Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining the construct validity of the positive coping behavioural inventory

Orientation: Positive coping strengths are important personal resources in helping employees deal constructively with the complex interaction between the individual and the environment. Research purpose: The present study examined the usefulness and validity of the factor structure of the positive coping behavioural inventory (PCBI) with the view to further refine the scale and increase its usefulness and application value in the South African workplace. Motivation for the study: Valid and reliable multidimensional measures of positive psychological constructs are considered important in understanding the array of personal resources that help employees cope constructively with work–life stressors in today’s fastpaced and more turbulent work environment. Research design, approach and method: A cross-sectional survey design was utilised to collect primary data from a sample of ( N = 525) male and female employees from white and black ethnicity origin in the services industry. The participants’ self-evaluations of their positive coping behaviour were measured by means of the PCBI. Confirmatory factor analysis was performed to examine the construct validity of the PCBI. Main findings: The convergent validity and internal consistency reliability of the PCBI as a measure of three higher-order dimensions of positive coping behaviour (inventive, engaging and intentional coping behaviours) were demonstrated in this study. Practical and managerial implications: Researchers may confidently use the three-factor solution of the PCBI to measure employees’ self-evaluations of their capacity to demonstrate positive coping behaviour in the workplace. Contribution and value-add: This study contributed to the emerging body of knowledge on the assessment of positive psychology constructs that contribute to employees’ well-being and flourishing in the South African workplace. The results provide preliminary evidence of the usefulness of the PCBI as a valid and reliable multidimensional measure that integrates a wide array of positive psychology attributes in a single measure.
Social media analytics for YouTube comments: potential and limitations

Abstract The need to elicit public opinion about predefined topics is widespread in the social sciences, government and business. Traditional survey-based methods are being partly replaced by social media data mining but their potential and limitations are poorly understood. This article investigates this issue by introducing and critically evaluating a systematic social media analytics strategy to gain insights about a topic from YouTube. The results of an investigation into sets of dance style videos show that it is possible to identify plausible patterns of subtopic difference, gender and sentiment. The analysis also points to the generic limitations of social media analytics that derive from their fundamentally exploratory multi-method nature.
Automatic Lung Cancer Detection and Diagnosis Using Hand Crafted and Deep Learning Features

This paper presents a lung nodule detection and classification system which utilizes a combination of hand crafted and deep learning features. Hand crafted features were obtained from modified methods of bag of frequencies, and taxonomic indices. We included a robust radius estimation algorithm that resulted in an average error of 1.29 pixels. Hand crafted features were obtained from 3D low dose CT scans pertaining to lung cancer patients as well as control subjects, and we used the following specific features: the suspected nodule location, radius of the nodule, spectral signatures, taxonomic diversity and distinctness. Deep learning features were obtained with Inception-v3, a pretrained network trained on ImageNet, that is currently the state of the art Convolutional Neural Network (CNN) architecture for the ILSVRC challenge. Our work aims to expand upon existing detection and classification methods to improve lung cancer screening accuracies. Promising results indicated the superiority of combined features for lung tumor detection and diagnosis. Keywords—lung nodules, computed tomography (CT), computeraided detection, nodule detection, nodule characterization, pulmonary nodules, deep learning
Coin Recognition with Reduced Feature Set SIFT Algorithm Using Neural Network

Coin recognition is one of the prime important activities for modern banking and currency processing systems. These systems are widely used for coin sorting, automatic counting, and vending machines. The technique at the heart of such systems is object recognition in a digital image. Object classification and recognition is still one of the challenging research areas because we put our cognitive capabilities in a computer system through an algorithm. The reliability of such systems mainly depends on feature selection and extraction mechanism. This paper presents a novel approach for coins recognition. The proposed method uses Scale Invariant Feature Transform (SIFT) algorithm to handle the issues of rotations, scaling and illumination in a digital image. This is followed by Principle Component Analysis (PCA) for reducing extracted features set. This reduced feature set is passed to feed forward back-propagation artificial neural network (ANN) for classification and recognition. The experimental results indicate that proposed approach achieves state-of-the-art results for Pakistani coin recognition.
Structured variable selection in support vector machines

When applying the support vector machine (SVM) to high-dimensional classification problems, we often impose a sparse structure in the SVM to eliminate the influences of the irrelevant predictors. The lasso and other variable selection techniques have been successfully used in the SVM to perform automatic variable selection. In some problems, there is a natural hierarchical structure among the variables. Thus, in order to have an interpretable SVM classifier, it is important to respect the heredity principle when enforcing the sparsity in the SVM. Many variable selection methods, however, do not respect the heredity principle. In this paper we enforce both sparsity and the heredity principle in the SVM by using the so-called structured variable selection (SVS) framework originally proposed in Yuan, Joseph and Zou (2007). We minimize the empirical hinge loss under a set of linear inequality constraints and a lasso-type penalty. The solution always obeys the desired heredity principle and enjoys sparsity. The new SVM classifier can be efficiently fitted, because the optimization problem is a linear program. Another contribution of this work is to present a nonparametric extension of the SVS framework, and we propose nonparametric heredity SVMs. Simulated and real data are used to illustrate the merits of the proposed method.
Overexpression of microRNA-99a attenuates heart remodelling and improves cardiac performance after myocardial infarction

