Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationships Among Particle Number, Surface Area, and Respirable Mass Concentrations in Automotive Engine Manufacturing

This study investigated the relationships between particle number, surface area, and respirable mass concentration measured simultaneously in a foundry and an automotive engine machining and assembly center. Aerosol concentrations were measured throughout each plant with a condensation particle counter for number concentration, a diffusion charger for active surface area concentration, and an optical particle counter for respirable mass concentration. At selected locations, particle size distributions were characterized with the optical particle counter and an electrical low pressure impactor. Statistical analyses showed that active surface area concentration was correlated with ultrafine particle number concentration and weakly correlated with respirable mass concentration. Correlation between number and active surface area concentration was stronger during winter (R 2 = 0.6 for both plants) than in the summer (R 2 = 0.38 and 0.36 for the foundry and engine plant respectively). The stronger correlation in winter was attributed to use of direct-fire gas fired heaters that produced substantial numbers of ultrafine particles with a modal diameter between 0.007 and 0.023 μ m. These correlations support findings obtained through theoretical analysis. Such analysis predicts that active surface area increasingly underestimates geometric surface area with increasing particle size, particularly for particles larger than 100 nm. Thus, a stronger correlation between particle number concentration and active surface area concentration is expected in the presence of high concentrations of ultrafine particles. In general, active surface area concentration may be a concentration metric that is distinct from particle number concentration and respirable mass concentration. For future health effects or toxicological studies involving nano-materials or ultrafine aerosols, this finding needs to be considered, as exposure metrics may influence data interpretation.
A three-phase soft-switched high power density DC/DC converter for high power applications

The authors present three DC/DC converter topologies suitable for high-power-density high-power applications. All three circuits operate in a soft-switched manner, making possible a reduction in device switching losses and an increase in switching frequency. The three-phase dual-bridge converter proposed is seen to have the most favorable characteristics. This converter consists of two three-phase inverter stages operating in a high frequency six-step mode. In contrast to existing single-phase AC-link DC/DC converters, low RMS current ratings are obtained for both the input and output filter capacitors. This is in addition to smaller filter element values due to the higher-frequency content of the input and output waveforms. The use of a three-phase symmetrical transformer instead of single-phase transformers and a better utilization of the available apparent power of the transformer (as a consequence of the controlled output inverter) significantly increase the power density attainable. <<ETX>>
Register Transfer Level Simulation Acceleration via Process Migration

An epoxy resin composition consisting essentially of a heat-melted mixture obtained by mixing under heat 100 parts by weight of an epoxy resin having an epoxy equivalent of 200 or below and 0.5 to 10 parts by weight of polysulfone resin; a curing agent; and an inorganic filling material.
One Size Doesn ’ t Fit All : Knowledge Management Systems and Knowledge Sharing Practices in Global Learning Organizations

An increasing number of global organizations have adopted knowledge management practices and implemented worldwide knowledge management systems utilizing global communication networks and collaborative technology. The existing literature on knowledge management has focused on a common, firm-wide approach to knowledge sharing. Substantial differences exist, however, among the sub-units within many global organizations in terms of strategic, operational, and socio-cultural contexts. Such differences in the environments lead to internal differences in knowledge sharing practices. A field study at four offices of a large, global management consulting firm revealed that knowledge sharing practices at local offices were shaped by the unique strategic roles of the offices. The results suggest that global organizations must, contrary to the frequently-suggested uniform approach, understand the the strategic roles of the local units, and consider these in designing knowledge management support tools and practices.
Delayed triggering of radio Active Galactic Nuclei in gas-rich minor mergers in the local Universe

We examine the processes triggering star formation and active galactic nucleus (AGN) activity in a sample of 25 low-redshift (z 107 K) brightness temperature required for an mJIVE-20 detection allows us to unambiguously identify the radio AGN in our sample. We find three such objects. Our VLBI AGN identifications are classified as Seyferts or low-ionization nuclear emission-line regions (LINERs) in narrow line optical diagnostic plots; mid-infrared colours of our targets and the comparison of Hα star formation rates with integrated radio luminosity are also consistent with the VLBI identifications. We reconstruct star formation histories in our galaxies using optical and UV photometry, and find that these radio AGN are not triggered promptly in the merger process, consistent with previous findings for non-VLBI samples of radio AGN. This delay can significantly limit the efficiency of feedback by radio AGN triggered in galaxy mergers. We find that radio AGN hosts have lower star formation rates than non-AGN radio-selected galaxies at the same starburst age. Conventional and VLBI radio imaging shows these AGN to be compact on arcsecond scales. Our modelling suggests that the actual sizes of AGN-inflated radio lobes may be much larger than this, but these are too faint to be detected in existing observations. Deep radio imaging is required to map out the true extent of the AGN, and to determine whether the low star formation rates in radio AGN hosts are a result of the special conditions required for radio jet triggering, or the effect of AGN feedback.
The Acceleration of the Nebular Shells in Planetary Nebulae in the Milky Way Bulge

