Search results for: thin film processing

Authors: Ashish Agarwal, Vaibhav Singh

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Harmful emissions from oil and gas processing facilities have long remained a matter of concern for governments and environmentalists throughout the world. This paper analyses Oil and Natural Gas Corporation (ONGC) gas processing plant in Hazira, Gujarat, India. It is the largest gas-processing complex in the country designed to process 41MMSCMD sour natural gas & associated sour condensate. The complex, sprawling over an area of approximate 705 hectares is the mother plant for almost all industries at Hazira and enroute Hazira Bijapur Jagdishpur pipeline. Various sources of pollution from each unit starting from Gas Terminal to Dew Point Depression unit and Caustic Wash unit along the processing chain were examined with the help of different emission data obtained from ONGC. Pollution discharged to the environment was classified into Water, Air, Hazardous Waste and Solid (Non-Hazardous) Waste so as to analyze each one of them efficiently. To protect air environment, Sulphur recovery unit along with automatic ambient air quality monitoring stations, automatic stack monitoring stations among numerous practices were adopted. To protect water environment different effluent treatment plants were used with due emphasis on aquaculture of the nearby area. Hazira plant has obtained the authorization for handling and disposal of five types of hazardous waste. Most of the hazardous waste were sold to authorized recyclers and the rest was given to Gujarat Pollution Control Board authorized vendors. Non-Hazardous waste was also handled with an overall objective of zero negative impact on the environment. The effect of methods adopted is evident from emission data of the plant which was found to be well under Gujarat Pollution Control Board limits.

Keywords: sulphur recovery unit, effluent treatment plant, hazardous waste, sour gas

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Authors: Amandeep Kaur

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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

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Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan

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In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.

Keywords: break even point, fuzzy crisp data, fuzzy sets, productivity, productivity cycle, total productive maintenance

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Authors: Suwarsono, Ario S. Baskoro, Gandjar Kiswanto, Budiono

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Friction Stir Welding (FSW) is a relatively new technique for joining metal. In some cases on aluminum joining, FSW gives better results compared with the arc welding processes, including the quality of welds and produces less distortion.FSW welding process for a light structure and thin materials requires small forces as possible, to avoid structure deflection. The joining process on FSW occurs because of melting temperature and compressive forces, the temperature generation of caused by material deformation and friction between the cutting tool and material. In this research, High speed rotation of spindle was expected to reduce the force required for deformation. The welding material was Aluminum A1100, with thickness of 0.4 mm. The tool was made of HSS material which was shaped by micro grinding process. Tool shoulder diameter is 4 mm, and the length of pin was 0.6 mm (with pin diameter= 1.5 mm). The parameters that varied were the plunge speed (2 mm/min, 3 mm/min, 4 mm/min). The tool speed is fixed at 33,000 rpm. Responses of FSSW parameters to analyze were Axial Force (Z-Force), Temperature and the Shear Strength of welds. Research found the optimum µFSSW parameters, it can be concluded that the most important parameters in the μFSSW process was plunge speed. lowest plunge speed (2 mm / min) causing the lowest axial force (110.40 Newton). The increases of plunge speed will increase the axial force (maximum Z-Farce= 236.03 Newton), and decrease the shear strength of welds.

Keywords: friction stir spot welding, aluminum A1100, plunge speed, axial force, shear strength

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Authors: José Luis Carrillo-Medina, Roberto Latorre

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Experimental evidence has revealed that different living neural systems can sign their output signals with some specific neural signature. Although experimental and modeling results suggest that neural signatures can have an important role in the activity of neural networks in order to identify the source of the information or to contextualize a message, the functional meaning of these neural fingerprints is still unclear. The existence of cellular mechanisms to identify the origin of individual neural signals can be a powerful information processing strategy for the nervous system. We have recently built different models to study the ability of a neural network to process information based on the emission and recognition of specific neural fingerprints. In this paper we further analyze the features that can influence on the information processing ability of this kind of networks. In particular, we focus on the role that the duration of a refractory period in each neuron after emitting a signed message can play in the network collective dynamics.

Keywords: neural signature, neural fingerprint, processing based on signal identification, self-organizing neural network

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Authors: Theresa Slump, Paula Neumeister, Katharina Feldker, Carina Y. Heitmann, Thomas Straube

