Miracle-dz/UniFAR-FTUs huggingface dataset:
“MOVE” ANALYSIS IN CLASSROOM INTERACTION (An Functional Grammar Approach

Find out the form of “move” in students classssroom interaction of UNRIKA during teaching practice program was the aim of this study. Conversation texts taken froms tudents’ classssroom interaction of UNRIKA during teaching practice program were the data of this research. To analize the data, in this study , descriptive qualitative method was used. There were five classroom interaction s selected as the data source. The data were taken by recording then transcripted. Rewriting, Identifing utterences, elaborating and then analized were the process of data analysi. The findings of this study show ed that were 261 clauses analysis. T here were two types of move” in students classssroom interaction found , namely congruent and metaphorical “move” coding. Congruent and metaphorical “move” coding was 76.63 % and metaphorical “move” coding was 27.37 % . Congruent “move” coding was built in “knower” and “actor” analysis , but “ k n ower ” analysis was more dominant. It means the conversation texts dominnated by the statement and question, in another word, the content of the interaction refered to the lecturing and discussion situation. Keywords: “Move”,” Knower”, “Actor” Congruent and Metaphor Coding.
2-π Crosstalk noise model for deep submicron VLSI global RC interconnects

Noise estimation and avoidance are becoming very important issues in today's high performance IC design. This paper presents a much improved, highly accurate and efficient noise model called 2-π model for the estimation of crosstalk noise. The proposed model incorporates all the physical properties including victim and aggressor drivers, distributed RC characteristics of interconnects and coupling locations of both victim and aggressor lines. Then with the help of this model, expressions for peak noise and noise width as well as sensitivity expressions to the various model parameters are calculated. We then use these sensitivity expressions to analyze and evaluate the effectiveness of various noise avoidance techniques for the reduction of this crosstalk noise.
Dynamic group communication in mobile peer-to-peer environments

This paper presents an approach to integrate publish/subscribe semantics with on-demand multicast in wireless ad hoc networks, providing dynamic group communication with fine-grained subscriptions. A prototype application 'PGM Golf Forum' is developed, which enables a dynamic publish/subscribe system among the gallery during a golf tournament. Dynamic construction of an event dissemination structure to route events from event publishers to subscribers is important, especially to support rapidly changing multi-hop topologies over wireless links. The proposed approach aggregates content-based subscriptions in a compact data format (Bloom filters), and ODMRP (On-Demand Multicast Routing Protocol) is extended to use this context from the middleware-tier to construct an optimized dynamic dissemination mesh. It operates dynamic multicast grouping by aggregated subscriptions applying clustering techniques. Cooperation between middleware-tier and network components provides reliable finegrained publish/subscribe by ODMRP's mesh topology.
Single sample face recognition based on sample augments and MSD fusion

To overcome the limitation of traditional face recognition methods for single sample face recognition, a single sample face recognition algorithm based on sample augments and MSD fusion is proposed in this paper. First, according to the facial symmetry theory, some relevant information of possible change could be extract to adapt to the future samples. A combination of the original training sample and its virtual average face, symmetrical face as the training sample set is proposed. Then, the maximum scatter difference algorithm was performed on the new training sample set to get the optimal projection matrix, therefore, the features of the training sample and testing facial images could be obtained by projecting them on the optima projection matrix achieved above. During the recognition stage, the fuzzy decision was used to do the classification. Extensive experiment results on famous ORL and FERET show that the algorithm can improve the recognition rate, and has certain robustness.
Research , part of a Special Feature on Ecological Restoration in Northern Regions Demonstration Restoration Measures in Tributaries of the Vindel River Catchment

Some ecological restoration projects include elements of trial and error where new measures are repeatedly tried, evaluated, and modified until satisfactory results are achieved. Thereafter, the resulting methods may be applied on larger scales. A difficult step is judging whether developed “best-practice” methods have become reasonably ecologically functional or whether further experimentation “demonstration” methods can lead to yet better results. Here, we use a stream restoration project as a case study for evaluating methods and abiotic effects and outlining stakeholder support for demonstration restoration measures, rather than only using best-practice methods. Our work was located in the Vindel River system, a free-flowing river that is part of the Natura 2000 network. The river was exploited for timber floating from 1850–1976, and rapids in the main channel and tributaries below timberline were channelized to increase timber transport capacity. Several side channels in multi-channeled rapids were blocked and the flow was concentrated to a single channel from which boulders and large wood were removed. Hence, previously heterogeneous environments were replaced by more homogeneous systems with limited habitat for riverine species. The restoration project strives to alleviate the effects of fragmentation and channelization in affected rapids by returning coarse sediment from channel margins to the main channel. However, only smaller, angular sediment is available given blasting of large boulders, and large (old-growth) wood is largely absent; therefore, original levels of large boulders and large wood in channels cannot be achieved with standard restoration practices. In 10 demonstration sites, we compensated for this by adding large boulders and large wood (i.e., entire trees) from adjacent upland areas to previously best-practice restored reaches and compared their hydraulic characteristics with 10 other best-practice sites. The demonstration sites exhibited significantly reduced and more variable current velocities, and wider channels, but with less variation than pre-restoration. The ecological response to this restoration has not yet been studied, but potential outcomes are discussed.
Cardiac arrhythmia detection using DCT based compressive sensing and random forest algorithm