We present a systematic study of line widths in the [O III] λ5007 and Hα lines for a sample of 86 planetary nebulae in the Milky Way bulge based on spectroscopy obtained at the Observatorio Astronómico Nacional in the Sierra San Pedro Mártir (OAN-SPM) using the Manchester Echelle Spectrograph. The planetary nebulae were selected with the intention of simulating samples of bright extragalactic planetary nebulae. We separate the planetary nebulae into two samples containing cooler and hotter central stars, defined by the absence or presence, respectively, of the He II λ6560 line in the Hα spectra. This division separates samples of younger and more evolved planetary nebulae. The sample of planetary nebulae with hotter central stars has systematically larger line widths, larger radii, lower electron densities, and lower Hβ luminosities. The distributions of these parameters in the two samples all differ at significance levels exceeding 99%. These differences are all in agreement with the expectations from hydrodynamical models, but for the first time confirmed for a homogeneous and statistically significant sample of Galactic planetary nebulae. We interpret these differences as evidence for the acceleration of the nebular shells during the early evolution of these intrinsically bright planetary nebulae. As is the case for planetary nebulae in the Magellanic Clouds, the acceleration of the nebular shells appears to be the direct result of the evolution of the central stars.
Global Index Oriented Non-Shard Key for Multi-tenant Database

For SaaS applications, multi-tenant data storage can be mixed to make full use of storage resources, which makes the single tenant's data may be spread across multiple data nodes. For queries based on shard key, they can be located directly to the relevant nodes. However, for queries based on non-shard key, they need to implement a global parallel retrieval even if there are indices on the conditions. In response to these issues, the paper introduces global index to multi-tenant data storage model. By publishing tenant's the local index to establish and maintain a global index entries, it can reduce the number of computing nodes involved in the query operation. Experiments and analysis shows that the global index effectively reduces the resource usage of parallel search operation to improve the query efficiency.
Multi-User Detection Scheme Based on Hidden Training Sequence for DS-UWB Systems

SUMMARY In this letter, we propose a multi-user detection scheme based on a hidden training sequence for DS-UWB systems. The hidden training sequence, which uses a fraction of the informative sequence’s transmitting power as training information, is utilized for the receiver filter adaptation and channel estimation. By using this, the proposed scheme offers increased bandwidth efficiency (no period dedicated for training) and also shows reasonably good performance and near-far resistance in single
An efficient VLSI architecture for variable threshold simple edge preserved denoising algorithm with improved signal to noise ratio

Image acquisition and transmission stands challenging in applications such as medical imaging, underwater imaging, image segmentation and face recognition where images are often corrupted by impulse noise. The key aim is to reduce the impulse noise effectively by less number of computations, less memory, less power consumption and yet achieving good visual quality of the images compared to the existing techniques. In this paper, a new intelligent low cost hardware module suitable for reduction of impulse noise is proposed. The technique which we follow here is Improved Simple Edge Preserved Denoising (ISEPD) technique with variable threshold. Simulation results show that the PSNR has improved compared to other previous techniques. Synthesis results show that the processing rate is 133 M samples/second by using TSMC 0. 18µm technology.
Preliminary study of DSRC using MIMO technique and software defined radio for ITS

The development of DSRC (Dedicate Short Range Communication) for ITS (Intelligence Transportation System) has been recently concerned for high speed data transmission. However, the existing DSRC technique provides a low speed data transmission. The searching for new techniques to support transmission requirement is still on focus. This paper introduces to apply MIMO (Multiple-Input Multiple-Output) technique and SDR technology to study the performance of 5.9GHz DSRC based on IEEE802.11p (WAVE-DSRC) standard. The experiment results show that both BER and throughput performances are improved by using the proposed system.
Small vessel detection in high quality optical satellite imagery - using component tree image representation and random forest classification

Maritime vessel detection is an important part of maritime safety and at its heart lies detection of vessels in satellite imagery. Current developments have made the detection of small vessels particularly important as pronounced by the International Maritime Organization. The growing availability of high-quality (sub-meter resolution) images has made feasible the detection of small vessels that previously seemed impossible. As the amount of data increases so does the need for ecient methods of processing such data. The work here presented introduces a new method for detection of small vessels in high resolution optical satellite images. The isolation of vessel candidates is performed by filtering applied to a component tree representation of the satellite image. The classification of the extracted vessel candidates is performed by a feature based random forest classifier. Performance of the vessel detection introduced in this work ranges from 85-99% depending on the tolerance for the amount of false detections. The method presented performs well compared to other work in the are and gives confidence in the possibilities of a method based on the approach presented in this work.
Data-Driven Risk Assessment from Small Scale Epidemics: Estimation and Model Choice for Spatio-Temporal Data with Application to a Classical Swine Fever Outbreak