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A characteristic feature of post-traumatic stress disorder (PTSD) is the automatic processing of disorder-specific stimuli that expresses itself in intrusive symptoms such as intense physical and psychological reactions to trauma-associated stimuli. That automatic processing plays an essential role in the development and maintenance of symptoms. The aim of our study was, therefore, to investigate the behavioral and neural correlates of automatic processing of trauma-related stimuli in PTSD. Although interpersonal traumatization is a form of traumatization that often occurs, it has not yet been sufficiently studied. That is why, in our study, we focused on patients suffering from interpersonal traumatization. While previous imaging studies on PTSD mainly used faces, words, or generally negative visual stimuli, our study presented complex trauma-related and neutral visual scenes. We examined 19 female subjects suffering from PTSD and examined 19 healthy women as a control group. All subjects did a geometric comparison task while lying in a functional-magnetic-resonance-imaging (fMRI) scanner. Trauma-related scenes and neutral visual scenes that were not relevant to the task were presented while the subjects were doing the task. Regarding the behavioral level, there were not any significant differences between the task performance of the two groups. Regarding the neural level, the PTSD patients showed significant hyperactivation of the hippocampus for task-irrelevant trauma-related stimuli versus neutral stimuli when compared with healthy control subjects. Connectivity analyses revealed altered connectivity between the hippocampus and other anxiety-related areas in PTSD patients, too. Overall, those findings suggest that fear-related areas are involved in PTSD patients' processing of trauma-related stimuli even if the stimuli that were used in the study were task-irrelevant.

Keywords: post-traumatic stress disorder, automatic processing, hippocampus, functional magnetic resonance imaging

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: J. Mrazek, R. Skala, S. Bysakh, Ivan Kasik

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Lanthanide-doped yttrium titanium oxides, which crystallize in a pyrochlore structure with general formula (RExY1-x)2Ti2O7 (RE=rare earth element), have been extensively investigated in recent years for their interesting physical and chemical properties. Despite that the pure pyrochlore structure does not present luminescence ability, the presence of yttrium ions in the pyrochlore structure significantly improves the luminescence properties of the RE. Moreover, the luminescence properties of pyrochlores strongly depend on the size of formed nanocrystals. In this contribution, we present a versatile sol-gel synthesis of nanocrystalline EuYTi2O7pyrochlore. The nanocrystalline powders and thin films were prepared by the condensation of titanium(IV)butoxide with europium(III) chloride followed by the calcination. The introduced method leads to the formation of the highly-homogenous nanocrystalline EuYTi2O7 with tailored grain size ranging from 20 nm to 200 nm. The morphology and the structure of the formed nanocrystals are linked to the luminescence properties of Eu3+ ions incorporated into the pyrochlore lattice. The results of XRD and HRTEM analysis show that the Eu3+ and Y3+ ions are regularly distributed inside the lattice. The lifetime of Eu3+ ions in calcinated powders is regularly decreasing from 140 us to 68 us and the refractive index of prepared thin films regularly increases from 2.0 to 2.45 according to the calcination temperature. The shape of the luminescence spectra and the decrease of the lifetime correspond with the crystallinity of prepared powders. The results present fundamental information about the effect of the size of the nanocrystals to their luminescence properties. The promising application of prepared nanocrystals in the field of lasers and planar optical amplifiers is widely discussed in the contribution.

Keywords: europium, luminescence, nanocrystals, sol-gel

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Authors: Siyang Wang, Yujin Hu, Xuelin Wang, Wenqian Zhang

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Austenitic stainless steels are widely used in nuclear industry to manufacture critical components owing to their excellent corrosion resistance at high temperatures. Almost all the components used in nuclear power plants are produced by surface finishing (surface cold work) such as milling, grinding and so on. The change of surface states induced by machining has great influence on the corrosion behavior. In the present study, long time oxidation behavior of machined 316 austenitic stainless steel exposed to simulated pressure water reactor environment was investigated considering different surface states. Four surface finishes were produced by electro-polishing (P), grinding (G), and two milling (M and M1) processes respectively. Before oxidation, the surface Vickers micro-hardness, surface roughness of each type of sample was measured. Corrosion behavior of four types of sample was studied by using oxidation weight gain method for six oxidation periods. The oxidation time of each period was 120h, 216h, 336h, 504h, 672h and 1344h, respectively. SEM was used to observe the surface morphology of oxide film in several period. The results showed that oxide film on austenitic stainless steel has a duplex-layer structure. The inner oxide film is continuous and compact, while the outer layer is composed of oxide particles. The oxide particle consisted of large particles (nearly micron size) and small particles (dozens of nanometers to a few hundred nanometers). The formation of oxide particle could be significantly affected by the machined surface states. The large particle on cold worked samples (grinding and milling) appeared earlier than electro-polished one, and the milled sample has the largest particle size followed by ground one and electro-polished one. For machined samples, the large particles were almost distributed along the direction of machining marks. Severe exfoliation was observed on one milled surface (M) which had the most heavily cold worked layer, while rare local exfoliation occurred on the ground sample (G) and the other milled sample (M1). The electro-polished sample (P) entirely did not exfoliate.

