Miracle-dz/UniFAR-FTUs huggingface dataset:
Research and application of association rule mining algorithm based on multidimensional sets

In this paper, we describe the basic concepts of multidimensional sets and multidimensional association rules, and propose a improved algorithm of association rule mining based on multidimensional sets. This algorithm can find out the maximal frequent item sets of each dimensional subset, and at the same time pruning the database, this can substantially reduce the workload of the subsequent mining and lead to efficient processing. Appling the algorithm to students' synthesis marks evaluation system, analyzing the related factors which influence the students' synthesis marks, for educators to improve teaching methods, to improve the quality of talent training.
The importance of the learning conditions in hyper-heuristics

Evolutionary Algorithms are problem solvers inspired by nature. The effectiveness of these methods on a specific task usually depends on a non trivial manual crafting of their main components and settings. Hyper-Heuristics is a recent area of research that aims to overcome this limitation by advocating the automation of the optimization algorithm design task. In this paper, we describe a Grammatical Evolution framework to automatically design evolutionary algorithms to solve the knapsack problem. We focus our attention on the evaluation of solutions that are iteratively generated by the Hyper-Heuristic. When learning optimization strategies, the hyper-method must evaluate promising candidates by executing them. However, running an evolutionary algorithm is an expensive task and the computational budget assigned to the evaluation of solutions must be limited. We present a detailed study that analyses the effect of the learning conditions on the optimization strategies evolved by the Hyper-Heuristic framework. Results show that the computational budget allocation impacts the structure and quality of the learned architectures. We also present experimental results showing that the best learned strategies are competitive with state-of-the-art hand designed algorithms in unseen instances of the knapsack problem.
A sort of improved image segmentation algorithm based on geometry characteristc

Aimed at the over-segmentation phenomenon when adopted traditional watershed algorithm to segment the image, the paper proposed a sort of new improved image segmentation algorithm based fuzzy mathematical morphology. Firstly it smoothed the image by means of opening-closing algorithm based fuzzy mathematical morphology. And based on the mathematical morphology it secondly computed the gradient operators. It finally segmented the gradient image to get the result based on fuzzy mathematical morphology. The result of simulation experiment showed that it is better in eliminating over segmentation phenomenon, and more applicable in image recognition.
Loss-of-Function Mutations in Three Homoeologous PHYTOCLOCK 1 Genes in Common Wheat Are Associated with the Extra-Early Flowering Phenotype

Triticum aestivum L. cv ‘Chogokuwase’ is an extra-early flowering common wheat cultivar that is insensitive to photoperiod conferred by the photoperiod insensitive alleles at the Photoperiod-B1 (Ppd-B1) and Ppd-D1loci, and does not require vernalization for flowering. This reduced vernalization requirement is likely due to the spring habitat allele Vrn-D1 at the VERNALIZATION-D1 locus. Genotypes of the Ppd-1 loci that determine photoperiod sensitivity do not fully explain the insensitivity to photoperiod seen in ‘Chogokuwase’. We detected altered expression patterns of clock and clock-output genes including Ppd-1 in ‘Chogokuwase’ that were similar to those in an einkorn wheat mutant that lacks the clock-gene homologue, wheat PHYTOCLOCK 1 (WPCL1). Presumptive loss-of-function mutations in all WPCL1 homoeologous genes were found in ‘Chogokuwase’ and ‘Geurumil’, one of the parental cultivars. Segregation analysis of the two intervarietal F2 populations revealed that all the examined F2 plants that headed as early as ‘Chogokuwase’ had the loss-of-function wpcl1 alleles at all three homoeoloci. Some F2 plants carrying the wpcl1 alleles at three homoeoloci headed later than ‘Chogokuwase’, suggesting the presence of other loci influencing heading date. Flowering repressor Vrn-2 was up-regulated in ‘Chogokuwase’ and ‘Geurumil’ that had the triple recessive wpcl1 alleles. An elevated transcript abundance of Vrn-2 could explain the observation that ‘Geurumil’ and some F2 plants carrying the three recessive wpcl1 homeoealleles headed later than ‘Chogokuwase’. In spite of the up-regulation of Vrn-2, ‘Chogokuwase’ may have headed earlier due to unidentified earliness genes. Our observations indicated that loss-of-function mutations in the clock gene wpcl1 are necessary but are not sufficient to explain the extra-early heading of ‘Chogokuwase’.
Intelligent Information Dissemination in Vehicular Ad Hoc Networks