Livestock epidemics have the potential to give rise to significant economic, welfare, and social costs. Incursions of emerging and re-emerging pathogens may lead to small and repeated outbreaks. Analysis of the resulting data is statistically challenging but can inform disease preparedness reducing potential future losses. We present a framework for spatial risk assessment of disease incursions based on data from small localized historic outbreaks. We focus on between-farm spread of livestock pathogens and illustrate our methods by application to data on the small outbreak of Classical Swine Fever (CSF) that occurred in 2000 in East Anglia, UK. We apply models based on continuous time semi-Markov processes, using data-augmentation Markov Chain Monte Carlo techniques within a Bayesian framework to infer disease dynamics and detection from incompletely observed outbreaks. The spatial transmission kernel describing pathogen spread between farms, and the distribution of times between infection and detection, is estimated alongside unobserved exposure times. Our results demonstrate inference is reliable even for relatively small outbreaks when the data-generating model is known. However, associated risk assessments depend strongly on the form of the fitted transmission kernel. Therefore, for real applications, methods are needed to select the most appropriate model in light of the data. We assess standard Deviance Information Criteria (DIC) model selection tools and recently introduced latent residual methods of model assessment, in selecting the functional form of the spatial transmission kernel. These methods are applied to the CSF data, and tested in simulated scenarios which represent field data, but assume the data generation mechanism is known. Analysis of simulated scenarios shows that latent residual methods enable reliable selection of the transmission kernel even for small outbreaks whereas the DIC is less reliable. Moreover, compared with DIC, model choice based on latent residual assessment correlated better with predicted risk.
Brief Communication on Parents’ Perception towards Favourite Play Equipment, Satisfaction Level and Safety of Public Climbing Equipment in Malaysia

Public playground injuries caused by unsafe climbing equipment is a public health concern. This study aims to measure Malaysian parents’ perception towards their children’s favourite play equipment and satisfaction level on public equipment safety. A self-administered survey was employed among 50 Malaysians citizen, aged between 18 to 45 years. Data was descriptively analysed using SPSS version 21.0. The results showed that climbing equipment was favourite playing equipment among children. Furthermore, our study revealed that (90%) of parents were dissatisfied with public climbing equipment. We found that while (92%) of the parents agreed that safety levels of the climbing equipment should be improved. In addition, the study revealed that more than three quarters of respondents agreed to reduce free fall height, improve product materials, focus on reducing falls, and implement effective safety inspection including regular maintenance to improve the safety level of public climbing equipment. Results from this study could assist in advanced urban recreation safety for controlling injuries and regain parents’ trust on playground safety.
A Brief Study of Open Source Graph Databases

With the proliferation of large irregular sparse relational datasets, new storage and analysis platforms have arisen to fill gaps in performance and capability left by conventional approaches built on traditional database technologies and query languages. Many of these platforms apply graph structures and analysis techniques to enable users to ingest, update, query and compute on the topological structure of these relationships represented as set(s) of edges between set(s) of vertices. To store and process Facebook-scale datasets, they must be able to support data sources with billions of edges, update rates of millions of updates per second, and complex analysis kernels. These platforms must provide intuitive interfaces that enable graph experts and novice programmers to write implementations of common graph algorithms. In this paper, we explore a variety of graph analysis and storage platforms. We compare their capabil- ities, interfaces, and performance by implementing and computing a set of real-world graph algorithms on synthetic graphs with up to 256 million edges. In the spirit of full disclosure, several authors are affiliated with the development of STINGER.
Minimum waste scheduling of dynamic variable-latency and non-manifest fuctional units

In this paper we address the problem of scheduling algorithms embodied with a mixture of nonmanifest-loops [1], variable-latency and fixed-latency units [2], [3] for high throughput DSP-applications. Nonmanifest loops are loops where the number of iterations needed for a calculation is data dependent and hence not known at compile time. The body of a non-manifest loop can either have fixed-latency or variable-latency. Variable latency units are hardware execution units, that will complete a given operation after a variable quantity of clock cycles. When designing an Application Specific Processor for high throughput applications, the task is to design the processor based on prior knowledge of the algorithm to be implemented. If the algorithm body can be represented as a directed acyclic graph, a static schedule can be obtained by assuming the worst case latency of the units. However such a schedule might be inefficient in terms of latency and throughput due to the worst case latency assumption. A dynamic hardware scheduler on the other hand can outperform a static scheduler by gaining those waisted clock cycles. In this paper we present a self scheduling hardware execution unit, based on ideas taken from dynamic data flow machines. This execution unit is capable of scheduling an algorithm body that contains a mixture of non-manifest loops, variable-latency and fixed-latency units without wasting any extra clock cycles
Bi-directional SOVA decoding for turbo-codes

