Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Word Vectors for Video Semantic

We propose vocabulary expansion for video semantic indexing. From many semantic concept detectors obtained by using training data, we make detectors for concepts not included in training data. First, we introduce Mikolov’s word vectors to represent a word by a low-dimensional vector. Second, we represent a new concept by a weighted sum of concepts in training data in the word vector space. Finally, we use the same weighting coe ﬃ cients for combining detectors to make a new detector. In our experiments, we evaluate our methods on the TRECVID Video Semantic In-dexing (SIN) Task. We train our models with Google News text documents and ImageNET images to generate new semantic detectors for SIN task. We show that our method performs as well as SVMs trained with 100 TRECVID example videos.
Research on object-background segmentation of color image based on LabVIEW

Automatic threshold segmentation or magic wand processing usually can't perfectly extract target from a color image with complex background. A method combining color threshold segmentation with the magic wand processing is proposed to solve this problem. The thresholds in H, S, L color plane are respectively set on the HSL model to avoid single gray variation. Combined with morphological image processing the boundaries of the object and background of the image is more obvious. The magic wand processing is used to extract the object from the background. Experiments which designed based on LabVIEW and NI-IMAQ Vision can greatly shorten the developing cycle and can be easily implemented and maintained. The results show the method proposed above work better than the usual method.
Performance analysis for clusters of symmetric multiprocessors

In this article we analyze and model the performance of a symmetrical multiprocessor cluster. The obtained model takes into account the heterogeneity of the architecture's communications, which allows for a better adjustment and predictive ability of the performance. We used diverse applications with different parallel schemes to check the quality of the adjustments. The adjustment of the theoretical model and the experimental results is clearly improved when we take into account the combination of various mechanisms of communication
How Early Childhood Learning Influences Beginning Literacy Teachers’ Professional Learning

Research has shown that teachers’ beliefs and personal experiences play a significant role in their professional decision-making and practice, including their experiences as school children. This research study examined how the professional learning of Canadian beginning elementary teachers was influenced by their own early learning experiences in school. Six teachers were observed and interviewed in their classrooms 5 times over the first 3 years of their teaching career. Case studies were developed for each teacher and themes were explored across cases. The findings from this study suggest that pre-service and in-service teacher education programs need to provide teachers with opportunities to critically examine how their early learning experiences influence their professional learning experiences and priorities.
THERMODYNAMICS AND LARGE-SCALE NON-LINEAR DYNAMICAL SYSTEMS : A VECTOR DISSIPATIVE SYSTEMS APPROACH

Recent technological demands have required the analysis and control design of increasingly complex, large-scale nonlinear dynamical systems. In analyzing these largescale systems, it is often desirable to treat the overall system as a collection of interconnected subsystems. Solution properties of the large-scale system are then deduced from the solution properties of the individual subsystems and the nature of the system interconnections. In this paper we develop an energy flow modeling framework for large-scale dynamical systems based on vector dissipativity notions. Specifically, using vector storage functions and vector supply rates, dissipativity properties of the composite large-scale system are shown to be determined from the dissipativity properties of the subsystems and their interconnections. Thermodynamic principles are also established using a large-scale systems perspective.
Sensitivity Analysis of a 3D Convective Storm: Implications for Variational Data Assimilation and Forecast Error

In this study a nonhydrostatic 3D cloud model, along with an automatic differentiation tool, is used to investigate the sensitivity of a supercell storm to prescribed errors (perturbations) in the water vapor field. The evolution of individual storms is strongly influenced by these perturbations, though the specific impact depends upon their location in time and space. Generally, perturbations in the rain region above cloud base have the largest impact on storm dynamics, especially for subsequent storms, while perturbations in the ambient environment above cloud base influence mostly the main storm. Although perturbations in the subcloud layer have a relatively small impact on upper-level storm structure, they do impact the low-level structure, especially during the period immediately following insertion. Sensitivities are also examined in the context of variational data assimilation and forecast error. For perturbations added inside the active storm, the cost function, which is prescribed to measure the discrepancy between forecast and observations for all variables over time and space, is found to be most sensitive to temperature, followed by pressure and water vapor. This implies that the quality of variational data assimilation can be affected by the inaccuracy of observing or retrieving those quantities. It is also noted that, at least for the case studied here, the pressure field has the largest influence on forecast error immediately after the errors are inserted, while the temperature field does so over a longer time period.
Robust lateral-plane motion control of four-wheel independently actuated electric vehicles

