bluuebunny/crossref_metadata_2025 huggingface dataset:
Ancient Greek Tragedy as Performance: the Literature–Performance Problematic
Authors: Frendo Mario
Published: January 2019

In this article Mario Frendo engages with the idea of ancient Greek tragedy as a performance phenomenon, questioning critiques that approach it exclusively via literary–dramatic methodologies. Based on the premise that ancient Greek tragedy developed within the predominantly oral context of fifth-century BCE Greece, he draws on Hans-Thies Lehmann's study of tragedy and its relation to dramatic theatre, where it is argued that the genre is essentially ‘predramatic’. Considered as such, ancient Greek tragedy cannot be fully investigated using dramatic theories developed since early modernity. In view of this, Walter J. Ong's caution with respect to the rational processes produced by generations of literate culture will be acknowledged and alternative critiques sought, including performance criticism and performance-oriented frameworks such as orality, via which Frendo traces possible critical trajectories that would allow contemporary scholarship to deal with ancient tragedy as a performance rather than literary phenomenon. Reference will be made to Aristotle's use of the term ‘poetry’, and how performance criticism may provide new insight into how the Poetics deals with one of the earliest performance phenomena in the West. Mario Frendo is lecturer of theatre and performance and Head of the Department of Theatre Studies at the School of Performing Arts, University of Malta, where he is director of CaP, a research group focusing on links between culture and performance. His research interests include musicality in theatre, ancient tragedy, and relations between philosophical thought and performance.
FAT or FiTT: Are Anvil Clouds or the Tropopause Temperature Invariant?
Authors: Seeley Jacob T. , Jeevanjee Nadir , Romps David M.
Published: January 2019

The Fixed Anvil Temperature (FAT) hypothesis proposes that upper tropospheric cloud fraction peaks at a special isotherm that is independent of surface temperature. It has been argued that a FAT should result from simple ingredients: Clausius‐Clapeyron, longwave emission from water vapor, and tropospheric energy and mass balance. Here the first cloud‐resolving simulations of radiative‐convective equilibrium designed to contain only these basic ingredients are presented. This setup does not produce a FAT: the anvil temperature varies by about 40% of the surface temperature range. However, the tropopause temperature varies by only 4% of the surface temperature range, which supports the existence of a Fixed Tropopause Temperature (FiTT). In full‐complexity radiative‐convective equilibrium simulations, the spread in anvil temperature is smaller by about a factor of 2, but the tropopause temperature remains more invariant than the anvil temperature by an order of magnitude. In other words, our simulations have a FiTT, not a FAT.
Extrinsic Elastic Anisotropy in a Compositionally Heterogeneous Earth's Mantle
Authors: Faccenda Manuele , Ferreira Ana M. G. , Tisato Nicola , Lithgow‐Bertelloni Carolina , Stixrude Lars , Pennacchioni Giorgio
Published: January 2019

Several theoretical studies indicate that a substantial fraction of the measured seismic anisotropy could be interpreted as extrinsic anisotropy associated with compositional layering in rocks, reducing the significance of strain‐induced intrinsic anisotropy. Here we quantify the potential contribution of grain‐scale and rock‐scale compositional anisotropy to the observations by (i) combining effective medium theories with realistic estimates of mineral isotropic elastic properties and (ii) measuring velocities of synthetic seismic waves propagating through modeled strain‐induced microstructures. It is shown that for typical mantle and oceanic crust subsolidus compositions, rock‐scale compositional layering does not generate any substantial extrinsic anisotropy (<1%) because of the limited contrast in isotropic elastic moduli among different rocks. Quasi‐laminated structures observed in subducting slabs using P and S wave scattering are often invoked as a source of extrinsic anisotropy, but our calculations show that they only generate minor seismic anisotropy (<0.1–0.2% of Vp and Vs radial anisotropy). More generally, rock‐scale compositional layering, when present, cannot be detected with seismic anisotropy studies but mainly with wave scattering. In contrast, when grain‐scale layering is present, significant extrinsic anisotropy could exist in vertically limited levels of the mantle such as in a mid‐ocean ridge basalt‐rich lower transition zone or in the uppermost lower mantle where foliated basalts and pyrolites display up to 2–3% Vp and 3–6% Vs radial anisotropy. Thus, seismic anisotropy observed around the 660‐km discontinuity could be possibly related to grain‐scale shape‐preferred orientation. Extrinsic anisotropy can form also in a compositionally homogeneous mantle, where velocity variations associated with major phase transitions can generate up to 1% of positive radial anisotropy.
The Beaufort Gyre Extent, Shape, and Location Between 2003 and 2014 From Satellite Observations
Authors: Regan Heather C. , Lique Camille , Armitage Thomas W. K.
Published: January 2019