Keywords: austenitic stainless steel, oxidation, machining, SEM

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Authors: Onyedikachi Ulelu, Andrew P. Longstaff, Simon Fletcher, Simon Parkinson

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The widespread interest in 'Industry 4.0' or 'digital manufacturing' has led to significant research requiring the acquisition of data from sensors, instruments, and machine signals. In-depth research then identifies methods of analysis of the massive amounts of data generated before and during manufacture to solve a particular problem. The ultimate goal is for industrial Internet of Things (IIoT) data to be processed automatically to assist with either visualisation or autonomous system decision-making. However, the collection and processing of data in an industrial environment come with a cost. Little research has been undertaken on how to specify optimally what data to capture, transmit, process, and store at various levels of an edge-cloud network. The first step in this specification is to categorise IIoT data for efficient and effective use. This paper proposes the required attributes and classification to take manufacturing digital data from various sources to determine the most suitable location for data processing on the edge-cloud network. The proposed classification framework will minimise overhead in terms of network bandwidth/cost and processing time of machine tool data via efficient decision making on which dataset should be processed at the ‘edge’ and what to send to a remote server (cloud). A fast-and-frugal heuristic method is implemented for this decision-making. The framework is tested using case studies from industrial machine tools for machine productivity and maintenance.

Keywords: data classification, decision making, edge computing, industrial IoT, industry 4.0

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Authors: Martin Elstner

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Processing of information by means of handling chemicals is a ubiquitous phenomenon in nature. Technical implementations of chemical information processing lack of low integration densities compared to electronic devices. Stimuli responsive hydrogels are promising candidates for materials with information processing capabilities. These hydrogels are sensitive toward chemical stimuli like metal ions or amino acids. The binding of an analyte molecule induces conformational changes inside the polymer network and subsequently the water content and volume of the hydrogel varies. This volume change can control material flows, and concurrently information flows, in microfluidic devices. The combination of this technology with powerful chemical logic gates yields in a platform for highly integrated chemical circuits. The manufacturing process of such devices is very challenging and rapid prototyping is a key technology used in the study. 3D printing allows generating three-dimensional defined structures of high complexity in a single and fast process step. This thermoplastic master is molded into PDMS and the master is removed by dissolution in an organic solvent. A variety of hydrogel materials is prepared by dispenser printing of pre-polymer solutions. By a variation of functional groups or cross-linking units, the functionality of the hole circuit can be programmed. Finally, applications in the field of bio-molecular analytics were demonstrated with an autonomously operating microfluidic chip.

Keywords: bioanalytics, hydrogels, information processing, microvalve

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Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

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Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

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Authors: Muhammad R. Islam, Mohammad Dalour H. Beg, Saidatul S. Jamari

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Considering palm oil as non-drying oil owing to its low iodine value, an attempt was taken to increase the unsaturation in the fatty acid chains of palm oil for the preparation of alkyds. To increase the unsaturation in the palm oil, sulphuric acid (SA) and para-toluene sulphonic acid (PTSA) was used prior to alcoholysis for the dehydration process. The iodine number of the oil samples was checked for the unsaturation measurement by Wijs method. Alkyd resin was prepared using the dehydrated palm oil by following alcoholysis and esterification reaction. To improve the film properties 0.5 wt% multi-wall carbon nano tubes (MWCNTs) were used to manufacture polymeric film. The properties of the resins were characterized by various physico-chemical properties such as density, viscosity, iodine value, acid value, saponification value, etc. Structural elucidation was confirmed by Fourier transform of infrared spectroscopy and proton nuclear magnetic resonance; surfaces of the cured films were observed by scanning electron microscopy. In addition, pencil hardness and chemical resistivity was also measured by using standard methods. The effect of enhancement of the unsaturation in the fatty acid chain found significant and motivational. The resin prepared with dehydrated palm oil showed improved properties regarding hardness and chemical resistivity testing. The incorporation of MWCNTs enhanced the thermal stability and hardness of the films as well.

Keywords: alkyd resin, nano-coatings, dehydration, palm oil

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Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

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Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

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Authors: Daniel Li

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We present a novel application of neural rendering methods to confocal microscopy. Neural rendering and implicit neural representations have developed at a remarkable pace, and are prevalent in modern 3D computer vision literature. However, they have not yet been applied to optical microscopy, an important imaging field where 3D volume information may be heavily sought after. In this paper, we employ neural rendering on confocal microscopy focus stack data and share the results. We highlight the benefits and potential of adding neural rendering to the toolkit of microscopy image processing techniques.

