Search results for: computer generated holograms

Authors: Kiran Kumar K., Ramesh Babu Bejjam, Atul Najan

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A thermosyphon system is a heat transfer loop which operates on the basis of gravity and buoyancy forces. It guarantees a good reliability and low maintenance cost as it does not involve any mechanical pump. Therefore it can be used in many industrial applications such as refrigeration and air conditioning, electronic cooling, nuclear reactors, geothermal heat extraction, etc. But flow instabilities and loop configuration are the major problems in this system. Several previous researchers studied that stabilities can be suppressed by using nanofluids as loop fluid. In the present study a rectangular thermosyphon loop with end heat exchangers are considered for the study. This configuration is more appropriate for many practical applications such as solar water heater, geothermal heat extraction, etc. In the present work, steady-state analysis is carried out on thermosyphon loop with parallel flow coaxial heat exchangers at heat source and heat sink. In this loop nano fluid is considered as the loop fluid and water is considered as the external fluid in both hot and cold heat exchangers. For this analysis one-dimensional homogeneous model is developed. In this model, conservation equations like conservation of mass, momentum, energy are discretized using finite difference method. A computer code is written in MATLAB to simulate the flow in thermosyphon loop. A comparison in terms of heat transfer is made between water and nano fluid as working fluids in the loop.

Keywords: heat exchanger, heat transfer, nanofluid, thermosyphon loop

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Authors: James Cairns, Marco Vezza, Richard Green, Donald MacVicar

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Significant legislative changes are set to revolutionise the commercial shipping industry. Upcoming emissions restrictions will force operators to look at technologies that can improve the efficiency of their vessels -reducing fuel consumption and emissions. A device which may help in this challenge is the Ship Wind-Assisted Propulsion system (SWAP), an actively controlled aerofoil mounted vertically on the deck of a ship. The device functions in a similar manner to a sail on a yacht, whereby the aerodynamic forces generated by the sail reach an equilibrium with the hydrodynamic forces on the hull and a forward velocity results. Numerical and experimental testing of the SWAP device is presented in this study. Circulation control takes the form of a co-flow jet aerofoil, utilising both blowing from the leading edge and suction from the trailing edge. A jet at the leading edge uses the Coanda effect to energise the boundary layer in order to delay flow separation and create high lift with low drag. The SWAP concept has been originated by the research and development team at SMAR Azure Ltd. The device will be retrofitted to existing ships so that a component of the aerodynamic forces acts forward and partially reduces the reliance on existing propulsion systems. Wind tunnel tests have been carried out at the de Havilland wind tunnel at the University of Glasgow on a 1:20 scale model of this system. The tests aim to understand the airflow characteristics around the aerofoil and investigate the approximate lift and drag coefficients that an early iteration of the SWAP device may produce. The data exhibits clear trends of increasing lift as injection momentum increases, with critical flow attachment points being identified at specific combinations of jet momentum coefficient, Cµ, and angle of attack, AOA. Various combinations of flow conditions were tested, with the jet momentum coefficient ranging from 0 to 0.7 and the AOA ranging from 0° to 35°. The Reynolds number across the tested conditions ranged from 80,000 to 240,000. Comparisons between 2D computational fluid dynamics (CFD) simulations and the experimental data are presented for multiple Reynolds-Averaged Navier-Stokes (RANS) turbulence models in the form of normalised surface pressure comparisons. These show good agreement for most of the tested cases. However, certain simulation conditions exhibited a well-documented shortcoming of RANS-based turbulence models for circulation control flows and over-predicted surface pressures and lift coefficient for fully attached flow cases. Work must be continued in finding an all-encompassing modelling approach which predicts surface pressures well for all combinations of jet injection momentum and AOA.

Keywords: CFD, circulation control, Coanda, turbo wing sail, wind tunnel

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Stanley Russell

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Until the end of the 19th century, European painting dealt almost exclusively with the realistic representation of objects and landscapes, as can be seen in the work of realist artists like Gustav Courbet. Architects of the day typically made reference to and recreated historical precedents in their designs. The curriculum of the first architecture school in Europe, The Ecole des Beaux Artes, based on the study of classical buildings, had a profound effect on the profession. Painting exhibited an increasing level of abstraction from the late 19th century, with impressionism, and the trend continued into the early 20th century when Cubism had an explosive effect sending shock waves through the art world that also extended into the realm of architectural design. Architect /painter Le Corbusier with “Purism” was one of the first to integrate abstract painting and building design theory in works that were equally shocking to the architecture world. The interrelationship of the arts, including architecture, was institutionalized in the Bauhaus curriculum that sought to find commonality between diverse art disciplines. Renowned painter and Bauhaus instructor Vassily Kandinsky was one of the first artists to make a semi-scientific analysis of the elements in “non-objective” painting while also drawing parallels between painting and architecture in his book Point and Line to plane. Russian constructivists made abstract compositions with simple geometric forms, and like the De Stijl group of the Netherlands, they also experimented with full-scale constructions and spatial explorations. Based on the study of historical accounts and original artworks, of Impressionism, Cubism, the Bauhaus, De Stijl, and Russian Constructivism, this paper begins with a thorough explanation of the art theory and several key works from these important art movements of the late 19th and early 20th century. Similarly, based on written histories and first-hand experience of built and drawn works, the author continues with an analysis of the theories and architectural works generated by the same groups, all of which actively pursued continuity between their art and architectural concepts. With images of specific works, the author shows how the trend toward abstraction and geometric purity in painting coincided with a similar trend in architecture that favored simple unornamented geometries. Using examples like the Villa Savoye, The Schroeder House, the Dessau Bauhaus, and unbuilt designs by Russian architect Chernikov, the author gives detailed examples of how the intersection of trends in Art and Architecture led to a unique and fruitful period of creative synergy when the same concepts that were used by artists to generate paintings were also used by architects in the making of objects, space, and buildings. In Conclusion, this article examines the extremely pivotal period in art and architecture history from the late 19th to early 20th century when the confluence of art and architectural theory led to many painted, drawn, and built works that continue to inspire architects and artists to this day.

