Miracle-dz/UniFAR-FTUs huggingface dataset:
Word Orientation Recognition Based on Semantic Analysis

With the development of internet and the rising of people's demand for information,the research on text orientation recognition is promising and challenging.As the basis of the text orientation recognition, the semantic orientation research of single word is presented in this paper.Using the integrated and detailed definitions of words in HowNet,two seed sets are built by the words with intense sentiment orientation.Then,with the context,the orientation similarity between seed words and common ones is calculated to recognize the sentiment orientation of the latter.The experimental results show that by the proposed method good results can be obtained in common word orientation recognition.Moreover,this method is of certain practical value for large granularity research.
Task Effects on Linguistic Complexity and Accuracy: A Large-Scale Learner Corpus Analysis Employing Natural Language Processing Techniques

Large-scale learner corpora collected from online language learning platforms, such as the EF-Cambridge Open Language Database (EFCAMDAT), provide opportunities to analyze learner data at an unprecedented scale. However, interpreting the learner language in such corpora requires a precise understanding of tasks: Howdoes the prompt and input of a task and its functional requirements influence task-based linguistic performance? This question is vital for making large-scale task-based corpora fruitful for second language acquisition research. We explore the issue through an analysis of selected tasks in EFCAMDAT and the complexity and accuracy of the language they elicit.
Breaking Binaries: #BlackGirlMagic and the Black Ratchet Imagination.

: CaShawn Thompson’s hashtag, #BlackGirlMagic, has transformed into a movement over the past five years. The hashtag focuses on celebrating the beauty, influence, and strength of Black women and girls. However, Thompson’s term sits in a space of tension, where contradictory interpretations create boundaries around what Black girl celebration means as well as who gets to celebrate Black girl magic, specifically when it comes to girls without a celebrity status and girls who are considered hood or ratchet. In this paper, the author contends that the tension between respectability and ratchetness must be further explored, as it is an essential component in discussions of Black girl identities. To do this, the Afrofuturist young adult literature of Nnedi Okorafor is analyzed using a conceptual framework that highlights the Black Ratchet Imagination and its aversion to respectability politics and the ways in which Afrofuturism challenges notions of respectability in terms of traditional Black literary cultural production. Findings suggest that, although each character, like real Black girls, exhibits traits of respectability, they also depict traits of ratchetness. Thus, the author calls for all literacy stakeholders to dissolve preconceived binaries and conceptualize ratchetness as another celebratory space of agency and Black Girl Magic.
Security of Passwords

Authentication has become a very important security mechanism. Recently, many attackers have been looking to attack organisations’password databases, since they are the sources which attackers can potentially used to gain unauthorised access to information, network and resources. Therefore, it is important to understand how to securely choose and store passwords in such a way that it can prevent attackers from learning what the users’passwords are. This paper discusses many aspects of password security, starting from a way to generate a secure password to ways to securely store a password. It will be explained that the most common method used to store passwords today, i.e., MD5 or SHA-1 hashing, may not be the best solution. Thus, better solutions in salting passwords and using slower hash functions are introduced.
Mathematical Representation, Modeling and Linearization for Fixed Wing UAV

The UAV is an acronym for Unmanned Aerial Vehicle, which is an aircraft without pilot on board. UAVs can be remote controlled by a pilot at a ground control station or can fly autonomously base on pre-programmed flight plans or more complex dynamic automation systems. Technology advancements have enabled the development of it to do many excellent jobs as reconnaissance, surveillance, battle fighters, and communications relays. Simulating an unmanned aerial vehicle (UAV) dynamics and analyzing its behavior at the preflight stage is too important and more efficient. In this paper, shows a mathematical modeling of the aircraft and derivation full non-linear equations of motion on modeling technique (Ultrastick-25e) and then the linearized airframe transfer function is derived in longitudinal and lateral plane via two synthesis, Jacobin and analytical manipulation from the derived equation of motion. And show the validation of analytical linearization transfer function with Jacobin and nonlinear model in each lateral and longitudinal channel.
Expanding Evidence Approaches for Learning in a Digital World.