The Beaufort Gyre is a significant reservoir of freshwater in the Arctic. It is thought to play a key role in regulating Arctic freshwater discharge to the North Atlantic, and in recent decades its freshwater content has increased in a time of rapid Arctic change. Despite this, its exact dynamical behavior is not fully understood. Here, we make use of an Arctic‐wide dataset of dynamic ocean topography, including data under sea ice, to characterize the time‐varying extent, shape, and location of the Beaufort Gyre. We show that the gyre expanded toward the northwest between 2003 and 2014, resulting in increased proximity to the Chukchi Plateau and Mendeleev Ridge by 2014. We find that the gyre strength and maximum dynamic ocean topography both respond readily to changes in intensity of the surface forcing, but the gyre area is additionally affected by the location of the Beaufort Sea High. This results in expansion over the Chukchi Plateau and increased asymmetry of the gyre as it becomes constrained by the shallow bathymetry. The gyre strength is correlated with the integrated surface stress on the ocean over the previous 3 months. We discuss the implications of the expansion over shallow bathymetry on gyre dynamical behavior and the potential impacts on the physical properties in the Canada Basin.
Meteorological Conditions During an Ozone Episode in Dallas‐Fort Worth, Texas, and Impact of Their Modeling Uncertainties on Air Quality Prediction
Authors: Hu Xiao‐Ming , Xue Ming , Kong Fanyou , Zhang Hongliang
Published: January 2019

The Southern Great Plains experiences an unhealthy level of ozone (O3) at times. The formation mechanisms contributing to these O3 events are not always clear and in some cases are related to particular atmospheric circulation patterns. A severe O3 pollution event on 27 August 2011 in the Dallas‐Fort Worth (DFW) area is investigated with a combination of observations and simulations using the Weather Research and Forecasting model with Chemistry (WRF/Chem). During the O3 episode, a stationary front with a stagnant zone at the leading edge persisted to the west of DFW. At the time, Hurricane Irene was located in western Atlantic, displacing the Bermuda Subtropical High and affecting the circulations over the Southern Great Plains. The stagnant zone confined the pollutant plume originating from DFW, leading to accumulation of primary pollutants and prominent O3 formation. Emission sources from a few urban areas east of DFW as well as power plants near Mount Pleasant and Carthage also contributed to this DFW O3 pollution episode. This scenario is different from the typical summer days over the Southern Great Plains when southerly winds prevail along the west edge of the Bermuda High and the pollutant plumes from DFW are advected downstream, resulting in low O3. Ensemble WRF/Chem predictions driven by the operational Short‐Range Ensemble Forecast outputs are conducted to examine the impact of meteorological uncertainties (particularly transport uncertainties) on air quality forecasting. The ensemble mean gives a better prediction in terms of plume directions than individual members.
The Geology and Astrobiology of McLaughlin Crater, Mars: An Ancient Lacustrine Basin Containing Turbidites, Mudstones, and Serpentinites
Authors: Michalski Joseph R. , Glotch T. D. , Rogers A. Deanne , Niles Paul B. , Cuadros J. , Ashley James W. , Johnson Sarah Stewart
Published: January 2019

McLaughlin crater is a 92‐km diameter complex crater that formed on Mars ~4 billion years ago. The resulting basin was the site of a large (~3,000 km2), deep (~500 m), voluminous (~1,500 km3) Martian lake circa 3.8 Ga. While there is strong evidence that hundreds of lakes have existed on Mars at some point during the same time period, the geology of McLaughlin crater is extraordinary for a number of reasons. Detailed spectral analyses show that the deep‐water sediments include detrital inputs of olivine and pyroxene, but the lake‐floor sediments include lithologies with abundant Fe‐rich, Mg‐bearing smectite, serpentine‐rich deposits, and ferrihydrite. For astrobiologists, this site provides a treasure trove of high‐priority targets. Serpentinization reactions are thought to have played a key role in abiogenesis on Earth, and within McLaughlin crater, deposits of subterranean and probably sublacustrine serpentinites are well preserved. In addition, delta sequences are well exposed throughout the east side of the basin; such deposits are endorsed by some as the highest priority targets for preservation of organics on Mars. Yet deep‐water turbidites, which might have flowed through hydrothermal environments, may be the most intriguing aspect of this geology. Such rapid sedimentation could have sequestered and preserved any potential organic materials for future exploration by a rover.
Tunable and enhanced light emission in hybrid WS2-optical-fiber-nanowire structures
Authors: Chen Jin-hui , Tan Jun , Wu Guang-xing , Zhang Xue-jin , Xu Fei , Lu Yan-qing
Published: January 2019

In recent years, the two-dimensional (2D) transition metal dichalcogenides (TMDCs) have attracted renewed interest owing to their remarkable physical and chemical properties. Similar to that of graphene, the atomic thickness of TMDCs significantly limits their optoelectronic applications. In this study, we report a hybrid WS2-optical-fiber-nanowire (WOFN) structure for broadband enhancement of the light–matter interactions, i.e., light absorption, photoluminescence (PL) and second-harmonic generation (SHG), through evanescent field coupling. The interactions between the anisotropic light field of an optical fiber nanowire (OFN) and the anisotropic second-order susceptibility tensor of WS2 are systematically studied theoretically and experimentally. In particular, an efficient SHG in the WOFN appears to be 20 times larger than that in the same OFN before the WS2 integration under the same conditions. Moreover, we show that strain can efficiently manipulate the PL and SHG in the WOFN owing to the large configurability of the silica OFN. Our results demonstrate the potential applications of waveguide-coupled TMDCs structures for tunable high-performance photonic devices.
Divergent methyl-coenzyme M reductase genes in a deep-subseafloor Archaeoglobi
Authors: Boyd Joel A , Jungbluth Sean P , Leu Andy O , Evans Paul N , Woodcroft Ben J , Chadwick Grayson L , Orphan Victoria J , Amend Jan P , Rappé Michael S , Tyson Gene W
Published: January 2019

