Miracle-dz/UniFAR-FTUs huggingface dataset:
Student volunteers perspectives on roles/functions of university counseling centers in Taiwan

This study discussed the student volunteers’ perspectives on the roles/functions of University Counseling Center (UCC). Fifteen student volunteers of a university in northern Taiwan participated. Phenomenological method was employed to analyze in-depth interviews. Themes emerged including volunteers viewed; roles and functions of UCC as enhancing the quality of mental health on campus, psychological and counseling education beneficial to students for comprehending counseling and UCC, specialized counseling services designed to take the initiative to reach out to students, and direct counseling interventions provided to tailor individual students’ needs. Participants suggested that UCPs should help students know more about UCC and the counseling profession. Students will “be familiarized with UCC, trust UCP, and visit UCC. ” Consequently, they will utilize UCC resources when needed. Key words: University counseling center, student volunteer, role and function.
A Longitudinal Study on the Psychological Well-Being of College Students

An inventory on the psychological well-being of college students was developed then given to a cohort of students in their freshman, sophomore and senior years. Overall, the well-being of students steadily improved. The largest improvements were in the social relations with staff and faculty, and with personal competencies such as self-discipline and academic skills. However, declines were also observed in health habits and spiritual practices. These results have implications for colleges interested in strengthening the wellbeing of their students. Poster presented at the 117th convention of the American Psychological Association, 2009. The author can be contacted at the Department of Psychology, St. Bonaventure University, St. Bonaventure, NY, 14778. More information on the Inventory of Learning Climate and Student Well-Being is available at wellbeingincollege.org
Review of selected research in applied linguistics published in Australia (2008–2014)

This article reviews the significant and diverse range of research in applied linguistics published in Australia in the period 2008–2014. Whilst acknowledging that a great deal of research by Australian scholars has been published internationally during these seven years, this review is based on books, journal articles, and conference proceedings published in Australia. Many of these sources will be unfamiliar to an international audience, and the purpose of this article is to highlight this body of research and the themes emerging from it. The journals selected in this review include Australian Journal of Language and Literacy, Australian Review of Applied Linguistics (ARAL), BABEL, English in Australia, English Australia, Papers in Language Testing and Assessment, Prospect: An Australian Journal of TESOL, TESOL in Context, and University of Sydney Papers in TESOL. Selected refereed proceedings are from key national conferences including: ALAA (Applied Linguistics Association of Australia), ACTA (Australian Council of TESOL Association), ASFLA (Australian Systemic Functional Linguistics Association), and ALS (Australian Linguistics Society). Our review of selected applied linguistics work revolves around the following themes: the responses to the needs of government planning and policy; the complexity of Australia's multicultural, multilingual society; the concern for recognizing context and culture as key factors in language and language learning; social activism in supporting language pedagogy and literacy programmes at all levels of education; and acknowledgement of the unique place held by Indigenous languages and Aboriginal English in the national linguistic landscape.
Financial Statement Fraud Detection by Data Mining

------------------------------------------------------------------- ABSTRACT ---------------------------------------------------------------------- Financial losses due to financial statement frauds (FSF) are increasing day by day in the world. The industry recognizes the problem and is just now starting to act. Although prevention is the best way to reduce frauds, fraudsters are adaptive and will usually find ways to circumvent such measures. Detecting fraud is essential once prevention mechanism has failed. Several data mining algorithms have been developed that allow one to extract relevant knowledge from a large amount of data like fraudulent financial statements to detect FSF. It is an attempt to detect FSF ; We present a generic framework to do our analysis.
Casson-Lin's invariant of a knot and Floer homology

A. Casson defined an intersection number invariant which can be roughly thought of as the number of conjugacy classes of irreducible representations of $\pi_1(Y)$ into $SU(2)$ counted with signs, where $Y$ is an oriented integral homology 3-sphere. X.S. Lin defined an similar invariant (signature of a knot) to a braid representative of a knot in $S^3$. In this paper, we give a natural generalization of the Casson-Lin's invariant to be (instead of using the instanton Floer homology) the symplectic Floer homology for the representation space (one singular point) of $\pi_1(S^3 \setminus K)$ into $SU(2)$ with trace-free along all meridians. The symplectic Floer homology of braids is a new invariant of knots and its Euler number of such a symplectic Floer homology is the negative of the Casson-Lin's invariant.
Diagnosis of Clostridium difficile Infection: an Ongoing Conundrum for Clinicians and for Clinical Laboratories