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RESEARCH ON WEB TEXT MINING

With the flood of information on the Web, Web mining is a new research issue which draws great interest from many communities. Currently, there is no agreement about Web mining yet. It needs more discussion among scientists in order to define what it is exactly. Meanwhile, the development of Web mining system will promote its research in turn. In this paper, a systemic discussion about the principle of Web mining is presented, including the definition, the relationship between information mining and retrieval on the Web, the taxonomy and function. Then the methods of text mining on the Web are discussed in detail and a prototype of Web text mining system WebMiner is introduced. WebMiner is a multi agent system which combines text mining and multi dimension text analysis in order to help user in mining HTML documents on the Web efficiently and effectively.
Real-time depth camera tracking with geometrically stable weight algorithm

Abstract. We present an approach for real-time camera tracking with depth stream. Existing methods are prone to drift in sceneries without sufficient geometric information. First, we propose a new weight method for an iterative closest point algorithm commonly used in real-time dense mapping and tracking systems. By detecting uncertainty in pose and increasing weight of points that constrain unstable transformations, our system achieves accurate and robust trajectory estimation results. Our pipeline can be fully parallelized with GPU and incorporated into the current real-time depth camera tracking system seamlessly. Second, we compare the state-of-the-art weight algorithms and propose a weight degradation algorithm according to the measurement characteristics of a consumer depth camera. Third, we use Nvidia Kepler Shuffle instructions during warp and block reduction to improve the efficiency of our system. Results on the public TUM RGB-D database benchmark demonstrate that our camera tracking system achieves state-of-the-art results both in accuracy and efficiency.
BEBaC user manual

BEBaC [1] (Bayesian estimation of bacterial communities) is a software devoting to estimate bacterial communities from large amounts of deep sequencing data of 16S rRNA gene. A dataset which contains 4K~100K reads of length 400bp~2000bp is suitable for BEBaC. Larger datasets are also possible, but we have not tested on these datasets. Here “reads” means DNA sequences produced by a sequencing machine.
Data-Driven Learning: The Perpetual Enigma

Many uses have been found for corpora in language teaching and learning, most radically perhaps where learners explore the data themselves. Such procedures are especially associated with Tim Johns, who proposed what he called ‘data-driven learning’ over 20 years ago. While he described his techniques in detail in a number of papers, researchers and practitioners over the years have adapted Johns’ procedures and invented new ones of their own, with the result that it can be difficult to pin down exactly what DDL is. In a tribute to Johns, this paper traces the evolution of DDL through his work from 1984 up until his death in 2009, as well as in DDL studies by other researchers. The enormous variety of activities possible with corpora means it is difficult if not impossible to identify any single element which is either necessary or sufficient for an activity to qualify as DDL. This paper therefore defends a prototype definition of DDL: the further an activity is from the central, prototypical core, the less DDL-like it is, but any cut-off point beyond which we might like to say ‘this is no longer DDL’ seems likely to be arbitrary rather than empirically grounded or based on a coherent, hermetic definition.
Application Study of Hidden Markov Model Based on Genetic Algorithm in Noun Phrase Identification

To increase further the accuracy of noun phrase(NP)identification and utilize features of the genetic algorithm(GA)and the hidden markov model(HMM),a novel HMM identification method based on GA was proposed.The method was based on a high-performance POS(parts of speech)tagging.During the training phase,model parameters were gained by the genetic algorithm.And during the identifying phase,an improved Viterbi algorithm for dynamic programming was first presented to identify the same hierarchy noun phrase,then the combination method of hierarchical syntax parsing and Viterbi algorithm was brought forward to identify those recursive noun phrases.Experimental results show that this combined algorithm has achieved a high precision and recall rate of 94.78% and 94.29%,respectively,fully inosculating the strength of genetic algorithms and hidden markov model.This proves that the combination method has much better identification effect than the unitary hidden markov model identification approach.
KeyNote Trust Management System

The trust management approach , introduced by Blaze, is a unified and flexible approach that allows direct authorization of security-critical actions in open and distributed applications. This paper gives an overview of trust management and a brief discussion of related works, describes the implementation specification of KeyNote trust management system, and aims to facilitate the use of trust manage approach in a variety of network services.
Algorithms for Source Separation - with Cocktail Party Applications