Keywords: modern art, architecture, design methodologies, modern architecture

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Authors: José de Jesús Rivero Oliva, Jesús Salomón Llanes, Manuel Perdomo Ojeda, Antonio Torres Valle

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Combinatorial explosion is a common problem to both predominant methods for solving fault trees: Minimal Cut Set (MCS) approach and Binary Decision Diagram (BDD). High memory consumption impedes the complete solution of very complex fault trees. Only approximated non-conservative solutions are possible in these cases using truncation or other simplification techniques. The paper proposes a method (CSolv+) for solving complex fault trees, without any possibility of combinatorial explosion. Each individual MCS is immediately discarded after its contribution to the basic events importance measures and the Top gate Upper Bound Probability (TUBP) has been accounted. An estimation of the Top gate Exact Probability (TEP) is also provided. Therefore, running in a computer cluster, CSolv+ will guarantee the complete solution of complex fault trees. It was successfully applied to 40 fault trees from the Aralia fault trees database, performing the evaluation of the top gate probability, the 1000 Significant MCSs (SMCS), and the Fussell-Vesely, RRW and RAW importance measures for all basic events. The high complexity fault tree nus9601 was solved with truncation probabilities from 10-²¹ to 10-²⁷ just to limit the execution time. The solution corresponding to 10-²⁷ evaluated 3.530.592.796 MCSs in 3 hours and 15 minutes.

Keywords: system reliability analysis, probabilistic risk assessment, fault tree analysis, basic events importance measures

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Authors: K. S. Rao, Ankesh Kumar

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The search for alternative energy sources to petroleum has increased these days because of increase in need and depletion of petroleum reserves. Therefore the importance of oil shales as an economically viable substitute has increased many folds in last 20 years. The technologies like hydro-fracturing have opened the field of oil extraction from these unconventional rocks. Oil shale is a compact laminated rock of sedimentary origin containing organic matter known as kerogen which yields oil when distilled. Oil shales are formed from the contemporaneous deposition of fine grained mineral debris and organic degradation products derived from the breakdown of biota. Conditions required for the formation of oil shales include abundant organic productivity, early development of anaerobic conditions, and a lack of destructive organisms. These rocks are not gown through the high temperature and high pressure conditions in Mother Nature. The most common approach for oil extraction is drastically breaking the bond of the organics which involves retorting process. The two approaches for retorting are surface retorting and in-situ processing. The most environmental friendly approach for extraction is In-situ processing. The three steps involved in this process are fracturing, injection to achieve communication, and fluid migration at the underground location. Upon heating (retorting) oil shale at temperatures in the range of 300 to 400°C, the kerogen decomposes into oil, gas and residual carbon in a process referred to as pyrolysis. Therefore it is very important to understand the physico-mechenical behavior of such rocks, to improve the technology for in-situ extraction. It is clear from the past research and the physical observations that these rocks will behave as an anisotropic rock so it is very important to understand the mechanical behavior under high pressure at different orientation angles for the economical use of these resources. By knowing the engineering behavior under above conditions will allow us to simulate the deep ground retorting conditions numerically and experimentally. Many researchers have investigate the effect of organic content on the engineering behavior of oil shale but the coupled effect of organic and inorganic matrix is yet to be analyzed. The favourable characteristics of Assam coal for conversion to liquid fuels have been known for a long time. Studies have indicated that these coals and carbonaceous shale constitute the principal source rocks that have generated the hydrocarbons produced from the region. Rock cores of the representative samples are collected by performing on site drilling, as coring in laboratory is very difficult due to its highly anisotropic nature. Different tests are performed to understand the petrology of these samples, further the chemical analyses are also done to exactly quantify the organic content in these rocks. The mechanical properties of these rocks are investigated by considering different anisotropic angles. Now the results obtained from petrology and chemical analysis are correlated with the mechanical properties. These properties and correlations will further help in increasing the producibility of these rocks. It is well established that the organic content is negatively correlated to tensile strength, compressive strength and modulus of elasticity.

Keywords: oil shale, producibility, hydro-fracturing, kerogen, petrology, mechanical behavior

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Authors: Christabel Ihedike, John Mooney, Monica Price

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Summary: This study aims to critically evaluate effect of photochemical smog on respiratory health in Nigeria. Cohort of chronic obstructive pulmonary disease (COPD) patients was recruited from two large hospitals in Abuja Nigeria. Respiratory health questionnaires, daily diaries, dyspnoea scale and lung function measurement were used to obtain health data and investigate the relationship with air quality data (principally ozone, NOx and particulate pollution). Concentrations of air pollutants were higher than WHO and Nigerian air quality standard. The result suggests a correlation between measured air quality and exacerbation of respiratory illness. Introduction: Photochemical smog is a significant health challenge in most cities and its effect on respiratory health is well acknowledged. This type of pollution is most harmful to the elderly, children and those with underlying respiratory disease. This study aims to investigate impact of increasing temperature and photo-chemically generated secondary air pollutants on respiratory health in Abuja Nigeria. Method and Result: Health data was collected using spirometry to measure lung function on routine attendance at the clinic, daily diaries kept by patients and information obtained using respiratory questionnaire. Questionnaire responses (obtained using an adapted and internally validated version of St George’s Hospital Respiratory Questionnaire), shows that ‘time of wheeze’ showed an association with participants activities: 30% had worse wheeze in the morning: 10% cannot shop, 15% take long-time to get washed, 25% walk slower, 15% if hurry have to stop and 5% cannot take-bath. There was also a decrease in Forced expiratory volume in the first second and Forced Vital Capacity, and daily change in the afternoon–morning may be associated with the concentration level of pollutants. Also, dyspnoea symptoms recorded that 60% of patients were on grade 3, 25% grade 2 and 15% grade 1. Daily frequency of the number of patients in the cohort that cough /brought sputum is 78%. Air pollution in the city is higher than Nigerian and WHO standards with NOx and PM10 concentrations of 693.59ug/m-3 and 748ugm-3 being measured respectively. The result shows that air pollution may increase occurrence and exacerbation of respiratory disease. Conclusion: High temperature and local climatic conditions in urban Nigeria encourages formation of Ozone, the major constituent of photochemical smog, resulting also in the formation of secondary air pollutants associated with health challenges. In this study we confirm the likely potency of the pattern of secondary air pollution in exacerbating COPD symptoms in vulnerable patient group in urban Nigeria. There is need for better regulation and measures to reduce ozone, particularly when local climatic conditions favour development of photochemical smog in such settings. Climate change and likely increasing temperatures add impetus and urgency for better air quality standards and measures (traffic-restrictions and emissions standards) in developing world settings such as Nigeria.

