Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Genetic Diversity of the Gyeongju Donggyeong Dog in Korea

ABSTRACT The present study was conducted to analyze the genetic characteristics of the Donggyeong dog and establish parentage conservation systems for it by using 10 microsatellite markers recommended by the International Society for Animal Genetics (ISAG). A total of 369 dogs from 12 dog breeds including the Donggyeong dog were genotyped using 10 microsatellite loci. The number of alleles per locus varied from 5 to 10 with a mean value of 7.6 in the Donggyeong dog. The observed heterozygosity and expected heterozygosity ranged from 0.4706 to 0.9020 (mean 0.7657) and from 0.4303 to 0.8394 (mean 0.7266), respectively. The total exclusion probability of 10 microsatellite loci was 0.99955. Of the 10 microsatellite markers, the AHT121, AHTh260 and CXX279 markers had relatively high PIC values (≥0.7). This study found that there were specific alleles, 116 allele at AHT121 in the Donggyeong dog when compared with other dog breeds. Also, the results showed two (Korean native dogs and the foreign dog breeds) distinct clusters. The closest distance (0.1184) was observed between the Donggyeong dog and Jindo dog, and the longest distance (0.3435) was observed between the Donggyeong dog and Bulgae. The Korean native dog breeds have comparatively near genetic distances between each other.
AUTOMATIC VIDEO ANNOTATION BY CLASSIFICATION

Automatic video annotation is a technique to provide semantic video retrieval. The proposed method of automatic video annotation consists of two main steps i.e.; feature extraction and algorithm for annotation. The features are extracted from the images in the database and these feature vectors are then provided as a training set to the classifier algorithm. The classifier algorithm is a combination of graph based algorithm and K nearest Neighbor algorithm. In graph based algorithm, the computed feature vectors of each image in the database are taken as nodes of the graph and the neighbourhood information of each node is used for classification. In KNN, the classification is using majority vote among the K objects. When a query video is provided by the user, the key frame is extracted and, pre-processing and feature extraction is performed on this key frame of the video. The extracted feature is then provided to the trained algorithm for annotation. The proposed system has a precision rate of 81.14%. The system also compares the results of different combinations of features and descriptors. An automatic annotation system can be used for effective search and retrieval of news videos, event detection, video summarization and highlight generation, video content analysis, etc.
Underground WMSN distributed video coding based on HVS

DVC is a suitable code scheme to overcome the limited memory capacity and low power consumption of video sensor nodes in Wireless Multimedia Sensor Network (WMSN). To further improve the coding performance, we propose a distributed video coding (DVC) scheme with the human visual system (HVS) which seldom senses any changes below the just noticeable distortion (JND) threshold around a pixel due to their underlying temporal/spatial sensitivity and masking properties. On this view, it is unnecessary to spend parity bits on correcting the un-noticeable signal differences between the original frame and side information. Experimental results show that the proposed scheme can significantly improve the WZ coding efficiency in terms of bit rate having subjective quality performance guaranteed.
Fraud Classification Using Principal Component Analysis of Ridits

This article introduces to the statistical and insurance literature a mathematical technique for an a priori classification of objects when no training sample exists for which the exact correct group membership is known. The article also provides an example of the empirical application of the methodology to fraud detection for bodily injury claims in automobile insurance. With this technique, principal component analysis of RIDIT scores (PRIDIT), an insurance fraud detector can reduce uncertainty and increase the chances of targeting the appropriate claims so that an organization will be more likely to allocate investigative resources efficiently to uncover insurance fraud. In addition, other (exogenous) empirical models can be validated relative to the PRIDIT-derived weights for optimal ranking of fraud/nonfraud claims and/or profiling. The technique at once gives measures of the individual fraud indicator variables' worth and a measure of individual claim file suspicion level for the entire claim file that can be used to cogently direct further fraud investigation resources. Moreover, the technique does so at a lower cost than utilizing human insurance investigators, or insurance adjusters, but with similar outcomes. More generally, this technique is applicable to other commonly encountered managerial settings in which a large number of assignment decisions are made subjectively based on "clues," which may change dramatically over time. This article explores the application of these techniques to injury insurance claims for automobile bodily injury in detail.
In Search of a Good Novel Examining Results Matter

We studied how an enriched public library catalogue is used to access novels. 58 users searched for interesting novels to read in a simulated situation where they had only a vague idea of what they would like to read. Data consist of search logs, pre and post search questionnaires and observations. Results show, that investing effort on examining results improves search success, i.e. finding interesting novels, whereas effort in querying has no bearing on it. In designing systems for fiction retrieval, enriching result presentation with detailed book information would benefit users.
Simplified controller for three wheeled omni directional mobile robot

