Miracle-dz/UniFAR-FTUs huggingface dataset:
Student’s strategies in building coherence in writing English essay

Building coherence in writing English essay is not easy as what people imagined. The writer should maintain the ideas from the first paragraph to the end of paragraph. Coherence can be achieved to the use of appropriate transition signals to link the ideas, pronouns consistency, repetition of keyword, and logical order arrangement. In other words, all the sentences must be linked with the right use of transition signals as the conjunction, pronouns reference consistently, repeat keyword or repeat the idea as the sign for the writer and the reader when reading the text, and arrange the idea chronologically. This study aims to find out the student’s strategies in building coherence for writing English essay and the student’s reasons for selecting the strategies. This study uses descriptive qualitative design. Based on the findings, this research figured out that the use of transition signals was 59%, 25% consistent pronouns, 15% repetition of keywords, and 1 % logical order arrangement. Furthermore, the student’s reasons for selecting the strategies is categorized to each strategy. The students used transition signals to connect the sentences, explain the topic, and organize the sentence. In using consistent pronouns all students argued that it used to replace the subjects, objects, names of people, things, and so on. The students used repetition of keyword to make the readers remember about the topics discussed in essay and maintain the topic from the beginning to the end. In arranging the ideas in logical order, the way students arrange is based on their experience and the lecture’s outline.
“I don’t even know where Turkey is.”: Developing intercultural competence through e-pal exchanges

Using current events to help preservice teachers understand the world they live in encourages preservice teachers to learn about global issues. It also encourages them to develop skills in analytical thinking and reflective judgment by reading and discussing complex real-life scenarios. A semester-long pen-pal project was crafted to help understand how preservice teachers develop intercultural competence, critical empathy, and become less ethnocentric. Twenty-Six American early childhood preservice teachers in a Midwestern state were randomly paired with Turkish early childhood preserivce teachers as their pen-pals. The findings of this qualitative study revealed American preservice teachers had learning curves, but many eventually came to unpack their privileges and preconceived notions, as well as expend their worldviews. Implications of how to assist preservice teachers to work with culturally and linguistically diverse students are addressed.
Distributed Control of Spatially Invariant Systems in Multiple Dimensions : A Structure Preserving Computational Technique

We consider the problem of analysis and control of discretely distributed systems in multidimensional arrays or lattices. For spatially(shift) invariant systems distributed in one spatial dimension, we build an efficient arithmetic that preserves the rational Laurent operator structure, leading to fast iterative methods of solving Lyapunov and Riccati equations and block diagonalizations, and thus arbitrarily non-conservative stability, H2 and H∞ analysis and H2 and H∞ distributed controller synthesis. These one-dimensional results are then used to build an efficient arithmetic and controller synthesis procedure in two dimensions, and by induction n-dimensions. The extension of these techniques from Laurent operators with rational symbols to sequentially semi-separable matrices yields a procedure for linear computational complexity analysis and controller synthesis for finite extent heterogeneous multidimensional systems with boundary conditions. The accuracy and versatility of the procedures are demonstrated on two computational examples.
Using matrices to model symbolic relationships

We describe a way of learning matrix representations of objects and relationships. The goal of learning is to allow multiplication of matrices to represent symbolic relationships between objects and symbolic relationships between relationships, which is the main novelty of the method. We demonstrate that this leads to excellent generalization in two different domains: modular arithmetic and family relationships. We show that the same system can learn first-order propositions such as(2, 5) ∈ +3 or (Christopher, Penelope) ∈ has wife, and higher-order propositions such as (3,+3) ∈ plus and (+3,−3) ∈ inverse or (has husband, has wife) ∈ higher oppsex. We further demonstrate that the system understands how higher-order propositions are related to first-order ones by showing that it can correctly answer questions about first-order propositions involving the relations +3 or has wife even though it has not been trained on any first-order examples involving these relations.
A Multicultural Approach in Music Information Research

Our information technologies do not respond to the world's multicultural reality; in fact, we are imposing the paradigms of our market-driven western culture also on IT, thus facilitating the access of a small part of the world’s information to a small part of the world's population. The current IT research efforts may even make it worse, and future IT will accentuate this information bias. Most IT research is being carried out with a western centered approach and as a result, most of our data models, cognition models, user models, interaction models, ontologies, etc., are culturally biased. This fact is quite evident in music information research, since, despite the world's richness in terms of musical culture, most research is centered on CDs and metadata of western commercial music. This is the motivation behind a large and ambitious project funded by the European Research Council entitled "CompMusic: Computational Models for the discovery of the world's music. " In this paper we present the ideas supporting this project, the challenges that we want to work on, and the proposed approaches to tackle these challenges.
PopHist: inferring population history from the spectrum of allele frequencies