Keywords: Abuja-Nigeria, effect, photochemical smog, respiratory health

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Authors: Mst Shapna Akter, Hossain Shahriar

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Neural network approaches are machine learning methods used in many domains, such as healthcare and cyber security. Neural networks are mostly known for dealing with image datasets. While training with the images, several fundamental mathematical operations are carried out in the Neural Network. The operation includes a number of algebraic and mathematical functions, including derivative, convolution, and matrix inversion and transposition. Such operations require higher processing power than is typically needed for computer usage. Central Processing Unit (CPU) is not appropriate for a large image size of the dataset as it is built with serial processing. While Graphics Processing Unit (GPU) has parallel processing capabilities and, therefore, has higher speed. This paper uses advanced Neural Network techniques such as VGG16, Resnet50, Densenet, Inceptionv3, Xception, Mobilenet, XGBOOST-VGG16, and our proposed models to compare CPU and GPU resources. A system for classifying autism disease using face images of an autistic and non-autistic child was used to compare performance during testing. We used evaluation matrices such as Accuracy, F1 score, Precision, Recall, and Execution time. It has been observed that GPU runs faster than the CPU in all tests performed. Moreover, the performance of the Neural Network models in terms of accuracy increases on GPU compared to CPU.

Keywords: autism disease, neural network, CPU, GPU, transfer learning

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Authors: Siu-Siu Guo, Qingxuan Shi

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In this paper, single-degree-of-freedom (SDOF) systems to white noise and colored noise excitations are investigated. By expressing colored noise excitation as a second-order filtered white noise process and introducing colored noise as an additional state variable, the equation of motion for SDOF system under colored noise is then transferred artificially to multi-degree-of-freedom (MDOF) system under white noise excitations. As a consequence, corresponding Fokker-Planck-Kolmogorov (FPK) equation governing the joint probabilistic density function (PDF) of state variables increases to 4-dimension (4-D). Solution procedure and computer programme become much more sophisticated. The exponential-polynomial closure (EPC) method, widely applied for cases of SDOF systems under white noise excitations, is developed and improved for cases of systems under colored noise excitations and for solving the complex 4-D FPK equation. On the other hand, Monte Carlo simulation (MCS) method is performed to test the approximate EPC solutions. Two examples associated with Gaussian and non-Gaussian colored noise excitations are considered. Corresponding band-limited power spectral densities (PSDs) for colored noise excitations are separately given. Numerical studies show that the developed EPC method provides relatively accurate estimates of the stationary probabilistic solutions. Moreover, statistical parameter of mean-up crossing rate (MCR) is taken into account, which is important for reliability and failure analysis.

Keywords: filtered noise, narrow-banded noise, nonlinear dynamic, random vibration

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Authors: Thomas D. Collin, Rachel Cunningham, Bruce Jefferson, Raffaella Villa

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Fats, oils and grease (FOG) are by-products of food preparation and cooking processes. FOG enters wastewater systems through a variety of sources such as households, food service establishments, and industrial food facilities. Over time, if no source control is in place, FOG builds up on pipe walls, leading to blockages, and potentially to sewer overflows which are a major risk to the Environment and Human Health. UK water utilities spend millions of pounds annually trying to control FOG. Despite UK legislation specifying that discharge of such material is against the law, it is often complicated for water companies to identify and prosecute offenders. Hence, it leads to uncertainties regarding the attitude to take in terms of FOG management. Research is needed to seize the full potential of implementing current practices. The aim of this research was to undertake a comprehensive study to document the extent of FOG problems in sewer lines and reinforce existing knowledge. Data were collected to develop a model estimating quantities of FOG available for recovery within Thames Water wastewater catchments. Geographical Information System (GIS) software was used in conjunction to integrate data with a geographical component. FOG was responsible for at least 1/3 of sewer blockages in Thames Water waste area. A waste-based approach was developed through an extensive review to estimate the potential for FOG collection and recovery. Three main sources were identified: residential, commercial and industrial. Commercial properties were identified as one of the major FOG producers. The total potential FOG generated was estimated for the 354 wastewater catchments. Additionally, raw and settled sewage were sampled and analysed for FOG (as hexane extractable material) monthly at 20 sewage treatment works (STW) for three years. A good correlation was found with the sampled FOG and population equivalent (PE). On average, a difference of 43.03% was found between the estimated FOG (waste-based approach) and sampled FOG (raw sewage sampling). It was suggested that the approach undertaken could overestimate the FOG available, the sampling could only capture a fraction of FOG arriving at STW, and/or the difference could account for FOG accumulating in sewer lines. Furthermore, it was estimated that on average FOG could contribute up to 12.99% of the primary sludge removed. The model was further used to investigate the relationship between estimated FOG and number of blockages. The higher the FOG potential, the higher the number of FOG-related blockages is. The GIS-based tool was used to identify critical areas (i.e. high FOG potential and high number of FOG blockages). As reported in the literature, FOG was one of the main causes of sewer blockages. By identifying critical areas (i.e. high FOG potential and high number of FOG blockages) the model further explored the potential for source-control in terms of ‘sewer relief’ and waste recovery. Hence, it helped targeting where benefits from implementation of management strategies could be the highest. However, FOG is still likely to persist throughout the networks, and further research is needed to assess downstream impacts (i.e. at STW).

Keywords: fat, FOG, GIS, grease, oil, sewer blockages, sewer networks

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Authors: Jesus Kombaya, Nadia Hamani, Lyes Kermad

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The preservation of a company’s place on the market in such aggressive competition is becoming a survival challenge for manufacturers. In this context, survivors are only those who succeed to satisfy their customers’ needs as quickly as possible. The production system should be endowed with a certain level of flexibility to eliminate or reduce the rigidity of the production systems in order to facilitate the conversion and/or the change of system’s features to produce different products. Therefore, it is essential to guarantee the quality, the speed and the flexibility to survive in this competition. According to literature, this adaptability is referred to as the notion of "change". Indeed, companies are trying to establish a more flexible and agile manufacturing system through several reconfiguration actions. Reconfiguration contributes to the extension of the manufacturing system life cycle by modifying its physical, organizational and computer characteristics according to the changing market conditions. Reconfigurability is characterized by six key elements that are: modularity, integrability, diagnosability, convertibility, scalability and customization. In order to control the production systems, it is essential for manufacturers to make good use of this capability in order to be sure that the system has an optimal and adapted level of reconfigurability that allows it to produce in accordance with the set requirements. This document develops a measure of customization of reconfigurable production systems. These measures do not only impact the production system but also impact the product design and the process design, which can therefore serve as a guide for the customization of manufactured product. A case study is presented to show the use of the proposed approach.