This paper presents the work on developing a controller for the three wheeled omni-directional mobile robot for the operation on a flat terrain. Central to a robot base are omni-directional wheels. In addition to providing traction normal to the rotor axis like an ordinary wheel, they are capable of sliding parallel to the rotor axis without much friction. We have designed and implemented a robot utilizing three omni-directional wheels mounted 120° apart. Trajectory of the robot is specified as the time variation of the position coordinates and the orientation of the robot with respect to a fixed frame. The trajectory is dictated by the speeds of the three omni-directional wheels. Been a holonomic robot, the designed robot can achieve any continuous trajectory. The trajectory is planned on the fixed world frame. Then, it is transformed to the time-varying robot body frame. The velocities of the wheels are computed with respect to the body frame. A PID controller is utilized for the control of each parameter. Consequently, several PID controllers are employed for trajectory control. The MATLAB® SIMULINK® platform is used to develop the kinetic model of the system. The designed robot has been implemented in hardware.
A grid of MARCS model atmospheres for late-type stars. I. Methods and general properties

Context. In analyses of stellar spectra and colours, and for the analysis of integrated light from galaxies, a homogeneous grid of model atmospheres of late-type stars and corresponding flux spectra is needed. Aims. We construct an extensive grid of spherically-symmetric models (supplemented with plane-parallel ones for the highest surface gravities), built on up-to-date atomic and molecular data, and make it available for public use. Methods. The most recent version of the MARCS program is used. Results. We present a grid of about 104 model atmospheres for stars with 2500K <= T-eff <= 8000 K, -1 <= log g = log (GM/R-2) <= 5 (cgs) with various masses and radii, -5 <= [Me/H] <= + 1, with [alpha/Fe] = 0.0 and 0.4 and different choices of C and N abundances. This includes "CN-cycled" models with C/N=4.07 (solar), 1.5 and 0.5, C/O ranging from 0.09 to (normally) 5.0 to also represent stars of spectral types R, S and N, and with 1.0 <= xi(t) = 5km s(-1). We also list thermodynamic quantities (T, P-g, P-e, rho, partial pressures of molecules, etc.) and provide them on the World Wide Web, as well as calculated fluxes in approximately 108 000 wavelength points. Underlying assumptions in addition to 1D stratification (spherical or plane-parallel) include hydrostatic equilibrium, mixing-length convection and local thermodynamic equilibrium. We discuss a number of general properties of the models, in particular in relation to the effects of changing abundances, of blanketing, and of sphericity. We illustrate positive and negative feedbacks between sphericity and molecular blanketing. We compare the models with those of other available grids and find excellent agreement with planeparallel models of Castelli & Kurucz (if convection is treated consistently) within the overlapping parameter range. Although there are considerable departures from the spherically-symmetric NextGen models, the agreement with more recent PHOENIX models is gratifying. Conclusions. The models of the grid show considerable regularities, but some interesting departures from general patterns occur for the coolest models due to the molecular opacities. We have tested a number of approximate "rules of thumb" concerning effects of blanketing and sphericity and often found them to be astonishingly accurate. Some interesting new phenomena have been discovered and explored, such as the intricate coupling between blanketing and sphericity, and the strong effects of carbon enhancement on metal-poor models. We give further details of line absorption data for molecules, as well as details of models and comparisons with observations in subsequent papers.
Towards Latency-Optimal Distributed Relay Selection

Latency-sensitive multiparty applications involve intensive communication between multiple participating nodes. Relays are usually adopted for matchmaking end hosts, filtering unwanted traffics, bypassing routing outages and so on. Speeding up the relay-communication becomes increasingly important to improve the QoE of clients. Currently, no rigorous guarantees have been made for the latency-optimal relay communication. We propose a novel framework to truthfully represent the relay communication in the latency space. Real-world data sets show that nearly 90% of node triples obey the average triangle inequality, while our new model allows for the asymmetry and triangle inequality violations to occur. We propose the general triangle to rigorously locate a candidate relay closer to multiple nodes, with which we systematically analyze the feasibility of finding an optimal relay node for arbitrarily sized groups. Our results show that distributed greedy methods are able to locate optimal relays with modest communication overhead and small search hops.
Experimental characterisation of the impact of IP-based distribution network QoS on the QoE of DVB-H mobile broadcast video services