SUMMARY PopHist is a computer program that uses the frequency spectrum of alleles to: (a) estimate maximum likelihood parameters describing a population's history; and (b) compare alternative hypotheses about population history using likelihood ratio tests. The program uses the matrix coalescent, a method for calculating theoretical frequency spectra that can be applied to sets of unlinked sites. AVAILABILITY Source code and documentation are available at http://mombasa.anthro. utah.edu/wooding/PopHist
WMF information filter for multisensor descriptor system with same measurement matrix and correlated noises

For the multisensor linear stochastic descriptor system with same measurement matrix and correlated noises, the weighted measurement fusion information filter is presented, based on the weighted measurement fusion algorithm and the Kalman information filtering theory. This information filtering is a new repression of Kalman filtering based on information matrix, which can reduce computational burden and has important application in many theory analysis. And the presented weighted measurement fusion information filter has global optimality, and can avoid computing these cross-variances of the local Kalman filters, compared with the state fusion method. A simulation example about 3-sensors stochastic descriptor system verifies the effectiveness.
Exact evaluation of equal-gain diversity in the presence of Nakagami fading

An exact closed formulation for the evaluation of the error probability of L-branches equal-gain combiners over Nakagami fading channels and additive Gaussian noise is presented. Using the definition and the properties of the characteristic function of a sum of random variables, the error performance is evaluated directly for coherent detection and several modulation techniques (BPSK, BFSK).
Autonomous resource provisioning for multi-service web applications

Dynamic resource provisioning aims at maintaining the end-to-end response time of a web application within a pre-defined SLA. Although the topic has been well studied for monolithic applications, provisioning resources for applications composed of multiple services remains a challenge. When the SLA is violated, one must decide which service(s) should be reprovisioned for optimal effect. We propose to assign an SLA only to the front-end service. Other services are not given any particular response time objectives. Services are autonomously responsible for their own provisioning operations and collaboratively negotiate performance objectives with each other to decide the provisioning service(s). We demonstrate through extensive experiments that our system can add/remove/shift both servers and caches within an entire multi-service application under varying workloads to meet the SLA target and improve resource utilization.
Body Involvement in Video Gaming as a Support for Physical and Cognitive Learning

Despite a steady increase in the social visibility of video games in all spheres of daily life, persistent preconceived ideas about video games reveal a tendency to focus on either their positive or negative values, especially concerning the place of the player’s body. First, this article questions the different degrees of bodily involvement in the practice of video games according to the different types of games and the mechanisms that allow the player to learn the games’ gesture patterns. Then, the objective is to study the effects of video gaming on the physical, psychological, and social dimensions of the player and to identify potential correlations between bodily involvement and health benefit. Indeed, bodily involvement translates into physical engagement, and sometimes motor expertise as required by the game, but also into the mobilization of the player’s cognitive and interactive resources with the video game devices.
Extending a Nonlinear SNR Estimator to Include Shaping Distribution Identification for Probabilistically Shaped 64-QAM Signals

An estimation method for the nonlinear signal-to-noise ratio (SNR) is extended to simultaneously identify the shaping distribution for rate-adaptive probabilistically shaped (PS) 64-ary quadrature amplitude modulation (QAM) constellations. An artificial neural network (ANN) is trained with the fiber nonlinearity induced amplitude noise covariance and phase noise correlation extracted from received symbols. The identification employs estimates of the nonlinear signal-to-noise ratio $(\text{SNR}_{nl})$ and nonlinear system coefficients obtained from the ANN to extract the standardized constellation moments and hence identify the shaping distribution. The data used for training are 504 input–output sets, which are obtained from a simplified MATLAB simulation for a 32 Gbaud dual polarization PS 64-QAM signal considering seven different shaping distributions and a wide range of link configurations with varying fiber lengths and number of wavelength division multiplexed channels. Validation using 180 input–output sets that include five shaping distributions corresponding to a bit rate granularity of 25 Gb/s for bit rates between 200 and 300 Gb/s, exhibits high identification success rates, albeit for a limited set of examples. Reduced success rates are achieved for five shaping distributions corresponding to a bit rate granularity of 12.5 Gb/s for bit rates between 200 and 250 Gb/s. For completeness, the identification success rate is also quantified for the case of all seven shaping distributions in the validation.
Real-Time 3D Rendering Based on Multiple Cameras and Point Cloud