Keywords: reconfigurable manufacturing systems, customization, measure, flexibility

Procedia PDF Downloads 118

Authors: Anshu Anshu

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In the red corridor famed for the Left Wing Extremism, lies small district of Jamui in Bihar, India. The district lies at 24º20´ N latitude and 86º13´ E longitude, covering an area of 3,122.8 km2 The undulating topography, with widespread forests provides pristine environment for invigorating experience of tourists. Natural landscape in form of forests, wildlife, rivers, and cultural landscape dotted with historical and religious places is highly purposive for tourism. The study is primarily related to the identification of potential ecotourism sites, using Geographic Information System. Data preparation, analysis and finally identification of ecotourism sites is done. Secondary data used is Survey of India Topographical Sheets with R.F.1:50,000 covering the area of Jamui district. District Census Handbook, Census of India, 2011; ERDAS Imagine and Arc View is used for digitization and the creation of DEM’s (Digital Elevation Model) of the district, depicting the relief and topography and generate thematic maps. The thematic maps have been refined using the geo-processing tools. Buffer technique has been used for the accessibility analysis. Finally, all the maps, including the Buffer maps were overlaid to find out the areas which have potential for the development of ecotourism sites in the Jamui district. Spatial data - relief, slopes, settlements, transport network and forests of Jamui District were marked and identified, followed by Buffer Analysis that was used to find out the accessibility of features like roads, railway stations to the sites available for the development of ecotourism destinations. Buffer analysis is also carried out to get the spatial proximity of major river banks, lakes, and dam sites to be selected for promoting sustainable ecotourism. Overlay Analysis is conducted using the geo-processing tools. Digital Terrain Model (DEM) generated and relevant themes like roads, forest areas and settlements were draped on the DEM to make an assessment of the topography and other land uses of district to delineate potential zones of ecotourism development. Development of ecotourism in Jamui faces several challenges. The district lies in the portion of Bihar that is part of ‘red corridor’ of India. The hills and dense forests are the prominent hideouts and training ground for the extremists. It is well known that any kind of political instability, war, acts of violence directly influence the travel propensity and hinders all kind of non-essential travels to these areas. The development of ecotourism in the district can bring change and overall growth in this area with communities getting more involved in economically sustainable activities. It is a known fact that poverty and social exclusion are the main force that pushes people, resorting towards violence. All over the world tourism has been used as a tool to eradicate poverty and generate good will among people. Tourism, in sustainable form should be promoted in the district to integrate local communities in the development process and to distribute fruits of development with equity.

Keywords: buffer analysis, digital elevation model, ecotourism, red corridor

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Authors: Drew Commandeur, Ryan Brodie, Sandra Hundza, Marc Klimstra

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The amplitude of raw electromyography (EMG) is affected by recording conditions and often requires normalization to make meaningful comparisons. Bioelectric methods normalize with an EMG signal recorded during a standardized task or from the experimental protocol itself, while biomechanical methods often involve measurements with an additional sensor such as a force transducer. Common bioelectric normalization techniques for treadmill walking include maximum voluntary isometric contraction (MVIC), dynamic EMG peak (EMGPeak) or dynamic EMG mean (EMGMean). There are several concerns with using MVICs to normalize EMG, including poor reliability and potential discomfort. A limitation of bioelectric normalization techniques is that they could result in a misrepresentation of the absolute magnitude of force generated by the muscle and impact the interpretation of EMG between functionally disparate groups. Additionally, methods that normalize to EMG recorded during the task may eliminate some real inter-individual variability due to biological variation. This study compared biomechanical and bioelectric EMG normalization techniques during treadmill walking to assess the impact of the normalization method on the functional interpretation of EMG data. For the biomechanical method, we normalized EMG to a target torque (EMGTS) and the bioelectric methods used were normalization to the mean and peak of the signal during the walking task (EMGMean and EMGPeak). The effect of normalization on muscle activation pattern, EMG amplitude, and inter-individual variability were compared between disparate cohorts of OLD (76.6 yrs N=11) and YOUNG (26.6 yrs N=11) adults. Participants walked on a treadmill at a self-selected pace while EMG was recorded from the right lower limb. EMG data from the soleus (SOL), medial gastrocnemius (MG), tibialis anterior (TA), vastus lateralis (VL), and biceps femoris (BF) were phase averaged into 16 bins (phases) representing the gait cycle with bins 1-10 associated with right stance and bins 11-16 with right swing. Pearson’s correlations showed that activation patterns across the gait cycle were similar between all methods, ranging from r =0.86 to r=1.00 with p<0.05. This indicates that each method can characterize the muscle activation pattern during walking. Repeated measures ANOVA showed a main effect for age in MG for EMGPeak but no other main effects were observed. Interactions between age*phase of EMG amplitude between YOUNG and OLD with each method resulted in different statistical interpretation between methods. EMGTS normalization characterized the fewest differences (four phases across all 5 muscles) while EMGMean (11 phases) and EMGPeak (19 phases) showed considerably more differences between cohorts. The second notable finding was that coefficient of variation, the representation of inter-individual variability, was greatest for EMGTS and lowest for EMGMean while EMGPeak was slightly higher than EMGMean for all muscles. This finding supports our expectation that EMGTS normalization would retain inter-individual variability which may be desirable, however, it also suggests that even when large differences are expected, a larger sample size may be required to observe the differences. Our findings clearly indicate that interpretation of EMG is highly dependent on the normalization method used, and it is essential to consider the strengths and limitations of each method when drawing conclusions.

Keywords: electromyography, EMG normalization, functional EMG, older adults

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Authors: Moez Yeddes

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The property of opacity is widely used in the formal verification of security in computer systems and protocols. Opacity is a general language-theoretic scheme of many security properties of systems. Opacity is parametrized with framework in which several security properties of a system can be expressed. A secret behaviour of a system is opaque if a passive attacker can never deduce its occurrence from the system observation. Instead of considering the case of static observability where the set of observable events is fixed off-line or dynamic observability where the set of observable events changes over time depending on the history of the trace, we introduce Orwellian partial observability where unobservable events are not revealed provided that downgrading events never occurs in the future of the trace. Orwellian partial observability is needed to model intransitive information flow. This Orwellian observability is knwon as ipurge function. We show in previous work how to verify opacity for regular secret is opaque for a regular language L w.r.t. an Orwellian projection is PSPACE-complete while it has been proved undecidable even for a regular language L w.r.t. a general Orwellian observation function. In this paper, we address two problems of opacification of a regular secret ϕ for a regular language L w.r.t. an Orwellian projection: Given L and a secret ϕ ∈ L, the first problem consist to compute some minimal regular super-language M of L, if it exists, such that ϕ is opaque for M and the second consists to compute the supremal sub-language M′ of L such that ϕ is opaque for M′. We derive both language-theoretic characterizations and algorithms to solve these two dual problems.