The discrimination of ECG signals is of crucial importance in clinical diagnoses of cardiac diseases. Manual analysis of ECG signals is very complex and time consuming task due to their composite nature. This paper proposes a novel scheme for reliable automatic classification of ECG signals into normal and three different abnormal (arrhythmia affected) categories. The feature extraction is based on an amalgamation of discrete cosine transform and random projection for dimensionality reduction. Furthermore, the classification is performed using random forest algorithm. The performance of the proposed scheme is evaluated on the restricted subset of ECG recordings from MIT-BIH arrhythmia database. In the experiments, a near perfect recognition accuracies of 99.33% and 99%, depending on the definition of projection matrix, are achieved with only 50 random projected coefficients; i.e. after considerable dimensionality reduction of the input ECG signal.
Superresolution software manual

This manual describes the use of the software application implementing the SR algorithms developed in [1, 2, 3, 4, 5] as well as other superresolution methods developed by the authors [6]. The application has been developed in MATLAB R (7.13/R2011b) including the graphic user interface (see figure 1). The developed software: • Allows the execution of SR methods in real and simulate modes. • Evaluates the following SR methods: – Bicubic interpolation. – The TV prior based method proposed in [6]. – The method described in the algorithm 3.1 of [1] which utilizes a SAR prior model. – The algorithm proposed in [2], with the 1-norm of the horizontal and vertical gradients as the image prior model. – The method proposed in [3] based on a SAR and 1-norm model combination with registration parameter estimation. – The method described in the work [4] which combines SAR and TV prior models with the estimation of the registration parameters. – The method proposed in [5], where a prior distribution based on a general combination of spatially adaptive or non-stationary image filters is used with the estimation of all parameters. 1 If you use this software to evaluate any of the described methods, please cite the corresponding papers. The papers can be downloaded for research purposed from • Saves the results (HR images and registration parameters). • Allows the user to stop the execution at any time, with the possibility of saving all the estimated parameters as well as the estimated HR image. We assume here that a digital camera captures a sequence of L low resolution images of size N pixels. In the spatial domain, the process to capture the k-th image, y k , can be expressed using matrix-vector notation, as y k = AH k C(s k)x + n k , (1) where x represents a digitalization of the real scene with a resolution of P N pixels, with P > 1 representing the magnification factor, C(s k) is a P N × P N matrix representing the motion of the k-th image in the sequence with respect to the reference image, with s k = (θ k , c k , d k) T the motion parameters (rotation angle and horizontal and vertical displacement), H k is a P N ×P N matrix representing the blur, A is the N × P N integration and subsampling matrix and n …
Fast tracking algorithm based on improved particle filter

In recent years, occluded target tracking has become a hot topic in the research field of machine vision. Mean shift(MS) and particle filter(PF) are two successful methods for target tracking. Both have respective advantages and weaknesses. MS algorithm is good at prompting tracking but sensitive to occlusion while PF algorithm is robust to occlusion but need extensive computation cost. In order to achieve the efficient tracking algorithm, a novel improved particle filter was proposed for target tracking in this paper. First, The proposed mean shift forecasted particle filter(MSFPF) improves the sampling efficiency considerably by incorporating MS into PF as a forecasting progress. Meanwhile, the MS vector makes a difference in increasing accuracy of target tracking and reducing computation complexity. The experimental results demonstrated that the proposed algorithm is robust and achieved real-time tracking, the algorithm presented satisfactory performance in full stationary occlusion, the moving completely occlusion with similar color interference as well as the target deformation in an omni-directional vision system.
Industry Clusters and Rural Labor Markets

Along with the recent resurgence of interest in the agglomeration and clustering of economic activity, there has been increasing interest in industry clusters as a potential economic development strategy. Ultimately, the question of whether or not clusters are an appropriate focus of economic development strategies for rural areas depends on the relationship between clusters and local economic growth. The primary purpose ofthis paper is to discuss some of the issues involved in measuring the relationship between clusters and rural economic growth. Preliminary evidence of a positive association between industry clusters and rural earnings growth are presented, supporting the notion that a cluster-focused development strategy may be effective in some rural areas.
Localization of Metallothionein-I and -III Expression in the CNS of Transgenic Mice with Astrocyte-Targeted Expression of Interleukin 6