Many apparently difficult problems can be solved by reduction to linear programming. Such problems are often subproblems within larger systems. When gradient optimisation of the entire larger system is desired, it is necessary to propagate gradients through the internally-invoked LP solver. For instance, when an intermediate quantity z is the solution to a linear program involving constraint matrix A, a vector of sensitivities dE/dz will induce sensitivities dE/dA. Here we show how these can be efficiently calculated, when they exist. This allows algorithmic differentiation to be applied to algorithms that invoke linear programming solvers as subroutines, as is common when using sparse representations in signal processing. Here we apply it to gradient optimisation of overcomplete dictionaries for maximally sparse representations of a speech corpus. The dictionaries are employed in a single-channel speech separation task, leading to 5 dB and 8 dB target-to-interference ratio improvements for same-gender and opposite-gender mixtures, respectively. Furthermore, the dictionaries are successfully applied to a speaker identification task.
Comparative Study of Several Simulated Annealing Algorithms for Optimal Arrangement Problem in Multi-state Consecutive-k-out-of-n:F System

In a multi-state consecutive-k-out-of-n:F system, both the system and its components are allowed to be in two or more possible states. One of the most important problems for this system is to obtain the optimal arrangement that maximizes the expectation of the syst em state. Many researchers have studied the optimal arrangement problem in a multi-state consecutive-k-out-of-n:F system. However, the optimal solution for this problem is obtained by calculating the expectation of the system state as an enumeration method. As the number of n increases, the number of calculations becomes too many to obtain the optimal solution within a reasonable time even if a high-performance computer is used. Therefore, to solve optimal arrangement problem quickly, simulated annealing (SA), which is a kind of metaheuristics, was applied to the optimal arrangement problem in a multi state consecutive-k-out-of-n:F system. However, although it is possible obtain a solution for the optimal arrangement problem using a simulated annealing algorithm, there is no guarantee that the solution is optimal. Therefore, the simulated annealing algorithm applied to an optimal arrangement problem in a multi-state consecutive-k-out-of-n:F system must be improved in order to search more efficiently. In this paper, we propose three types of simulated annealing algorithms with the aim of obtaining an optimal arrangement efficiently. We execute numerical experiments to compare their performances and investigate the efficiencies of these algorithms.
Resource-aware business process management : analysis and support

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A schema modification methodology for an objet-oriented database system

Proper and efficient handling of schema changes is an important aspect of any object-oriented database management system. This paper deals with the definition of a schema modification methodology for ODS; an object-oriented database management system prototype designed at Bilken University. A brief description of the basic features of ODS is included to facilitate the treatment. The invariants of the class lattice as well as the rules for resolving ambiguities due to schema changes are identified. In addition, schema changes handled by ODS are described within the realm of the specified invariants and rules. The described methodology efficiently handles deletions which are unmanagable in object-oriented systems due to the unidirectional relationship between objects in different classes.
Variance error quantifications that are exact for finite model order

This paper is concerned with the frequency domain quantification of noise induced errors in dynamic system estimates. Preceding seminal work on this problem provides general expressions that are approximations whose accuracy increases with observed data length and model order. In the interests of improved accuracy, this paper provides new expressions whose accuracy depends only on data length. They are therefore 'exact' for arbitrarily small true model order and apply to the general cases of output-error and box-Jenkins model structures.
Exploring Electronic HRM: Management Fashion or Fad?

At the end of the 1990s and in the early 2000s organisations started to adopt electronic human resource management (e-HRM). This was motivated by assurances that it would reduce paperwork, make HR processes more efficient, improve HR’s service quality and allow HR to become a more strategic business partner. HR and IT scholars quickly ‘jumped on’ the ‘e-HRM train’. They questioned these promises and sought to provide more solid insights on e-HRM implementation, adoption and its impact. Defining e-HRM did not seem to be that easy, as many definitions have been proposed in scholarly work. Today, the most cited definition of e-HRM describes it as either a set of information technology (IT) applications that cover ‘all possible integration mechanisms and contents between HRM and is aiming at creating value within and across organisations for targeted employees and management’ (Bondarouk & Ruël, 2009, p. 507), or ‘the planning, implementation and application of IT for both networking and supporting at least two individual or collective actors in their shared performing of HR activities’ (Strohmeier, 2007, p. 20). Today, the accumulated scholarly literature on e-HRM has provided findings on whether e-HRM reduces the administrative burden under certain circumstances, improves HRM service quality and improves HR’s strategic orientation (Bondarouk & Ruël, 2013). A still growing group of e-HRM scholars also have researched the changing role of the HR function towards becoming a business partner, for example using HR metrics for strategic decision-making (Hendrickson, 2003) and the empowerment of managers through the development and support of management capacity to conduct HR activities (Parry & Tyson, 2011). Some studies show that e-HRM increases the time available for strategic HR issues (such as strategic people management activities) because of the automation of routine HR tasks (Bondarouk & Ruël, 2013; 16
Cohesion-based Sentence Ordering for Multi-document Summarization

