Miracle-dz/UniFAR-FTUs huggingface dataset:
Formal Vocabulary Instruction in EFL Context

This paper discusses various methods of formal vocabulary instruction in Taiwan's EFL context. It will begin by examining vocabulary learning difficulties that Taiwanese students may experience in terms of English letter-sound relationships, written and spoken forms, word meaning, and usage, each followed by direct vocabulary teaching strategies for minimizing the learning burden. Next, the paper will explore teaching strategies that can be used to guide students towards successful vocabulary learning in the classroom. The paper will conclude with a brief review of vocabulary learning strategies that students can use to improve vocabulary learning, including using word cards, the Keyword Method, learning word parts, and bilingual dictionary use.
Simulation of Flow Past a Sphere using the Fluent Code

Abstract : We use the commercial computational fluid dynamics code Fluent to simulate the flow around a sphere in several different flow regimes; steady-state laminar flow at a Reynolds number (Re) of 100, time-dependent laminar flow at Re = 300, and turbulent flow at Re = 10,000 and Re = 1,000,000. These simulations provide a test of the ability of the code to accurately reproduce typical flow structures observed in generic bluff body flows, such as those experienced by submarines and Unmanned Underwater Vehicles (UUVs). The simulations are compared both with experimental results and computations from other computer codes and it is found that Fluent is able to accurately simulate the fluid behaviour in each of the above flow regimes.
The Analysis and Simulation of a Hybrid Video Broadcast Architecture

Recent research efforts have demonstrated the promising potential of building cost-effective media streaming systems on top of peer-to-peer (P2P) networks. The P2P systems have long setup and source to end delay. We proposes a hybrid architecture MTreeTV which combines the use of P2P networks with dedicated streaming servers, and was proposed to build on the advantages of both P2P and CDN paradigms. We offer a novel locality-aware overlay construction and scheduling algorithm to assure the effectiveness of P2P overlay. We also study the placement of the servers with constraints on the client to server paths and evaluate the effect of the server parameters. Through analysis and simulation, we show that MTreeTV supports fast channel switching (ang4s), it can provide high playback continuity (>98%) with little control overload (<2%).
A QPSO Based Multiuser Detection for Antenna-Diversity-Aided MC-CDMA Systems

The paper proposes a quantum particle swarm optimization (QPSO) based multiuser detection for the antenna-diversity-aided multicarrier code-division multiple-access (MC-CDMA) systems. Due to the spatial receive-diversity, the received signals at the different antennas are faded independently, resulting in an independent log-likelihood function (LLF) for each receive-antenna. To resolve the multi-objective dilemma when choosing one signal estimation for multiple receive-antenna-branches, the proposed scheme updates each quantum particle in a Pareto optimal way. Simulations and comparisons with the QPSO of linear combining strategy and the maximum likelihood detection (MLD) verified the effectiveness of the proposed scheme.
Macroblock-Level Adaptive Frequency Weighting for Perceptual Video Coding

In the perceptual coding scheme, the properties of the human visual system (HVS) are usually used to improve the coding efficiency. The frequency sensitivity is one of the most important properties of HVS and is usually used to improve the subjective quality. The frequency weighting technique is adopted in many video coding standards, such as MP EG 2 and H.264/AVC High Profile. However, the frequency weighting algorithms used in those standards are all in picture level. In this paper, a novel macroblock (MB)- level adaptive frequency weighting (MBAFW) algorithm is investigated. Compared with the picture-level adaptive frequency weighting (PAFW) algorithms, the encoder with MBAFW can select different frequency weighting strategies and different quantization matrices for each MB. The spatial context and the motion activities of one picture are both taken into consideration, which makes the frequency weighting adaptation more efficient and reasonable. The experimental results show that MBAFW can improve the subjective quality significantly. Additionally, MBAFW algorithm can achieve 10%~15% bitrate reductions with almost the same subjective quality.
Factor Model based on contents analysis of Stock BBS Postings

We aim to develop a new factor of stock BBS postings that is different from our BMB factor. In our previous study, the contents of stock BBS postings are classified into two categories; i.e. the bullish postings and the bearish postings, and our BMB factor is based on these categories. The results of recent study suggest that the contents of stock BBS postings may be represented by employing more than one index. To develop a new factor, we use a morphological analysis and a PCA to analyze the contents of stock BBS postings. As results, we develop a new factor that based on principal component score and it represented the return of stock, and in that they are not correlated with our BMB factor.
A Parallel Recovery Scheme for Update Intensive Main Memory Database Systems