The methyl-coenzyme M reductase (MCR) complex is a key enzyme in archaeal methane generation and has recently been proposed to also be involved in the oxidation of short-chain hydrocarbons including methane, butane, and potentially propane. The number of archaeal clades encoding the MCR continues to grow, suggesting that this complex was inherited from an ancient ancestor, or has undergone extensive horizontal gene transfer. Expanding the representation of MCR-encoding lineages through metagenomic approaches will help resolve the evolutionary history of this complex. Here, a near-complete Archaeoglobi metagenome-assembled genome (MAG; Ca. Polytropus marinifundus gen. nov. sp. nov.) was recovered from the deep subseafloor along the Juan de Fuca Ridge flank that encodes two divergent McrABG operons similar to those found in Ca. Bathyarchaeota and Ca. Syntrophoarchaeum MAGs. Ca. P. marinifundus is basal to members of the class Archaeoglobi, and encodes the genes for β-oxidation, potentially allowing an alkanotrophic metabolism similar to that proposed for Ca. Syntrophoarchaeum. Ca. P. marinifundus also encodes a respiratory electron transport chain that can potentially utilize nitrate, iron, and sulfur compounds as electron acceptors. Phylogenetic analysis suggests that the Ca. P. marinifundus MCR operons were horizontally transferred, changing our understanding of the evolution and distribution of this complex in the Archaea.
Nanocrystalline Sb-doped SnO2 films modified with cyclometalated ruthenium complexes for two-step electrochromism
Authors: Li Zhi-Juan , Shao Jiang-Yang , Wu Si-Hai , Zhong Yu-Wu
Published: January 2019

Sb-Doped SnO2 films modified with redox-active cyclometalated ruthenium complexes show two-step electrochromism in the near infrared region with a rapid response and good contrast ratio.
Goodbye to Silvia Atrian
Authors: Capdevila Mercè , Palacios Òscar
Published: January 2019

Mercè Capdevila and Òscar Palacios, longtime collaborators and friends of Silvia Atrian, reflect on Silvia's impact on the field of metallomics, as highlighted in a collection of papers published in Metallomics.
Dye-sensitized upconversion nanocomposites for ratiometric semi-quantitative detection of hypochloritein vivo
Authors: Zou Xianmei , Zhou Xiaobo , Cao Cong , Lu Wenyi , Yuan Wei , Liu Qingyun , Feng Wei , Li Fuyou
Published: January 2019

We report an upconversion ratiometric probe possessing the same emission peaks under a largely separated excitation spectra for hypochlorite detectionin vivo.
Perfluoroalkylative pyridylation of alkenesvia4-cyanopyridine-boryl radicals
Authors: Cao Jia , Wang Guoqiang , Gao Liuzhou , Chen Hui , Liu Xueting , Cheng Xu , Li Shuhua
Published: January 2019

A metal- and photo-free method for the perfluoroalkylative pyridylation of alkenes has been developed.
Achieving an exceptionally high loading of isolated cobalt single atoms on a porous carbon matrix for efficient visible-light-driven photocatalytic hydrogen production
Authors: Shi Rui , Tian Chengcheng , Zhu Xiang , Peng Cheng-Yun , Mei Bingbao , He Lin , Du Xian-Long , Jiang Zheng , Chen Yong , Dai Sheng
Published: January 2019

Isolated cobalt single atoms with a high loading of 5.9 wt% are generated through an in situ preparation strategy.
Positive Behavioral Interventions and Supports in Schools: A Tutorial
Authors: Keller-Bell Yolanda , Short Maureen
Published: January 2019

Purpose

Positive behavioral interventions and supports (PBIS) provide a framework for behavioral expectations in school systems for children with and without disabilities. Speech-language pathologists who work in school settings should be familiar with this framework as part of their role in improving the outcomes for children. The purpose of this tutorial is to discuss PBIS and its use in school settings.

Method

The authors provide an overview of the PBIS framework and focus on its applicability in classroom-based settings. The process of implementing PBIS in classrooms and other settings such as speech-language therapy is discussed.

Conclusions

This tutorial provides speech-language pathologists with an overview of PBIS and may facilitate their understanding of how to implement PBIS in nonclassroom settings.
Parent–Child Interaction Therapy as a Behavior and Spoken Language Intervention for Young Children With Hearing Loss
Authors: Costa Elizabeth Adams , Day Lori , Caverly Colleen , Mellon Nancy , Ouellette Meredith , Wilson Ottley Sharlene
Published: January 2019

Purpose

The importance of early intervention for fostering language in children with hearing loss has been well documented; those that facilitate parent engagement are particularly effective. Listening and spoken language outcomes among children with hearing loss continue to fall short compared to hearing peers, despite improvements in hearing technologies. The current study evaluated the effectiveness of parent–child interaction therapy (PCIT) as a behavioral intervention for children with hearing loss and its applicability as a language intervention.

