Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Evaluation of Fade , Wipe and Dissolve in Detection of Shots in Video Mrs .

To Detect interesting part from video in large database with less time consumption is a big issue.Decomposition of video into shots and scenes with key frame extractions are useful to some extent with the compromise in spatio-temporal characteristics. We have presented techniques for frame base shot boundary detection, scene change detection and key frame extraction in videos. It is useful to define particular frame ranges of gradual transitions as a fade and dissolve as sequence of frames in presence of motion, which are difficult to detect compare to the sharp transitions. Approach is based on the discrete cosine transform based DC Coefficients and DC image,where mean and variance of DC image values are sufficient to choose threshold to detect these transitions effectively. This concept was applied and verified on large database and here we presented results applied on different videos. Performance is verified with existing techniques in terms of recall, precision measures and results reflect more about this concept at the end. In this algorithm, adaptive thresholds are automatically selected for a given video the effects of flashlight, object motion, and temporal shot on abrupt shot boundary detection are filtered by the thresholds.
Query-Free Clothing Retrieval via Implicit Relevance Feedback

Image-based clothing retrieval is receiving increasing interest with the growth of online shopping. In practice, users may often have a desired piece of clothing in mind (e.g., either having seen it before on the street or requiring certain specific clothing attributes), but may be unable to supply an image as a query. We model this problem as a new type of image retrieval task, in which the target image resides only in the user's mind (called “mental image retrieval” hereafter). Because of the absence of an explicit query image, we propose solving this problem through relevance feedback. Specifically, a new Bayesian formulation is proposed that simultaneously models the retrieval target and its high-level representation in the mind of the user (called the “user metric” hereafter) as posterior distributions of prefetched shop images and heterogeneous features extracted from multiple clothing attributes, respectively. Requiring only clicks as user feedback, the proposed algorithm is able to account for the variability in human decision-making. Experiments with real users demonstrate the effectiveness of the proposed algorithm.
Do Institutional Investors and Security Analysts Mitigate the Effects of Investor Sentiment?

One of most significant empirical findings in the behavioral finance literature is that investor sentiment affects asset prices. However, the mechanism by which sentiment affects asset prices is not well understood. Individuals are widely believed to be more influenced by sentiment than other investors, and individual noise traders combined with limits to arbitrage could explain sentiment-driven mispricing in stocks. Another explanation for sentiment-driven mispricing is that sentiment affects all market participants. To explore these two possibilities, we investigate decisions made by institutional investors and security analysts. We find that institutional investors tend to increase holdings in, and analysts tend to issue buy recommendations for, firms with subjective values when sentiment is high, even though these firms exhibit lower subsequent stock returns. Furthermore, returns tests show that these decisions by institutional investors and analysts are associated with greater sentiment-related mispricing of stocks. Thus, although we find that sentiment-related mispricing is mitigated when institutional investors and analysts act against it, more often than not they fail to do so.
An algebraic-based structural framework for the ontology alignment

To use ontologies in semantic Web we meet two major challenges. First, we have to use a logical formalism to write concepts with enough expression power. Second, we must guarantee a maximum interoperability if different ontologies are used. To do that, ontology alignment is one of the most appropriate solutions. It is based on the syntactic, semantic and structural similarities of the different input ontologies. To write the ontology concepts, we propose in this work, a description logic whose semantics is algebraic-based. Then, based on this representation formalism, we show how to improve the measure used to compute the structural similarity and we propose an argumentation-based method to deal with the ontology alignment problem.
Testing non-linear dependence and market timing ability. An application to the Hedge Fund industry

We show that managers who use market timing signals can generate returns with strong non-linear exposure to the market. When those signals are biased, this eect can be highly harmful for investors. We propose the dependence structures implied by the Student t and the Generalised Hyperbolic distributions to model these features. Specification tests for linear and Student t models are derived and used to analyse the dependence of hedge fund returns on market conditions. We find a significant presence of non-linear dependence and market mis-timing eects, which tends to worsen the performance of hedge funds during episodes of distressed markets.
Particle swarm and NSGA-II based evacuation simulation and multi-objective optimization

Because of the high-dense population and complex structure, the large public building faces a unique challenge in developing effective emergency evacuation plans. And due to the large scale and numbers of evacuees in real evacuation, real tests are impractical. Therefore, the simulation of evacuation becomes a wonderful choice in program planning. Particle Swarm is as one of the multi-agent based simulation method that can simulate complex behaviors of individuals. NSGA-II (Non-dominated Sorting Genetic Algorithm II) is a kind of optimization method for multi-objective optimization problem. In this paper, we propose a novel multi-objective evolutionary algorithm (named as PNMO, Particle swarm & NSGA-II based Multi-objective Optimization) which simulates evacuation process as well as optimizing the generated evacuation plans. The experiment shows that this method possesses superior performance in evacuation planning.
Sequence of a cDNA from the mosquito Anopheles gambiae encoding a homologue of human ribosomal protein S7.