Keywords: neural rendering, implicit neural representations, confocal microscopy, medical image processing

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Authors: R. Sri Karthi Krishna, A. Saravana Kumar, Kesava Brahmaji, V. S. Vinoj

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The lunar surface may contain rough and non-uniform terrain with dips and peaks. Soft-landing is a method of landing the lander on the lunar surface without any damage to the vehicle. This project focuses on finding a safe landing site for the vehicle by developing a method for the lateral velocity determination of the lunar lander. This is done by processing the real time images obtained by means of an on-board vision sensor. The hazard avoidance phase of the soft-landing starts when the vehicle is about 200 m above the lunar surface. Here, the lander has a very low velocity of about 10 cm/s:vertical and 5 m/s:horizontal. On the detection of a hazard the lander is navigated by controlling the vertical and lateral velocity. In order to find an appropriate landing site and to accordingly navigate, the lander image processing is performed continuously. The images are taken continuously until the landing site is determined, and the lander safely lands on the lunar surface. By integrating this vision-based navigation with the INS a better accuracy for the soft-landing of the lunar lander can be obtained.

Keywords: vision aided INS, image processing, lateral velocity estimation, materials engineering

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Authors: Hatem Diaf, Patrice Melinon, Antonio Pereira, Bernard Moine, Nicholas Blanchard, Florent Bourquard, Florence Garrelie, Christophe Donnet

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Glassy carbon exhibits excellent biological compatibility with live tissues meaning it has high potential for applications in life science. Moreover, glassy carbon has interesting properties including 'high temperature resistance', hardness, low density, low electrical resistance, low friction, and low thermal resistance. The structure of glassy carbon has long been a subject of debate. It is now admitted that glassy carbon is 100% sp2. This term is a little bit confusing as long sp2 hybridization defined from quantum chemistry is related to both properties: threefold configuration and pi bonding (parallel pz orbitals). Using plasma laser deposition of carbon clusters combined with pulsed nano/femto laser annealing, we are able to synthesize thin films of glassy carbon of good quality (probed by G band/ D disorder band ratio in Raman spectroscopy) without thermal post annealing. A careful inspecting of Raman signal, plasmon losses and structure performed by HRTEM (High Resolution Transmission Electron Microscopy) reveals that both properties (threefold and pi orbitals) cannot coexist together. The structure of the films is compared to models including schwarzites based from negatively curved surfaces at the opposite of onions or fullerene-like structures with positively curved surfaces. This study shows that a huge collection of porous carbon named vitreous carbon with different structures can coexist.

Keywords: glassy carbon, cluster deposition, coating, electronic structure

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Authors: Zainab Mohammed Shukur, Najlaa Ali Alboshmina, Ali Safa Alsaegh

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The project was investigated tribological behavior of polyether ether ketone (PEEK1000) against PEEK1000 rolling sliding (non-conformal) configuration with slip ratio 83.3%, were tested applications using a TE77 wear mechanisms and friction coefficient test rig. Under marginal lubrication conditions and the absence of film thick conditions, load 100 N was used to simulate the torque in gears 7 N.m. The friction coefficient and wear mechanisms of PEEK were studied under reciprocating roll/slide conditions with water, ethylene glycol, silicone, and base oil. Tribological tests were conducted on a TE77 high-frequency tribometer, with a disc-on-plate slide/roll (the energy pulse criterion) configuration. An Alicona G5 optical 3D micro-coordinate measurement microscope was used to investigate the surface topography and wear mechanisms. The surface roughness had been a significant effect on the friction coefficient for the PEEK/PEEK the rolling sliding contact test ethylene glycol and on the wear mechanisms. When silicone, ethylene glycol, and oil were used as a lubricant, the steady state of friction coefficient was reached faster than the other lubricant. Results describe the effect of the film thick with slip ratio of 83.3% on the tribological performance.

Keywords: polymer, rolling- sliding, energy pulse, gear contact

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Authors: Apichet Boonsoong

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In the Chanthaburi-Trat basalts, xenoliths are composed of essentially ultramafic xenoliths (particularly spinel lherzolite) with a few of an aggregate of feldspar. Some 19 ultramafic xenoliths were collected from 13 different locations. They range in size from 3.5 to 60mm across. Most are weathered and oxidized on the surface but fresh samples are obtained from cut surfaces. Chemical analyses were performed on carbon-coated polished thin sections using a fully automated CAMECA SX-50 electron microprobe (EMPA) in wavelength-dispersive mode. In thin section, they are seen to consist of variable amounts of olivine, clinopyroxene, orthopyroxene with minor spinel and plagioclase, and are classed as lherzolite. Modal compositions of the ultramafic nodules vary with olivine (60-75%), clinopyroxene (20-30%), orthopyroxene (0-15%), minor spinel (1-3%) and plagioclase (<1%). The essential minerals form an equigranular, medium- to coarse-grained, granoblastic texture, and all are in mutual contact indicating attainment of equilibrium. Reaction rims are common along the nodule margins and in some are also present along grain boundaries. Zoning occurs in clinopyroxene, and to a lesser extent in orthopyroxene. The homogeneity of mineral compositions in lherzolite xenoliths suggests the attainment of equilibrium. The equilibration temperatures of these xenoliths are estimated to be in the range of 973 to 1063°C. Pressure estimates are not so easily obtained because no suitable barometer exists for garnet-free lherzolites and so an indirect method was used. The general mineral assemblage of the lherzolite xenoliths and the absence of garnet indicate a pressure range of approximately 12–19kbar, which is equivalent to depths approximately of 38 to 60km.