SUMMARY Clostridium difficile is a formidable nosocomial and community-acquired pathogen, causing clinical presentations ranging from asymptomatic colonization to self-limiting diarrhea to toxic megacolon and fulminant colitis. Since the early 2000s, the incidence of C. difficile disease has increased dramatically, and this is thought to be due to the emergence of new strain types. For many years, the mainstay of C. difficile disease diagnosis was enzyme immunoassays for detection of the C. difficile toxin(s), although it is now generally accepted that these assays lack sensitivity. A number of molecular assays are commercially available for the detection of C. difficile. This review covers the history and biology of C. difficile and provides an in-depth discussion of the laboratory methods used for the diagnosis of C. difficile infection (CDI). In addition, strain typing methods for C. difficile and the evolving epidemiology of colonization and infection with this organism are discussed. Finally, considerations for diagnosing C. difficile disease in special patient populations, such as children, oncology patients, transplant patients, and patients with inflammatory bowel disease, are described. As detection of C. difficile in clinical specimens does not always equate with disease, the diagnosis of C. difficile infection continues to be a challenge for both laboratories and clinicians.
A Bitmap-Based Algorithm for Detecting Stealthy Superpoints

The host cardinality refers to the number of different peers that an Internet host communicates with. Stealthy superpoint is a host that its cardinality is between two thresholds during a measurement period. Detecting stealthy superpoints helps intrusion systems identify potential attackers. However, stealthy superpoints may perform scanning deliberately at a low rate, and they can easily evade the detection. The existing algorithm can not directly be used to detect them. This paper proposes an algorithm based on Bitmap which can detect stealthy superpoints. The algorithm includes online module and offline module. The online module consists of two submodules. One uses a bloom filter to filter the duplicate packets and store the source addresses. The other uses two-dimensional bit arrays to process packets. The offline estimates the cardinality. The theoretical analysis and experimental results show that our algorithm can precisely detect stealthy superpoints and estimate their cardinalities.
Representing Kidney Development Using the Gene Ontology

Gene Ontology (GO) provides dynamic controlled vocabularies to aid in the description of the functional biological attributes and subcellular locations of gene products from all taxonomic groups (www.geneontology.org). Here we describe collaboration between the renal biomedical research community and the GO Consortium to improve the quality and quantity of GO terms describing renal development. In the associated annotation activity, the new and revised terms were associated with gene products involved in renal development and function. This project resulted in a total of 522 GO terms being added to the ontology and the creation of approximately 9,600 kidney-related GO term associations to 940 UniProt Knowledgebase (UniProtKB) entries, covering 66 taxonomic groups. We demonstrate the impact of these improvements on the interpretation of GO term analyses performed on genes differentially expressed in kidney glomeruli affected by diabetic nephropathy. In summary, we have produced a resource that can be utilized in the interpretation of data from small- and large-scale experiments investigating molecular mechanisms of kidney function and development and thereby help towards alleviating renal disease.
The Necessary And Sufficient Condition for Generalized Demixing

Demixing is the problem of identifying multiple structured signals from a superimposed observation. This work analyzes a general framework, based on convex optimization, for solving demixing problems. We present a new solution to determine whether or not a specific convex optimization problem built for generalized demixing is successful. This solution will also bring about the possibility to estimate the probability of success by the approximate kinematic formula.
Quartz: a framework for correct and efficient reconfigurable design

We present Quartz, the first language supporting advanced features such as polymorphism, overloading, formal reasoning and generic VHDL library compilation, for correct and efficient reconfigurable design. Quartz is designed to support formal reasoning for design verification and generic optimisation strategies can be captured as algebraic transformations; the correctness of such transformations has been established using the Isabelle theorem prover. The parameterisation supported by Quartz higher-order combinators makes the expression of regular designs with a parameterised level of pipelining much easier than the equivalent in VHDL. The language also supports reconfiguration through the use of virtual multiplexer blocks. We have used Quartz to describe a range of designs with parameterised pipelining, and investigated the different tradeoffs in speed, size and power consumption. For designs where pipeline registers can reduce glitch propagation, increasing the level of pipelining can reduce power consumption by as much as 90%
Sequential Learning for Dialog Act Classification in Tutorial Dialog

Dialog act classification or tagging is the task of assigning labels such as “question”, “assertion”, “positive feedback” and “negative feedback” to the turns in a dialog. In this project, we study the dialog act classification task as applied to human-human tutoring dialogs in the domain of thermodynamics. We initially establish a baseline by posing the task as a classification problem and applying three supervised machine learning methods. We then view the task as a sequential labeling problem, to make use of previous dialog act labels for predicting future labels and compare the performance of sequential labeling algorithms with the baseline accuracy. The best performing sequential algorithm shows 5.59% improvement in macro-averaged accuracy over the best baseline algorithm.
At the Limits of Species Being: Sensing the Anthropocene