Studies of ribosomal proteins have given insight to the function and structure of the ribosome. During ribosome assembly, individual ribosomal proteins that initially recognize rRNA must bind to the assembly particle in a certain order and work cooperatively, rather than independently (1). Two of these important ribosomal proteins are S7 and S8. Detailed study of these and other ribosomal proteins is vital to the understanding of protein synthesis. Here we report the structure, chromosome location and complete sequence of a cDNA in the mosquito Anopheles gambiae encoding a homologue of the human ribosomal S7 protein. The clone was isolated from a cDNA library constructed using poly(A) RNA of adult female and male mosquitoes from the G3 strain of A.gambiae (2). The complete 817 nucleotidelong cDNA contains a continuous open reading frame of 193 codons which potentially encodes a peptide with a molecular weight of 22206.90 Daltons and an isoelectric point of 9.945. Furthermore, this peptide shows a high level of basic amino acids (37), consistent with characterizations of S7 and S8-like proteins in other organisms (3). A presumed polyadenylation signal, AATAAA is located at bases 771-776. At the amino acid level, the open reading frame shows 71.7% identity with human ribosomal protein S7; 70.6% identity with Xenopus laevis ribosomal protein S8, and 61.7% identity with rat ribosomal protein S8 (Figure 1). Nucleotide comparison of the A.gambiae ribosomal protein cDNA coding sequence reveals a 66.7% identity with human ribosomal protein S7, but there are no evident similarities among the 5' or 3' non-coding sequences. In situ hybridization to the ovarian nurse cell polyrene chromosomes of A.gambiae revealed its location at division 38B in the A.gambiae genome. REFERENCES
A Toolkit for Modeling and Simulating Cloud Data Storage: An Extension to CloudSim

With the popularity of cloud computing technology, cloud storage technology as a new kind of distributed storage technology is widely used to store and manage massive data. Large-scale data management and analysis is difficult to achieve in complex scenarios. In order to overcome this challenge, we extend the cloud simulation platform CloudSim by adding the file striping and data replica management function, making it into a simulation platform for computing and storage. The expanded CloudSim can be used to implement different data layout and replica management strategy. And it's easily to add functionality to meet other needs. This paper gives a detailed description of the design and proves the significance of it through examples.
SUPERCAPACITOR ELECTRODES BASED ON GRAPHENE MATERIALS

SUPERCAPACITOR ELECTRODES BASED ON GRAPHENE MATERIALS by Steven M. Selverston Graphene is a new type of carbon material with promising potential in energy-storage applications such as supercapacitor electrodes. This paper introduces engineering of graphene, as well as a related material called reduced graphene oxide, as materials for use in supercapacitors. The introduction explains the basic definitions of supercapacitors and graphene materials. Then, the fundamentals of supercapacitors and graphene materials are described in more detail in Chapters 1 and 2, respectively. Chapter 3 covers the synthesis and characterization of graphene-based electrodes.
Market driving in retail banking

Purpose – The purpose of this paper is to investigate the relationship between the proactive market orientation approach and business performance in retail banking.Design/methodology/approach – Based on a theoretical discussion, empirical research was conducted to test the proposed relationship. Multiple item indicators were employed to measure the constructs.Findings – Results from the study provide empirical support, suggesting that the proactive market orientation approach has a positive influence on business performance.Research limitations/implications – The study has pondered the relationship between the proactive market orientation approach and business performance, while other factors that have an influence on business performance have not been considered.Practical implications – Research results suggest that the proactive market orientation philosophy in the banking sector can be viewed as a threshold factor in order to increase business performance.Originality/value – The present study provides .
Towards consensus.

No wonder you activities are, reading will be always needed. It is not only to fulfil the duties that you need to finish in deadline time. Reading will encourage your mind and thoughts. Of course, reading will greatly develop your experiences about everything. Reading towards consensus is also a way as one of the collective books that gives many advantages. The advantages are not only for you, but for the other peoples with those meaningful benefits.
Disclosure Practices in Corporate Reporting of Public Sector Financial Institutions (Psfs)

The aim of accounting is to communicate economic message on the result of business decision to the users from time to time. Thus corporate reporting is total communication system between a company and users. This is the most direct least expensive, most timely and faired methods of reaching all shareholders and other, present and potential users. Financial reporting includes not only financial statements but also other means of communicating information that relates, directly or indirectly to the information provided by the accounting system. Corporate annual reports (CAR) are the subject of research emanating from different disciplines. A growing body of literature addresses their purpose, design, content and interpretation, as well as reasons for their changing content. This literature examine how different characteristics of organization affects disclosure pattern.
An optimization approach to determining the number of vendors to employ