In update intensive applications, main memory database systems produce large volume of log records, it is critical to write out the log records efficiently to speedup transaction processing. We propose a parallel recovery scheme based on XOR differential logging for main memory database systems in such environments. Some NVRAM is used to temporarily hold log records and decouple transaction committing from disk writes, inherited parallelism properties of differential logging are exploited to accelerate log flushing by using multiple log disks. During recovery, log records are loaded from multiple log disks and applied to data partition in time without the need of reordering according to serialization order, total recovery time is cut down. The scheme employs a data partition based consistent checkpointing method. The log records are classified according to IDs of data partitions accessed. Data partitions are recovered according to loading priorities computed from update frequencies and transaction waiting times, data access demands of new transactions coming after failure recovery are given attention immediately, thus the scheme provides system availability during recovery, which is of importance for large scale main memory database systems.
PowerTrust: A Robust and Scalable Reputation System for Trusted Peer-to-Peer Computing

We propose a new fair scheduling technique, called OCGRR (output controlled grant-based round robin), for the support of DiffServ traffic in a core router. We define a stream to be the same-class packets from a given immediate upstream router destined to an output port of the core router. At each output port, streams may be isolated in separate buffers before being scheduled in a frame. The sequence of traffic transmission in a frame starts from higher-priority traffic and goes down to lower-priority traffic. A frame may have a number of small rounds for each class. Each stream within a class can transmit a number of packets in the frame based on its available grant, but only one packet per small round, thus reducing the intertransmission time from the same stream and achieving a smaller jitter and startup latency. The grant can be adjusted in a way to prevent the starvation of lower priority classes. We also verify and demonstrate the good performance of our scheduler by simulation and comparison with other algorithms in terms of queuing delay, jitter, and start-up latency
Augmenting remote multimodal person verification by embedding voice characteristics into face images

This paper presents a biometric watermarking algorithm to augment remote multimodal recognition by embedding voice characteristics into face images. We embed both a fragile watermark for tampering detection, as well as a robust watermark to represent the GMM parameters extracted from voice. We show that the proposed scheme can detect tampering, and is also robust to various watermarking attacks. Person verification experiments on the XM2VTS database indicate the validity of combining face and voice classifiers.
A Typed Model for Linked Data

The term Linked Data is used to describe ubiquitous and emerging semi-structured data formats on the Web. URIs in Linked Data allow diverse data sources to link to each other, forming a Web of Data. A calculus which models concurrent queries and updates over Linked Data is presented. The calculus exhibits operations essential for declaring rich atomic actions. The operations recover emergent structure in the loosely structured Web of Data. The calculus is executable due to its operational semantics. A light type system ensures that URIs with a distinguished role are used consistently. The main theorem verifies that the light type system and operational semantics work at the same level of granularity, so are compatible. Examples show that a range of existing and emerging standards are captured. Data formats include RDF, named graphs and feeds. The primitives of the calculus model SPARQL Query and the Atom Publishing Protocol. The subtype system is based on RDFS, which improves interoperability. Examples focuss on the SPARQL Update proposal for which a fine grained operational semantics is developed. Further potential high level languages are outlined for exploiting Linked Data.
Efficient spatial and temporal resolution control for archiving and retrieving a series of remote sensing image data using 3D wavelet transform

Proposes efficient spatial and temporal resolution controlling methods for the time series of remote sensing images based on a 3D wavelet transform. For fast archiving and retrieving of the images, incremental decomposition of multi-resolution representation, and spatially and temporally local reconstruction are also proposed. The efficiencies of the methods are evaluated through simulations.
Foundation for Future Database Systems: The Third Manifesto

From the Publisher: A detailed study of the impact of objects and type theory on the relational model of data, including a comprehensive model of type inheritance! "This book should be recommended reading for software engineers, database designers, graduate students, undergraduate students, data modelers--for just about anybody with a serious interest in database technology. " --Declan Brady, MBCS, Lead Systems Architect, ICL "As a database application designer/architect, I'm interested in ideals as well as in currently available tools . This book is a rich source of worthy ideals. In particular, it provides good coverage of areas where SQL, and much commercial Object Orientation training material, are found lacking. " --Tom Pledger, Peace International Software Foundation for Future Database Systems: The Third Manifesto is a proposal for the future direction of data and database management systems (DBMSs). It consists of a precise, formal definition of an abstract model of data, to be considered as a blueprint for the design of a DBMS and a database language. Among other things, it provides a rock-solid foundation for integrating relational and object technologies. The proposed foundation represents an evolutionary step, not a revolutionary one; it builds on Codd's relational model of data and on the research that sprang from that work. It also incorporates a precise and comprehensive specification for a method of defining data types, including a comprehensive model of type inheritance, to address a lack that has been observed by many authorities; thus, it alsobuilds on research in the field of object orientation. With a sound footing in both camps of the object/relational divide, therefore, the Manifesto is offered as a firm foundation for the DBMSs of the future. Significant features of this new edition include: Major extensions to the inheritance model Significantly improved language proposals Improved discussions of read-only vs. update operators, selectors, THE_ operators, tuple types vs. possible representations, grouping and ungrouping, first normal form, assignment, constraints, predicates, and many other topics All SQL discussions upgraded to the level of the new SQL:1999 standard Several new appendixes 0201709287B04062001
RECONSTRUCTION OF PARTIALLY DAMAGED FACIAL IMAGE