Vehicular Ad hoc Networks (VANETs) are a compelling application of ad hoc networks, because of the potential to access specific context information (e.g. traffic conditions, service updates, route planning) and deliver multimedia services (VOIP, in-car entertainment, instant messaging, etc.). In this paper, we propose an agent based intelligent information dissemination model for VANETs. Safety information like cooperative driving, accident, road condition warnings, etc. play a major role for applications of VANET. Safety information dissemination poses a major challenge of delay-sensitive nature. This paper proposes an agent based model for intelligent information dissemination in VANETs. Proposed model uses cognitive agent concept for realizing intelligent information dissemination. To test the efficiency of the model, proposed scheme is simulated using NS-2 simulator. Some of the performance parameters analyzed are bandwidth utilized, push latency and push/pull decision latency.
Estimation of signal dependent noise parameters from a single image

The additive white Gaussian noise (AWGN) is usually assumed in many image processing algorithms. However, these algorithms cannot effectively deal with the noise from actual cameras which is better modeled as signal dependent noise (SDN). In this paper, we focus on the SDN model and propose an algorithm to accurately estimate its parameters without any assumption of the noise types. The noise parameters are estimated by using the selected weak textured patches from a single noisy image. Experiments on synthetic noisy images are conducted to test the algorithm, which show that our noise parameter estimation outperforms the existing algorithms. And based on our estimation, the performance of image processing applications like Wiener filter can be effectively improved.
Pelvic Organs Dynamic Feature Analysis for MRI Sequence Discrimination

Dynamic magnetic resonance imaging MRI acquisitions are used in the clinical assessment of the pelvic organs behaviour during an abdominal strain. The main organs (bladder, uterus-vagina, rectum) undergo deformations and intrinsic movements along a sequence. Anatomical references and measurements are generally used by clinicians to evaluate pathology grades. In this context, we have established quantitative elements, which consist of deformation and movement features, for the pelvic dynamic characterization, by using shape descriptors computed from organ contours. Moreover, the deformation and movement features relevance has been assessed towards an efficient sequence discrimination and pathology detection.
Dynamic critical-path task mapping and scheduling for collaborative in-network processing in multi-hop wireless sensor networks

Although task mapping and scheduling in wired networks of processors has been extensively studied, their application to WSNs remains largely unexplored. Existing algorithms cannot be directly implemented in WSNs due to limited resource availability and shared communication medium. In this work, an application-independent task mapping and scheduling solution in multi-hop WSNs is presented that provides realtime guarantees. Using a novel multi-hop channel model and a communication scheduling algorithm, computation tasks and associated communication events are scheduled simultaneously with a dynamic critical-path scheduling algorithm. Dynamic voltage scaling (DVS) mechanism is implemented to further optimize energy consumption. According to the simulation results, the proposed solution outperforms existing mechanisms in terms of guaranteeing application deadlines with minimum energy consumption
CIEL: COLLABORATIVE ENGAGEMENT TO REDUCE DEATHS FROM OPIATE OVERDOSE

Themed around “design for health and wellness”, undergraduate industrial design and masters of health design students undertook a design challenge to create responses to the opioid crisis. Engaging directly with the idea of context and with a range of stakeholders, this design challenge provided an opportunity to develop a framework for a learning experience inclusive of underserved, marginalized, and stigmatized groups.
Critical Consciousness, Racial Identity, and Appropriated Racial Oppression in Black Emerging Adults

CRITICAL CONSCIOUSNESS, RACIAL IDENTITY, AND APPROPRIATED RACIAL OPPRESSION IN BLACK EMERGING ADULTS By Keyona Allen, M.Ed. A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science at Virginia Commonwealth University. Virginia Commonwealth University, 2018 Major Director: Shawn O. Utsey, Ph.D., Chair of African American Studies Professor of Psychology Department of Psychology The present study explored private regard and public regard, two subcomponents of racial identity, as mediators of the association between critical consciousness and appropriated racial oppression. In a sample of 75 Black emerging adults, ages 18-25, the current study examined (1) the relationships between critical consciousness, racial identity, and appropriated racial oppression and (2) whether racial identity mediates the relationship between critical consciousness and appropriated racial oppression. Relationships in the expected direction were evident between private regard and both critical consciousness and appropriated racial oppression. Relationships in the expected direction were evident between public regard and critical consciousness. Further, mediation analyses indicated that the relationship between critical consciousness and appropriated racial oppression was mediated by private regard. These findings indicate how critical consciousness and private regard may play a significant role in influencing appropriated racial oppression in Black emerging adults.
The spectrum of surface-mode contributions to the excitation probability for an electron beam interacting with sharp-edged dielectric wedges

