Miracle-dz/UniFAR-FTUs huggingface dataset:
Web Information Extraction by Semantic Tagging

An important aspect of research for Web information extraction relates to the inference of complex reasoning and correlation based on distributed information available in many different Web data sources. By defining the semantics of information and services available on the Web, the World Wide Web becomes a vast store of information that can be easily processed by computer applications.
Articulated pose estimation via multiple mixture parts model

State-of-the-art methods for articulated human pose estimation are based on pictorial structures model (PS). Most of these methods predict the pose directly in part-based models and only consider rigid parts guided by human anatomy. In this paper, we propose a new framework for human pose estimation which is composed of two stages: pre-estimation and estimation. The first stage includes three steps: upper body detection, upper body categorization, and model selection. In the second stage, a new upper body category based multiple mixture parts (MMP) model is proposed. We present quantitative results demonstrating that our model significantly improves the accuracy of the pose estimation.
Optimization of Photosynthetic Rate Parameters using Adaptive Neuro-Fuzzy Inference System (ANFIS)

Crop growth is greatly affected by light intensity, temperature and CO2 concentration. The combinations of these factors are considered in growing crops. In this study, a system was developed using adaptive neuro-fuzzy inference system for the prediction of the photosynthetic rate of lettuce crop based on the temperature, light intensity and CO2. A fuzzy inference system is designed to generate the rules for the fuzzy logic where inputs of these are from the output of the trained neural network. Based on the result, the system was able to predict the photosynthetic rate of the lettuce crop based on the three input parameters. The RMSE value for the ANFIS model was found to be 2.7843e-05.
Eye movements and abducens motoneuron behavior during cholinergically induced REM sleep.

STUDY OBJECTIVES The injection of cholinergic drugs in the pons has been largely used to induce REM sleep as a useful model to study different processes during this period. In the present study, microinjections of carbachol in the nucleus reticularis pontis oralis (NRPO) were performed to test the hypothesis that eye movements and the behavior of extraocular motoneurons during induced REM sleep do not differ from those during spontaneous REM sleep. METHODS Six female adult cats were prepared for chronic recording of eye movements (by means of the search-coil technique) and electroencephalography, electromyography, ponto-geniculo-occipital (PGO) waves at the lateral geniculate nucleus, and identified abducens motoneuron activities after microinjections of the cholinergic agonist carbachol into the NRPO. RESULTS Unilateral microinjections (n = 13) of carbachol in the NRPO induced REM sleep-like periods in which the eyes performed a convergence and downward rotation interrupted by phasic complex rapid eye movements associated to PGO waves. During induced-REM sleep abducens motoneurons lost their tonic activity and eye position codification, but continued codifying eye velocity during the burst of eye movements. CONCLUSION The present results show that eye movements and the underlying behavior of abducens motoneurons are very similar to those present during natural REM sleep. Thus, microinjection of carbachol seems to activate the structures responsible for the exclusive oculomotor behavior observed during REM sleep, validating this pharmacological model and enabling a more efficient exploration of phasic and tonic phenomena underlying eye movements during REM sleep.
Innovations in Teaching: How Novice Teaching Assistants Include LGBTQ Topics in the Writing Classroom

This article examines how three novice graduate teaching assistants included lesbian, gay, bisexual, transgender, and queer topics in their first-year writing classrooms. Findings suggest that inclusion of these topics can be successfully done through attention to identity in the classroom, including current-day events, and structuring classroom activities that support inclusion. Further implications suggest the importance of including graduate teaching assistants in discussions about cutting-edge pedagogical practices in the classroom.
High-Speed Signature Matching in Network Interface Device using Bloom Filters

Network intrusion detection systems play a critical role in protecting the information infrastructure of an organization. Due to the sophistication and complexity of techniques used for the analysis they are commonly based on general-purpose workstations. Although cost-efficient, these general-purpose systems are found to be inadequate as they are unable to perform efficiently at high packet rates. The resulting packet loss degrades the system's overall effectiveness, as the analyzing capability of the system is reduced. It has been found that the performance of these sensors can be improved significantly by filtering out unwanted packets. This paper presents the design of a Programmable Ethernet Interface Card that is used to offload signature matching from software and thereby improve the detection ratio and performance of the system.
Test data compression using Hamming Encoder and Decoder for system on chip (SOC) testing

