Miracle-dz/UniFAR-FTUs huggingface dataset:
Onsager reciprocity principle for kinetic models and kinetic schemes

Boltzmann equation requires some alternative simpler kinetic model like BGK to replace the collision term. Such a kinetic model which replaces the Boltzmann collision integral should preserve the basic properties and characteristics of the Boltzmann equation and comply with the requirements of non equilibrium thermodynamics. Most of the research in development of kinetic theory based methods have focused more on entropy conditions, stability and ignored the crucial aspect of non equilibrium thermodynamics. The paper presents a new kinetic model formulated based on the principles of non equilibrium thermodynamics. The new kinetic model yields correct transport coefficients and satisfies Onsager's reciprocity relationship. The present work also describes a novel kinetic particle method and gas kinetic scheme based on this linkage of non-equilibrium thermodynamics and kinetic theory. The work also presents derivation of kinetic theory based wall boundary condition which complies with the principles of non-equilibrium thermodynamics, and can simulate both continuum and rarefied slip flow in order to avoid extremely costly multi-scale simulation.
Collaborative Filtering RecommendationAlgorithm Based on Trust Model

This paper proposes a collaborative filtering recommendation algorithm based on trust mechanism.Direct trust is based on common rating data and indirect trust is based on the predict data.By considering the social network between Person’s trust assessment method,the similarity between the users is more accurate,so that better neighbors for a target user and the better recommendation result can be gained.Experimental result indicates that based on the trust model’s recommendation system,can consistently achieve better prediction accuracy and improves system’s recommendation quality effectively.
A Neutron Star Binary Merger Model for GW170817/GRB 170817A/SSS17a

The merging neutron star gravitational-wave event GW170817 has been observed throughout the entire electromagnetic spectrum from radio waves to γ-rays. The resulting energetics, variability, and light curves are shown to be consistent with GW170817 originating from the merger of two neutron stars, in all likelihood followed by the prompt gravitational collapse of the massive remnant. The available γ-ray, X-ray, and radio data provide a clear probe for the nature of the relativistic ejecta and the non-thermal processes occurring within, while the ultraviolet, optical, and infrared emission are shown to probe material torn during the merger and subsequently heated by the decay of freshly synthesized r-process material. The simplest hypothesis, that the non-thermal emission is due to a low-luminosity short γ-ray burst (sGRB), seems to agree with the present data. While low-luminosity sGRBs might be common, we show here that the collective prompt and multi-wavelength observations are also consistent with a typical, powerful sGRB seen off-axis. Detailed follow-up observations are thus essential before we can place stringent constraints on the nature of the relativistic ejecta in GW170817.
A self-feedback synthesis method for spam filtering

A self-feedback based spam filtering method has been developed.In the construction of the log analysis module,the filtering system was implemented in a way that permited self-feedback when updating filtering rules.Self-analysis,self-decision,and self-optimization were all incorporated.In this way minimal human intervention was required.In traditional massive information filtering,human involvement was very high,leaving filtering accuracy and efficiency highly dependent on the skills of the human operator.Experiments proved that this method overcomes these shortcomings,greatly enhancing the speed and accuracy of information filtering and effectively automating information filtering.
To Think In Language Learning And Education

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The Effect of Fin Array Height and Spacing on Heat Transfer Performance during Pool Boiling from Extended Surfaces

The use of heat sinks is a promising approach to extend the range of immersion cooling in dielectric fluids to higher heat fluxes for thermal management of next-generation electronics. However, the effects of extended surface area enhancement on the heat transfer performance under pool boiling conditions are not well understood, even in the simple case of straight fins. Further investigation of the heat-flux-dependent variation of boiling modes that can manifest along the fin height is required. Although approaches exist to predict the extended surface pool boiling heat transfer coefficient, they have been developed from single fins. As a result, when applied to fin arrays, they are rarely accurate across the full operating range up to the critical heat flux, particularly if height or spacing varies drastically. To better understand the effects of fin arrays on heat transfer, pool boiling experiments are performed using copper fins in water, varying fin height and spacing. These variations span a range from much larger to less than half of the scale of the capillary length scale, Lb. The pool boiling data, complemented with high-speed visualization of the boiling regimes and bubble dynamics, strongly support a hypothesis that Lb is the key length scale. Heat transfer from fin array heat sinks with heights and spacings above Lb are shown to be accurately predicted using existing fin analysis approaches from the literature. However, spacings smaller than Lb affect the nucleate boiling superheat while heights shorter than Lb are unable to support multiple boiling regimes along the fin sidewall, both leading to disagreement between the experiments and predictions. These aspects, coupled with observation of vapor entrapment between closely spaced fins, indicate that new predictive methods must be developed. The valuable insights offered into the effects of fin array height and spacing on pool boiling provide a pathway toward heat sink design optimization for immersion cooling applications.
Design de wearables para uso esportivo : sensores inerciais aplicados à natação em piscinas