Method

PCIT effectiveness was evaluated for children with hearing loss (PCIT treatment group:
N
= 18). For a subset of the treatment group (matched experimental group:
n
= 6), pretreatment and posttreatment language samples were compared to a matched control group (
n
= 6).

Results

Significant changes were observed in parent skills and child behavior from pretreatment to posttreatment for the PCIT treatment group. A subset of the treatment group (matched experimental group) with available matched controls (matched control group) demonstrated a significant increase in utterances and a trend toward significant increase in receptive vocabulary compared to the control group.

Conclusion

PCIT is a promising intervention for children with hearing loss that empowers parents to engage in optimal indirect language stimulation, improves parent–child interactions, improves child behavior, and promotes spoken language skills.
Environmental changes around the Oligocene/Miocene boundary in the Limagne graben, Massif Central, France
Authors: Wattinne Aurélia , Lécuyer Christophe , Vennin Emmanuelle , Chateauneuf Jean-Jacques , Martineau François
Published: January 2019

Continental environments are very sensitive to climatic variations. A unique opportunity to study the climate changes around the Oligocene/Miocene boundary is offered by the Limagne graben Basin (France) where this stage boundary is well constrained by fossils. Indeed, some localities of the Limagne Graben Basin are so rich in mammal remains that they have become a European reference for mammal biostratigraphy. The dominant sedimentary facies of the lacustrine deposits in the northern part of the Limagne Graben Basin are composed of poorly cemented marls and calcarenites containing various plants and animals remains (e.g.algae, fish bones and teeth, gastropods, ostracods, mammals, birds and reptiles remains) associated with stromatolites. Mammal remains, well described in this area from the literature, were used to constrain the chronostratigraphic context of this lacustrine basin, with refinement thanks to new carbon and oxygen isotope measurements, palynological and sedimentological data. In this work, the available information obtained from a classical paleoecological study has been refined by new carbon and oxygen isotope analyses of carbonates and fish teeth retrieved from the washed sediment residues. The results of this study confirm that the Oligocene/Miocene boundary in Europe was a general period of aridity, associated with a cooler climate, which could be the cause of the decline in mammal paleodiversity observed during this period. The gradual evolution from brackish to fresh waters is indicated by the presence of ostracods and gastropods, and the major development of caddisflies. This period is associated to humid climatic conditions while a gradual increase in temperature took place throughout the second part of the Aquitanian. These environmental changes were driven by strong variations of temperatures and a contrasted seasonality.
Quasi-theoretical investigation of four circularly polarized metaloop antennas
Authors: Nakano Hisamatsu , Abe Tomoki , Yamauchi Junji
Published: January 2019

Four metamaterial line loop (metaloop) antennas, RND-MTLP-C, RND-MTLP-N, SQR-MTLP-C, and SQR-MTLP-N are investigated to clarify the antenna characteristics. Each metaloop is made up of either a C-type metamaterial line or an N-type metamaterial line, where the dispersion characteristics of the unit cell for the C- and N-type metamaterial lines are designed to be as similar as possible. The RND-MTLP-C and SQR-MTLP-C act as a dual-band counter circularly polarized antenna across a fast wave frequency region. It is found that, depending on the deviation factor, the SQR-MTLP-N behaves as a tri-band circularly polarized antenna, but the RND-MTLP-N does not have the tri-band characteristic. The radiation pattern, gain, and input characteristic in terms of the VSWR for the four antennas are clarified.
RGB Color Cluster and Graph Coloring Algorithm for Partial Color Blind Correction
Authors: Dody Qori Utama , Tati Latifah R. Mengko , Richard Mengko , Andika Prahasta Gandasubrata , Tauhid Nur Azhar
Published: January 2019

Partial color blindness is an anomaly occurring to 5-8% of the world's population. Color correction using re-coloring algorithm usually can be used to help partial color blindness patient. One of the existing re-coloring techniques is to use the RGB color cluster technique and combine it by utilizing the brute force algorithm to perform color tracing for correcting the color. It has massive time and memory complexity. This research aims to create a correction technique for color blind people using RGB Color Cluster combined with Graph Coloring Algorithm. The first process is to get the RGB color cluster for color blind subject. After getting RGB color cluster from the subject then the image which want to be corrected is grouped based on RGB color cluster. The threshold of color grouping in image is done by utilizing the upper and lower bound values of the RGB color cluster. After the cluster is grouped, then we can represent neighbourhood between the colors by utilizing graph. The adjacent color group will be a neighbour. The next process is color re-coloring using graph coloring algorithm. In graph coloring algorithm, same color group is prohibited to become neighbour. In this research, graph coloring algorithm is used to prevent 2 colors that are look almost similar for become neighbours because it will cause the subject cannot distinguish it. Re-coloring is done by increasing and decreasing the color intensity of a set of colors. This technique succeeds in decreasing the complexity of the brute force algorithm from O(N4) to O(2N2) where the first N2 is the complexity of building the cluster group and the second N2 is the complexity of the re- coloring. In addition, the color of the object becomes more natural because Re-coloring is based on color group not pixel based.
Automatic Image Annotation for Small and Ad hoc Intelligent Applications using Raspberry Pi
Authors: Syed Muslim Jameel , Manzoor Ahmed Hashmani , Syed Sajjad Hussain Rizvi , Vali Uddin , Mobashar Rehman
Published: January 2019