In this letter, we present a bi directional SOVA-based decoding scheme for turbo-codes, which combines the soft-outputs provided by both forward and backward SOVA decodings. Importantly, we explain why this bi-directional decoding improves SOVA decoding. The simulation results show that bi-directional SOVA can achieve about the same performance as the Max-Log-MAP algorithm in turbo decoding.
Maternal Age at Birth and Childhood Type 1 Diabetes: A Pooled Analysis of 30 Observational Studies

OBJECTIVE The aim if the study was to investigate whether children born to older mothers have an increased risk of type 1 diabetes by performing a pooled analysis of previous studies using individual patient data to adjust for recognized confounders. RESEARCH DESIGN AND METHODS Relevant studies published before June 2009 were identified from MEDLINE, Web of Science, and EMBASE. Authors of studies were contacted and asked to provide individual patient data or conduct prespecified analyses. Risk estimates of type 1 diabetes by maternal age were calculated for each study, before and after adjustment for potential confounders. Meta-analysis techniques were used to derive combined odds ratios and to investigate heterogeneity among studies. RESULTS Data were available for 5 cohort and 25 case-control studies, including 14,724 cases of type 1 diabetes. Overall, there was, on average, a 5% (95% CI 2–9) increase in childhood type 1 diabetes odds per 5-year increase in maternal age (P = 0.006), but there was heterogeneity among studies (heterogeneity I2 = 70%). In studies with a low risk of bias, there was a more marked increase in diabetes odds of 10% per 5-year increase in maternal age. Adjustments for potential confounders little altered these estimates. CONCLUSIONS There was evidence of a weak but significant linear increase in the risk of childhood type 1 diabetes across the range of maternal ages, but the magnitude of association varied between studies. A very small percentage of the increase in the incidence of childhood type 1 diabetes in recent years could be explained by increases in maternal age.
Recognizing and Resolving the Challenges of Being an Insider Researcher in Work-Integrated Learning.

Insider research studies are common in work-integrated learning (WIL) research, yet little has been written about the methodological and ethical dilemmas that WIL researchers face. Using a case study narrative, the position of an insider researcher is justified, and the challenges faced, when a researcher undertakes an in-depth study of their own WIL program is examined. The unique perspective of the history and culture of the researcher’s program was the most significant advantage, enabling a deep level of understanding and interpretation. Key challenges included: minimizing the potential for implicit coercion of the participants; acknowledging the desire for positive outcomes; ensuring tacit patterns and regularities were not taken for granted; and awareness of the potential conflicts of being an academic and researcher within the same context. In this paper, strategies to assist WIL researchers minimize these challenges are suggested. Insider research provides a valuable contribution to the theory and practice of WIL from a different perspective than may be obtained by someone not deeply embedded and involved.
Home away from home- the role of social support for international students' adjustment

Purpose – Academic and psychological adjustment of international students is central to their success while pursuing their degrees abroad. However, acculturation stress is abundant and may pose as a challenge. Thus, in this study we examined whether social support mediates the association between acculturation stress and academic and psychological adjustment.Methodology – A cross sectional research design was employed. A total of 200 postgraduate international students from three Malaysian public universities were recruited to participate in the study.The Student Adjustment to College Questionnaire was employed to measure their academic adjustment and psychological adjustment.The Multidimensional Scale for Perceived Social Support and the Acculturative Stress Scale for International Students were used to collect data on social support and acculturation stress. Path analysis by AMOS 23 was used to test the hypothesized relationship. Findings –Results provided support for the proposed model, revealing that social support was associated with greater academic and psychological adjustment among international students. Significance – The present study has implications for university policies, counsellors, and student affairs departments on the need to take measures to facilitate healthy academic and psychological adjustment among international students.
Strings and matrix models on genus g Riemann Surfaces

This is a summary of old work on connections between discrete area preserving diffeomorphisms, reduced SU(N) Yang-Mills, strings, and the quantum Hall effect on a Riemann surface of genus g. It is submitted to the archives due to the interest expressed by colleagues who are currently working on matrix models, and who could not have access to the proceedings in which the article was published. The text that follows is the version published in 1991.