The paper presents a vehicle lateral-plane motion stability control approach for four-wheel independently actuated (FWIA) electric ground vehicles considering the tire force saturations. Due to the possible modeling inaccuracies and parametric uncertainties, a linear parameter-varying (LPV) based robust H∞ controller is designed to yield the desired external yaw moment. The tire force constraints are considered in the controller design as well. Simulation results based on a high-fidelity, CarSim, full-vehicle model show the effectiveness of the control approach.
Query Optimization in Object Oriented Databases through Detecting Independent Subqueries

Query optimization is the refining process in database administration and it helps to bring down speed of execution. Some object-oriented languages allows to express queries explicitly in the code, which are optimized using the query optimization techniques from the database domain. With respect to this, a formalized object query language (OQL) has been developed that performs optimization of queries at compile time. Object Oriented Data Base (OODB) has all the features, functionality of a relational database system and also offers an Object Oriented Programming language interface. We follow the stack based approach to query languages, which is responsible for naming-scoping-binding principle. In this paper we proposed one of the methods of query optimization depending on rewriting. Optimization by rewriting concerns queries containing so called independent subqueries. It consists in detecting them and then factoring
An Attack Modeling Based on Colored Petri Net

A color petri net (CPN) based attack modeling approach is addressed. Compared with graph-based modeling, CPN based attack model is flexible enough to model Internet intrusions, because of their static and dynamic features. The processes and rules of building CPN based attack model from attack tree are also presented. In order to evaluate the risk of intrusion, some cost elements are added to CPN based attack modeling. This extended model is useful in intrusion detection and risk evaluation. Experiences show that it is easy to exploit CPN based attack modeling approach to provide the controlling functions, such as intrusion response and intrusion defense. A case study given in this paper shows that CPN based attack model has many unique characters which attack tree model hasn't.
A universal haptic device for arm and wrist rehabilitation

Robot-mediated rehabilitation is rapidly advancing field. However, robots that are used for rehabilitation purposes are usually single task oriented. One approach to overcome that issue is in introducing robotic devices with more Degrees-of-Freedom (DOF), which means complicated and expensive design. This paper presents the design of a universal haptic device (UHD) for arm and wrist rehabilitation, with only 2-DOF drive. The essence of the developed device is in mechanical design, which enables the rehabilitation of the upper limb in two different modes; “ARM” and “WRIST” mode. By simple mechanical reconfiguration it is possible to switch between both modes, which enables gradual rehabilitation of complete upper limb. Device is actuated by 2-DOF haptic drive based on Series Elastic Actuation (SEA).
Bit-stream-based Encryption for Regions of Interest in H.264/avc Videos with Drift Minimization

We propose a new encryption approach for regions of interest in H.264/AVC bit streams. By encrypting at bit stream level and applying drift minimization techniques, we reduce the processing time by up to 45% compared to full re-encoding. Depending on the input video quality, our approach induces an overhead between-0.5 and 1.5% (high resolution sequences) and-0.5 and 3% (low resolution sequences), respectively , to minimize the drift outside the regions of interest. The quality degradation in these regions remains small in most cases, and moderate in a worst-case scenario with a high number of small regions of interest.
Dynamic Modeling and Pneumatic Switching Control of a Submersible Drogue

This paper analyzes the dynamic properties of a submersible drogue for which buoyancy control is imple- mented by a flexible membrane and pneumatic actuation. It is shown how a simple on/off switching algorithm tuned on the basis of depth measurements and an estimated depth velocity can be used to achieve accurate depth control with small fluctuations. The switching control makes the pneumatically controlled drogue an inherent hybrid system and conditions for contraction and stability are given for the proposed switching con- trol algorithm. Numerical evaluation of the conditions for stability and experimental data of the switching control implemented on a pneumatic submersible drogue further demonstrates the soundness of the proposed switching control algorithm.
Identifying Long Haplotype Blocks with Low Diversity

Given an m×n haplotype matrix A, we show linear time algorithms for finding all interval diversities, farthest sites, and the longest block with low diversity. For selecting the multiple long blocks with diversity constraint, we show that selecting k blocks with longest total length can be be found in O(nk). We also propose linear time algorithms in calculating the all intra-longest-blocks and all intra-k-longestblocks. For dealing with missing SNP data, we propose methods that clarifies ambiguous SNP sites; furthermore, we show some hardness result concerning the minimum di-
System Impact of 3D Processor-Memory Interconnect: A Limit Study