The cutting-edge technology Machine Learning (ML) is successfully applied for Business Intelligence. Among the various pre-processing steps of ML, Automatic Image Annotation (also known as automatic image tagging or linguistic indexing) is the process in which a computer system automatically assigns metadata in the form of captioning or keywords to a digital image. Automatic Image Annotation (AIA) methods (which have appeared during the last several years) make a large use of many ML approaches. Clustering and classification methods are most frequently applied to annotate images. In addition, these proposed solutions require a high computational infrastructure. However, certain real-time applications (small and ad-hoc intelligent applications) for example, autonomous small robots, gadgets, drone etc. have limited computational processing capacity. These small and ad-hoc applications demand a more dynamic and portable way to automatically annotate data and then perform ML tasks (Classification, clustering etc.) in real time using limited computational power and hardware resources. Through a comprehensive literature study we found that most image pre-processing algorithms and ML tasks are computationally intensive, and it can be challenging to run them on an embedded platform with acceptable frame rates. However, Raspberry Pi is sufficient for AIA and ML tasks that are relevant to small and ad-hoc intelligent applications. In addition, few critical intelligent applications (which require high computational resources, for example, Deep Learning using huge dataset) are only feasible to run on more powerful hardware resources. In this study, we present the framework of “Automatic Image Annotation for Small and Ad-hoc Intelligent Application using Raspberry Pi” and propose the low-cost infrastructures (single node and multi node using Raspberry Pi) and software module (for Raspberry Pi) to perform AIA and ML tasks in real time for small and ad-hoc intelligent applications. The integration of both AIA and ML tasks in a single software module (with in Raspberry Pi) is challenging. This study will helpful towards the improvement in various practical applications areas relevant to small intelligent autonomous systems.
An intelligent order allocation system for effective order fulfilment under changing customer demand
Authors: Leung K.H. , Choy K.L. , Lam H.Y.
Published: January 2019

In today's intense global competition, problems still exist under the umbrella of Just-in-Time application in the field of order management. The management of a firm usually faces difficulty in allocating stock to fulfil customer order, especially in the case of receiving a sudden change request from customers. In order to ease order allocation issues aroused by JIT, an intelligent system, namely, Intelligent Sales Order Handling System (ISOAS), is developed through the integration of fuzzy-AHP approach for decision making process in order allocation. This approach enables the selection of desired sales orders based on multiple criteria which may be quantitative or qualitative in nature, according to the judgment of scholars and domain experts. With ISOAS, customer orders are prioritized with respect to the values according to their performance under each decision making attributes. The degree of confidence of the decision judgements are quantified through the spread of fuzzy numbers with fuzzy pairwise comparison calculations. The approach can transform the fuzziness of human preference into the measurable number, enabling the operation of the AI-based system to assist humans in decision-making. An order allocation case study in a logistics department is demonstrated in this study. Results indicate an improved efficiency during the decision making process.
Optimized ELM based on Whale Optimization Algorithm for gearbox diagnosis
Authors: Isham M. Firdaus , Leong M. Salman , Lim M. H. , Ahmad Z. A.B.
Published: January 2019

Extreme learning machine (ELM) is a fast and quick learning algorithm with better generalization performance. However, the randomness of input weight and hidden layer bias may affect the overall performance of ELM. This paper proposed a new approach to determine the optimized values of input weight and hidden layer bias for ELM using whale optimization algorithm (WOA), which we call WOA-ELM. An online gearbox vibration signals is used in this study. Empirical mode decomposition (EMD) and complementary mode decomposition (CEEMD) are used to decompose the signals into sub-signals known as intrinsic mode functions (IMFs). Then, statistical features are extracted from selected IMFs. WOA-ELM is used for classification of healthy and faulty condition of gearbox. The result shows that WOA-ELM provide better classification result as compared with conventional ELM. Therefore, this study provide a new diagnosis approach for gearbox application.
Working Principles of Vibroelectric Nano Generator in Wireless Sensor Networks: A Review
Authors: Siang Jee , Hee Lim Meng , Leong Mohd. Salman
Published: January 2019

Wireless sensor networks are solely dependent on battery limits the operation as well as maintenance effort. Vibroelectric nano generator able to prolong the operation by converting ambient vibration and power the equipment. The working principles includes Piezoelectric, Electromagnetic, Triboelectric, Magnetostrictive and Flexoelectric. This paper discussed the principle operations and key function materials, the advantages and disadvantages are specified. Hybrid incorporated with solar, thermal or radio frequency is considered as current trend of nano generator with further improvement as future work.
Review of Underground Storage Tank Condition Monitoring Techniques
Authors: Ching Sheng Ooi , Ngui Wai Keng , Kar Hoou Hui , Meng Hee Lim , Leong Mohd. Salman
Published: January 2019