Resumo: Este trabalho refere-se ao projeto e construção de wearables de baixo custo com foco na natação em piscinas, utilizando sensores inerciais para captura de dados com fins científicos. De forma ampla, os resultados deste projeto podem estender-se para diversas modalidades esportivas, com aplicações acadêmicas ou de ensino, tanto para atletas de alto rendimento como atletas amadores. Dispositivos desta natureza facilitam muito a coleta de dados “na borda da piscina”, que atualmente são obtidos a muito custo. Estes dados são variáveis importantes na compreensão do rendimento do atleta, pois provavelmente se correlacionam com indicadores fisiológicos e biomecânicos. O esforço no sentido de desenvolver tais dispositivos tem se intensificado desde 2010, em função da diminuição do custo de componentes eletrônicos utilizados em tais dispositivos, e do desenvolvimento da tecnologia destes componentes.
A robust HOG-based descriptor for pattern recognition

The Histogram of Oriented Gradients (HOG) is a popular feature descriptor used in computer vision and image processing. The technique counts occurrences of gradient orientation in localized portions of an image. The descriptor is sensible to the presence in images of noise, nonuniform illumination, and low contrast. In this work, we propose a robust HOG-based descriptor using the local energy model and phase congruency approach. Computer simulation results are presented for recognition of objects in images affected by additive noise, nonuniform illumination, and geometric distortions using the proposed and conventional HOG descriptors.
2016 IEEE GRSS Data Fusion Contest: Very high temporal resolution from space Technical Committees

The 2016 Data Fusion Contest, organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (GRSS), aims at providing a challenging image analysis opportunity including multitemporal, multiresolution, and multisensor fusion. The 2016 contest involves two data modalities acquired over the city of Vancouver, Canada (49? 15? N 123? 6? W): a very high-resolution multitemporal sequence and an ultrahigh definition (UHD) video from space acquired from the International Space Station (ISS). The data were acquired and provided by Deimos Imaging and UrtheCast (Figure 1).
Discriminative and articulatory feature-based pronunciation models for conversational speech recognition

Conversational (or spontaneous) speech is characterized by a great deal of pronunciation variability caused by various artifacts of natural speech (like the speaking style, speaking rate and surrounding words). This pronunciation variability is one of the main factors resulting in the poor performance of automatic speech recognition (ASR) systems on conversational speech. The main goal of this dissertation is to combine linguistic insights from speech production models and discriminative training techniques to tackle such variability. Also, for this purpose, we introduce two new techniques which are of potentially more general interest. We build on two popular tools that are used in ASR: dynamic Bayesian networks (DBNs) and weighted finite state transducers (WFSTs). First, we propose a discriminative training approach that allows selective training of WFST factors within an ASR system based on WFSTs. Second, we propose a technique to transform DBN models into equivalent WFST cascades that can be further discriminatively trained using our first approach. We employ the above approaches for building improved pronunciation models. We start with a prior DBN model of pronunciation that relates the movements of various articulators of a speaker to the sounds produced. We transform this
Contact Resistance and Leakage Current of GaN Devices with Annealed Ti/Al/Mo/Au Ohmic Contacts

In recent years, the on-resistance, power loss and cell density of Si power devices have not exhibited significant improvements, and performance is approaching the material limits. GaN is considered an attractive material for future high-power applications because of the wide band-gap, large breakdown field, high electron mobility, high switching speed and low on-resistance. Here we report on the Ohmic contact resistance and reversebias characteristics of AlGaN/GaN Schottky barrier diodes with and without annealing. Annealing in oxygen at 500℃ resulted in an increase in the breakdown voltage from 641 to 1,172 V for devices with an anode-cathode separation of 20 μm. However, these annealing conditions also resulted in an increase in the contact resistance of 0.183 Ω-mm, which is attributed to oxidation of the metal contacts. Auger electron spectroscopy revealed diffusion of oxygen and Au into the AlGaN and GaN layers following annealing. The improved reverse-bias characteristics following annealing in oxygen are attributed to passivation of dangling bonds and plasma damage due to interactions between oxygen and GaN/AlGaN. Thermal annealing is therefore useful during the fabrication of high-voltage GaN devices, but the effects on the Ohmic contact resistance should be considered.
Effects of dietary organic and inorganic zinc and copper supplements on performance, footpad dermatitis, carcass characteristics, and blood profile of broiler chickens