This paper addresses the problem for Reconstruction of Partially damaged Human Facial image. This is an ill posed problem. The process of reconstruction goes through a series of basic operations in image processing. Images are combination of shape and texture, so the approach is to reconstruct the shape and texture using a facial image database [9]. The proposed method takes input as a damaged image (10% to 30%), and applies Statistical approach to reconstruct the facial image. Experimental results show that the reconstructed images are realistic and very close to the undamaged (Original) image.
Persian Sign Language Numbers Recognition Using Thinning Method

Sign language is the most natural way of communication for the people with hearing problems. One of its most appealing applications is developing a more effective interfacing of humanmachine interaction. A hand gesture recognition system can provide an opportunity for deaf persons to communicate with normal people without the need of an interpreter or intermediate. In this article, we propose a method to recognize the image-based numbers of Persian sign language (PSL) using thinning method on segmented image. In this approach, after cleaning thinned image, the real endpoints have been used for recognition. The method is qualified to provide real-time recognition and is not affected by hand rotation and scaling. Experimental results on 300 images show that our approach recognition rate is 96.6 % as average. Keywords-Persian Sign Language; Gesture Recognition; Segmentation; Static Hand Gesture Recognition; Thinning
Extensive own-language use: a case study of tertiary English language teaching in China

Recent literature on language teaching has questioned the established view that a language is most effectively taught monolingually, arguing instead that the student’s own language has an important role to play, and this view is now widely accepted. While this literature draws attention to the extremism of some monolingual approaches, and advocates a judicious use of the own language, it often neglects the many educational contexts in which a very high proportion of teaching is conducted in the students’ own language. This article addresses this issue and adds to the growing literature on classroom own-language use and its pedagogic functions by examining an instance of such large-quantity use of the own language in an ‘intensive reading’ tertiary English-language course in China. Through analysis of lesson transcripts and interviews with participants, it documents the uses and functions of Chinese, and teacher and student attitudes to it. It also discusses speculatively how the large-scale use of Chinese relates to the aims of the Chinese curriculum, western influences, the textbooks, and teaching style: all matters which merit further research.
Recognizing Textual Entailment With a Modified BLEU Algorithm

The BLEU algorithm was proposed as a baseline technique for the task of recognizing textual entailment (RTE) by (Perez & Alfonseca, 2005) in the first PASCAL RTE challenge. However, because the BLEU algorithm was designed as a metric for measuring the accuracy of automatically generated translations, certain features of the algorithm are not appropriate for RTE. Specifically, BLEU penalizes brevity both explicitly and implicitly in its scoring algorithm; since entailment hypothesis are very often short phrases, this behavior is not desirable in RTE. Therefore, this paper proposes a variation on the BLEU scoring algorithm that does not penalize brevity and can consistently outperform both the unmodified BLEU algorithm and a dumb baseline.
Predicting ESL learners’ oral proficiency by measuring the collocations in their spontaneous speech