Keywords: chanthaburi-trat basalts, spinel lherzolite, xenoliths, 973 to 1063°C, 38 to 60km

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Authors: Muganyizi Jonas Bisheko, G. Rejikumar

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Reducing post-harvest losses could be a sustainable solution to enhance the food and income security of smallholder farmers in developing countries. While various research institutions have come up with a number of innovative post-harvest technologies for reducing post-harvest losses, most of them have not been extensively adopted by smallholder farmers. Despite this gap, the synthesized information about the major constraints of post-harvest technology is scarce. This study has been conducted to fill this gap and show the implications of the findings for future post-harvest research. The developed search strategy retrieved 2201 studies. However, after excluding duplicates, title, abstract and full article screening, a total of 41 documents were identified. The major findings are: (i) there is an outstanding deficiency of systematic evidence of the effect of climate change, off-farm income and sources of post-harvest information on the adoption of improved post-harvest technologies; (ii) there is very limited information on adoption constraints pertaining to matters of policy, rules and regulations; (iii) there is very thin literature on behavioral constraints associated with limited adoption of improved post-harvest technologies; (iv) most of the studies focused on post-harvest storage technologies (47%) followed by overall post-harvest management practices (25%), processing technologies (19%) and packaging technologies (3%). Much of the information was found on Cereals (58%), especially maize (44%); (v) geographically, Sub-Saharan Africa accounted for 79% of the reviewed interventions, while South Asia occupied only 21%. The findings of this review are intended to guide various post-harvest technologists and decision-makers in addressing the challenge of huge post-harvest losses.

Keywords: constraints, post-harvest loss, post-harvest technology , smallholder farmer

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Authors: Thanaa Abdel Moghny, Mohamed Keshawy, Mahmoud Fathy, Abdul-Raheim M. Abdul-Raheim, Khalid I. Kabel, Ahmed F. El-Kafrawy, Mahmoud Ahmed Mousa, Ahmed E. Awadallah

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Ecological pollution is of great concern for human health and the environment. Numerous organic and inorganic pollutants usually discharged into the water caused carcinogenic or toxic effect for human and different life form. In this respect, this work aims to treat water contaminated by organic and inorganic waste using sorbent based on polystyrene. Therefore, two different series of adsorbent material were prepared; the first one included the preparation of polymeric sorbent from the reaction of styrene acrylate ester and alkyl acrylate. The second series involved syntheses of composite ion exchange resins of waste polystyrene and   amorphous carbon thin film (WPS/ACTF) by solvent evaporation using micro emulsion polymerization. The produced ACTF/WPS nanocomposite was sulfonated to produce cation exchange resins ACTF/WPSS nanocomposite. The sorbents of the first series were characterized using FTIR, ¹H NMR, and gel permeation chromatography. The thermal properties of the cross-linked sorbents were investigated using thermogravimetric analysis, and the morphology was characterized by scanning electron microscope (SEM). The removal of organic pollutant was determined through absorption tests in a various organic solvent. The chemical and crystalline structure of nanocomposite of second series has been proven by studies of FTIR spectrum, X-rays, thermal analysis, SEM and TEM analysis to study morphology of resins and ACTF that assembled with polystyrene chain. It is found that the composite resins ACTF/WPSS are thermally stable and show higher chemical stability than ion exchange WPSS resins. The composite resin was evaluated for calcium hardness removal. The result is evident that the ACTF/WPSS composite has more prominent inorganic pollutant removal than WPSS resin. So, we recommend the using of nanocomposite resin as new potential applications for water treatment process.

Keywords: nanocomposite, sorbent materials, waste water, waste polystyrene

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Authors: Justyna Minkiewicz

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Artificial Intelligence (AI) applied in the arts may influence the development of AI knowledge in other sectors and then also impact mutual collaboration with the artistic environment. Hence this collaboration may also impact the development of art projects. The paper will reflect the qualitative research outcomes based on in-depth (IDI) interviews within the marketing sector in Poland and desk research. Art is a reflection of the spirit of our times. Moreover, now we are experiencing a significant acceleration in the development of technologies and their use in various sectors. The leading technologies that contribute to the development of the economy, including the creative sector, embrace technologies such as artificial intelligence, blockchain, extended reality, voice processing, and virtual beings. Artificial intelligence is one of the leading technologies developed for several decades, which is currently reaching a high level of interest and use in various sectors. However, the conducted research has shown that there is still low awareness of artificial intelligence and its wide application in various sectors. The study will show how artists use artificial intelligence in their art projects and how it can be translated into practice within the business. At the same time, the paper will raise awareness of the need for businesses to be inspired by the artistic environment. The research proved that there is still a need to popularize knowledge about this technology which is crucial for many sectors. Art projects are tools to develop knowledge and awareness of society and also various sectors. At the same time, artists may benefit from such collaboration. The paper will include selected aspects of mutual relations, areas of possible inspiration, and possible transfers of technological solutions. Those are AI applications in creative industries such as advertising and film, image recognition in art, and projects from different sectors.