Sentence ordering is a difficult but an important task for multi-document summarization. A wrong order of sentences not only makes it difficult to be understood but also convey entirely different ideas to the reader. In this paper, we describe two naive ordering algorithms and give the reasons why they do not perform well. We propose a new sentence ordering algorithm, which combines constraints from majority order of themes and cohesion. This algorithm ensures: if the cohesion between two themes is bigger than the threshold value, then the sentences of the two themes would be placed to the adjacent location in the final summary. Experimental results show that summary generated by our improved sentence ordering algorithm is more coherent and more readable than the two naive algorithms.
Research on Event Type Identification for Chinese Event Extraction

This paper proposes a new model for event type identification, namely: event mention based model. The model is divided into two steps: 1) filter out non-event sentences and obtain candidate event instances; 2) assign each candidate event instance with a specific event type, with the help of the multi-classification strategy. The experimental results on the ACE 2005 corpus show that our model is effective for the Chinese event type identification task.
Mode system effects in an online panel study : Comparing a probability-based online panel with two face-to-face reference surveys

One of the methods for evaluating online panels in terms of data quality is comparing the estimates that the panels provide with benchmark sources. For probability-based online panels, high-quality surveys or government statistics can be used as references. If differences among the benchmark and the online panel estimates are found, these can have several causes. First, the question wordings can differ between the sources, which can lead to differences in measurement. Second, the reference and the online panel may not be comparable in terms of sample composition. Finally, since the reference estimates are usually collected face-to-face or by telephone, mode effects might be expected. In this article, we investigate mode system effects, an alternative to mode effects that does not focus solely on measurement differences between the modes, but also incorporates survey design features into the comparison. The data from a probability-based offline-recruited online panel is compared to the data from two face-to-face surveys with almost identical recruitment protocols. In the analysis, the distinction is made between factual and attitudinal questions. We report both effect sizes of the differences and significances. The results show that the online panel differs from face-to-face surveys in both attitudinal and factual measures. However, the reference surveys only differ in attitudinal measures and show no significant differences for factual questions. We attribute this to the instability of attitudes and thus show the importance of triangulation and using two surveys of the same mode for comparison.
Crosstalk Reduction of Glasses-free 3D Displays using Multiview Image Processing

In this paper, we present a new method to reduce crosstalk of a glasses-free three-dimensional (3D) display using a multi-view image processing technique. Since crosstalk makes the current view image mixed with its neighboring ones, the output 3D image becomes severely blurred. We apply adaptive depth retargeting and view gradient-based crosstalk inverse filtering onto a multi-view image to minimize crosstalk of the glasses-free 3D display. In addition, overflow and underflow pixels are compensated by epipolar image pixel interpolation so that visual artifacts are minimized. Experimental results show that the proposed method reduces crosstalk more efficiently than the previous work while improving 3D image quality.
A Novice’s Perception of Partial Homomorphic Encryption Schemes

Objectives: Homomorphic Encryption is a way of performing computations on encrypted data. In this paper, we explore two famous Homomorphic Encryption schemes (RSA and ElGamal) with illustrations and related security issues. Methods/ Analysis: Both RSA and ElGamal encryption techniques possess multiplicative homomorphic property. These algorithms support only one operation (multiplication) on encrypted data and so they are termed as partial homomorphic encryption schemes. By using RSA and ElGamal, the encrypted data could be multiplied together without performing decryption. If needed, the results after such computations could be returned in decrypted form. This scheme reduces computation time and increases security and privacy of data being processed. Findings: It has been described how RSA and ElGamal algorithms perform key generation, encryption and decryption with simple illustrations. It has also been proved that RSA and ElGamal algorithms support multiplication operation on encrypted data with examples. Improvement/Applications: Many organizations rely on third party to outsource their large amount of electronic data for storage. It may be needed to perform some computations on the encrypted data on the server side provided by untrusted third party. Homomorphic Encryption will be much useful in such applications.