As per Moore's Law the growth of transistors in VLSI (Very Large Scale Integration) chip is doubled for every 18 months. Due to this rapid improvement, testing the VLSI integrated circuit for fault free conditions requires large duration of times. Hence this research paper going to propose the data compression technique using Hamming Encoder and Decoder to reduce the test time with small area overhead on chip. The novel methodology also reduces the switching activity between the modified test inputs which lead us to reduce the test power dissipation during testing. The estimation of area overhead is also determined through implementing the additional hardware component of novel circuit with the Field Programmable Gated Array (FPGA) SPARTAN III kit using XILINX ISE Design Suite 14.7 version tool. The entire hardware component of the chip is described using Hardware Description Language (HDL) Verilog. The estimation result shows as its required only minimum amount of hardware component approximately 5% is added to the chip.
Internal and External Visual Cue Preferences for Visualizations in Presentations

Presenters, such as analysts briefing to an executive committee, often use visualizations to convey information. In these cases, providing clear visual guidance is important to communicate key concepts without confusion. This paper explores visual cues that guide attention to a particular area of a visualization. We developed a visual cue taxonomy distinguishing internal from external cues, designed a web tool based on the taxonomy, and conducted a user study with 24 participants to understand user preferences in choosing visual cues. Participants perceived internal cues (e.g., transparency, brightness, and magnification) as the most useful visual cues and often combined them with other internal or external cues to emphasize areas of focus for their audience. Interviews also revealed that the choice of visual cues depends on not only the chart type, but also the presentation setting, the audience, and the function cues are serving. Considering the complexity of choosing visual cues, we provide design implications for improving the organization, consistency, and integration of visual cues within existing workflows.
Low-dose spectral CT reconstruction using L0 image gradient and tensor dictionary

Spectral computed tomography (CT) has a great superiority in lesion detection, tissue characterization and material decomposition. To further extend its potential clinical applications, in this work, we propose an improved tensor dictionary learning method for low-dose spectral CT reconstruction with a constraint of image gradient L0-norm, which is named as L0TDL. The L0TDL method inherits the advantages of tensor dictionary learning (TDL) by employing the similarity of spectral CT images. On the other hand, by introducing the L0-norm constraint in gradient image domain, the proposed method emphasizes the spatial sparsity to overcome the weakness of TDL on preserving edge information. The alternative direction minimization method (ADMM) is employed to solve the proposed method. Both numerical simulations and real mouse studies are perform to evaluate the proposed method. The results show that the proposed L0TDL method outperforms other competing methods, such as total variation (TV) minimization, TV with low rank (TV+LR), and TDL methods.
Modelorganismsforgenetics in thedomainArchaea : methanogens , halophiles , Thermococcales andSulfolobales

Modelorganismsforgenetics in thedomainArchaea:methanogens, halophiles,Thermococcales andSulfolobales John A. Leigh, Sonja-Verena Albers, Haruyuki Atomi & Thorsten Allers Department of Microbiology, University of Washington, Seattle, WA, USA; Max-Planck-Institute for Terrestrial Microbiology, Marburg, Germany; Department of Synthetic Chemistry and Biological Chemistry, Graduate School of Engineering, Kyoto University, Nishikyo-ku, Kyoto, Japan; and School of Biology, Queen’s Medical Centre, University of Nottingham, Nottingham, UK
Subcellular Redistribution of the Mitochondrial PG2 Epitope during Development from Cleavage to Primordial Germ Cell Formation in the Rabbit Embryo

Mitochondria are central players in diverse cellular functions and their efficient functioning has dramatic impact on embryonic development. Apparently, proliferation and transmission of well functioning mitochondria to the next generation require ingeniously adapted mechanisms, one of which, the ‘mitochondrial bottleneck’, is thought to occur early in mammalian development during primordial germ cell (PGC) specification. We used an antibody directed against the mitochondrial PG2 epitope, a reliable marker of primordial and adult female germ cells to monitor mitochondrial differentiation in the early rabbit embryo. Early development shows the PG2 epitope either tightly mitochondria-associated (zygote) or diffusely distributed throughout cytoplasm (cleavage stages). Mitochondrial colocalization of the PG2 epitope is regained in the early blastocyst but expression is then retained by the hypoblast and epiblast only, with the epiblast, although the forerunner of PGCs, showing weak and diffuse labeling only. At gastrulation, hypoblast cells lose PG2 expression but intensive PG2 labeling is found again on all mitochondria in the first PGCs and reveals the number of mitochondria to be in the range of 50 to 100 per PGC at this stage. The results highlight the dynamics of PG2 expression during early development and the usefulness of the epitope for testing the bottleneck theory.
Achieving up to zero communication delay in BSP-based graph processing via vertex categorization