Autonomous Marxism has generated a lexicon for responding to transformations in human labor, particularly around the role of technological development. Autonomists have mapped how the conditions of post-Fordism have put elements of the mind, sociability, virtuosity—or “the soul” in Franco Berardi's terms—to work. But that labor, in accordance with capitalist valorization, is nearly always human. At best, it is human labor supplemented with machines. But what are we to make of the lively materials—of human and nonhuman provenance alike—now at “work” alongside us? This essay takes up this question in an analysis of the field of biosensing. It explores Marx's concepts of species being and the general intellect to reconsider what can be said of “living labor” and its potential at a time when nonhuman life is increasingly a central component of production. It suggests that alongside the so-called Anthropocene, biosensing marks a redistribution of both the work and the precarity associated with our mode of production. While the field forges engagements with nonhuman others and a growing awareness of planetary life, it also operates according to an imaginary of planetary management, the possibility of producing for a collective health and the “whole of nature. ”
KD-KNN Text Categorization Method Based On Improvement TFI-DF

Text categorization under the assigned classification system, uses natural languages to express texts that sort automatically into the pre-set type set according to its contents and makes a piece of text correspond to one (several) type(s) of type set. In order to enhance the categorization performance, this paper proposes the improved TFI-DF feature extraction method and kernel-based distance-weighted KNN algorithm with the improved TFI-DF feature selection method to preprocess the data source and set up the space vector model, which provides a convenient data structure for text categorization, and enhances the precision of the feature selection method. The KNN algorithm (kernel-based distance-weighted KNN) has solved the multi-peak distribution and boundary overlap problems of samples and the precise classified decision problem of classifiers. The experimental system has proved the effectiveness of the new method.
A reranking method for syntactic parsing with heterogeneous treebanks

In the field of natural language processing (NLP), there often exist multiple corpora with different annotation standards for the same task. In this paper, we take syntactic parsing as a case study and propose a reranking method which is able to make direct use of disparate treebanks simultaneously without using techniques such as treebank conversion. The method proceeds in three steps: 1) build parsers on individual treebanks; 2) use parsers independently to generate n-best lists for each sentence in test set; 3) rerank individual n-best lists which correspond to the same sentence by using consensus information exchanged among these n-best lists. Experimental results on two open Chinese treebanks show that our method significantly outperforms the baseline system by 0.84% and 0.53% respectively.
Push-pull techniques in peer-to-peer video streaming systems with tree/forest topology

Peer-to-peer video streaming systems are overlay networks used to distribute, among other types of content, live video content to large sets of users by relying on computing and network resources directly provided by users that are receiving video streaming services. Peer-to-peer video streaming systems with tree or forest topology are typically push-based, since the video content is provided by parent peers with no need for periodical requests. In this paper we analyze the impact of two complementing pull-based mechanisms aiming at improving the overall performance of the overlay network. Results show that the proposed hybrid push-pull approaches can be beneficial when the stability of the system is low, i.e., the average permanence time of peers is short.
Construction of block-LDPC codes based on quadratic permutation polynomials

A new block low-density parity-check (Block-LDPC) code based on quadratic permutation polynomials (QPPs) is proposed. The parity-check matrix of the Block-LDPC code is composed of a group of permutation submatrices that correspond to QPPs. The scheme provides a large range of implementable LDPC codes. Indeed, the most popular quasi-cyclic LDPC (QC-LDPC) codes are just a subset of this scheme. Simulation results indicate that the proposed scheme can offer similar error performance and implementation complexity as the popular QC-LDPC codes.
An Unfolding-Based Semantics for Logic Programming with Aggregates

The paper presents two equivalent definitions of answer sets for logic programs with aggregates. These definitions build on the notion of unfolding of aggregates, and they are aimed at creating methodologies to translate logic programs with aggregates to normal logic programs or positive programs, whose answer set semantics can be used to defined the semantics of the original programs. The first definition provides an alternative view of the semantics for logic programming with aggregates described by Pelov et al. The second definition is similar to the traditional answer set definition for normal logic programs, in that, given a logic program with aggregates and an interpretation, the unfolding process produces a positive program. The paper shows how this definition can be extended to consider aggregates in the head of the rules. The proposed views of logic programming with aggregates are simple and coincide with the ultimate stable model semantics, and with other semantic characterizations for large classes of program (e.g., programs with monotone aggregates and programs that are aggregate-stratified). Moreover, it can be directly employed to support an implementation using available answer set solvers. The paper describes a system, called ASP^A, that is capable of computing answer sets of programs with arbitrary (e.g., recursively defined) aggregates.
Prolongation of Network Lifetime with Centralized Clustering Scheme Considering Residual Energy of Wireless Sensor Node