The aims of this study was to determine the effect of organic and inorganic Zn and Cu supplements on performance, footpad dermatitis (FPD), carcass characteristics and blood profile in broiler chickens. A total of 336 one-day-old Ross 308 broiler chicks were distributed into 24 floor pen and reared for 42 days. A basal mineral premix (without Zn and Cu) was supplemented with organic or inorganic Zn and Cu to meet 100% (i.e., 110 and 16 mg/kg of the mineral premix, respectively) or 50% (i.e., 55 and 8 mg/kg of the mineral premix, respectively) of the recommended levels. Six dietary trace mineral premix were formed with inclusion of 1) inorganic Zn and Cu at the level 100%, 2) organic Zn and Cu at the level 100%, 3) inorganic Zn and Cu at the level 50%, 4) organic Zn and Cu at the level 50%, 5) organic Zn at the level 50% and inorganic Cu at the level 100%, and 6) inorganic Zn at the level 100% and organic Cu at the level 50%. Results indicated that organic Zn and Cu supplementation improved (P< 0.05) body weight gain and feed conversion ratio than inorganic form. However, the incidence and severity of FPD were significantly lower in broilers received only organic Zn and Cu than those of birds under inorganic Zn and Cu at the level 50%. Broilers fed lower level of inorganic Zn and Cu supplement showed the lowest breast yield compared to the other treatments. In contrast to the alkaline phosphatase enzyme, serum cholesterol concentration decreased (P< 0.05) in broiler chickens received organic Zn when compared to the supplementing of inorganic Zn and Cu at the level 50%. The results showed that organic Zn and Cu, as a proper alternative to inorganic forms, are useful to improve performance and health of broilers.
MEDIA & COMMUNICATION STUDIES | RESEARCH ARTICLE Pre-trip tourism information search by smartphones and use of alternative information channels: A conceptual model

4 Abstract: This study developed a comprehensive model of how smartphone users search for pre-trip tourism information. Important dimensions and relationships in tourism information search (TIS) behavior were studied in 21 subjects. The data collection process included semi-structured in-depth interviewing data and field observation data. The analysis revealed 10 activities characteristic of TIS behavior: internal searches, mobile searches, saving information in the smartphones, preliminary collaborative TIS, barriers to TIS, bringing mobile search to an end, summarizing information, PC Internet search, advanced collaborative TIS, and searches via editorial communications. Such data collection was not performed in isolation. Further, 20 propositions have been developed for future testing. The results suggest that pre-trip TIS appears to consist in a diversity of search patterns with the usage of multiple information sources; in addition, it is no longer individual but collaborative behavior in the context of Web 2.0. Finally, the theoretical and practical implications of the research work are discussed, and directions for future work are suggested.
Design and Experiments of Clamp Type Force-feedback Tele-micromanipulation System

A force feedback tele-micromanipulation system is developed,which consists of a clamp master-hand, a micro- gripper driven by piezoelectric ceramic, and force-feedback control module of master-slave pattern. The system makes operators obtain the telepresence of grasping force and avoid damnifying the crisp objects in tele-micromanipulation. Design and control method of the clamp master-hand, slave-hand and force feedback are introduced in detail, the experimental platform is set up, and the tele-micromanipulation experiments are carried out. The position tracking, force feedback and time delay between master-hand and slave-hand are analyzed. The results of fabrication and experiments validate the feasibility of the system scheme, and it provides reference for tele-micromanipulation applied to micro-assembly and other fields.
Fast and Robust Link Prediction using Ontology

Link Prediction is the task of predicting miss-001 ing relations between knowledge graph entities 002 (KG). Recent work in link prediction mainly 003 attempted to adapt a model for increasing link 004 prediction accuracy by using more layers in 005 neural network architecture, which heavily rely 006 on computational resources and are not scal-007 able on big KGs. This paper proposes a method 008 of refining knowledge graphs to perform link 009 prediction operations more accurately using rel-010 atively fast translational models. Translational 011 link prediction models, such as TransE, TransH, 012 TransD, RotatE, and HAKE, have significantly 013 less complexity than deep learning approaches. 014 Our method uses the ontologies of knowledge 015 graphs to add information as auxiliary nodes 016 to the graph. Then, these auxiliary nodes are 017 connected to ordinary nodes of the KG that 018 contain auxiliary information in their hierarchy. 019 Our experiments show that our method can sig-020 nificantly increase the performance of trans-021 lational link prediction methods in Hit@10, 022 Mean Rank, Mean Reciprocal Rank. 023
Detecting Moving Object via Projection of Forward-Backward Frame Difference