DVB-H is an international broadcasting standard, which offers reliable high data reception to mobile handheld devices. Its main enhancements to conventional DVB-T systems include the addition of time-slicing and an extra stage of error correction called MPE-FEC at the link layer. Time-slicing means that each service will be sent in bursts while MPE-FEC increases the robustness of reception for mobile terminals. DVB-H is mostly used to offer real-time mobile video services, which have very stringent demands in terms of QoS. When deploying such a DVBH mobile television service, the broadcast operator has to feed all the DVB-H antennas through its primary distribution network. This is typically done by using a satellite uplink but in more dense arias existing fixed network infrastructure may be used. In this paper we present the effects of packet loss, introduced in an IP based distribution network, on the Quality of Experience (QoE), the quality of the mobile video service as perceived by the end user measured through PSNR, the most commonly used objective video quality metric. It is shown that, although MPE-FEC is introduced for better reception between antenna and receiver, that its use also has a major impact on the effects of packet loss that occurs in the distribution network. In order to reduce the impact of packet loss in the distribution link, additional error correction may be introduced in the distribution link. This paper also evaluates the benefit of such an additional error correction technique with respect to the QoE of the DVB-H service, with a given MPE-FEC rate.
Apoptosis induced in vivo by new type gosling viral enteritis virus

In this study, apoptosis was induced by new type gosling viral enteritis virus (NGVEV) in experimentally infected goslings is reported in detail for the first time. After 3-day-old goslings were orally inoculated with a NGVEV-CN strain suspension, the time course of NGVEV effects on apoptotic morphological changes of the internal tissues was evaluated. These changes were observed by histological analysis with light microscopy and ultrastructural analysis with transmission electron microscopy. DNA fragmentation was assessed with a terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL) assay and DNA ladder analysis. A series of characteristic apoptotic morphological changes including chromatin condensation and margination, cytoplasmic shrinkage, plasma membrane blebbing, and formation of apoptotic bodies were noted. Apoptosis was readily observed in the lymphoid and gastrointestinal organs, and sporadically occurred in other organs after 3 days post-infection (PI). The presence and quantity of TUNEL-positive cells increased with infection time until 9 days PI. DNA extracted from the NGVEV-infected gosling cells displayed characteristic 180~200 bp ladders. Apoptotic cells were ubiquitously distributed, especially among lymphocytes, macrophages, monocytes, and epithelial and intestinal cells. Necrosis was subsequently detected during the late NGVEV-infection phase, which was characterized by cell swelling, plasma membrane collapse, and rapidly lysis. Our results suggested that apoptosis may play an important role in the pathogenesis of NGVE disease.
Bacterial Outer Membrane Vesicles and Vaccine Applications

Vaccines based on outer membrane vesicles (OMV) were developed more than 20 years ago against Neisseria meningitidis serogroup B. These nano-sized structures exhibit remarkable potential for immunomodulation of immune responses and delivery of meningococcal antigens or unrelated antigens incorporated into the vesicle structure. This paper reviews different applications in OMV Research and Development (R&D) and provides examples of OMV developed and evaluated at the Finlay Institute in Cuba. A Good Manufacturing Practice (GMP) process was developed at the Finlay Institute to produce OMV from N. meningitidis serogroup B (dOMVB) using detergent extraction. Subsequently, OMV from N. meningitidis, serogroup A (dOMVA), serogroup W (dOMVW), and serogroup X (dOMVX) were obtained using this process. More recently, the extraction process has also been applied effectively for obtaining OMV on a research scale from Vibrio cholerae (dOMVC), Bordetella pertussis (dOMVBP), Mycobacterium smegmatis (dOMVSM), and BCG (dOMVBCG). The immunogenicity of the OMV has been evaluated for specific antibody induction, and together with functional bactericidal and challenge assays in mice has shown their protective potential. dOMVB has been evaluated with non-neisserial antigens, including with a herpes virus type 2 glycoprotein, ovalbumin, and allergens. In conclusion, OMV are proving to be more versatile than first conceived and remain an important technology for development of vaccine candidates.
Identity-Based Authentication Protocol with Paring of Tate on WSN

Identity cryptography is widely used in Security Authentication. This paper proposes a standard identity-based authentication scheme, and also proves the security of the scheme under passive attack. On the basis of ECC and Bilinear Maps, paper implements the authentication protocol in the platform of TinyOs. Finally, paper analyzes its result and proves its feasibility.
Knowledge Economy and the Necessity of Knowledge Management Drago ş CRISTEA