This article aims to provide a comprehensive review on the condition monitoring techniques of underground storage tanks (UST). Generally, the UST has long been a favourite toxic substance reservation apparatus, thanks to its large capacity and minimum floor space requirement. Recently, attention has been drawn to the safety risks of the complex cylindrical-shaped system and its surrounding environment due to contamination resulting from unwanted subsurface leakage. Studies on related countermeasures shows that numerous efforts have been focused on the damage remediation process and fault detection practice; however, it has also been observed that there are uncertainties in present technical complications involving the effectiveness of corrective actions and the robustness of condition monitoring techniques. As an alternative means to deliver spatial information on structural integrity, the feasibility of integrating non- destructive evaluation (NDE) techniques with machine learning algorithms, on observing the degradation process of UST, so as to enhance condition monitoring competency, is discussed.
Study of O3/S2O82- Advanced Oxidation Processes (AOPs) for Removal of Dye Industrial Effluents
Authors: Che Zulzikrami Azner Abidin , Fahmi Muhammad Ridwan , Ong Soon An , Abdul Haqi Ibrahim , Siti Nasuha Sabri , Nur Aqilah Razali
Published: January 2019

This research was carried out to study the efficiency of O3/S2O82- system in removal of Reactive Red 120 (RR120) dye sample. Different operating parameter such as pH, initial dye concentration and persulfate dosage were studied to evaluate the performance on removing colour and COD. The removal of colour and COD achieved higher efficiency at pH 7, 100 mg/L of initial dye concentration and persulfate dosage of 5 g S2O82-/1 g RR120. O3/S2O82- with the most effective conditions experienced effective decolourization and degradation of organic pollutants than O3 only. Furthermore, it achieved faster breakdown of azo bond and aromatic groups than O3 after treatment as observed with UV-Vis absorption spectra. The FT-IR analysis obtained new absorption peak that represents alkenes after 20 min of O3 treatment whereas mostly of the absorption bands of O3/S2O82- flattened.
Design of Elderly Behaviour Analytics Model in the Healthcare Industry in Hong Kong
Authors: Siu Paul K.Y. , Choy K.L. , Lam H.Y.
Published: January 2019

Due to the advancement of living standard and medical technologies, the life expectancy of people is further extended which brings tremendous impact to the society in the near future. The ageing population not only increases the pressure to public healthcare services, but also brings urgent needs in long term healthcare resources allocation planning in the society. This paper presents an Elderly Behaviour Analytics Model (EBAM) to identify the hospital healthcare service preferences of elderly for the future planning of healthcare industry. By conducting an elderly-targeted survey, the collected data is analysed to understand the factors affecting the decision of elderly to acquire healthcare services in hospitals. The model applies the genetic algorithm-guided clustering-based association rule mining approach for the segmentation of hospital service preferences of the elderly, and, the identification of relationship between personal characteristics within each cluster. This research study contributes to the understanding the actual healthcare needs of elderly which allows the government and healthcare service providers to adjust or modify the elderly policies and service content.
Deep learning Convolutional Neural Network for Unconstrained License Plate Recognition
Authors: Yee Yong Pang , Chee Hau Ong , Hiew Moi Sim
Published: January 2019

The evolve of neural networks algorithm into deep learning convolutional neural networks seems like the next generation for object detection. This algorithm works has a significantly better accuracy and did not tied to any particular aspect ratio. License plate and traffic signs detection and recognition have a number of different applications relevant for transportation systems, such as traffic monitoring, detection of stolen vehicles, driver navigation support or any statistical research. An exponential increase in number of vehicles necessitates the use of automated systems to maintain vehicle information. The information is highly required for both management of traffic as well as reduction of crime. Number plate recognition is an effective way for automatic vehicle identification. A number of methods have been proposed, but only for particular cases and working under constraints (e.g. known text direction or high resolution). Deep learning convolutional neural networks work well especially in handles occlusion/rotation better, therefore we believe this approach is able to provide a better solution to the unconstrained license plate recognition problem.
A hybrid k-means-GMM machine learning technique for turbomachinery condition monitoring
Authors: Yusoff Mohd. Dasuki , Ooi Ching Sheng , Lim Meng Hee , Leong Mohd. Salman
Published: January 2019

Industrial practise typically applies pre-set original equipment manufacturers (OEMs) limits to turbomachinery online condition monitoring. However, aforementioned technique which considers sensor readings within range as normal state often get overlooked in the developments of degradation process. Thus, turbomachinery application in dire need of a responsive monitoring analysis in order to avoid machine breakdown before leading to a more disastrous event. A feasible machine learning algorithm consists of k-means and Gaussian Mixture Model (GMM) is proposed to observe the existence of signal trend or anomaly over machine active period. The aim of the unsupervised k-means is to determine the number of clusters, k according to the total trend detected from the processed dataset. Next, the designated k is input into the supervised GMM algorithm to initialize the number of components. Experiment results showed that the k-means-GMM model set up not only capable of statistically define machine state conditions, but also yield a time-dependent clustering image in reflecting degradation severity, as a mean to achieve predictive maintenance.
Blade fault diagnosis using empirical mode decomposition based feature extraction method
Authors: Tan C. Y. , Ngui W. K. , Leong M. S. , Lim M. H.
Published: January 2019

