select an appropriate threshold for DP-based AIS trajectory simplification. Comprehensive experiments on realistic spatio-temporal datasets have illustrated that our proposed method can achieve a satisfactory visualization of AIS vessel density while reducing the visualization time.
Quantitative studies of single-cell properties in monkey striate cortex. I. Spatiotemporal organization of receptive fields.

1. The properties of single cells in striate cortex of the rhesus monkey, representing the visual field 2 degrees -5 degrees from the fovea, were examined quantitatively with stationary and moving stimuli. Three distinct classes of cells were identified: S type, CX type, and T type. 2. S-type cells were defined as those oriented cells which to the optimal direction of movement in their receptive fields exhibited one or more spatially separate subfields within each of which a response was obtained to either a light or dark edge, but not to both. Several different types of S-cells were distinguished: a) S1-type cells for which moving edges revealed a single excitatory area within which a response was elicited by either a light or a dark edge but not by both. Most of these cells were unidirectional. b) S2-type cells for which moving edges revealed two spatially separate response areas, one of which was excited by a light edge and the other by a dark edge. Both regions responded to the same direction of movement. c) S3-type cells which had two response areas, one of which was excited by a stimulus moving in one direction (at right angles to the axis of orientation) and the other, of opposite contrast, which responded in the opposite direction, d) S4-type cells which to one direction of movement showed two spatially separate regions sensitive to a light and dark edge and which in the other direction of movement had only one responsive area (either light or dark). e) Cells which had multiple spatially separate subfields (S5-7 types). 3. CX-type cells were defined as those oriented cells which in their receptive fields exhibited no spatial separation for light- and dark-edge responses; they discharged to both edges in the same direction of movement and in the same spatial area. Flashing stimuli elicited both on and off responses throughout the receptive field. CX-type cells were predominantly of two types: those which were selective for direction of stimulus movement and those which were not. 4. A third class of cells (T-type) were those which were excited by only one sign of contrast change and responded in a sustained fashion even when there was no contour within the receptive field. These cells were poorly or not at all oriented; some of them were selective to wavelength. 5. Quantitative comparisons showed the following differences between S-type and CX-type cells: a) S-type cells had smaller receptive fields than CX-type cells but the populations over-lapped considerably. Receptive-field size was smallest in layer 4c. In all other layers S-type cells had the same size fields. CX-type cells, by contrast, tended to have larger fields in layer 5-6 than 2-3. b) The spatial separation between light and dark response areas was the best criterion for distinguishing S-type and CX-type cells. The distribution of this measure disclosed two populations of cells with relatively limited overlap. c) In layers 2 and 3, both S-type and CX-type cells had low spontaneous activity.
3D growing deformable B-surface model for object detection

A new method, called 3D growing deformable B-surface model, is proposed for object detection which works in 3D space directly. First, the coarse boundary of the subject is extracted. The 3D external force field of the subject is generated based on this coarse boundary using modified GVF (gradient vector flow). After the initialization of a surface patch, growing B-surface model starts to deform it to locate the boundary of the object. Next, this surface patch is anchored to the surface of the subject and a new surface patch grows up based it. This process is repeated until a closed surface of the subject is obtained. 3D growing deformable B-surface model overcomes the difficulty that comes from analyzing 3D volume image slice by slice. And the computation load of B-surface is reduced since the internal force is not necessary in every iteration deformation step. Next, the geometric information on every surface point can be calculated easily. And it has the ability Io achieve high compression ratio (the ratio of data to parameters) by presenting the whole surface with only a relatively small number of control points. Growing B-surface model simplifies the initialization step of the surface model.
Making Sense of Corporate Social Responsibility and Work

Employees can be a driving force behind organizational corporate social responsibility (CSR) efforts, yet the vast majority of literature has focused on firm-level understanding and implementation of CSR. Recent literature that explores the relationship between employees and CSR has not investigated how employees conceive of their role in CSR. We propose that in order to understand the factors that affect employee engagement in CSR, we must first understand how employees conceptualize the phenomenon of CSR and how that conceptualisation fits into their work. Our exploratory, inductive study interviews two cohorts of employees, one in a not for profit and the other in a corporate organization, revealing stark contrasts in how the different cohorts conceptualize and engage in CSR, particularly with regards to how CSR contributes to meaningfulness at work. Implications for organizations are discussed.
A Framework for Automated Object Oriented Analysis of Natural Language Software Specifications