Keywords: artificial intelligence, business, art, creative industry, technology

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Authors: Tracey Lion-Cachet

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Eating disorders typically manifest in adolescence and are notoriously difficult to treat. There are two notable reasons for this. Firstly, research consistently demonstrates that early intervention is a critical mediator of prognosis, with early intervention leading to a better prognosis. However, because eating disorders do not originate as full-syndrome diagnoses but rather as prodromal cases, they often go undetected; by the time symptoms meet diagnostic criteria, they have become recalcitrant. Another interrelated issue is motivation to change. Research demonstrates that in the early stages of an eating disorder, adolescents are highly resistant to change, and motivation increases only once symptoms have shifted from egosyntonic to egodystonic in nature. The purpose of this project was to design a prevention model based on the social psychology paradigm of Entertainment-Education, which embeds messages within the genre of film as a means of affecting change. The resulting project was a narrative screenplay targeting teenagers/young adults from diverse backgrounds. The goals of the project were to create a film script that, if ultimately made into a film, could serve to: 1) interrupt symptom progression and improve prognosis through early intervention; 2) incorporate techniques from third-wave cognitive behavioral treatment models, acceptance and commitment therapy (ACT) and rational recovery (RR), with a focus on the effects of mindfulness as a means of informing recovery; 3) target issues to do with motivation to change by shifting the perception of eating disorders from culturally specific psychiatric illnesses to habit-based brain wiring issues. Nine licensed clinicians were asked to evaluate two excerpts taken from the final script. They subsequently provided feedback on a Likert-scale, which assessed whether the script had achieved its goals. Overall, evaluators agreed that the project’s etiological and intervention models have the potential to inspire change and serve as an effective means of prevention and treatment of eating disorders. However, one-third of the evaluators did not find the content developmentally appropriate. This is a notable limitation to the study and will need to be addressed in the larger script before the final project can potentially be targeted to a teenage and young adult audience.

Keywords: adolescents, eating disorders, pediatrics, entertainment-education, mindfulness-based intervention, prevention

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Authors: D. Bikiaris, M. Nerantzaki, I. Koliakou, A. Francone, N. Kehagias

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In the present study, the formation of structures in poly(lactic acid) (PLA) has been investigated with respect to producing areas of regular, superficial features with dimensions comparable to those of cells or biological macromolecules. Nanoimprint lithography, a method of pattern replication in polymers, has been used for the production of features ranging from tens of micrometers, covering areas up to 1 cm², down to hundreds of nanometers. Both micro- and nano-structures were faithfully replicated. Potentially, PLA has wide uses within biomedical fields, from implantable medical devices, including screws and pins, to membrane applications, such as wound covers, and even as an injectable polymer for, for example, lipoatrophy. The possibility of fabricating structured PLA surfaces, with structures of the dimensions associated with cells or biological macro- molecules, is of interest in fields such as cellular engineering. Imprint-based technologies have demonstrated the ability to selectively imprint polymer films over large areas resulting in 3D imprints over flat, curved or pre-patterned surfaces. Here, we compare nano-patterned with nano-patterned by nanoimprint lithography (NIL) PLA film. A silicon nanostructured stamp (provided by Nanotypos company) having positive and negative protrusions was used to pattern PLA films by means of thermal NIL. The polymer film was heated from 40°C to 60°C above its Tg and embossed with a pressure of 60 bars for 3 min. The stamp and substrate were demolded at room temperature. Scanning electron microscope (SEM) images showed good replication fidelity of the replicated Si stamp. Contact-angle measurements suggested that positive microstructuring of the polymer (where features protrude from the polymer surface) produced a more hydrophilic surface than negative micro-structuring. The ability to structure the surface of the poly(lactic acid), allied to the polymer’s post-processing transparency and proven biocompatibility. Films produced in this were also shown to enhance the aligned attachment behavior and proliferation of Wharton’s Jelly Mesenchymal Stem cells, leading to the observed growth contact guidance. The bacterial attachment patterns of some bacteria, highlighted that the nano-patterned PLA structure can reduce the propensity for the bacteria to attach to the surface, with a greater bactericidal being demonstrated activity against the Staphylococcus aureus cells. These biocompatible, micro- and nanopatterned PLA surfaces could be useful for polymer– cell interaction experiments at dimensions at, or below, that of individual cells. Indeed, post-fabrication modification of the microstructured PLA surface, with materials such as collagen (which can further reduce the hydrophobicity of the surface), will extend the range of applications, possibly through the use of PLA’s inherent biodegradability. Further study is being undertaken to examine whether these structures promote cell growth on the polymer surface.