The effect of interleukin-6 (IL-6) on metallothionein-I (MT-I) and MT-III expression in the brain has been studied in transgenic mice expressing IL-6 under the regulatory control of the glial fibrillary acidic protein gene promoter (GFAP-IL6 mice), which develop chronic progressive neurodegenerative disease. In situ hybridization analysis revealed that GFAP-IL6 (G16-low expressor line, and G36-high expressor line) mice had strongly increased MT-I mRNA levels in the cerebellum (Purkinje and granular layers of the cerebellar cortex and basal nuclei) and, to a lesser degree, in thalamus (only G36 line) and hypothalamus, whereas no significant alterations were observed in other brain areas studied. Microautoradiography and immunocytochemistry studies suggest that the MT-I expression is predominantly localized to astrocytes throughout the cerebrum and especially in Bergman glia in the cerebellum. However, a significant expression was also observed in microglia of the GFAP-IL6 mice. MT-III expression was significantly increased in the Purkinje cell layer and basal nuclei of the cerebellum, which was confirmed by Northern blot analysis of poly(A)+ mRNA and by ELISA of the MT-III protein. In contrast, in the G36 but not G16 mice, transgene expression of IL-6 was associated with significantly decreased MT-III RNA levels in the dentate gyrus and CA3 pyramidal neuron layer of the hippocampus and, in both G36 and G16 mice, in the occipital but not frontal cortex and in ependymal cells. Thus, both the widely expressed MT-I isoform and the CNS specific MT-III isoform are significantly affected in a MT isoform- and CNS area-specific manner in the GFAP-IL6 mice, a chronic model of brain damage.
Revisiting Link Prediction: Evolving Models and Real Data Findings

The explosive growth of Web 2.0, which was characterized by the creation of online social networks, has reignited the study of factors that could help us understand the growth and dynamism of these networks. Various generative network models have been proposed, including the Barabasi-Albert and Watts-Strogatz models. In this study, we revisit the problem from a perspective that seeks to compare results obtained from these generative models with those from real networks. To this end, we consider the dating network Skout Inc. An analysis is performed on the topological characteristics of the network that could explain the creation of new network links. Afterwards, the results are contrasted with those obtained from the Barabasi-Albert and Watts-Strogatz generative models. We conclude that a key factor that could explain the creation of links originates in its cluster structure, where link recommendations are more precise in Watts-Strogatz segmented networks than in Barabasi-Albert hierarchical networks. This result reinforces the need to establish more and better network segmentation algorithms that are capable of clustering large networks precisely and efficiently.
THE INFLUENCE OF TASK AND GENDER ON SEARCH AND EVALUATION USING GOOGLE

To improve search engine effectiveness, we have observed an increased interest in gathering additional feedback about users’ information needs that goes beyond the queries they type in. Adaptive search engines use explicit and implicit feedback indicators to model users or search tasks. In order to create appropriate models, it is essential to understand how users interact with search engines, including the determining factors of their actions. Using eye tracking, we extend this understanding by analyzing the sequences and patterns with which users evaluate query result abstracts returned to them when using Google. We find that the query result abstracts are viewed in the order of their ranking in only about one fifth of the cases, and only an average of about three abstracts per result page are viewed at all. We also compare search behavior variability with respect to different classes of users and different classes of search tasks to reveal whether user models or task models may be greater predictors of behavior. We discover that gender and task significantly influence different kinds of search behaviors discussed here. The results are suggestive of improvements to query-based search interface designs with respect to both their use of space and workflow.
ResurReaction: Competing Visions of Turkey’s (proto) Ottoman Past in Magnificent Century and Resurrection Ertuğrul

Abstract The Turkish TV dramas Magnificent Century and Resurrection Ertuğrul share a number of traits: Both reprise the country’s Ottoman (or proto-Ottoman) past by focusing their story on a heroic figure; both raised the ire of critics for their lack of historicity; and both have been highly successful, ruling ratings on the same competitive Wednesday night prime time slot, with Resurrection coming in to take Century’s place after that show left the air. Despite these similarities, the projects represent quite different takes on the Ottoman past and the issue of history’s role in the Turkish present. While Century arguably partakes in what Svetlana Boym calls reflective nostalgia, Resurrection is a highly restorative project. In this article, I detail the differences between these projects and explain their success in light of the shifting political environment in Turkey. I begin with a characterization of Century and the ‘problem’ it posed for a conservative government that was deeply invested in an idealized Ottoman past. I next turn to Resurrection, which I see as a government reaction to Century, and explain that it succeeds where other imitators failed due to the careful choice of a hero with a relatively blank historical slate. Finally, I argue that Resurrection practices a different attitude toward history than does Century, heralding for a government that not only seeks to glorify and idolize the past, but also to claim ownership of it.
Capacitated VRP : In the capacitated