Presents an approach for evaluating the number of vendors to employ in a procurement situation using multi‐objective programming (MOP) and data envelopment analysis (DEA). The approach advocates developing vendor‐order quantity solutions (referred to as supervendors) using MOP and then evaluating the efficiency of these supervendors on multiple criteria using DEA. Formulations are presented for both the MOP and DEA models. A case study is presented for a Fortune 500 company in a just‐in‐time (JIT) manufacturing environment.
Large sample inference for an assay quality measure used in high‐throughput screening

The Z′ factor, introduced by Zhang et al. (J. Biomol. Screening 1999; 4(10):67–73), is used extensively in drug discovery for evaluating the performance of high‐throughput screening (HTS) assays. These assays are time consuming and expensive. Important decisions regarding HTS assay development, validation and quality are often based solely on point estimates of Z′. Although it would be beneficial to have a confidence interval for Z′, it appears that a formal inferential procedure has not yet been proposed. We fill this gap in the literature by deriving a large sample interval estimator for Z′. Simulation studies found that the proposed confidence interval performed well with both independent and moderately correlated data. Our confidence interval is algebraically simple and amenable to spreadsheet programming. The new interval allows researchers to explicitly consider the variability of estimation when making decisions based on Z′. Copyright © 2010 John Wiley & Sons, Ltd.
Applying platform design to improve the integration of patient services across the continuum of care

Purpose – The purpose of this paper is to provide the results of a case study that examined the application of platform design to improve the integration of patient care services across the continuum of care. This paper is designed to spark discussion and encourage further research in this area.Design/methodology/approach – The research in the paper involved a case study of a large health care provider in a major metropolitan area. The authors of this paper worked with directors of case management departments and other managerial personnel within the enterprise to study the case management interface services between different inpatient and outpatient facilities to examine existing processes, identify deficiencies, and to recommend improvements in case management.Findings – The paper finds that the current case management system of the provider, as structured, was not fulfilling its potential for achieving medical quality, operational cost, or patient satisfaction. A number of areas where improvements coul.
A Non-stationary Noise Suppression Method Based on Particle Filtering and Polyak Averaging

This paper addresses a speech recognition problem in non-stationary noise environments: the estimation of noise sequences. To solve this problem, we present a particle filter-based sequential noise estimation method for front-end processing of speech recognition in noise. In the proposed method, a noise sequence is estimated in three stages: a sequential importance sampling step, a residual resampling step, and finally a Markov chain Monte Carlo step with Metropolis-Hastings sampling. The estimated noise sequence is used in the MMSE-based clean speech estimation. We also introduce Polyak averaging and feedback into a state transition process for particle filtering. In the evaluation results, we observed that the proposed method improves speech recognition accuracy in the results of non-stationary noise environments a noise compensation method with stationary noise assumptions.
Named entity recognition in functional neuroimaging literature

Human neuroimaging research aims to find mappings between brain activity and broad cognitive states. In particular, Functional Magnetic Resonance Imaging (fMRI) allows collecting information about activity in the brain in a non-invasive way. In this paper, we tackle the task of linking brain activity information from fMRI data with named entities expressed in functional neuroimaging literature. For the automatic extraction of those links, we focus on Named Entity Recognition (NER) and compare different methods to recognize relevant entities from fMRI literature. We selected 15 entity categories to describe cognitive states, anatomical areas, stimuli and responses. To cope with the lack of relevant training data, we proposed rule-based methods relying on noun-phrase detection and filtering. We also developed machine learning methods based on Conditional Random Fields (CRF) with morpho-syntactic and semantic features. We constructed a gold standard corpus to evaluate these different NER methods. A comparison of the obtained F1 scores showed that the proposed approaches significantly outperform three state-of-the-art methods in open and specific domains with a best result of 78.79% F1 score in exact span evaluation and 98.40% F1 in inexact span evaluation.
Application Note # 549 Quantitatively Measuring Surface Texture and Shaft Lead of Dynamic Sealing Systems

The average automobile has over eighty dynamic seals that can fail at any given time.1 Failures attributed to leaking seals cost the transportation and power industry many tens of millions of dollars a year in warranty costs, recalls and fines. Advances in seal/shaft design and materials have extended the service life and reliability of vehicles and engineered systems. However, traditional measurement techniques are unable to keep pace with today’s smoother shafts and more rigorously controlled seal interfaces. Tighter specifications demand a more robust, gage-capable metrology solution that can quantitatively measure lead angles to the tolerances outlined in industry specifications, such as ISO 6194-1:2009 and RMA OS-1-1 rev. 2004, thereby improving production quality and yield. This application note details a metrology solution that addresses these issues and provides manufacturers a way to measure lead angle both quantitatively and repeatably with complete confidence in the results.
Analysis of time and frequency synchronization error for wireless systems using OFDM