Keywords: poly(lactic acid), nano-imprint lithography, anti-bacterial properties, PLA

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Authors: Samantha Rix

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The purpose of this research paper is to investigate the cognitive processing of learners who receive input but produce very little or no output, and who, when they do produce output, exhibit a similar language proficiency as do those learners who produced output more regularly in the language classroom. Previous studies have investigated the benefits of output (with somewhat differing results); therefore, the presentation will begin with an investigation of what may underlie gains in proficiency without output. Consequently, a pilot study was designed and conducted to gain insight into the cognitive processing of low-output language learners looking, for example, at quantity and quality of noticing. This will be carried out within the paradigm of action classroom research, observing and interviewing low-output language learners in an intensive English program at a small Midwest university. The results of the pilot study indicated that autonomy in language learning, specifically utilizing strategies such self-monitoring, self-talk, and thinking 'out-loud', were crucial in the development of language proficiency for academic-level performance. The presentation concludes with an examination of pedagogical implication for classroom use in order to aide students in their language development.

Keywords: cognitive processing, language learners, language proficiency, learning strategies

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Authors: Mohammad Khosravi, Ali Kiani, Behroz Dastar, Parvin Showrang

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Review was carried out on important anti-nutritional compounds of livestock and poultry foods and the effect of radiation usage. Nowadays, with advancement in technology, different methods have been considered for the optimum usage of nutrients in livestock and poultry foods. Steaming, extruding, pelleting, and the use of chemicals are the most common and popular methods in food processing. Use of radiation in food processing researches in the livestock and poultry industry is currently highly regarded. Ionizing (electrons, gamma) and non-ionizing beams (microwave and infrared) are the most useable rays in animal food processing. In recent researches, these beams have been used to remove and reduce the anti-nutritional factors and microbial contamination and improve the digestibility of nutrients in poultry and livestock food. The evidence presented will help researchers to recognize techniques of relevance to them. Simplification of some of these techniques, especially in developing countries, must be addressed so that they can be used more widely.

Keywords: antitrypsin, gamma anti-nutritional components, phytic acid, radiation

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Authors: Daniel Tscharnuter, Eliza Truszkiewicz, Gerald Pinter

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High-quality surfaces of plastic parts can be achieved in a very cost-effective manner using in-mold processes, where e.g. scratch resistant or high gloss polymer films are pre-formed and subsequently receive their support structure by injection molding. The pre-forming may be done by high-pressure forming. In this process, a polymer sheet is heated and subsequently formed into the mold by pressurized air. Due to the heat transfer to the cooled mold the polymer temperature drops below its glass transition temperature. This ensures that the deformed microstructure is retained after depressurizing, giving the sheet its final formed shape. The development of a forming process relies heavily on the experience of engineers and trial-and-error procedures. Repeated mold design and testing cycles are however both time- and cost-intensive. It is, therefore, desirable to study the process using reliable computer simulations. Through simulations, the construction of the mold and the effect of various process parameters, e.g. temperature levels, non-uniform heating or timing and magnitude of pressure, on the deformation of the polymer sheet can be analyzed. Detailed knowledge of the deformation is particularly important in the forming of polymer films with integrated electro-optical functions. Care must be taken in the placement of devices, sensors and electrical and optical paths, which are far more sensitive to deformation than the polymers. Reliable numerical prediction of the deformation of the polymer sheets requires sophisticated material models. Polymer films are often either transversely isotropic or orthotropic due to molecular orientations induced during manufacturing. The anisotropic behavior affects the resulting strain field in the deformed film. For example, parts of the same shape but different strain fields may be created by varying the orientation of the film with respect to the mold. The numerical simulation of the high-pressure forming of such films thus requires material models that can capture the nonlinear anisotropic mechanical behavior. There are numerous commercial polymer grades for the engineers to choose from when developing a new part. The effort required for comprehensive material characterization may be prohibitive, especially when several materials are candidates for a specific application. We, therefore, propose a class of models for compressible hyperelasticity, which may be determined from basic experimental data and which can capture key features of the mechanical response. Invariant-based hyperelastic models with a reduced number of invariants are formulated in a semi-numerical way, such that the models are determined from a single uniaxial tensile tests for isotropic materials, or two tensile tests in the principal directions for transversely isotropic or orthotropic materials. The simulation of the high pressure forming of an orthotropic polymer film is finally done using an orthotropic formulation of the hyperelastic model.