Collocation, known as words that commonly co-occur, is a major category of formulaic language. There is now general consensus among language researchers that collocation is essential to effective language use in real-world communication situations (Ellis, 2008; Nesselhauf, 2005; Schmitt, 2010; Wray, 2002). Although a number of contemporary speech-processing theories assume the importance of formulaic language to spontaneous speaking (Bygate, 1987; de Bot, 1992; Kormos, 2006; Levelt, 1999), none of them gives an adequate explanation of the role that collocation plays in speech communication. In the practices of L2 speaking assessment, a test taker’s collocational performance is usually not separately scored mainly because human raters can only focus on a limited range of speech characteristics (Luoma, 2004). This paper argues for the centrality of collocation evaluation to communicationoriented L2 oral assessment. Based on a logical analysis of the conceptual connections among collocation, speech-processing theories, and rubrics for oral language assessment, I formulated a new construct called Spoken Collocational Competence (SCC). In light of Skehan’s (1998, 2009) trade-off hypothesis, I developed a series of measures for SCC, namely Operational Collocational Performance Measures (OCPMs), to cover three dimensions of learner collocation performance in spontaneous speaking: collocation accuracy, collocation complexity, and collocation fluency. I then investigated the empirical performance of these measures with 2344 lexical collocations extracted from sixty adult English as a second language (ESL) learners’ oral assessment data collected in two distinctive contexts of language use: conversing with an interlocutor on daily-life topics (or the SPEAK exam) and giving an academic lecture
Best Practice in RSS Measurements and Ranging

The term “ranging” is often used to indicate the operations that make it possible to estimate the distance between two nodes by processing some signals generated and/or received by the nodes. In wireless systems, a very popular ranging method makes use of the radio signal strength (RSS), which is a measure of the received radio signal power. However, RSS-based ranging is considered very inaccurate, particularly in indoor environments, mainly because of the randomness of the received signal power. In this tutorial paper, we provide an in-depth analysis of the main factors that affect the variability of the received signal power and the accuracy of the RSS measurements. Starting from a survey of the most common and widely accepted models for the radio signal propagation and the RSS-based ranging, we then focus our attention on some technological and procedural pitfalls that are often overlooked, but may significantly affect the accuracy of the RSS-based ranging, and we suggest possible techniques to alleviate such problems. The theoretical argumentation is backed up by a set of empirical results in different scenarios. We conclude this paper by providing some best-practice recommendations for proper RSS-based ranging estimation in wireless networks and discussing new approaches and open research challenges.
Entity Disambiguation With Comparable Entity Mining from Comparative Questions

Comparing substitute option is one of the necessary processes for making decision to take out each day. Though, it is not forever simple task to compare and other alternatives for each and every comparison. To perform this earlier work used a novel method to automatically extract equivalent entities from relative questions that are posted by online for each and every user . But the existing work it becomes difficult task to solve the entity ambiguity problem. To conquer these difficulty proposition numerous disambiguation formula/features and utilize a Markov logic network(MLN) to representation of interweaved constraints. It is one of the major types of entity linking method with genetic material state relating. Proposed MLN which is the combination of first order logic (FOL) and Markov networks with combination of NIL-filtering and entity disambiguation stages. For entity disambiguation problem the representation capture the entity information from background knowledge with familiar entities as well as the constraints while connecting an entity.
JPEG2000: A New Standard for Still Image Compression

With the increasing use of multimedia technologies, image compression requires higher performance as well as new functionality. To address this need in the specific area of still image encoding, a new standard is currently being designed: JPEG2000. We will see in this paper what the exact goals are of this future standard, which applications it addresses and the current standardisation process. Then we will show through the descriptions of two available demonstrations what kind of results are already reachable with the current status of the standard. The first demonstration describes a JAVA implementation of the future standard, details the advantages of such an implementation and compares the performance of JPEG2000 with that of JPEG. The second demonstration describes how JPEG2000 can be used in domains were the transmission bandwidth is very restricted, taking advantages of new functions such as the definition of Regions Of Interest and progressive transmission.
Obesity Management in Children on an iOS Device

The main objective of this paper is to create an application that makes use of gamification principles in order to teach and guide children and teens towards a healthier life and encourage them to lead it. The application also allows users to track their overall progress and it instructs them on how to proceed. While doing so it gives them tips and facts about improving their lifestyle. The application also tries to apply gamification techniques like having a sense of competition and providing feedback so that tasks like exercise are more engaging. To evaluate the application, a group of people made use of the application as they saw fit, for a period of time. The gamification techniques used were successful in giving them the desired experience. With the competitive element between friends encouraging them to make more use of the application and the tips and facts helping them towards a healthier lifestyle. The biggest concern was that the application did not encourage the users to keep using it as
SAR Image Compression and Reconstruction Based on Compressed Sensing

The appearance of multiplicative speckle noise in Synthetic Aperture Radar (SAR) imagery makes it very difficult to visualization and compression. This paper proposes a novel framework of Compressed Sensing (CS) to compress the SAR image. It combined the Nonsubsampled Contourlet Transform (NSCT) shrinkage method to SAR image sparse represent. And a modified Smoothed L0 norm (SL0) algorithm is used for SAR image accurate reconstruction. The experimental results show the proposed method is very effective and can get better reconstruction performances.