Keywords: security policies, opacity, formal verification, orwellian observation

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Authors: Okolie Pius Ifeanyi, Emerenini Emilymary Chima

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Aims: The study investigated the diversity and identities of Lactic Acid Bacteria (LAB) isolated from different fresh fruits using Molecular Nested PCR analysis and the efficacy of cell free supernatants from Lactic Acid Bacteria (LAB) isolated from fresh fruits for in vitro control of some tomato pathogens. Study Design: Nested PCR approach was used in this study employing universal 16S rRNA gene primers in the first round PCR and LAB specific Primers in the second round PCR with the view of generating specific Nested PCR products for the LAB diversity present in the samples. The inhibitory potentials of supernatant obtained from LAB isolates of fruits origin that were molecularly characterized were investigated against some tomato phytopathogens using agar-well method with the view to develop biological agents for some tomato disease causing organisms. Methodology: Gram positive, catalase negative strains of LAB were isolated from fresh fruits on Man Rogosa and Sharpe agar (Lab M) using streaking method. Isolates obtained were molecularly characterized by means of genomic DNA extraction kit (Norgen Biotek, Canada) method. Standard methods were used for Nested Polymerase Chain Reaction (PCR) amplification targeting the 16S rRNA gene using universal 16S rRNA gene and LAB specific primers, agarose gel electrophoresis, purification and sequencing of generated Nested PCR products (Macrogen Inc., USA). The partial sequences obtained were identified by blasting in the non-redundant nucleotide database of National Center for Biotechnology Information (NCBI). The antimicrobial activities of characterized LAB against some tomato phytopathogenic bacteria which include (Xanthomonas campestries, Erwinia caratovora, and Pseudomonas syringae) were obtained by using the agar well diffusion method. Results: The partial sequences obtained were deposited in the database of National Centre for Biotechnology Information (NCBI). Isolates were identified based upon the sequences as Weissella cibaria (4, 18.18%), Weissella confusa (3, 13.64%), Leuconostoc paramensenteroides (1, 4.55%), Lactobacillus plantarum (8, 36.36%), Lactobacillus paraplantarum (1, 4.55%) and Lactobacillus pentosus (1, 4.55%). The cell free supernatants of LAB from fresh fruits origin (Weissella cibaria, Weissella confusa, Leuconostoc paramensenteroides, Lactobacillus plantarum, Lactobacillus paraplantarum and Lactobacillus pentosus) can inhibits these bacteria by creating clear zones of inhibition around the wells containing cell free supernatants of the above mentioned strains of lactic acid bacteria. Conclusion: This study shows that potentially LAB can be quickly characterized by molecular methods to specie level by nested PCR analysis of the bacteria isolate genomic DNA using universal 16S rRNA primers and LAB specific primer. Tomato disease causing organisms can be most likely biologically controlled by using extracts from LAB. This finding will reduce the potential hazard from the use of chemical herbicides on plant.

Keywords: nested pcr, molecular characterization, 16s rRNA gene, lactic acid bacteria

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Authors: Márcia Afonso, Cristina Fael, Marisa Dinis-Almeida

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Population growth in cities has led to an increase in the infrastructures construction, including buildings and roadways. This aspect leads directly to the soils waterproofing. In turn, changes in precipitation patterns are developing into higher and more frequent intensities. Thus, these two conjugated aspects decrease the rainwater infiltration into soils and increase the volume of surface runoff. The practice of green and sustainable urban solutions has encouraged research in these areas. The porous asphalt pavement, as a green infrastructure, is part of practical solutions set to address urban challenges related to land use and adaptation to climate change. In this field, permeable pavements with porous asphalt mixtures (PA) have several advantages in terms of reducing the runoff generated by the floods. The porous structure of these pavements, compared to a conventional asphalt pavement, allows the rainwater infiltration in the subsoil, and consequently, the water quality improvement. This green infrastructure solution can be applied in cities, particularly in streets or parking lots to mitigate the floods effects. Over the years, the pores of these pavements can be filled by sediment, reducing their function in the rainwater infiltration. Thus, double layer porous asphalt (DLPA) was developed to mitigate the clogging effect and facilitate the water infiltration into the lower layers. This study intends to deepen the knowledge of the performance of DLPA when subjected to clogging. The experimental methodology consisted on four evaluation phases of the DLPA infiltration capacity submitted to three precipitation events (100, 200 and 300 mm/h) in each phase. The evaluation first phase determined the behavior after DLPA construction. In phases two and three, two 500 g/m² clogging cycles were performed, totaling a 1000 g/m² final simulation. Sand with gradation accented in fine particles was used as clogging material. In the last phase, the DLPA was subjected to simple sweeping and vacuuming maintenance. A precipitation simulator, type sprinkler, capable of simulating the real precipitation was developed for this purpose. The main conclusions show that the DLPA has the capacity to drain the water, even after two clogging cycles. The infiltration results of flows lead to an efficient performance of the DPLA in the surface runoff attenuation, since this was not observed in any of the evaluation phases, even at intensities of 200 and 300 mm/h, simulating intense precipitation events. The infiltration capacity under clogging conditions decreased about 7% on average in the three intensities relative to the initial performance that is after construction. However, this was restored when subjected to simple maintenance, recovering the DLPA hydraulic functionality. In summary, the study proved the efficacy of using a DLPA when it retains thicker surface sediments and limits the fine sediments entry to the remaining layers. At the same time, it is guaranteed the rainwater infiltration and the surface runoff reduction and is therefore a viable solution to put into practice in permeable pavements.