Frame difference is a quick dissimilarity based segmentation approach for object detection, unfortunately, it gets trapped in over-segmented when the pixels of interest over time overlap each other. This paper presents a rather fast visual object detection approach capable of approximating the location of moving object under heavy background noise or big overlap caused by negative similarity. Specifically, frame forward-backward difference concept is proposed to extract object features in current frame through fusion of pixel-based current-previous and current-following frame difference. Based on this, we formulate object localization applying the statistics of horizontal-vertical projection of the fused difference. Therefore, our object detection can be regarded as a direct thresholding process which guarantees high efficiency while holds good accuracy performance. We evaluate our method on Weizmann human action dataset and some traffic videos for both single and multiple objects detection which demonstrates its applicability and prospect.
Spherical Coordinate System Based New Background Subtraction Algorithm that Supplemented Existing Background Subtraction Algorithms

: The present paper proposes a new background subtraction algorithm (Rolling Sphere Algorithm: ROSA) intended to implement ‘background subtraction using spherical coordinate system based sphere rolling’, which is a vector application technology for separation between objects and backgrounds in digital images. This ROSA can be largely divided into a pre-treatment stage where target images are processed for the sphere rolling and a stage where the sphere is rolled on the pre-treated target image to subtract the actual background. This algorithm groups the edges of the subject of extraction in the image to divide the image into areas, processes the areas as if they are 3D images by making the areas into layers, and make a sphere roll over the layers to subtract the backgrounds. Experiments were conducted to compare the ROSA with the CodeBook (CD) and the Gaussian Mixture Model (GMM). In terms of pixel removal accuracy, results that were improved by 15% compared to the CD and the GMM. Since a process to make the target image into a reduced or compressed image filled with average values between adjacent pixels is necessary and vector sphere rolling is applied on the compressed image to apply the ROSA, it could be seen that flexibility in image magnification/reduction and the accuracy of background subtraction are improved compared to existing algorithms.
Proposal of a Ranking Method for Comments in Social Media Using Ratings of Comment Posters

Many social media adopt a ranking method in which comments are ranked in the order of the number of ratings attached to each comment. However, this method has the disadvantage of ratings being concentrated on comments posted at an early stage. Even if there are high-quality comments posted later, most of them are buried without being noticed. This paper proposes a ranking method that considers not only the ratings for each comment but also the previous ratings the comment poster has received. The effectiveness of the proposed method is evaluated through a simulation. We demonstrate that with the proposed method, high-quality comments are displayed in the higher positions regardless of the posting period.
Pivot-Based Bilingual Dictionary Creation for Low-Resource Languages

The goal of this thesis is to support the construction of new language resources for low-resource languages. To this end, we propose an automatic method of creating bilingual dictionaries for intra-family languages. High quality bilingual dictionaries are very useful in variety of tasks in natural language processing and cross-lingual information retrieval, but such resources are rarely available for low-resource language especially for those that are closely related such as Uyghur and Kazakh in Turkic language family. This reality has been an obstacle in creating advanced systems like machine translator of these language pairs which are becoming increasingly important for overcoming the language barrier. Automatic extraction of bilingual dictionaries from large size of parallel corpora has long been studied and resulted in relatively high quality of output. However, the parallel corpora is also an expansive resource that is available in large only for the popular languages, and for non-poplar languages, it remains sparse, dated, or simply unavailable. This makes such studies less applicable for poorly resourced languages. Therefore, a challenge has been emerged to creating the bilingual dictionaries by taking advantage of the limited amount of existing language resources which are presented in different forms such as parallel
Information theoretical analysis of bounded and unbounded channels in programming languages

This work proposes a quantitative study of the behaviour of looping constructs in programs, both in terms of absolute and rate of leakage, the main interest being the investigation and classification of bounded and unbounded covert channels. This analysis of looping programs is based on information theoretical formulas derived from the denotational semantics of the while statement.
Implementing the Algorithm of Target Recognition for Laser Imaging Radar Based on Digital Signal Processing

Laser imaging radar has high space resolution,and can output four-dimensional(4D) image(intensity image+three-dimensional(3D) range image),so it is fit to be the sensor of target recognition.Support vector machine(SVM) is a way of target recognition,which has high correct recognition rate,in the case of learning with small samples.Through optimizing the algorithm of SVM,it is embedded into digital signal processing(DSP) of laser imaging radar,achieving the function of target recognition,which has high practical meaning.The experiments with the real intensity images of laser imaging radar are finished.In the experiments,the testing set totally has 56 samples,and the costing time is 31. 97μs,which can state that the algorithm can meet the real-time requirement,and the correct recognition rate is 98.2%. Another experiments with simulated range images of laser imaging radar validate the generalization of SVM.The experiments results show that SVM can meet the recognition demands of laser imaging radar in the real-time and recognition performance.