MicroRNAs are involved in the regulation of various cellular processes, including cell apoptosis and autophagy. Expression of microRNA‐99a (miR‐99a) is reduced in apoptotic neonatal mice ventricular myocytes (NMVMs) subjected to hypoxia. We hypothesize that miR‐99a might restore cardiac function after myocardial infarction (MI) by up‐regulation of myocyte autophagy and apoptosis. We observed down‐regulated miR‐99a expression in NMVMs exposed to hypoxia using TaqMan quantitative reverse transcriptase‐polymerase chain reaction analysis (RT‐PCR). We also observed that miR‐99a overexpression decreased hypoxia‐mediated apoptosis in cultured NMVMs. To investigate whether overexpression of miR‐99a in vivo could improve cardiac function in ischaemic heart, adult C57/BL6 mice undergoing MI were randomized into two groups and were intra‐myocardially injected with lenti‐99a‐green fluorescent protein (GFP) or lenti‐GFP (control). Four weeks after MI, lenti‐99a‐GFP group showed significant improvement in both left ventricular (LV) function and survival ratio, as compared to the lenti‐GFP group. Histological analysis, western blotting analysis and electron microscopy revealed decreased cellular apoptosis and increased autophagy in cardiomyocytes of lenti‐99a‐GFP group. Furthermore, western blotting analysis showed inhibited mammalian target of rapamycin (mTOR) expression in the border zones of hearts in miR‐99a‐treated group. Our results demonstrate that miR‐99a overexpression improves both cardiac function and survival ratio in a murine model of MI by preventing cell apoptosis and increasing autophagy via an mTOR/P70/S6K signalling pathway. These findings suggest that miR‐99a plays a cardioprotective role in post‐infarction LV remodelling and increased expression of miR‐99a may have a therapeutic potential in ischaemic heart disease.
Trivial Compiler Equivalence: A Large Scale Empirical Study of a Simple, Fast and Effective Equivalent Mutant Detection Technique

Identifying equivalent mutants remains the largest impediment to the widespread uptake of mutation testing. Despite being researched for more than three decades, the problem remains. We propose Trivial Compiler Equivalence (TCE) a technique that exploits the use of readily available compiler technology to address this long-standing challenge. TCE is directly applicable to real-world programs and can imbue existing tools with the ability to detect equivalent mutants and a special form of useless mutants called duplicated mutants. We present a thorough empirical study using 6 large open source programs, several orders of magnitude larger than those used in previous work, and 18 benchmark programs with hand-analysis equivalent mutants. Our results reveal that, on large real-world programs, TCE can discard more than 7% and 21% of all the mutants as being equivalent and duplicated mutants respectively. A human- based equivalence verification reveals that TCE has the ability to detect approximately 30% of all the existing equivalent mutants.
Shortest Path Routing Algorithm for Ficonn in Load Balanced Data Center Networks

This paper explores a Ficonn interconnection structure for load balanced data center servers using bi-ports. The tree-based structures are increasingly difficult to meet the design goals of data centers because of a single-point failure spot for its sub tree branch. And using excessive switches does not fundamentally solve the problem, but results even higher cost. So we are going for a new structure to interconnect a large number of servers which contain dual Ethernet ports, in which one is used for network connections and another for the backup purposes. If we make that both the ports are used for network connections then we can build an effective inter connection structure for the data center networks. We call such a network structure called as Ficonn. In addition, in this paper, we are using A* algorithm to find the shortest path and boost up the routing of packets transmitted between the commodity servers. And we have also proposed the deployment of Ficonn.
Feature Based Landmark Extraction for Real Time Visual SLAM

Recently, there has been a marked increase in using machine learning techniques for object detection because of its immunity to noise and variations in backgrounds. SLAM (Simultaneous Localization and Mapping) is an approach to mapping the environment in which the robot moves, by using landmarks, much like the human visual system. The application of a robust object detection system can be extended into the field of SLAM by using these as powerful visual landmarks. While the traditional approach to SLAM (based on sensors like the SONARs or LASERs) can provide a good perception of depth, they cannot form effective landmarks. The output of these devices contain the range data mapped on a 2D space. The landmark has to be significant to show up as a pattern and hence only significant landmarks get extracted. While the visual information may be more than enough to form very good landmarks, the required computational resource increases way beyond the realm of the present day embedded processors. We use GPUs (Graphic Processing Units) to process the visual information since they have been very successful in doing real-time rendering for graphics application which involve similar mathematics. The presence of a large number of cores makes this a challenging problem to solve as programming them can be quite complex to exploit the full bandwidth of these processors. Much work is going on to integrate these units into embedded devices which make it feasible to solve the problem of visual SLAM.
An asymmetric network coding algorithm in wireless networks