The Bulk Synchronous Parallel (BSP) model, which divides a graphing algorithm into multiple supersteps, has become extremely popular in distributed graph processing systems. However, the high number of network messages exchanged in each superstep of the graph algorithm will create a long period of time. We refer to this as a communication delay. Furthermore, the BSP's global synchronization barrier does not allow computation in the next superstrep to be scheduled during this communication delay. This communication delay makes up a large percentage of the overall processing time of a superstep. While most recent research has focused on reducing number of network messages, but communication delay is still a deterministic factor for overall performance. In this paper, we add a runtime communication and computation scheduler into current graph BSP implementations. This scheduler will move some computation from the next superstep to the communication phase in the current superstep to mitigate the communication delay. Finally, we prototyped our system, Zebra, on Apache Hama, which is an open source clone of the classic Google Pregel. By running a set of graph algorithms on an in-house cluster, our evaluation shows that our system could completely eliminate the communication delay in the best case and can achieve average 2X speedup over Hama.
Practitioner capability: Supporting critical reflection during workbased placement – a pilot study

Purpose – The purpose of this paper is to investigate the role of creative activity and storytelling in assisting development of students’ reflective ability and critical thinking. Design/methodology/approach – Eight biomedical science students undertaking year-long work-based placements took part in this action research study. A coding scheme was designed to assess students’ reflections initially and at each stage of the study. Intervention activities involved students using mood boards, images and storytelling to assist development of creative learning spaces with a thematic approach employed to analyse both personal and collective reflections. Post-intervention evaluation considered possible long-term impact on students’ reflective ability. Findings – Students’ pre-intervention reports showed little reflection focusing mainly on competence demonstration and descriptive situation summaries. During the intervention workshops, all students demonstrated both identification of self as a practitioner and a critically reflective approach. However, this was not maintained long term as initial post-intervention reports tended to revert to a more descriptive style of writing suggesting longer-term support is required. Research limitations/implications – The importance of further research into the long-term usefulness of creative collaborative learning spaces in work-based programmes is suggested. Originality/value – This is the first study investigating the approach to supporting critical reflection during work placement in biomedical scientists. It is suggested that the current competence-based training programme provides limited opportunities for developing and embedding critical reflection. Where opportunities are provided, such as creative learning spaces, students’ critical reflection was greatly enhanced. However, it appears essential that this approach is maintained throughout training as critically reflective skills developed during collaborative learning have limited transferability to subsequent reflective report writing.
An Empirical Investigation of the Level of User's Acceptance of E-Banking among Some Customers of Banks in Iran

: With the high speed of advances in different aspects of technology, the use of electronic banking as a creative solution for various daily banking affairs has been disseminated around the world, simultaneously. Iran has not been the exception of this stream and the number of e-banking contracts seems to get increased in recent years. The purpose of this paper is to investigate the level of user's acceptance of electronic banking among some customers of banks in Iran. Extended TAM model was conducted as a conceptual framework in this paper. The survey instrument was employed to collect data. 188 questionnaires were analyzed based on correlation and regression analyses and independent sample t-test using the statistical package for social sciences (SPSS). Result has showed that customers have found e-banking system enjoyable, convenient, and easy to use; however, there is low level of reliability in the security measure of e-banking technology.
REGRET: reputation in gregarious societies

In a broad sense, reputation is the \opinion or view of one (agent) about something". Each agent may have a di erent opinion about a given entity and, therefore, reputation is linked to subjectivity. This opinion is formed and updated along time through interactions. As a result of these interactions, agents record impressions that re ect how they value the experience. Impressions are the bricks that properly combined permit to value the reputation of agents. In societies where agents belong to groups that condition their behaviour not only the direct interaction with the agent whose reputation we want to determine is important (the individual dimension of reputation), the interaction with other members of his group becomes very in uential. Also, as in human societies, previous experiences of the members of our group with that agent or his mates may be important [1]. This is what we call the social dimension of reputation. Finally, we consider that the reputation of an agent is not a single and abstract concept but rather it is a multi-facet concept. How these facets are combined to build reputations for complex concepts is what we call the ontological dimension of reputation. The approach followed in this paper is similar to that used in the work of Michael Schillo et al. [3] and Bin Yu et al. [4]. Our approach radically di ers from these in the sense that we take the stance that the agents' social structure is an essential factor in weighing the other agents' opinions. Another major contribution of our work is the way we model reputation as a multi-facet concept.
The value of interfirm cooperation : An event-study of new partnership announcements in the pharmaceutical industry

We investigate share price responses to the formation of 237 partnerships in the biotechnology/pharmaceutical industry spanning 1995-2000. The average stock price response is positive, more so than in previous empirical works, which could be interpreted as evidence that interfirm collaboration is particularly valuable in high-technology industries. We find no evidence of wealth transfers. While all sorts of alliances can be associated to significantly positive returns, more value accrues to the partnership when it involves the creation or the transfer of technological knowledge. Looking at the firm characteristics, we conclude that being the smaller partner in a technological alliance generates higher abnormal returns (while no correlation is found in non-technological partnerships). Finally, the stock market value associated to the partnership increases with the profitability of the member firm. JEL classification : L22; G32; D23; L65
The Optimality Analysis of Hybrid Reinforcement Learning Combined with SVMs