Due to frequency-selective and time-variant property of wireless channel together with additive noise and mismatch of oscillators between transmitter and receiver, there are always time and frequency synchronization errors in a practical OFDM system. To investigate the effect of the two kinds of errors on system performance, the average normalized interference power (NIP) is defined. A simple supper bound for NIP caused by time synchronization error (TSE) and the tighter upper bound for NIP resulting from frequency synchronization error (FSE) are derived independently. Simulations in typical short wave (SW) and medium wave (MW) channels further verify the correctness and tightness of these upper bounds. They actually provide good approximations to NIPs. Moreover, the upper bound for NIP resulting from FSE is tighter than traditional upper bound. Additionally, a new solution is proposed to relax the precision requirement for time synchronization algorithm, which can achieve a better tradeoff between time synchronization precision and bandwidth efficiency. These upper bounds will be useful in developing and choosing time and frequency synchronization algorithms in OFDM system to achieve a specific NIP value for a given channel condition.
The Differential Sensitivity of Human and Rhesus Macaque CCR5 to Small-Molecule Inhibitors of Human Immunodeficiency Virus Type 1 Entry Is Explained by a Single Amino Acid Difference and Suggests a Mechanism of Action for These Inhibitors

ABSTRACT AD101 and SCH-C are two chemically related small molecules that inhibit the entry of human immunodeficiency virus type 1 (HIV-1) via human CCR5. AD101 also inhibits HIV-1 entry via rhesus macaque CCR5, but SCH-C does not. Among the eight residues that differ between the human and macaque versions of the coreceptor, only one, methionine-198, accounts for the insensitivity of macaque CCR5 to inhibition by SCH-C. Thus, the macaque coreceptor engineered to contain the natural human CCR5 residue (isoleucine) at position 198 is sensitive to HIV-1 entry inhibition by SCH-C, whereas a human CCR5 mutant containing the corresponding macaque residue (methionine) is resistant. Position 198 is in CCR5 transmembrane (TM) helix 5 and is not located within the previously defined binding site for AD101 and SCH-C, which involves residues in TM helices 1, 2, 3, and 7. SCH-C binds to human CCR5 whether residue 198 is isoleucine or methionine, and it also binds to macaque CCR5. However, the binding of a conformation-dependent monoclonal antibody to human CCR5 is inhibited by SCH-C only when residue 198 is isoleucine. These observations, taken together, suggest that the antiviral effects of SCH-C and AD101 involve stabilization, or induction, of a CCR5 conformation that is not compatible with HIV-1 infection. However, SCH-C is unable to exert this effect on CCR5 conformation when residue 198 is methionine. The region of CCR5 near residue 198 has, therefore, an important influence on the conformational state of this receptor.
A Chemical Inhibitor of p 53 That Protects Mice from the Side Effects of Cancer Therapy

In congenitally deaf cats, the central auditory system is deprived of acoustic input because of degeneration of the organ of Corti before the onset of hearing. Primary auditory afferents survive and can be stimulated electrically. By means of an intracochlear implant and an accompanying sound processor, congenitally deaf kittens were exposed to sounds and conditioned to respond to tones. After months of exposure to meaningful stimuli, the cortical activity in chronically implanted cats produced field potentials of higher amplitudes, expanded in area, developed long latency responses indicative of intracortical information processing, and showed more synaptic efficacy than in naı̈ve, unstimulated deaf cats. The activity established by auditory experience resembles activity in hearing animals.
Swampman, response-dependence, and meaning

Toward the end of their chapter “Externalism and the Impossibility of Massive Error,” Lepore and Ludwig (2007a, pp. 335–42) explain—correctly, I think—that the privileged position that Davidson grants the radical interpreter in being able to determine all things semantic suggests that his externalism is synchronic and physical. They clarify: “Synchronic externalism holds that our thought contents depend only on our current environment and our dispositions to respond. Physical externalism holds that our thought contents are determined in part by our relations to our physical, nonsocial environment” (p. 336). They might have added that Davidson’s externalism concerns thought and talk. But their point is clear enough. Lepore and Ludwig then observe that Davidson’s externalism is in fact physical and diachronic. “He holds . that there is a historical element to thought content” (p. 337). They contend that Davidson’s argument for diachronism is his Swampman thought experiment:
Trademark dilution and the practice of marketing

This article considers the marketing implications of the Federal Trademark Dilution Act (FTDA) of 1995. The FTDA, an amendment to the Lanham Act, will influence the manner in which marketing is practiced well into the twenty-first century. Although the FTDA is specifically concerned with protecting famous trademarks from being diluted—either by having their distinctiveness diminished or positive associations tarnished—by similar trademarks, its influence will not be limited to trademark or branding issues. Implications range from the allocation of advertising resources to the increased use of marketing research.