In the existing wireless network coding mechanism, the packets used to coded are always with equal length, which is always called symmetric network coding. This coding method can effectively improve the network performance. But it also limits the further improvement of network performance in the multimedia application environment, where data packets length is usually unequal. Here we propose an asymmetric network coding mechanism. Through splicing combination of the packets, asymmetric network coding could overcome the shortage of symmetric network coding.
MULTI-CHANNEL SPCMB-TOPS SAR FOR HIGH- RESOLUTION WIDE-SWATH IMAGING

To improve the impaired azimuth resolution of the novel Terrain Observation by Progressive Scans (TOPS) mode, a new multi- channel single phase center multiple beam (SPCMB) TOPS mode is proposed in this paper for high-resolution wide-swath (HRWS) imaging. However, the progressive azimuth beam scanning leads to the Doppler spectrum aliasing and both beam center time and Doppler centroid varying with the target's azimuth location. Challenges may arise for processing the SPCMB-TOPS SAR data from these problems. In this paper, an e-cient full aperture imaging approach is proposed to process the raw data. The sketch of the proposed imaging approach is described in detail. Simulation results of point targets validate the proposed imaging approach.
Knowledge, Attitude and Use of Evidence-Based Practice among nurses active on the Internet.

OBJECTIVE to determine the evidence-based practice (EBP) competence of Spanish and Latin-American nurses participating in professional forums on the Internet and estimate the influence of socio-demographic and professional factors on their competence, which was defined as knowledge of, attitude towards, and implementation of EBP. METHODOLOGY An online survey was administered to a convenience sample of nurses active in Internet forums, comprising validated Spanish versions of the Evidence-Based Practice Questionnaire (EBPQ) and Practice Environment Scale of the Nursing Work Index (PES-NWI) and socio-demographics and professional variables. RESULTS 314 questionnaires were obtained (76.96%). The mean EBPQ score was 5.02 out of 7 (95%CI, 4.89-5.14). The variables associated with a higher competence in EBP were academic level, (p<03001), professional category (p=0.001), country of work (p<0.001), perception of practice environment (p=0,018) and research activities (p<0,036). CONCLUSIONS These nurses showed a moderate level of EBP competence. They revealed a positive attitude towards EBP and achieved intermediate scores in both EBP-related skills and knowledge and their implementation. Higher academic levels and professional categories were associated with greater EBP competence. A practice environment perceived to be unfavorable has a negative influence on EBP implementation.
Classical and Bayesian Linear Data Estimators for Unique Word OFDM

Unique word-orthogonal frequency division multiplexing (UW-OFDM) is a novel OFDM signaling concept, where the guard interval is built of a deterministic sequence - the so-called unique word - instead of the conventional random cyclic prefix. In contrast to previous attempts with deterministic sequences in the guard interval the addressed UW-OFDM signaling approach introduces correlations between the subcarrier symbols, which can be exploited by the receiver in order to improve the bit error ratio performance. In this paper we develop several linear data estimators specifically designed for UW-OFDM, some based on classical and some based on Bayesian estimation theory. Furthermore, we derive complexity optimized versions of these estimators, and we study their individual complex multiplication count in detail. Finally, we evaluate the estimators' performance for the additive white Gaussian noise channel as well as for selected indoor multipath channel scenarios.
Shifting toward a Constructivist Philosophy for Teaching Biblical Principles in K-12 Christian Schools

Traditionally, the Bible curriculum in many K-12 Christian schools is based on memory work. If students can correctly reproduce a passage of Scripture, then they are somehow considered to be “educated. ” The authors of this paper suggest that a Bible curriculum should be shifted away from this traditional approach and towards an approach that is based in constructivist philosophy. Such a shift is necessary if the goal is to move students toward a mature and thoughtful Christian life. After establishing the need for this shift and describing what the shift would entail, the authors offer brief vignettes of classrooms where the constructivist approach is being used. These vignettes should provide readers with ideas for application of the constructivist approach.
Balanced Guides Assignment for Multi-Objective Particle Swarm Optimizer