Blade fault diagnosis had become more significant and impactful for rotating machinery operators in the industry. Many works had been carried out using different signal processing techniques and artificial intelligence approaches for blade fault diagnosis. Frequency and wavelet based features are usually used as the input to the artificial neural network for blade fault diagnosis. However, the application of others time-frequency based feature extraction technique and artificial intelligence approach for blade fault diagnosis is still lacking. In this study, a novel blade fault diagnosis method based on ensemble empirical mode decomposition and extreme learning machine was developed. Bandpass filtering was applied to the raw vibration signals and integrated with the high pass filter to obtain the velocity signal. Synchronous time averaging was then applied to the velocity signals. Three ensemble empirical mode decomposition based feature extraction methods were proposed: direct statistical parameters extraction, intrinsic mode functions averaging statistical parameters extraction and features averaging statistical parameters extraction. The effectiveness of different feature vector sets for blade fault diagnosis was examined. Feature vector set of intrinsic mode functions averaging statistical parameters extraction was found to be more effective for blade fault diagnosis. With the novel proposed method, blade fault diagnosis could be more accurate and precise.
Identification of Natural Bamboo Fiber and Regenerated Bamboo Fiber by the Method of Modified near Infrared Spectroscopy
Authors: Li Weidong , Li Zhixiong , Wang Xinhou
Published: January 2019

In this work, the applicability and effectiveness of identification of natural bamboo fiber and regenerated bamboo fiber by near infrared spectroscopy are investigated. A discrimination model based on Ward’s algorithm and Hierarchical Cluster Analysis is pretreated by the first derivative and vector normalization, which can be used to distinguish natural bamboo fiber and regenerated bamboo fiber. In addition, the near infrared spectra model exhibits a high accuracy with an effective identification of the double fibers.
Thermal Characteristics Analysis for Motorized Spindle System of CNC Machining Center
Authors: Deng Xiaolei , Zhang Xinghui , Zhang Mucheng , Zhou Yibo , Lin Huan , Wang Jianchen
Published: January 2019

Based on the comprehensive analysis of the heat sources of the motorized spindle system, the thermal loads, including the heat generation of bearing friction and the electromagnetic loss of the built-in motor, are carried out for a machining center motorized spindle system. And then, the convective heat transfer coefficients of the whole spindle system are analyzed. The thermal characteristics of the motorized spindle system are calculated by finite element analysis. The steady state temperature field distribution of the motorized spindle is obtained. It provides some references for improving the thermal characteristics of the motorized spindle and reducing the difficulty of thermal error compensation.
A Novel Process Model of Ship Rust Removal by Premixed Abrasive Jet based on Neural Network
Authors: Guo Qing , Yang Shuzhen , Yu Tao
Published: January 2019

In view of the technological requirements of the development of green shipbuilding technology on the effect of ship surface rust removal, the premixed abrasive jet technology is used to remove rust. Because the rust removal of ships with premixed abrasive jet is influenced by multiple parameters and has a high nonlinear relationship between various parameters, the accurate process model of it is difficult to establish. On the basis of artificial neural network modelling technology, the model of ship rust removal with premixed abrasive jet is built. The model takes the system pressure, the target distance, the moving speed of the spray gun and the particle size of the abrasive as input parameters, and the score which can most reflect the effect of the rust removal as output parameter. The test results show that the prediction error of the model is small, and it can better reflect the process rule between the effect of the premixed abrasive jet and the process parameters. We can guide the selection of process parameters according to the model.
Designing of Ultrasonic Horns to Improve Amplitude Uniformity in Ultrasonic Metal Welding
Authors: Lee Yeon Ju , Shahid Muhammad Bilal , Park Dong Sam
Published: January 2019

The ultrasonic metal welding has been used extensively in many fields because it can weld thin layers of highly conductive and dissimilar materials with high reliability. In particular, one-wave length horns with four welding tips on both sides of the horn are widely used for welding positive and negative electrodes and tabs of rechargeable lithium ion batteries. As the vibrational amplitude of each tip is known to be non-uniform, this causes some problems in welding performance. In this study, the one-wave length horn which has four welding tips on both sides of the horn is newly designed to improve amplitude uniformity of each tip. The design of experiment technique is employed to determine the optimum configuration of the horn. The modal analysis and harmonic response analysis are repeatedly conducted to obtain the uniform amplitude of horn tips, and stress distribution in the horn is analyzed finally. It is shown that the uniformity of amplitude can be improved by making appropriate grooves on both sides of the conventional horn.
Finite Element Simulation of Forming Process for Automotive Components from Advanced High Strength Steel
Authors: Peraprutchaya Yachita , Suranantchai Surasak
Published: January 2019