Keywords: hyperelastic, anisotropic, polymer film, thermoforming

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Authors: Angela Fabris, Joerg Helbig

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Our paper deals with feature films set in Venice which focus on the influence of Italian life style on anglophone characters. Usually, these films emphasize the different cultures and mentalities of Italian and British (or American) people. More often than not, these encounters result in a profound change of the anglophone characters' attitude towards romance and sensuality. A case in point is David Lean's Summer Madness (UK 1955). This film recounts the love affair between the American tourist Jane Hudson (Katherine Hepburn) and the Venetian antique shop owner Renato de Rossi (Rossano Brazzi). Jane is a spinster in her mid-forties who longs for love and romance. The chance arrives when she meets Renato who feels attracted to her. Jane's immediate reaction, however, is to reject Renato's advances. What follows is a struggle between the strict morality of a puritan upbringing and the irresitable charm of Mediterranean temptations. Similar conflicts can be found in many other movies. Apart from Summer Madness we will discuss Aldo Lado's Chi l'ha vista morire? (It 1972), Nicolas Roeg's Don't Look Now (UK/It 1973) and Paul Schrader's The Comfort of Strangers (It/UK/USA 1990). Our paper raises the question whether or not these and other films present false stereotypes and chlichés. The paper is part of our large-scale research project which explores the history of erotic cinema in Italy and England.

Keywords: culture clash, erotic cinema, film, Venice

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Authors: Natalia Kalinowska

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The adoption of the General Data Protection Regulation, (GDPR) finished the four-year work of the European Commission in this area in the European Union. Considering far-reaching changes, which will be applied by GDPR, the European legislator envisaged two-year transitional period. Member states and companies have to prepare for a new regulation until 25 of May 2018. The idea, which becomes a new look at an attitude to data protection in the European Union is risk-based approach. So far, as a result of implementation of Directive 95/46/WE, in many European countries (including Poland) there have been adopted very particular regulations, specifying technical and organisational security measures e.g. Polish implementing rules indicate even how long password should be. According to the new approach from May 2018, controllers and processors will be obliged to apply security measures adequate to level of risk associated with specific data processing. The risk in GDPR should be interpreted as the likelihood of a breach of the rights and freedoms of the data subject. According to Recital 76, the likelihood and severity of the risk to the rights and freedoms of the data subject should be determined by reference to the nature, scope, context and purposes of the processing. GDPR does not indicate security measures which should be applied – in recitals there are only examples such as anonymization or encryption. It depends on a controller’s decision what type of security measures controller considered as sufficient and he will be responsible if these measures are not sufficient or if his identification of risk level is incorrect. Data protection regulation indicates few levels of risk. Recital 76 indicates risk and high risk, but some lawyers think, that there is one more category – low risk/now risk. Low risk/now risk data processing is a situation when it is unlikely to result in a risk to the rights and freedoms of natural persons. GDPR mentions types of data processing when a controller does not have to evaluate level of risk because it has been classified as „high risk” processing e.g. processing on a large scale of special categories of data, processing with using new technologies. The methodology will include analysis of legal regulations e.g. GDPR, the Polish Act on the Protection of personal data. Moreover: ICO Guidelines and articles concerning risk based approach in GDPR. The main conclusion is that an appropriate risk assessment is a key to keeping data safe and avoiding financial penalties. On the one hand, this approach seems to be more equitable, not only for controllers or processors but also for data subjects, but on the other hand, it increases controllers’ uncertainties in the assessment which could have a direct impact on incorrect data protection and potential responsibility for infringement of regulation.

Keywords: general data protection regulation, personal data protection, privacy protection, risk based approach

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Authors: Theresia El Khoury, Georges Badr, Amir Hajjam El Hassani, Stéphane N’Guyen Van Ky

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The widespread adoption of machine learning and artificial intelligence across different domains can be attributed to the digitization of data over several decades, resulting in vast amounts of data, types, and structures. Thus, data processing and preparation turn out to be a crucial stage. However, applying these techniques to S1000D standard-based data poses a challenge due to its complexity and the need to preserve logical information. This paper describes SALERNO, an S1000d AppLicability dEpended pRocessiNg mOdel. This python-based model analyzes and converts the XML S1000D-based files into an easier data format that can be used in machine learning techniques while preserving the different logic and relationships in files. The model parses the files in the given folder, filters them, and extracts the required information to be saved in appropriate data frames and Excel sheets. Its main idea is to group the extracted information by applicability. In addition, it extracts the full text by replacing internal and external references while maintaining the relationships between files, as well as the necessary requirements. The resulting files can then be saved in databases and used in different models. Documents in both English and French languages were tested, and special characters were decoded. Updates on the technical manuals were taken into consideration as well. The model was tested on different versions of the S1000D, and the results demonstrated its ability to effectively handle the applicability, requirements, references, and relationships across all files and on different levels.

Keywords: aeronautics, big data, data processing, machine learning, S1000D

Procedia PDF Downloads 156