Recently, more and more studies to apply particle swarm optimization (PSO) algorithm for solving multi-objective problems (MOPs) have been proposed. Due to there will be more than one global best solution gbest found can be solution searching clue in MOPs. For leading more particles toward to potential searching space and find global optimum, suitable local guide (global best solution) assignment becomes an important issue in multi-objective particle swarm optimizer. This paper presents a density-based local guide assign approach called balanced guide assignment (BGA) for multi-objective particle swarm optimization. Besides, for making proposed method more robust, a cluster archive approach and perturbation method are also involved with BGA. They can efficient improve particles’ solution searching ability to find more solutions located on/near to the Pareto front. Six benchmarks were adopted for testing and compare the proposed method with other related works. From the results, the proposed method performed better in performance metrics can be observed.
The combination of palm print and hand geometry for biometrics palm recognition

Biometrics as a method for identification systems has been widely used for its robustness; one of its used is based on human palm. Palm has unique characteristics to be used in personal identification because of it features, nam ely palm print and hand geometry. This paper studied about biometrics of palm for identification system using the physical form o f human hands, represented by the image of the palm. The methodology for palm recognition consisted of block-based line detection which dealing with palm print feature extraction process, and cha in code which solved the hand geometric feature extraction. We combined those two respective features and recognized it using Dynamic Time Warping (DTW) method which was able to measure the distance between two different features. The result can be u sed for personal identification in authentication systems f or information security.
How Does Code Obfuscation Impact Energy Usage?

Software piracy is an important concern for application developers. Such concerns are especially relevant in mobile application development, where piracy rates can approach 90%. The most commonly used approach by mobile developers for preventing piracy is code obfuscation. However, the decision to apply such transformations is currently made without regard to the impacts of obfuscations on another area of increasing concern for mobile application developers: energy consumption. Because both software piracy and battery life are important concerns, mobile application developers must strike a balance between protecting their applications and preserving the battery lives of their users' devices. To help them make such choices, we conducted an empirical study of the effects of 18 code obfuscations on the amount of energy consumed by executing a total of 15 usage scenarios spread across 11 Android applications. The results of the study indicate that, while obfuscations can have a statistically significant impact on energy usage and are significantly more likely to increase energy usage than to decrease energy usage, the magnitudes of such impacts are unlikely to impact mobile application users.
Multi-agent learning approach to WWW information retrieval using neural network

In this paper, we propose a multi-agent learning approach to information retrieval on the World Wide Web where each agent collaboratively learns its environment from user’s relevance feedback using a neural network mechanism. Our approach makes it possible to discover information sources that will give the desired information, and retrieve that information efficiently and effectively. First, we present a framework for our multi-agent learning approach and introduce a training procedure for capturing knowledge about user’s interests and preferences in the information retrieval domain. Secondly, we mathematically analyze the performance of our approach. Finally, to show the utility of our approach, we present the experimental results of our approach and compare them to those obtained by a traditional search service on the World Wide Web.
Josephson voltage standard as a current reference and practical method for stabilization of high current

A stable reference source with a high current capability is useful for many metrological applications. Unlike the conventional Josephson voltage standard, one can couple the programmable Josephson voltage standard (PJVS) to a current source below milliamp range to stabilize the current. For higher current ranges, we tested a feedback method which allowed us to stabilize the 0.1-A output current of a commercial current source to within a standard deviation of 2 /spl times/ 10/sup -8/ A/A.
Portuguese-language version of the COPD Assessment Test: validation for use in Brazil

OBJECTIVE: To validate a Portuguese-language version of the COPD assessment test (CAT) for use in Brazil and to assess the reproducibility of this version. METHODS: This was multicenter study involving patients with stable COPD at two teaching hospitals in the city of Fortaleza, Brazil. Two independent observers (twice in one day) administered the Portuguese-language version of the CAT to 50 patients with COPD. One of those observers again administered the scale to the same patients one week later. At baseline, the patients were submitted to pulmonary function testing and the six-minute walk test (6MWT), as well as completing the previously validated Portuguese-language versions of the Saint George's Respiratory Questionnaire (SGRQ), modified Medical Research Council (MMRC) dyspnea scale, and hospital anxiety and depression scale (HADS). RESULTS: Inter-rater and intra-rater reliability was excellent (intraclass correlation coefficient [ICC] = 0.96; 95% CI: 0.93-0.97; p < 0.001; and ICC = 0.98; 95% CI: 0.96-0.98; p < 0.001, respectively). Bland Altman plots showed good test-retest reliability. The CAT total score correlated significantly with spirometry results, 6MWT distance, SGRQ scores, MMRC dyspnea scale scores, and HADS-depression scores. CONCLUSIONS: The Portuguese-language version of the CAT is a valid, reproducible, and reliable instrument for evaluating patients with COPD in Brazil.
The Effect of Violent Star Formation on the State of the Molecular Gas in M 82

We present the results of a high angular resolution (4″), multi-transition analysis of the molecular gas in M 82. The analysis is based on the two lowest transitions of 12CO and the ground transition of the rare isotopomeres 13CO and C18O measured with the PdBI, the BIMA array and the IRAM 30m telescope.