Advance high strength (AHS) steel has been widely used in the automotive industry and order to reduce the weight of automotive components that effect to reduce fuel consumption, but vehicles maintain safety. However, forming process with AHS steel has many problems which the main defect was spring-back. Therefore, the usage of finite element (FE) method simulation with kinematic hardening materials model sustains and improve production processes. Yoshida-Uemori (Y-U) model is the one of kinematic hardening materials model that show the great capability for prediction of elastic recovery behavior. Consequencely, this work has been research on AHS steel as the NSC980D grade for automotive components in the drawing process and applied FE simulation with Y-U model to improve the production process. Moreover, NSC980D steel was inspected in tension-compression and tensile tests were proceeded. As a result, material parameters from testing simulate with designed die and improvement were shown. Finally, comparing FE simulation forming with experiment forming, showed FE simulation with Y-U model is suitable for prediction and process improvement.
Co-carbonization of single coking coal and pyrolytic extracts from datong long-flame coal
Authors: Zhu Yaming , Tang Shuai , Zhao Xuefei , Gao Lijuan
Published: January 2019

Using modified coal as the raw material to produce coke is a novel method to improve the quality of coke during the process of coal blend coking. In this work, the activated components from low-rank coal were used as a common modifier for coal modification process. The properties of co-carbonization coke were studied. The pyrolytic extracts of Chinese Datong long-flame coal (DTLFPE) were used as the additive, while Jinjian gas coal and Zhongwei lean coal were used as the basic coals. The influence of the addition of DTLFPE on coke’s micro-strength, optical texture index (OTI), microstructure and coke reactivity were studied. The results showed that DTLFPE exhibited a significant impact on the performance of Zhongwei lean coal coke. The micro-strength and the OTI index of each coke significantly improved due to the addition of DTLFPE, which meant that their anisotropy degree was enhanced. The addition of DTLFPE also decreased the porosity of Jinjian gas coal coke, and improved the melting ability of the particles in Zhongwei lean coal coke. The DTLFPE was found to be a very suitable modifier for single coking coal, whereas moderate amounts of additives exhibited positive effects on improving the quality of coke.
A review on China's current situation and prospects of poverty alleviation with photovoltaic power generation
Authors: Hou Jianchao , Luo Sai , Cao Mengchao
Published: January 2019

China is one of the countries with abundant solar energy resources and also has rapid development in the photovoltaic (PV) industry. Since 2014, the Chinese government has begun to implement the PV power generation for poverty alleviation, which not only was in line with the concept of green development but also accelerated the pace of poverty alleviation in rural regions. This paper first reviews the status quo of energy poverty in rural China and elicits the necessity of developing PV power generation in those regions. Then, from the perspective of precision poverty alleviation, the status quo of PV power generation for poverty alleviation is introduced from the types of poverty alleviation, business modes, and the scale of poverty alleviation projects. This paper also introduces the policy status, which mainly involves national and regional policies, and shows that all departments give importance to PV power generation in rural regions. Furthermore, through the PEST-SWOT strategic analysis model, the internalities (strengths and weaknesses) and externalities (opportunities and threats) of PV power generation are analyzed, including policy, economy, society, and technology. According to the analysis of the strategic model, countermeasures are given in terms of policy recommendations, market mechanism, and technical support to solve some existing problems. Finally, this paper puts forward three key conclusions and prospects that the application of power alleviation with PV power generation is promising.
A condensed phase model of the initial Al/CuO reaction stage to interpret experimental findings
Authors: Brotman Sarah , Rouhani Mehdi Djafari , Rossi Carole , Estève Alain
Published: January 2019

A model based uniquely on condensed phase reactions coupled with the thermal equation is developed to study the initiation and early stage of the redox reaction in Al/CuO nanothermites. It considers the effect of a wetting contact angle between Al and CuO particles, which may be induced by sintering mechanisms and/or the synthesis method. In order to validate the model, two published experiments are reproduced in silico. Results provide the first quantification of: (i) how sintering affects the initiation of Al/CuO nanoparticle mixtures, depending on experimental conditions, (ii) the extent to which condensed phase mechanisms dominate gas-mediated reactions in the initiation process, two subjects that have been highly debated in the literature. It was found that initiation appears more strongly affected by sintering when particles are exposed to an ultra-short and intense heat pulse (∼1011 K s−1) than those exposed to a lower heating rate (∼105 K s−1). Additionally, calculations show that sintering may cause a drastic decrease in the initiation delay (down to the ns regime) when using CuO nanoparticles below 50 nm in diameter that can be brought to melting temperature through optical absorption. Finally, the role of gas-surface versus condensed phase reactions in the Al/CuO initiation process is evaluated theoretically. Initiation through condensed phase reactions, while slightly faster and more efficient, exhibits a comparable timescale (∼1–2 ms) to initiation through gas-surface reactions, providing clear evidence for the contribution of both during the initiation phase.
Two possible mechanisms of water-assisted proton transfer in the stack of adenine-thymine: Displacement polarization and oriented polarization
Authors: Lv Zengtao , Cui Shouxin , Guo Feng , Zhang Guiqing
Published: January 2019

Proton transfer in DNA has attracted much attention because of its close relationship with charge transfer and DNA base damage. In the present study, the relationship between proton transfer and water polarization at a certain temperature in the radical cation stack of adenine-thymine is investigated by QM/MM molecular dynamics simulations. By analyzing the polarization of aqueous solution, it is found that at low temperature water molecules promote proton transfer by means of displacement polarization and oriented polarization, while at high temperature, water molecules promote proton transfer only by displacement polarization.