3D integration with through-silicon-vias (TSVs) can provide enormous bandwidth between processor die and memory die. The central goal of our work is to explore the limits of performance improvement that can be achieved with such integration. Towards this end we propose a model of the impact of 3D TSVs on system performance. The model leads to several key observations i) increased miss tolerance (smaller caches) and hence improved core scaling for a fixed die size, ii) higher sustained IPC per core, iii) significantly smaller, energy efficient DRAM banks, iv) redistribution of system power to the cores and on -die interconnect, and v) TSV utilization is a function of the relationship between reference locality and the bandwidth properties of the intradie network. These observations are repeated in cycle level simulations of a 64 tile architecture.
A neural network nonlinear predictor

Summary form only given, as follows. The authors demonstrate that a backpropagation neural network can be used for nonlinear time series prediction. In a computer experiment an example nonlinear time series is used to teach a network the necessary mapping in a supervised manner. Predictor learning curves are presented, showing successful operation. Improvements to the neural network structure with regard to the reduction of the observed performance deficit are discussed. <<ETX>>
Measurement and Transfer of Catastrophic Risks. A Simulation Analysis

Abstract When analyzing catastrophic risk, traditional measures for evaluating risk, such as the probable maximum loss (PML), value at risk (VaR), tail-VaR, and others, can become practically impossible to obtain analytically in certain types of insurance, such as earthquake, and certain types of reinsurance arrangements, specially non-proportional with reinstatements. Given the available information, it can be very difficult for an insurer to measure its risk exposure. The transfer of risk in this type of insurance is usually done through reinsurance schemes combining diverse types of contracts that can greatly reduce the extreme tail of the cedant's loss distribution. This effect can be assessed mathematically. The PML is dei ned in terms of a very extreme quantile. Also, under standard operating conditions, insurers use several “layers” of non proportional reinsurance that may or may not be combined with some type of proportional reinsurance. The resulting reinsurance structures will then be very complicated to analyze and to evaluate their mitigation or transfer effects analytically, so it may be necessary to use alternative approaches, such as Monte Carlo simulation methods. This is what we do in this paper in order to measure the effect of a complex reinsurance treaty on the risk profile of an insurance company. We compute the pure risk premium, PML as well as a host of results: impact on the insured portfolio, risk transfer effect of reinsurance programs, proportion of times reinsurance is exhausted, percentage of years it was necessary to use the contractual reinstatements, etc. Since the estimators of quantiles are known to be biased, we explore the alternative of using an Extreme Value approach to complement the analysis.
Application of BP neural network in the digital recognition system

the purpose of digital identification technology based on artificial neural networks is to achieve efficient character recognition through the simulation of human brain function and structure. This paper uses BP neural network to design three classifiers which separately extract the input vector with different characteristics, proposes a weighted integration multi-classifier method based on the analysis of common used integrated multi-classifiers, and uses the method to integrate the designed three classifiers to design a weight-based integrated multi-classifier handwritten digital identification system.
A Mathematical Framework for the Detection of Elephant Flows

How large is a network flow? Traditionally this question has been addressed by using metrics such as the number of bytes, the transmission rate or the duration of a flow. We reason that a formal mathematical definition of flow size should account for the impact a flow has on the performance of a network: flows that have the largest impact, should have the largest size. In this paper we present a theory of flow ordering that reveals the connection between the abstract concept of flow size and the QoS properties of a network. The theory is generalized to accommodate for the case of partial information, allowing us to model real computer network scenarios such as those found in involuntary lossy environments or voluntary packet sampling protocols (e.g., sFlow). We explore one application of this theory to address the problem of elephant flow detection at very high speed rates. The algorithm uses the information theoretic properties of the problem to help reduce the computational cost by a factor of one thousand.
Applying attachment theory and the wounded healer hypothesis to clinical psychology and mental health counseling graduate students

APPLYING ATTACHMENT THEORY AND THE WOUNDED HEALER HYPOTHESIS TO CLINICAL PSYCHOLOGY AND MENTAL HEALTH COUNSELING GRADUATE STUDENTS by Alison B. Levine, M.S. Nova Southeastern University ABSTRACT The personal characteristics of the therapist are strongly associated with therapeutic alliance and treatment outcome. Since treatment techniques are often shown to be equally effective, differential outcomes may be attributed to the therapist’s early experiences and personality features. The purpose of this study was to determine the influence of childhood relational trauma in predicting specific components of mentalizing skills (i.e., affect consciousness, psychological mindedness, mindfulness, cognitive empathy and theory of mind) among therapists. Participants were 121 clinical psychology doctoral and master’s in mental health counseling students (20 males, 101 females) aged 22 to 53 years old (M = 27.26, SD = 5.25). Measures included the Child Abuse and Trauma Scale (CATS), Kentucky Inventory of Mindfulness Skills (KIMS), Toronto Alexithymia Scale (TAS), Psychological Mindedness Scale (PMS), Reading the Mind in the Eyes Test-revised (RMET), Interpersonal Reactivity Index (IRI-PT/IRI-EC), Relationship Structures Questionnaire (RSQ) and a questionnaire assessing demographic information, graduate training and interests, personal therapy, objective childhood
A Language and Algorithm for Automatic Merging of Ontologies