Keywords: clogging, double layer porous asphalt, infiltration capacity, rainfall intensity

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Ejiobih Hyginus Chidozie

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Geographic Information System (GIS) is a configuration of computer hardware and software specifically designed to effectively capture, store, update, manipulate, analyse and display and display all forms of spatially referenced information. GIS database is referred to as the heart of GIS. It has location data, attribute data and spatial relationship between the objects and their attributes. Sewage and wastewater management have assumed increased importance lately as a result of general concern expressed worldwide about the problems of pollution of the environment contamination of the atmosphere, rivers, lakes, oceans and ground water. In this research GIS database was created to study the impacts of domestic wastewater disposal methods on Bida town, Niger State as a model for investigating similar impacts on other cities in Nigeria. Results from GIS database are very useful to decision makers and researchers. Bida Town was subdivided into four regions, eight zones, and 24 sectors based on the prevailing natural morphology of the town. GIS receiver and structured questionnaire were used to collect information and attribute data from 240 households of the study area. Domestic wastewater samples were collected from twenty four sectors of the study area for laboratory analysis. ArcView 3.2a GIS software, was used to create the GIS databases for ecological, health and socioeconomic impacts of domestic wastewater disposal methods in Bida town.

Keywords: environment, GIS, pollution, software, wastewater

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Authors: Rajasekar Elangopandian, Anand Shanmugam

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Now-a-days for surveillances unmanned aerial vehicle plays a vital role. Not only for surveillances, aerial photography disaster management and the notice of earth behavior UAV1s envisages meticulously. To reduce the maintenance and fuel nuclear powered Vehicles are greater support. The design consideration is much important for the UAV manufacturing industry and Research and development agency. Eventually design is looking like a pentagon shaped fuselage and black rubber coated paint in order to escape from the enemy radar and other targets. The pentagon shape fuselage has large space to keep the mini nuclear reactor inside and the material is carbon – carbon fiber specially designed by the software called cosmol and hyper mesh 14.2. So the weight consideration will produce the positive result for productivity. The walls of the fuselage are coated with lead and protective shield. A double layer of W/Bi sheet is proposed for radiation protection at the energy range of 70 Kev to 90 Kev. The designed W/bi sheet, only 0.14 mm thick and is 36% light. The properties of the fillers were determined from zeta potential and particle size measurements. The Exposes of the radiation can be attenuated by 3 ways such as minimizing exposure time, Maximizing distance from the radiation source and shielding the whole vehicle. The inside reactor will be switched ON when the UAV starts its cruise. The moderators and the control rods can be inserted by automation technique by newly developed software. The heat generated by the reactor will be used to run the turbine which is fixed inside the UAV called mini turbine with natural rubber composite Shaft radiation shield. Cooling system will be in two mode such as liquid and air cooled. Liquid coolant for the heat regeneration is ordinary water, liquid sodium, helium and the walls are made up of regenerative and radiation protective material. The other components like camera and arms bay will be located at the bottom of the UAV high are specially made products in order to escape from the radiation. They are coated with lead Pb and natural rubber composite material. This technique provides the long rang and endurance for eternal flight mission until we need any changeability of parts or product. This UAV has the special advantage of ` land on String` means it`ll land at electric line to charge the automated electronics. Then the fuel is enriched uranium (< 5% U - 235) contains hundreds of fuel pins. This technique provides eternal duty for surveillances and aerial photography. The landing of the vehicle is ease of operation likewise the takeoff is also easier than any other mechanism which present in nowadays. This UAV gives great immense and immaculate technology for surveillance and target detecting and smashing the target.

Keywords: mini turbine, liquid coolant for the heat regeneration, in order to escape from the radiation, eternal flight mission, it`ll land at electric line

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Timothy Gray

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This paper will present work and discuss lessons learned during a semester-long travel study based in Southeast Asia, which was run in the Spring Semester of 2019 and again in the summer of 2023. The first travel group consisted of fifteen students, and the second group consisted of twelve students ranging from second-year to graduate level, student participants majoring in either architecture or planning. Students worked in interdisciplinary teams, each team beginning their travel study, living together in a separate small town for over a month in (relatively) remote conditions in rural Thailand. Students became intimately familiar with these towns, forged strong personal relationships, and built reservoirs of knowledge one conversation at a time. Rather than impose external ideas and solutions, students were asked to learn from and be open to lessons from the people and the place. The following design statement was used as a point of departure for their investigations: It is our shared premise that architecture exists in small villages and towns of Southeast Asia in the ingenuity of the people, that architecture exists in a shared language of making, modifying, and reusing. It is a modest but vibrant architecture, an architecture that is alive and evolving, an architecture that is small in scale, accessible, and one that emerges from the people. It is an architecture that can exist in a modified bicycle, a woven bamboo bridge, or a self-built community. Students were challenged to engage in existing conditions as design professionals, both empowering and lending coherence to the energies that already existed in the place. As one of the student teams noted in their design narrative: “During our field study, we had the unique opportunity to tour a number of informal settlements and meet and talk to residents through interpreters. We found that many of the residents work in nearby factories for dollars a day. Others find employment in self-generated informal economies such as hand carving and textiles. Despite extreme poverty, we found these places to be vibrant and full of life as people navigate these challenging conditions to live lives with purpose and dignity.” Students worked together with local community members and colleagues to develop a series of varied proposals that emerged from their interrogations of place and partnered with community members and professional colleagues in the development of these proposals. Project partners included faculty and student colleagues Yangon University, the mayor's Office, Planning Department Officials and religious leaders in Sawankhalok, Thailand, and community leaders in Natonchan, Thailand, to name a few. This paper will present a series of student community-based design projects that emerged from these conditions. The paper will also discuss this model of travel study as a way of building an architecture which uses social and cultural issues as a catalyst for design. The paper will discuss lessons relative to sustainable development that the Western students learned through their travels in Southeast Asia.