The interaction of a nonrelativistic charged-particle beam travelling parallel to the surface of a sharp-edged dielectric wedge is analysed. The general expressions for the excitation probability are obtained for a beam moving along the direction of a symmetry axis, either outside or inside the dielectric wedge. The dielectric function of the medium is assumed to be isotropic, and numerical results are given for the materials of experimental interest.
Specific and Sensitive Detection of Venturia nashicola, the Scab Fungus of Asian Pears, by Nested PCR

The fungus Venturia nashicola is the causal agent of scab on Asian pears. For the rapid and reliable identification as well as sensitive detection of V. nashicola, a PCR-based technique was developed. DNA fingerprints of three closely related species, V. nashicola, V. pirina, and V. inaequalis, were obtained by random amplified polymorphic DNA (RAPD) analysis. Two RAPD markers specific to V. nashicola were identified by PCR, after which two pairs of sequence characterized amplified region (SCAR) primers were designed from the nucleotide sequences of the markers. The SCAR primer pairs, designated as D12F/D12R and E11F/E11R, amplified 535-bp and 525-bp DNA fragments, respectively, only from genomic DNA of V. nashicola. The specificity of the primer sets was tested on strains representing three species of Venturia and 20 fungal plant pathogens. The nested PCR primer pair specific to V. nashicola was developed based on the sequence of the species-specific 525-bp DNA fragment amplified by primer set E11F/E11R. The internal primer pair Na11F/Na11R amplified a 235-bp fragment from V. nashicola, but not from any other fungal species tested. The nested PCR assay was sensitive enough to detect the specific fragment in 50 fg of V. nashicola DNA.
Author ' s personal copy Are the bankrupt skies the friendliest ? ☆

Article history: Received 13 August 2010 Received in revised form 12 July 2012 Accepted 17 July 2012 Available online 23 July 2012 We use data from the US airline industry to investigate whether firms that are under bankruptcy protection, as well as these firm's product market rivals, change the quality of the products they offer. We measure the quality of the services offered by a carrier using flight cancelations and delays, and the age of the aircraft used by the carrier. We find that delays and cancelations are less frequent during bankruptcy filings but return to their pre-bankruptcy levels once the bankrupt firm emerges from bankruptcy. We also find that firms use Chapter 11 filings to permanently reduce the age of their fleet. We do not find evidence of statistically and economically significant changes by the airline's competitors along any of the dimensions above. © 2012 Elsevier B.V. All rights reserved. JEL classification:
Encoderless Finite-State Predictive Torque Control for Induction Machine With a Compensated MRAS

An encoderless predictive torque control (PTC) is proposed in this paper. By using a rotor flux model reference adaptive system (MRAS) estimation method to PTC, the system has the virtue of low cost due to the absence of PWM and speed measurement components. PTC requires not only estimated speed but also estimated stator and rotor flux. In implementation, a compensated MRAS is considered for obtaining good flux estimations. The experimental results confirm that this control strategy has very fast dynamics, can adapt a very wide speed range, and shows good performance both at transient and steady states.
Towards Key Issues of Disaster Aid based on Wireless Body Area Networks

With recent advances in wireless communication and low-power miniaturized biomedical sensor and semiconductor technologies, wireless body area networks (WBAN) has become an integral part of the disaster aid system. Wearable vital sign sensors can track patients’ status and location, thus enhancing disaster rescue efficiency. In the past few years, most of the literatures in the area of disaster aid system based on WBAN have focused on issues concerning wireless sensor design, sensor miniaturization, energy efficiency and communication protocols. In this paper, we will give an overview of disaster aid, discuss about the types of network communication as well as outline related issues. We will emphasize on analyzing six key issues in employing the disaster aid system. Finally, we will also highlight some of the challenges that still need to be addressed in the future in order to help the disaster aid system be truly and widely accepted by the public.
Information retrieval from social networks: A survey

Social networks are becoming an integral part of people's life to share and disseminate information instantly. Users share their views on a particular topic or events and receive feedback from their followers, friends and colleagues in form of comments, like, dislike, upvote, downvote etc. Since the user has a very limited control on previously shared information and has limited storage space in his/her account, the management of users information is a very tedious task. In this paper, we discuss different types of social networking services and user's information shared on these services. We categorize the content based information into two categories namely textual content based information and visual content based information. Then we discuss the major efforts made for retrieval of these information from different social networks. We also outline a procedure for content based information retrieval from multiple social networks.
It’s Not Just What You Say, But How You Say It: Muiltimodal Sentiment Analysis Via Crowdsourcing

This paper examines the effect of various modalities of expression on the reliability of crowdsourced sentiment polarity judgments. A novel corpus of YouTube video reviews was created, and sentiment judgments were obtained via Amazon Mechanical Turk. We created a system for isolating text, video, and audio modalities from YouTube videos to ensure that annotators could only see the particular modality or modalities being evaluated. Reliability of judgments was assessed using Fleiss Kappa inter-annotator agreement values. We found that the audio only modality produced the most reliable judgments for video fragments and that across modalities video fragments are less ambiguous than full videos.
Another look at market power in the Australian fresh meat industries