To reduce the learning time of reinforcement learning (RL), hybrid algorithms that combine reinforcement learning with various supervised learning methods have attracted many research interests. However, the global convergence and optimality become one of the main problems for hybrid reinforcement learning algorithms. In this paper, the convergence of a hybrid RL algorithm, which is combined with support vector machines (SVMs) is analyzed theoretically. It is shown that by making use of policy gradient learning and the SVM regression, the hybrid algorithm can easily escape from local optima
Journal of Object Technology Computational Abstraction Steps

In this paper we discuss computational abstraction steps as a way to create class abstractions from concrete objects, and from examples. Computational abstraction steps are regarded as symmetric counterparts to computational concretisation steps, which are well-known in terms of function calls and class instantiations. Our teaching experience shows that many novice programmers find it difficult to write programs with abstractions that materialise to concrete objects later in the development process. The contribution of this paper is the idea of initiating a programming process by creating or capturing concrete values, objects, or actions. As the next step, some of these are lifted to a higher level by computational means. In the object-oriented paradigm the target of such steps is classes. We hypothesise that the proposed approach primarily will be beneficial to novice programmers or during the exploratory phase of a program development process. In some specific niches it is also expected that our approach will benefit professional programmers.
Does the Media Matter? A Field Experiment Measuring the Effect of Newspapers on Voting Behavior and Political Opinions

We conducted a field experiment to measure the effect of exposure to newspapers on political behavior and opinion. Before the 2005 Virginia gubernatorial election, we randomly assigned individuals to a Washington Post free subscription treatment, a Washington Times free subscription treatment, or a control treatment. We find no effect of either paper on political knowledge, stated opinions, or turnout in post-election survey and voter data. However, receiving either paper led to more support for the Democratic candidate, suggesting that media slant mattered less in this case than media exposure. Some evidence from voting records also suggests that receiving either paper led to increased 2006 voter turnout.
Fuzzy Nonlinear Optimization for the Linear Fuzzy Real Number System

Quite a few problems in production planning and scheduling, location, transportation, finance, and engineering design require that decisions be made under uncertainty. In this paper, we focus on Fuzzy nonlinear optimization problems in the Linear Fuzzy Real (LFR) numbers. The problems will consist of fuzzy constraints and objective functions, crisp constraints with a fuzzy objective function, or fuzzy constraints with a crisp objective function. In this paper, we propose LFR Newton’s method for solving nonlinear systems and use it to solve optimization problems.
Toward Generalization of Automated Temporal Abstraction to Partially Observable Reinforcement Learning

Temporal abstraction for reinforcement learning (RL) aims to decrease learning time by making use of repeated sub-policy patterns in the learning task. Automatic extraction of abstractions during RL process is difficult but has many challenges such as dealing with the curse of dimensionality. Various studies have explored the subject under the assumption that the problem domain is fully observable by the learning agent. Learning abstractions for partially observable RL is a relatively less explored area. In this paper, we adapt an existing automatic abstraction method, namely extended sequence tree, originally designed for fully observable problems. The modified method covers a certain family of model-based partially observable RL settings. We also introduce belief state discretization methods that can be used with this new abstraction mechanism. The effectiveness of the proposed abstraction method is shown empirically by experimenting on well-known benchmark problems.
Discriminative Link Prediction using Local, Community, and Global Signals

Predicting plausible links that may emerge between pairs of nodes is an important task in social network analysis, with over a decade of active research. Here, we propose a novel framework for link prediction. It integrates signals from node features, the existing local link neighborhood of a node pair, community-level link density, and global graph properties. Our framework uses a stacked two-level learning paradigm. At the lower level, the first two kinds of features are processed by a novel local learner. Its outputs are then integrated with the last two kinds of features by a conventional discriminative learner at the upper-level. We also propose a new stratified sampling scheme for evaluating link prediction algorithms in the face of an extremely large number of potential edges, out of which very few will ever materialize. It is not tied to a specific application of link prediction, but robust to a range of application requirements. We report on extensive experiments with seven benchmark datasets and over five competitive baseline systems. The system we present consistently shows at least 10 percent accuracy improvement over state-of-the-art, and over 30 percent improvement in some cases. We also demonstrate, through ablation, that our features are complementary in terms of the signals and accuracy benefits they provide.