Keywords: travel study, CAPasia, architecture of empowerment, modular housing

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Authors: C. Virgilio, J. Carlier, P. Campistron, M. Toubal, P. Garnier, L. Broussous, V. Thomy, B. Nongaillard

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Wetting efficiency of microstructures or nanostructures patterned on Si wafers is a real challenge in integrated circuits manufacturing. In fact, bad or non-uniform wetting during wet processes limits chemical reactions and can lead to non-complete etching or cleaning inside the patterns and device defectivity. This issue is more and more important with the transistors size shrinkage and concerns mainly high aspect ratio structures. Deep Trench Isolation (DTI) structures enabling pixels’ isolation in imaging devices are subject to this phenomenon. While low-frequency acoustic reflectometry principle is a well-known method for Non Destructive Test applications, we have recently shown that it is also well suited for nanostructures wetting characterization in a higher frequency range. In this paper, we present a high-frequency acoustic reflectometry characterization of DTI wetting through a confrontation of both experimental and modeling results. The acoustic method proposed is based on the evaluation of the reflection of a longitudinal acoustic wave generated by a 100 µm diameter ZnO piezoelectric transducer sputtered on the silicon wafer backside using MEMS technologies. The transducers have been fabricated to work at 5 GHz corresponding to a wavelength of 1.7 µm in silicon. The DTI studied structures, manufactured on the wafer frontside, are crossing trenches of 200 nm wide and 4 µm deep (aspect ratio of 20) etched into a Si wafer frontside. In that case, the acoustic signal reflection occurs at the bottom and at the top of the DTI enabling its characterization by monitoring the electrical reflection coefficient of the transducer. A Finite Difference Time Domain (FDTD) model has been developed to predict the behavior of the emitted wave. The model shows that the separation of the reflected echoes (top and bottom of the DTI) from different acoustic modes is possible at 5 Ghz. A good correspondence between experimental and theoretical signals is observed. The model enables the identification of the different acoustic modes. The evaluation of DTI wetting is then performed by focusing on the first reflected echo obtained through the reflection at Si bottom interface, where wetting efficiency is crucial. The reflection coefficient is measured with different water / ethanol mixtures (tunable surface tension) deposited on the wafer frontside. Two cases are studied: with and without PFTS hydrophobic treatment. In the untreated surface case, acoustic reflection coefficient values with water show that liquid imbibition is partial. In the treated surface case, the acoustic reflection is total with water (no liquid in DTI). The impalement of the liquid occurs for a specific surface tension but it is still partial for pure ethanol. DTI bottom shape and local pattern collapse of the trenches can explain these incomplete wetting phenomena. This high-frequency acoustic method sensitivity coupled with a FDTD propagative model thus enables the local determination of the wetting state of a liquid on real structures. Partial wetting states for non-hydrophobic surfaces or low surface tension liquids are then detectable with this method.

Keywords: wetting, acoustic reflectometry, gigahertz, semiconductor

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Authors: Evridiki Papachristou, Nikolaos Bilalis

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Imagine an apparel industry where fashion design does not begin with a paper-and-pen drawing which is then translated into pattern and later to a 3D model where the designer tries out different fabrics, colours and contrasts. Instead, imagine a fashion designer in the future who produces that initial fashion drawing in a three-dimensional space and won’t leave that environment until the product is done, communicating his/her ideas with the entire development team in true to life 3D. Three-dimensional (3D) technology - while well established in many other industrial sectors like automotive, aerospace, architecture and industrial design, has only just started to open up a whole range of new opportunities for apparel designers. The paper will discuss the process of 3D simulation technology enhanced by high quality visualization of data and its capability to ensure a massive competitiveness in the market. Secondly, it will underline the most frequent problems & challenges that occur in the process chain when various partners in the production of textiles and apparel are working together. Finally, it will offer a perspective of how the Virtual Prototyping Technology will make the global textile and apparel industry change to a level where designs will be visualized on a computer and various scenarios modeled without even having to produce a physical prototype. This state-of-the-art 3D technology has been described as transformative and“disruptive”comparing to the process of the way apparel companies develop their fashion products today. It provides the benefit of virtual sampling not only for quick testing of design ideas, but also reducing process steps and having more visibility.A so called“digital asset” that can be used for other purposes such as merchandising or marketing.

Keywords: 3D visualization, apparel, virtual prototyping, prototyping technology

Procedia PDF Downloads 581

Authors: G. Cunningham, E. Cantor, X. Wu, F. Shen, G. Jiang, S. Philips, C. Bales, Y. Xiao, T. R. Cummins, J. C. Fehrenbacher, B. P. Schneider

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Background: Taxane-induced peripheral neuropathy (TIPN) is the most devastating survivorship issue for patients receiving therapy. Dose reductions due to TIPN in the curative setting lead to inferior outcomes for African American patients, as prior research has shown that this group is more susceptible to developing severe neuropathy. The mechanistic underpinnings of TIPN, however, have not been entirely elucidated. While it would be appealing to use primary tissue to study the development of TIPN, procuring nerves from patients is not realistically feasible, as nerve biopsies are painful and may result in permanent damage. Therefore, our laboratory has investigated paclitaxel-induced neuronal morphological and molecular changes using an ex vivo model of human-induced pluripotent stem cell (iPSC)-derived neurons. Methods: iPSCs are undifferentiated and endlessly dividing cells that can be generated from a patient’s somatic cells, such as peripheral blood mononuclear cells (PBMCs). We successfully reprogrammed PBMCs into iPSCs using the Erythroid Progenitor Reprograming Kit (STEMCell Technologiesᵀᴹ); pluripotency was verified by flow cytometry analysis. iPSCs were then induced into neurons using a differentiation protocol that bypasses the neural progenitor stage and uses selected small-molecule modulators of key signaling pathways (SMAD, Notch, FGFR1 inhibition, and Wnt activation). Results: Flow cytometry analysis revealed expression of core pluripotency transcription factors Nanog, Oct3/4 and Sox2 in iPSCs overlaps with commercially purchased pluripotent cell line UCSD064i-20-2. Trilineage differentiation of iPSCs was confirmed with immunofluorescent imaging with germ-layer-specific markers; Sox17 and ExoA2 for ectoderm, Nestin, and Pax6 for mesoderm, and Ncam and Brachyury for endoderm. Sensory neuron markers, β-III tubulin, and Peripherin were applied to stain the cells for the maturity of iPSC-derived neurons. Patch-clamp electrophysiology and calcitonin gene-related peptide (CGRP) release data supported the functionality of the induced neurons and provided insight into the timing for which downstream assays could be performed (week 4 post-induction). We have also performed a cell viability assay and fluorescence-activated cell sorting (FACS) using four cell-surface markers (CD184, CD44, CD15, and CD24) to select a neuronal population. At least 70% of the cells were viable in the isolated neuron population. Conclusion: We have found that these iPSC-derived neurons recapitulate mature neuronal phenotypes and demonstrate functionality. Thus, this represents a patient-derived ex vivo neuronal model to investigate the molecular mechanisms of clinical TIPN.