The issue of market power in the Australian food marketing chain is of continuing and growing concern. Contributing factors include sharply rising retail food prices in recent years together with relatively stable farm prices, and thus increasing marketing margins; high and increasing concentration in the retail food sector, where the two largest supermarket chains account for a large percentage of total national grocery sales; and the legacy of past deregulation of agricultural marketing institutions and trade liberalisation. In this paper an updated quantitative analysis of the competitive behaviour of the marketing chains for beef, lamb, pork and chicken, from farm gate to retail, is reported. A New Empirical Industrial Organisation model is used. Both linear and nonlinear, and single equation and SUR, regression analyses are estimated. As with previous studies, no evidence is found that the marketing chains for the Australian fresh meat industries are non-competitive.
Viewsphere: A GIS-Based 3D Visibility Analysis for Urban Design Evaluation

Previously, GIS-based visibility analysis has been conducted mainly in two dimensions, based on the concept of an isovist in the built environment or the concept of a viewshed in terrain and landscape analysis. The Viewsphere, a GIS approach towards 3D visibility analysis is proposed for measuring visible urban space quantitatively in a way that is different from its predecessors, the isovist and the viewshed. A test case of Singapore's urban space was conducted by evaluating the visibility of three alternative urban design scenarios and their potential impacts on the visual quality of open space. Both directional and nondirectional approaches were applied to the mapping of visibility based on the 2D and 3D indices. The proposition that 3D visibility indices are more effective than 2D indices was verified. The findings show that the 3D indices are sensitive to the changes of z-dimension.
Using Shape models for Error Correction of On-line Handwriting

A writer-dependent technique is proposed for automatically correcting written spelling errors in on-line cursive handwriting. In a training process, handwriting samples of the user are collected and segmented into characters by using a writer-independent segmentation algorithm. Shape models are built on these samples to capture the user’s writing style for each character. In the application process, handwriting errors are accurately located using a shape model-based character spotting algorithm. The handwriting trajectory is segmented at the error location and if necessary, a new character is generated from shape models and connected with previous strokes smoothly with the guidance of a conditional sampling algorithm. Experimental results show that the corrected handwriting still maintains the user’s writing style without perceptible artifacts.
Cepstral and long-term features for emotion recognition

In this paper, we describe systems that were developed for the Open Performance Sub-Challenge of the INTERSPEECH 2009 Emotion Challenge. We participate in both two-class and fiveclass emotion detection. For the two-class problem, the best performance is obtained by logistic regression fusion of three systems. These systems use short- and long-term speech features. Fusion allowed to an absolute improvement of 2:6% on the unweighted recall value compared with [1]. For the fiveclass problem, we submitted two individual systems: cepstral GMM vs. long-term GMM-UBM. The best result comes from a cepstral GMM and produces an absolute improvement of 3:5% compared to [6].
In vitro morphogenesis of chick embryo hypertrophic cartilage

Dedifferentiated chick embryo chondrocytes (Castagnola, P., G. Moro, F. Descalzi-Cancedda, and R. Cancedda, 1986, J. Cell Biol., 102:2310- 2317), when transferred to suspension culture on agarose-coated dishes in the presence of ascorbic acid, aggregate and remain clustered. With time in culture, clusters grow in size and adhere to each other, forming structures that may be several millimeters in dimension. These structures after 7 d of culture have the histologic appearance of mature hypertrophic cartilage partially surrounded by a layer of elongated cells resembling the perichondrium. Cells inside the aggregates have ultrastructural features of stage I (proliferating) or stage II (hypertrophic) chondrocytes depending on their location. Occurrence and distribution of type I, II, and X collagens in the in vitro-formed cartilage at different times of culture, show a temporal and spatial distribution of these antigens reminiscent of the maturation events occurring in the cartilage in vivo. A comparable histologic appearance is shown also by cell aggregates obtained starting with a population of cells derived from a single, cloned, dedifferentiated chondrocyte.
Mining online software tutorials: challenges and open problems

Web-based software tutorials contain a wealth of information describing software tasks and workflows. There is growing interest in mining these resources for task modeling, automation, machine-guided help, interface search, and other applications. As a first step, past work has shown success in extracting individual commands from textual instructions. In this paper, we ask: How much further do we have to go to more fully interpret or automate a tutorial? We take a bottom-up approach, asking what it would take to: (1) interpret individual steps, (2) follow sequences of steps, and (3) locate procedural content in larger texts.