Abstract The currently available approaches for processing natural language (NL) software requirements specifications are semi-automatic and require user intervention. Moreover, these approaches result in less accurate and imprecise object oriented software models. Recent research in the area attributes the informal nature of natural languages for less accurate analysis of software requirements. On the basis of this axiom, we have identified that direct translation of a natural language to a formal language is the actual problem. In this paper, we propose that instead of direct translation of a natural language to a formal language, first, we will transform the natural language text to a semi-formal language that is not only simple and easy to translate to a formal language but also provides with higher accuracy. We have incorporated Structured Business Vocabulary and Rules (SBVR) language as the semi-formal medium in natural language to object-oriented models. The presented approach automatically generates the object-oriented software models from natural language software specifications using SBVR as a pivot representation.
The HPV16 E6 Oncoprotein Causes Prolonged Receptor Protein Tyrosine Kinase Signaling and Enhances Internalization of Phosphorylated Receptor Species

The high-risk human papillomavirus (HPV) E6 proteins are consistently expressed in HPV-associated lesions and cancers. HPV16 E6 sustains the activity of the mTORC1 and mTORC2 signaling cascades under conditions of growth factor deprivation. Here we report that HPV16 E6 activated mTORC1 by enhanced signaling through receptor protein tyrosine kinases, including epidermal growth factor receptor and insulin receptor and insulin-like growth factor receptors. This is evidenced by sustained signaling through these receptors for several hours after growth factor withdrawal. HPV16 E6 increased the internalization of activated receptor species, and the signaling adaptor protein GRB2 was shown to be critical for HPV16 E6 mediated enhanced EGFR internalization and mTORC1 activation. As a consequence of receptor protein kinase mediated mTORC1 activation, HPV16 E6 expression increased cellular migration of primary human epithelial cells. This study identifies a previously unappreciated mechanism by which HPV E6 proteins perturb host-signaling pathways presumably to sustain protein synthesis during the viral life cycle that may also contribute to cellular transforming activities of high-risk HPV E6 proteins.
Improved Weighted Matching for Speaker Recognition

Matching algorithms have significant importance in speaker recognition. Feature vectors of the unknown utterance are compared to feature vectors of the modeled speakers as a last step in speaker recognition. A similarity score is found for every model in the speaker database. Depending on the type of speaker recognition, these scores are used to determine the author of unknown speech samples. For speaker verification, similarity score is tested against a predefined threshold and either acceptance or rejection result is obtained. In the case of speaker identification, the result depends on whether the identification is open set or closed set. In closed set identification, the model that yields the best similarity score is accepted. In open set identification, the best score is tested against a threshold, so there is one more possible output satisfying the condition that the speaker is not one of the registered speakers in existing database. This paper focuses on closed set speaker identification using a modified version of a well known matching algorithm. The results of new matching algorithm indicated better performance on YOHO international speaker recognition database. Keywords— Automatic Speaker Recognition, Voice Recognition, Pattern Recognition, Digital Audio Signal Processing.
Techniques of Privacy Preservation in Data Publishing

Privacy-preservation in data mining is used to safeguard susceptible information from unsanctioned disclosure. Due to the increasing ability to store personal data about users in privacy is an important issue involved data publishing. The different techniques such as bucketization, generalization have been proposed to perform privacy- preservation in data publishing. Recent work has shown that the technique generalization does not support for high- dimensional data. And also, bucketization cannot prevent membership disclosure and does not apply for data that do not have a clear separation between quasi-identifying attributes and sensitive attributes. The anonymization procedure, such as generalization along with bucketization, is actually intended regarding privacy conservation in microdata creating. In this paper, we presented different techniques of privacy preservation in data publishing. Here, we also study some application areas of privacy preservation in data publishing.
Hamstring muscle tightness. Reliability of an active-knee-extension test.

The purpose of this study was to examine intratester reliability of a test designed to measure tightness in the hamstring muscles. The test measures the angle of knee flexion with a pendulum goniometer after active knee extension with the hip stabilized at 90 degrees flexion. The angle of knee flexion represents hamstring tightness. After an instruction session for the subjects, the hamstring muscle tightness of both extremities of 15 men was measured during test and retest sessions. The reliability coefficients for test and retest measurements were . 99 for the left extremity and . 99 for the right extremity. High reliability resulted from strict body stabilization methods, a well-defined end point of motion, and accurate instrument placement. If conducted properly, the test should provide therapists with an objective and reliable tool for measuring hamstring muscle tightness.
Advance care planning in patients with incurable cancer: study protocol for a randomised controlled trial