Keywords: chemotherapy, iPSC-derived neurons, peripheral neuropathy, taxane, paclitaxel

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Authors: Duncan Wallace, M-Tahar Kechadi

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In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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Authors: Derya Duran, Christine Jacknick

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This study explores post-task reflections in an English as a Medium of Instruction (EMI) setting, and it specifically focuses on how a teacher performs pedagogical practices such as reformulating, extending and evaluating following students’ spontaneous experience tellings in EMI classrooms. The data consist of 30 hours of video recordings from two EMI content classes, which were recorded for an academic term at a university in Turkey. The course, Guidance, is offered to fourth year undergraduate students as a compulsory course in the Department of Educational Sciences. The participants (n=78) study at the Faculty of Education, majoring in different educational departments (i.e., Computer Education and Instructional Technology, Elementary Education, Foreign Language Education). Using conversation analysis, we demonstrate that the teacher employs a variety of interactional resources to elicit (i.e., asking specific questions) and also provides (i.e., giving scientific information) as much content as possible, which also sheds light on the institutional fingerprints of the current research context. The study contributes to the existing research by unpacking articulation of personal experiences and cultivation of collaborativeness in classroom interaction. Moreover, describing the dialogic nature of these specific occasions, the study demonstrates how teacher and students address learning tasks together (collectivity), how they orient to each other turns interactionally (reciprocity), and how they keep the pedagogical focus in mind (purposefulness).

Keywords: conversation analysis, English as a medium of instruction, higher education, post-task reflections

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Authors: A. Chávez, A. Rodríguez, F. Pinzón

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Society is concerned about measures of environmental, economic and social impacts generated in the solid waste disposal. These places of confinement, also known as landfills, are locations where problems of pollution and damage to human health are reduced. They are technically designed and operated, using engineering principles, storing the residue in a small area, compact it to reduce volume and covering them with soil layers. Problems preventing liquid (leachate) and gases produced by the decomposition of organic matter. Despite planning and site selection for disposal, monitoring and control of selected processes, remains the dilemma of the leachate as extreme concentration of pollutants, devastating soil, flora and fauna; aggressive processes requiring priority attention. A biological technology is the activated sludge system, used for tributaries with high pollutant loads. Since transforms biodegradable dissolved and particulate matter into CO2, H2O and sludge; transform suspended and no Settleable solids; change nutrients as nitrogen and phosphorous; and degrades heavy metals. The microorganisms that remove organic matter in the processes are in generally facultative heterotrophic bacteria, forming heterogeneous populations. Is possible to find unicellular fungi, algae, protozoa and rotifers, that process the organic carbon source and oxygen, as well as the nitrogen and phosphorus because are vital for cell synthesis. The mixture of the substrate, in this case sludge leachate, molasses and wastewater is maintained ventilated by mechanical aeration diffusers. Considering as the biological processes work to remove dissolved material (< 45 microns), generating biomass, easily obtained by decantation processes. The design consists of an artificial support and aeration pumps, favoring develop microorganisms (denitrifying) using oxygen (O) with nitrate, resulting in nitrogen (N) in the gas phase. Thus, avoiding negative effects of the presence of ammonia or phosphorus. Overall the activated sludge system includes about 8 hours of hydraulic retention time, which does not prevent the demand for nitrification, which occurs on average in a value of MLSS 3,000 mg/L. The extended aeration works with times greater than 24 hours detention; with ratio of organic load/biomass inventory under 0.1; and average stay time (sludge age) more than 8 days. This project developed a pilot system with sludge leachate from Doña Juana landfill - RSDJ –, located in Bogota, Colombia, where they will be subjected to a process of activated sludge and extended aeration through a sequential Bach reactor - SBR, to be dump in hydric sources, avoiding ecological collapse. The system worked with a dwell time of 8 days, 30 L capacity, mainly by removing values of BOD and COD above 90%, with initial data of 1720 mg/L and 6500 mg/L respectively. Motivating the deliberate nitrification is expected to be possible commercial use diffused aeration systems for sludge leachate from landfills.

Keywords: sludge, landfill, leachate, SBR

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Authors: Vivien Chee Pei Wei

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Today we live in a scenario in which letters share space with images on screens that vary in size, shape, and style. The popularization of television, then the computer and now the e-readers, tablets, and smartphones made the electronic assume the role that previously was restricted to printed materials. Since the extensive use of new technologies to produce, disseminate, collect and access electronic publications began, the changes to reading has been intensified. To be able to read online, it involves more than just utilizing specific skills, strategies, and practices, but also in negotiating multiple information sources. In this study, different perspectives of digital reading are being explored in order to define the key aspects of the term. The focus is to explore how new technologies affect how undergraduates’ reading behavior, which in turn, gives readers different reading levels and engagement with the text and other support materials in the same media. There is also the importance of the relationship between reading platforms, reading levels and formats of electronic publications. The study looks at the online reading practices of about 100 undergraduates from a local university. The data collected using the survey and interviews with the respondents are analyzed thematically. Findings from this study found that both digital and traditional reading are interrelated, and should not be viewed as separate, but complementary to each other. However, reading online complicates some of the skills required by traditional reading. Consequently, in order to successfully read and comprehend multiple sources of information online, undergraduates need regular opportunities to practice and develop their skills as part of their natural reading practices.

Keywords: concepts, digital reading, literacy, traditional reading

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Authors: Michael G. Pantelyat

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Fundamental basics of pure and applied research in the area of magneto-thermo-mechanical numerical analysis and design of innovative electromagnetic devices (modern induction heaters, novel thermoelastic actuators, rotating electrical machines, induction cookers, electrophysical devices) are elaborated. Thus, mathematical models of magneto-thermo-mechanical processes in electromagnetic devices taking into account main interactions of interrelated phenomena are developed. In addition, graphical representation of coupled (multiphysics) phenomena under consideration is proposed. Besides, numerical techniques for nonlinear problems solution are developed. On this base, effective numerical algorithms for solution of actual problems of practical interest are proposed, validated and implemented in applied 2D and 3D computer codes developed. Many applied problems of practical interest regarding modern electrical engineering devices are numerically solved. Investigations of the influences of various interrelated physical phenomena (temperature dependences of material properties, thermal radiation, conditions of convective heat transfer, contact phenomena, etc.) on the accuracy of the electromagnetic, thermal and structural analyses are conducted. Important practical recommendations on the choice of rational structures, materials and operation modes of electromagnetic devices under consideration are proposed and implemented in industry.

Keywords: electromagnetic devices, multiphysics, numerical analysis, simulation and design

Procedia PDF Downloads 380