3D model construction technic is very popular in recent decades. The movie "Avatar" is a milestone of this research, the surrounding, characters and alien creatures in Avatar are so lifelike that viewers would be impressed and shocked by the impact of virtual reality. The video game World of War craft and Diablo are another successful instance about 3D model. Kinect is a 3D sensor produced by Microsoft, and is widely used in many research fields, such as Computer Vision, Computer Graphics-Ketc. With Kinect, the task of efficiently acquiring 3D data would be possible. In other words, the distances between all the positions in Kinect vision and Kinect can be captured and reliable. According to these data, Kinect is able to divide the image into foreground (human) and background quickly and easily draw the geography of human. So this paper would integrate the traditional model building technic and much research about Kinect, and then propose a real-time 3D point cloud displaying method by multiple Kinect.
Evolution as computation: integrating self-organization with generalized Darwinism

Abstract: Generalized Darwinism and self-organization have been positioned as competing frameworks for explaining processes of economic and institutional change. Proponents of each view question the ontological validity and explanatory power of the other. This paper argues that information theory, rooted in modern thermodynamics, offers the potential to integrate these two perspectives in a common and rigorous framework. Both evolution and self-organization can be generalized as computational processes that can be applied to human social phenomena. Under this view, evolution is a process of algorithmic search through a combinatorial design space, while self-organization is the result of non-zero sum gains from information aggregation. Evolution depends on the existence of self-organizing forces, and evolution acts on designs for self-organizing structures. The framework yields insights on the role of agency and the emergence of novelty. The paper concludes that information theory may provide a fundamental ontological basis for economic and institutional evolution.
Random sampling and approximation of MAX-CSP problems

We present a new efficient sampling method for approximating r-dimensional Maximum Constraint Satisfaction Problems, MAX-rCSP, on n variables up to an additive error εnr. We prove a newgeneral paradigm in that it suffices, for a given set of constraints, to pick a small uniformly random subset of its variables, and the optimum value of the subsystem induced on these variables gives (after a direct normalization and with high probability) an approximation to the optimum of the whole system up to an additive error of εnr. Our method gives for the first time a polynomial in ε—1 bound on the sample size necessary to carry out the above approximation. Moreover, this bound is independent in the exponent on the dimension r. The above method gives a completely uniform sampling technique for all the MAX-rCSP problems, and improves the best known sample bounds for the low dimensional problems, like MAX-CUT. The method of solution depends on a new result on t he cut norm of random subarrays, and a new sampling technique for high dimensional linear programs. This method could be also of independent interest.
GWO tuned multi degree of freedom PID controller for load frequency control

In order to enhance the control action, in this article multi degree of freedom PID controllers (MDFPID) like 2DOF-PID and 3DOF-PID controllers are suggested for frequency control in a multi-unit hydro-thermal interconnected system. The finest gains of the recommended MDFPID controllers are achieved with Grey Wolf Optimization (GWO) Technique considering a time based evaluative function. The dom-inating performance of the suggested control technique is validated by relating the outcomes with a pre-published journal results. The robust behavior of the MDFPID controller is also validated by abruptly amplifying the loading of the system. The system dynamic responses are analyzed in consideration with time response parameters like minimum undershoots, settling time and peak overshoots.
Implementing an e-business model for a dot-com SME: Lessons Learned

One of the key steps to develop an e-business solution is the definition of a Business Model (BM), which requires the expertise from different areas such as finance, technology, marketing, and project management. It is known that Small and Medium Enterprises (SMEs) count with limited resources to undertake this type of e-business initiatives, and thus prompt to failure. This paper tells the story of the process of selection of a BM (and related documents) needed for the design and implementation of an undergoing dot-com initiative leaded by an SME in Mexico. The results of such study are summarized in a series of recommendations that SME may found useful when embarking in similar projects. Some key findings from these recommendations are: partnership with academic/research institutions, the key role of project management, communication, and identification of links between strategy and technology.
Automatic Design of Synchronous Reluctance Motors Focusing on Barrier Shape Optimization

The automated design of synchronous reluctance (SyR) motors based on multiobjective genetic optimization and finite-element analysis is considered in this paper. Three types of barrier shapes are considered, all described by an effective limited set of input variables. The three solutions are investigated to establish which of the geometries can give the best torque output and also which one represents the best compromise between output performance and computational time. The analysis presented in this paper shows that SyR motors designed automatically can give a good performance and can be designed in a reasonable time, and it is also shown that not all design degrees of freedom are useful in terms of motor performance. Two prototypes of automatically designed machines have been fabricated and experimentally compared with a third prototype designed according to state-of-the-art design principles.
Temporal Spatial-Keyword Top-k publish/subscribe