Introduction There is limited evidence documenting the effectiveness of Advance Care Planning (ACP) in cancer care. The present randomised trial is designed to evaluate whether the administration of formal ACP improves compliance with patients' end-of-life (EOL) wishes and patient and family satisfaction with care. Methods and analysis A randomised control trial in eight oncology centres across New South Wales and Victoria, Australia, is designed to assess the efficacy of a formal ACP intervention for patients with cancer. Patients with incurable cancer and an expected survival of 3–12 months, plus a nominated family member or friend will be randomised to receive either standard care or standard care plus a formal ACP intervention. The project sample size is 210 patient–family/friend dyads. The primary outcome measure is family/friend-reported: (1) discussion with the patient about their EOL wishes and (2) perception that the patient's EOL wishes were met. Secondary outcome measures include: documentation of and compliance with patient preferences for medical intervention at the EOL; the family/friend's perception of the quality of the patient's EOL care; the impact of death on surviving family; patient–family and patient–healthcare provider communication about EOL care; patient and family/friend satisfaction with care; quality of life of patient and family/friend subsequent to trial entry, the patient's strength of preferences for quality of life and length of life; the costs of care subsequent to trial entry and place of death. Ethics and dissemination Ethical approval was received from the Sydney Local Health District (RPA Zone) Human Research Ethical Committee, Australia (Protocol number X13-0064). Study results will be submitted for publication in peer-reviewed journals and presented at national and international conferences. Trial registration number Pre-results; ACTRN12613001288718.
Transformation of Legacy Software into Client/Server Applications through Pattern-Based Rearchitecturing

In this article, we address the problem of modularizing legacy applications with monolithic structure, primarily focusing on business software written in an object-oriented programming language. We introduce the TransFormr toolkit that guides the developer through the entire incremental transformation process. It is the goal of the transformation to separate the original software into several independent replaceable components to support the migration of legacy code to new hardware or to integrate legacy components into modern enterprise applications. We show the effectiveness of our approach by demonstrating a pattern-based transformation of classes in a case study.
Enhancement of spontaneous emission from CdSe quantum dots by 3-D silica photonic crystal

We have demonstrated that the luminescence properties of CdSe nanoparticles can be manipulated by self-assembled silica photonic crystal. When the emitting wavelength of nanoparticles matches the stop band of photonic crystal, the photoluminescence of the CdSe nanoparticles can be greatly enhanced by up to 5 times, by changing the collection angle of photoluminescence measurements, the photoluminescence intensity of CdSe embedded in photonic crystal can also be controlled.
Restricted Boltzmann Machine supervectors for speaker recognition

The use of Restricted Boltzmann Machines (RBM) is proposed in this paper as a non-linear transformation of GMM supervectors for speaker recognition. It will be shown that the RBM transformation will increase the discrimination power of raw GMM supervectors for speaker recognition. The experimental results on the core test condition of the NIST SRE 2006 corpus show that the proposed RBM supervectors will achieve a comparable performance to i-vectors. Furthermore, the combination of RBM supevectors and i-vectors in the score level improves the performance of the i-vector approach by more than 10% in terms of EER.
Control relevant identification for controlling a continuous-stream bioreactor with unknown dynamics

This paper presents an iterative procedure for control relevant identification for closed-loop system with unknown dynamics. At each step of iteration, an optimal controller is designed for the worst case model that obtained from identification task. The proposed framework uses simple model for identification task and an optimal Hinfin controller will be designed. This method is also applied on a continuous stream bioreactor and the result was quite satisfactory.
Meta-learning and Model Selection in Multi-objective Evolutionary Algorithms

Most existing surrogate based evolutionary algorithms deal with only one model selected by the authors and different models are not considered. In this paper we propose a framework which enables automatic selection of types of surrogate models, and evaluate the effect of the type of selection on the overall performance of the resulting evolutionary algorithm. Two different types of model selection are tested and compared both in pre-selection scenario and in local search scenario.
Interpersonal trust measurements from social interactions in Facebook

©COPYRIGHT by Xiaoming Li 2014 All Rights Reserved iii ACKNOWLEDGEMENTS Please allow me to express my sincere gratitude to Prof. Qing Yang, my mentor and friend, for his continuous support on my study and research, for his great encouragement when I want to give up, for his unselfish help on both my study and personal life, for his tremendous guidance when I felt confused and helpless. Without him, it would not have been possible for me to study in U.S. and keep doing research. He has been and will continue to be a role model for me in the future. I am deeply indebted to Qing for his tremendous love, support and encouragement. This thesis is dedicated to my past two years.
Single color image super-resolution using quaternion-based sparse representation

In current color image super-resolution methods, superresolution based on sparse representation achieves state-of-the-art performance. However, the exploited sparse representation models deal with the color images as independent channel planes. Consequently, these approaches process the color pixels as scalar quantity, lacking of accuracy in describing inter-relationship among color channels. In this paper, we propose a quaternion-based online dictionary learning method and solve color image super-resolution by employing a quaternion-based sparse representation model. This sparse representation model implements color image superresolution in a kind of vectorial reconstruction, effectively accounting for both luminance and chrominance geometry in images. The proposed color image super-resolution method can better describe the inter-channel changes. In the case that changing lighting conditions affect color more than the luminance perception, it can obtain superior performance comparing to the methods based on monochromatic sparse models with 1dB improvement.