This paper is a survey of the literature on applications of evolutionary algorithms for vehicle routing problems. It reports about genetic algorithms, evolution strategies and particle swarm optimization, when applied to the classical capacitated vehicle routing problem and many of its variants. The performance of evolutionary algorithms is also compared with the best alternative problem-solving approaches on benchmark instances.
TagSNP selection using weighted CSP and russian doll search with tree decomposition

The TagSNP problem is a specific form of compression problem arising in genetics. Given a very large set of SNP (genomic positions where polymorphism is observed in a given population), the aim is to select a smallest subset of SNPs which represents the complete set of tagSNP reliably. This is possible because strong correlations existing between neighboring SNPs. Typically, besides minimizing the tagSNP set size (mostly for economical reasons), one also seek a maximally informative subset for the given size, generating di erent secondary criteria. This problem, which is also closely related to a set covering problem, can be simply described as a weighted CSP. We report here our experiments with human tag SNP data using a recently designed WCSP algorithm combining the "Russian Doll Search" algorithm with local consistency for cost functions and an active exploitation of the problem structure, through a tree decomposition of the problem.
ConvKN at SemEval-2016 Task 3: Answer and Question Selection for Question Answering on Arabic and English Fora

We describe our system, ConvKN, participating to the SemEval-2016 Task 3 “Commu-nity Question Answering”. The task targeted the reranking of questions and comments in real-life web fora both in English and Arabic. ConvKN combines convolutional tree kernels with convolutional neural networks and additional manually designed features including text similarity and thread speciﬁc features. For the ﬁrst time, we applied tree kernels to syntactic trees of Arabic sentences for a reranking task. Our approaches obtained the second best results in three out of four tasks. The only task we performed averagely is the one where we did not use tree kernels in our classiﬁer.
Evaluation of Lane Change Collision Avoidance Systems Using the National Advanced Driving Simulator

This study evaluated the performance of lane change collision avoidance systems (CASs) on lane change characteristics and drivers’ acceptance of CASs for drivers in two age groups. Thirty-two male drivers (16 aged 16 to 21, and 16 aged 65 or older) drove a practice run with standard mirrors followed by four trials on the National Advanced Driving Simulator (NADS) with one of four types of CAS: 1) TRW’s proximity-only system, 2) TRW’s proximity and fast-approach system, 3) limited proximity warning system (LPWS), and 4) a non-planar mirror. The lane change scenarios were simulated by varying blind-spot vehicle status, lane change direction, and leading vehicle action. A variety of quantitative and subjective measures were applied to driver performance and driver opinion. The pattern of analyses indicates that the non-planar mirror and the LPWS mirror were more effective than the TRW proximity only and the TRW proximity and fast-approach system. Older drivers drove somewhat more cautiously according to some, but not all measures. Research is proposed to identify which CAS features to retain, to delete and which features can be enhanced to improve lane changing safety and effectiveness.
Rapid and reliable universal cloning of influenza A virus genes by target-primed plasmid amplification

Reverse genetics has become pivotal in influenza virus research relying on rapid generation of tailored recombinant influenza viruses. They are rescued from transfected plasmids encoding the eight influenza virus gene segments, which have been cloned using restriction endonucleases and DNA ligation. However, suitable restriction cleavage sites often are not available. Here, we describe a cloning method universal for any influenza A virus strain which is independent of restriction sites. It is based on target-primed plasmid amplification in which the insert provides two megaprimers and contains termini homologous to plasmid regions adjacent to the insertion site. For improved efficiency, a cloning vector was designed containing the negative selection marker ccdB flanked by the highly conserved influenza A virus gene termini. Using this method, we generated complete sets of functional gene segments from seven influenza A strains and three haemagglutinin genes from different serotypes amounting to 59 cloned influenza genes. These results demonstrate that this approach allows rapid and reliable cloning of any segment from any influenza A strain without any information about restriction sites. In case the PCR amplicon ends are homologous to the plasmid annealing sites only, this method is suitable for cloning of any insert with conserved termini.
A modular open platform for systematic functional studies under physiological conditions

Any profound comprehension of gene function requires detailed information about the subcellular localization, molecular interactions and spatio-temporal dynamics of gene products. We developed a multifunctional integrase (MIN) tag for rapid and versatile genome engineering that serves not only as a genetic entry site for the Bxb1 integrase but also as a novel epitope tag for standardized detection and precipitation. For the systematic study of epigenetic factors, including Dnmt1, Dnmt3a, Dnmt3b, Tet1, Tet2, Tet3 and Uhrf1, we generated MIN-tagged embryonic stem cell lines and created a toolbox of prefabricated modules that can be integrated via Bxb1-mediated recombination. We used these functional modules to study protein interactions and their spatio-temporal dynamics as well as gene expression and specific mutations during cellular differentiation and in response to external stimuli. Our genome engineering strategy provides a versatile open platform for efficient generation of multiple isogenic cell lines to study gene function under physiological conditions.