Nowadays, most of the important information resources that the people require are available through the Internet. The use of several sources in the Internet requires merging the information into a knowledge base in a reasonable way. We will use an ontology, an information technology that manages this knowledge in computers. Merging is an important task and many languages and tools have been developed to describe and process Internet content but the current languages (DAML+OIL, RDF, OWL, etc.) lack a complete expressiveness. For this reason, we present two important improvements to facilitate knowledge interchange: 1) The OM (ontology merging) notation that provides substantial improvements to these languages and 2) The OM algorithm, this is totally automatic in comparison with others (Prompt, Chimaera, OntoMerge, FCA-Merge, IF-Map and ISI) where the user manually solves the most important problems found in the merging
Chemical control of phospholipid distribution across bilayer membranes

Most biological membranes possess an asymmetric transbilayer distribution of phospholipids. Endogenous enzymes expend energy to maintain the arrangement by promoting the rate of phospholipid translocation, or flip‐flop. Researchers have discovered ways to modify this distribution through the use of chemicals. This review presents a critical analysis of the phospholipid asymmetry data in the literature followed by a brief overview of the maintenance and physiological consequences of phospholipid asymmetry, and finishes with a list of chemical ways to alter phospholipid distribution by enhancement of flip‐flop. © 2002 Wiley Periodicals, Inc. Med Res Rev, 22, No. 3, 251–281, 2002; Published online in wiley InterScience (www.interscience.wiley.com). DOI 10.1002/med.10009
New nonvolatile FPGA concept using magnetic tunneling junction

This paper describes a real time reconfigurable (RTR) micro-FPGA using new non volatile memory. Magnetic tunneling junctions (MTJ) used in magnetic random access memories (MRAM) are compatible with classical CMOS processes. Moreover remanent property of such a memory could limit configuration time and power consumption required at each power up of the device. Each configuration memory point has to be readable independently from each other, which makes this approach radically different from the classical memory array one
Exploiting Constraint Weights for Revision Ordering in Arc Consistency Algorithms

Coarse grained arc consistency algorithms, like AC-3, operate by maintaining a list of arcs (or variables) that records the revisions that are still to be performed. It is well known that the performance of such algorithms is affected by the order in which revisions are carried out. As a result, several heuristics for ordering the elements of the revision list have been proposed. These heuristics exploit information about the original and the current state of the problem, such as domain sizes, variable degrees, and allowed combinations of values, to reduce the number of constraint checks and list operations aiming at speeding up arc consistency computation. Recently, Boussemart et al. proposed novel variable ordering heuristics that exploit information about failures gathered throughout search and recorded in the form of constraint weights. Such heuristics are now considered as the most efficient general purpose variable ordering heuristic for CSPs. In this paper we show how information about constraint weights can be exploited to efficiently order the revision list when AC is applied during search. We propose a number of simple revision ordering heuristics based on constraint weights for arc, variable, and constraint oriented implementations of coarse grained arc consistency algorithms, and compare them to the most efficient existing revision ordering heuristic. Importantly, the new heuristics can not only reduce the numbers of constraints checks and list operations, but also cut down the size of the explored search tree. Results from various structured and random problems demonstrate that some of the proposed heuristics can offer significant speed-ups.
Mobility-Aware Caching in D2D Networks

Caching at mobile devices can facilitate device-to-device (D2D) communications, which may significantly improve spectrum efficiency and alleviate the heavy burden on backhaul links. However, most previous works ignored user mobility, thus having limited practical applications. In this paper, we take advantage of the user mobility pattern by the inter-contact times between different users, and propose a mobility-aware caching placement strategy to maximize the data offloading ratio, which is defined as the percentage of the requested data that can be delivered via D2D links rather than through base stations. Given the NP-hard caching placement problem, we first propose an optimal dynamic programming algorithm to obtain a performance benchmark with much lower complexity than exhaustive search. We then prove that the problem falls in the category of monotone submodular maximization over a matroid constraint, and propose a time-efficient greedy algorithm, which achieves an approximation ratio as $\frac {1}{2}$ . Simulation results with real-life data sets will validate the effectiveness of our proposed mobility-aware caching placement strategy. We observe that users moving at either a very low or very high speed should cache the most popular files, while users moving at a medium speed should cache less popular files to avoid duplication.