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date tweets such that their locations are close to a user specified location and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic “food poisoning vomiting. ” We consider the Temporal Spatial-Keyword Top-k Subscription (TaSK) query. Given a TaSK query, we continuously maintain up-to-date top-k most relevant results over a stream of geo-textual objects (e.g., geo-tagged Tweets) for the query. The TaSK query takes into account text relevance, spatial proximity, and recency of geo-textual objects in evaluating its relevance with a geo-textual object. We propose a novel solution to efficiently process a large number of TaSK queries over a stream of geotextual objects. We evaluate the efficiency of our approach on two real-world datasets and the experimental results show that our solution is able to achieve a reduction of the processing time by 70-80% compared with two baselines.
Identification of Leptospira serovars by RFLP of the RNA polymerase beta subunit gene (rpoB)

Leptospires are usually classified by methods based on DNA-DNA hybridization and the conventional cross-agglutination absorption test, which uses polyclonal antibodies against lipopolysaccharides. In this study, the amplification of the rpoB gene, which encodes the beta-subunit of RNA polymerase, was used as an alternative tool to identify Leptospira. DNA extracts from sixty-eight serovars were obtained, and the hypervariable region located between 1990 and 2500-bp in the rpoB gene was amplified by polymerase chain reaction (PCR). The 600-bp amplicons of the rpoB gene were digested with the restriction endonucleases TaqI, Tru1I, Sau3AI and MslI, and the restriction fragments were separated by 6% polyacrylamide gel electrophoresis. Thirty-five fragment patters were obtained from the combined data of restriction fragment length polymorphism (PCR-RFLP) analysis and used to infer the phylogenetic relationships among the Leptospira species and serovars. The species assignments obtained were in full agreement with the established taxonomic classifications. Twenty-two serovars were effectively identified based on differences in their molecular profiles. However, the other 46 serovars remained clustered in groups that included more than one serovar of different species. This study demonstrates the value of RFLP analysis of PCR-amplified rpoB as an initial method for identifying Leptospira species and serovars.
The development of brand attitudes among young consumers

Purpose – The purpose of this paper is to examine factors affecting the development of brand attitudes and brand behavior among children aged seven to 12. Design/methodology/approach – The study involved a literature review investigating the theoretical models underlying studies of brand attitude development among children and empirical studies of brand attitude development, and an empirical study using a questionnaire administered to a sample of 221 Cypriot children. Findings – Cypriot children are found to have high awareness of internationally famous brands. The principal influences on children's brand attitudes are older siblings, parents, and close friends. Brand attitudes are the principal influence on brand behavior (brand requesting and brand buying). Age is found to be an important factor affecting brand buying decisions, with older children more likely than younger children to buy brands. Research limitations/implications – Generalization of the results beyond the population from which the sampl.
Investigation of Organizational Interaction and Support in an NGO through Computer-Mediated Discussions

Discussion forums have been used to support organizational communication and they have become a candidate for study of organizational behaviors. However, online behaviors of NGOs have been insufficiently studied compared to those studies conducted in education and industries. Our empirical study examined how social workers in one NGO used an internal discussion forum to help them disseminate time-sensitive employment opportunities for people with mental impairments, provide space for collective expressions of support, and enable sharing of information and experiences. The main purpose of the paper is to study a multifaceted assessment methodology to assess online discussion forums in an NGO. In this paper, we carry out a systemic set of assessment methods including network analysis, category analysis, and content analysis for evaluating online social software, and particularly discussion forums. The methods are used empirically to assess patterns of information sharing, social network, and peer support in an NGO.
Adaptive control of hydraulic excavator manipulator

The retrofitted electro-hydraulic system and hardware architecture of control system for hydraulic robotic excavator was introduced; the model of electro-hydraulic system was derived according to the principle of LUDV system. on the base of the above and results of experiments, the model was simplified, and the reference model for control was given; An adaptive controller (AC) and the adaptive control law were developed from the local parameter optimum. The test experiment on the trajectory tracking control of the excavator bucket tip was carried out, The result of tracking objective line for the AC and PID controller were present respectively. Form these results, the errors between the tested data and the target data for PID controller are more than 110mm when the level tracking velocity of the bucket speed was 107mm/s; for AC in this paper are less than 100mm at the speed of 135mm/s, the maximal nonlinearity is reduced to 3.8% from 4.8%. It shows that the proposed AC in this paper is valid and feasible.