This paper tries to present an existing relation between knowledge economy and knowledge management. We started by emphasizing the main principles of knowledge society and the consequences that determine the movement to a new economical paradigm. Further, we discussed organization competitiveness as being a critical success factor for modern organizations. At last we described the link between knowledge and sustainable competitiveness and presented knowledge management as the perfect “recipe” to obtain it.
An improved feature selection approach based on ReliefF and Mutual Information

A fundamental problem in machine learning is to discriminate a representative set of features on which to construct a classification model for a particular task. This paper presents a feature selection algorithm RF-MI for multiple classes based on ReliefF algorithm and Mutual Information (MI) measure. RF-MI algorithm gets a feature subset by excluding irrelevant and redundant features from original features based on ReliefF algorithm and MI measure respectively, adjusting the feature weight threshold δ and the correlation threshold θ respectively by the classification performance of a specific classifier when using newly generated feature subsets on training data sets, and repeating above procedures until the best classification performance is achieved. Experiments conducted on UCI data sets showed that the presented RF-MI algorithm is better than both ReliefF and GR algorithms in minishing the feature set on the premise that better classification accuracy is maintained. That means classification models based on the feature subset derived from the algorithm can have lower time and space complexity.
Troposphere‐stratosphere dynamical coupling in the southern high latitudes and its linkage to the Amundsen Sea

Extremes in the distribution of Southern Hemisphere stratospheric heat flux are connected simultaneously to anomalous high‐latitude tropospheric weather patterns in reanalysis, consistent with results from the Northern Hemisphere. The dynamical links are revealed using a metric based on extreme stratospheric planetary‐scale wave heat flux events, defined as the 10th and 90th percentiles of the daily high‐latitude wave 1 heat flux distribution at 50 hPa. We show extreme negative (positive) heat flux events are linked to a westward (eastward) shift in the Amundsen Sea Low and anomalous warming (cooling) over the Amundsen Bellingshausen Seas in reanalysis data. Since coupling to the stratosphere via planetary waves has significant impacts on the tropospheric circulation of both hemispheres, it is important to understand which coupled climate models can reproduce this phenomenon. The heat flux metric is used to evaluate troposphere‐stratosphere coupling in models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) and compare their performance across hemispheres. The results show that models with a degraded representation of stratospheric extremes exhibit robust biases in tropospheric sea level pressure variability over the Antarctic Peninsula. Models which fail to capture the extremes in stratospheric heat flux, significantly underestimate the variance of the distribution of mean sea level pressure anomalies over Western Antarctica.
Automatic dominance detection in dyadic conversations

Dominance is referred to the level of influence that a person has in a conversation. Dominance is an important research area in social psychology, but the problem of its automatic estimation is a very recent topic in the contexts of social and wearable computing. In this paper, we focus on the dominance detection of visual cues. We estimate the correlation among observers by categorizing the dominant people in a set of face-to-face conversations. Different dominance indicators from gestural communication are defined, manually annotated, and compared to the observers’ opinion. Moreover, these indicators are automatically extracted from video sequences and learnt by using binary classifiers. Results from the three analyses showed a high correlation and allows the categorization of dominant people in public discussion video sequences.
LetsMT ! Platform for Online Sharing of Training Data and Building User Tailored

The core engine of the LetsMT! platform is Moses, which is adapted for rapid training and updating tasks. The LetsMT! platform hides the complexity of the Moses toolkit. It provides the infrastructure and an easy user interface, where users can upload data, train the SMT, and use it. User does not have to worry about the complexities of installation, compilation, configuration, and data processing.
Real-time data management on wireless sensor network : A survey

In the recent past, search in sensor systems focused on node hardware constraints and very limited energy resources. But nowadays, that new applications need data processing with temporal constraints in their tasks; then one of the new challenges faced by wireless sensor networks (WSNs) is handling real-time storage and querying the data they process. Two main approaches to storage and querying data are generally considered warehousing and distributed. The warehousing approach stores data in a central database and then queries may be performed to it. In a distributed approach, sensor devices are considered as local databases and data are managed locally. The data collected by sensors must represent the current state of the environment; for this reason they are subject to logic and time constraints. Then, this paper identifies the main specifications of real-time data management and presents the available real-time data management solutions for WSNs, in order to discuss them and identify some open issues and provide guidelines for further contributions. & 2011 Elsevier Ltd. All rights reserved.