We propose details of a novel clustering scheme which combines distributed clustering considering local node density and centralized clustering considering residual energy of sensor nodes. Our scheme dynamically adjusts to a recommended numbers of clusters and cluster size. Differing to existing clustering schemes, our scheme deploys a base station that selects proper cluster heads based on their residual energy. Our scheme greatly extends network lifetime as compare to existing schemes.
Particle swarm optimization-based clustering and classification algorithms for analyzing DNA chip data

DNA chips are used for experiments on genes and provide useful information that could be further analyzed. Instead of experimenting with real genes which are expensive, DNA chips are increasingly being used for biological experiments. The data provided by the DNA chips could be represented as a two dimensional matrix, in which one axis represent genes and the other represent samples. Extracting data from the DNA chips with high accuracy and finding out the patterns or useful information from such data has become a very important issue. Some commonly used methods to find meaningful information from the data are clustering and classification. In this paper, we propose clustering and classification mechanisms that are based on the Particle Swarm Optimization algorithm. Considering that DNA chip data is extremely large and has a fuzzy characteristic, an algorithm that imitates the ecosystem such as the Particle Swarm Optimization algorithm is suitable to be used for analyzing such data. Experiments show that the algorithms can efficiently cluster and classify DNA chip data.
Iterative algorithm for inferring entity types from enumerative descriptions

Entity type matching has many real world applications, especially in entity clustering, de-duplication and efficient query processing. Current methods to extract entities from text usually disregard regularities in the order of entities appearing in the text. In this paper, we focus on enumerative descriptions which enlist entity names in a certain hidden order, often occurring in web documents as listings and tables. We propose an algorithm to discover entity types from enumerative descriptions, where a type hierarchy is known but enumerating orders are hidden and heterogeneous, and partial entity-type mappings are given as seed instances. Our algorithm is iterative: We extract skeletons from syntactic patterns, then train a hidden Markov model to find an optimum enumerating order from seed instances and skeletons, to find a best-fit entity-type assignment.
A GALS Network-on-Chip based on rationally-related frequencies

GALS Networks-on-Chip (NoCs) in which the frequency of every switch can be set independently would enable per-node DVFS without requiring asynchronous switch design. However, traditional GALS interfaces introduce high latency penalties and are therefore ill-suited for inter-switch links in a NoC. In this paper we introduce and study a GALS Network-on-Chip based on the Globally-Ratiochronous, Locally-Synchronous (GRLS) paradigm. GRLS constrains all switch frequencies to be rationally-related but enables the use of efficient interfaces which reduce the latency of the network 60% compared to GALS solutions and obtains better throughput-per-power ratios compared to synchronous and mesochronous solutions.
Sparsity-promoting optimal control for a class of distributed systems

We consider a linear quadratic optimal control problem with an additional penalty on the number of communication links in the distributed controller. We reformulate this combinatorial optimization problem as a sequence of weighted l1 problems, where the weighted l1 norm approximates the counting of the communication links. We identify a class of systems for which the weighted l1 problem can be formulated as a semideflnite program and therefore its solution can be computed efficiently. Application of the developed algorithm to the optimal control of vehicular formations reveals communication topologies that become sparser as the price of inter-vehicular communications is increased.
Duygusal Yılmazlık Ölçeğinin Türkçeye Uyarlanması: Güvenirlik ve Geçerlik Çalışması

Bu arastirmanin amaci Duygusal Yilmazlik Olceginin Turkceye uyarlanmasi ve psikometrik ozelliklerinin arastirilmasidir. Olcegin yapi gecerligini belirlemek icin Acimlayici Faktor Analizi (AFA) yapilmistir. AFA’dan elde edilen madde-faktor yapisinin dogrulayici faktor analizi (DFA) ile model uyumu test edilmistir. Olcegin ic tutarligi icin tum olcegin Cronbach Alpha katsayisi . 83 olarak hesaplanmistir. Madde toplam test korelâsyonlari ise . 25 ilâ . 53 arasinda degismektedir. Olcegin guvenirligiyle ilgili olarak yapisal guvenirlik olarak adlandirilan hesaplamalar yapilmistir. Olcegin guvenirligi ile ilgili yapilan son calisma ise test - tekrar test uygulamasidir. Iki olcum arasindaki korelasyon . 91 olarak bulunmustur. Sonuc olarak, Duygusal Yilmazlik Olceginin yapisal olarak uc alt boyut puani verdigi; psikometrik ozelliklerinin ise yeterli duzeyde oldugu soylenebilir.