Search results for: convolution conditions
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9660

Search results for: convolution conditions

9540 Malaria Parasite Detection Using Deep Learning Methods

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: convolution neural network, deep learning, malaria, thin blood smears

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9539 The Optimum Operating Conditions for the Synthesis of Zeolite from Waste Incineration Fly Ash by Alkali Fusion and Hydrothermal Methods

Authors: Yi-Jie Lin, Jyh-Cherng Chen

Abstract:

The fly ash of waste incineration processes is usually hazardous and the disposal or reuse of waste incineration fly ash is difficult. In this study, the waste incineration fly ash was converted to useful zeolites by the alkali fusion and hydrothermal synthesis method. The influence of different operating conditions (the ratio of Si/Al, the ratio of hydrolysis liquid to solid, and hydrothermal time) was investigated to seek the optimum operating conditions for the synthesis of zeolite from waste incineration fly ash. The results showed that concentrations of heavy metals in the leachate of Toxicity Characteristic Leaching Procedure (TCLP) were all lower than the regulatory limits except lead. The optimum operating conditions for the synthesis of zeolite from waste incineration fly ash by the alkali fusion and hydrothermal synthesis method were Si/Al=40, NaOH/ash=1.5, alkali fusion at 400 oC for 40 min, hydrolysis with Liquid to Solid ratio (L/S)= 200 at 105 oC for 24 h, and hydrothermal synthesis at 105 oC for 24 h. The specific surface area of fly ash could be significantly increased from 8.59 m2/g to 651.51 m2/g (synthesized zeolite). The influence of different operating conditions on the synthesis of zeolite from waste incineration fly ash followed the sequence of Si/Al ratio > hydrothermal time > hydrolysis L/S ratio. The synthesized zeolites can be reused as good adsorbents to control the air or wastewater pollutants. The purpose of fly ash detoxification, reduction and waste recycling/reuse is achieved successfully.

Keywords: alkali fusion, hydrothermal, fly ash, zeolite

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9538 Experimental Investigation of Cup Anemometer under Static and Dynamic Wind Direction Changes: Evaluation of Directional Sensitivity

Authors: Vaibhav Rana, Nicholas Balaresque

Abstract:

The 3-cup anemometer is the most commonly used instrument for wind speed measurement and, consequently, for the wind resource assessment. Though the cup anemometer shows accurate measurement under quasi-static conditions, there is uncertainty in the measurement when subjected to field measurement. Sensitivity to the angle of attacks with respect to horizontal plane, dynamic response, and non-linear behavior in calibration due to friction. The presented work aimed to identify the sensitivity of anemometer to non-horizontal flow. The cup anemometer was investigated under low wind speed wind tunnel, first under the static flow direction changes and second under the dynamic direction changes, at a different angle of attacks, under the similar conditions of reference wind tunnel speeds. The cup anemometer response under both conditions was evaluated and compared. The results showed the anemometer under dynamic wind direction changes is highly sensitive compared to static conditions.

Keywords: wind energy, cup anemometer, directional sensitivity, dynamic behavior, wind tunnel

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9537 The Impact of Type Two Diabetes and Comorbid Conditions on Self-Identity and Self-Management Practices

Authors: Virginia Maskill, Philippa Seaton, Marie Crowe, Maree Inder

Abstract:

A diagnosis of a chronic condition, including Type 2 diabetes can significantly impact an individual’s self-identity which in turn can have considerable implications on how they adapt to, and self-manage their condition. This paper reports on the findings from a qualitative PhD study of forty participants diagnosed with Type 2 diabetes mellitus and comorbid conditions. The primary objective of the study explored the impact conditions had on self-identity and the relationship with self-management practices. Participants were recruited from a larger study which explored the effectiveness of a therapeutic intervention on glycemic control. Interviews were audio-recorded, transcribed verbatim and analysed utilising a narrative thematic analysis methodological approach including a transitional conceptual framework. The majority of participants experienced a loss of their normal self and struggled to integrate diabetes and comorbid conditions into their self-identity. Acceptance, knowledge and integration of conditions were often found to directly influence self-management practices with individuals commonly experiencing four transitional phases from the onset of diagnosis. Successful negotiation of these four phases was influenced by a range of variables which also impacted on an individual’s self-identity and in turn their self-management practices.

Keywords: comorbidity, type two diabetes, self-identity, self-management

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9536 Developing an Accurate AI Algorithm for Histopathologic Cancer Detection

Authors: Leah Ning

Abstract:

This paper discusses the development of a machine learning algorithm that accurately detects metastatic breast cancer (cancer has spread elsewhere from its origin part) in selected images that come from pathology scans of lymph node sections. Being able to develop an accurate artificial intelligence (AI) algorithm would help significantly in breast cancer diagnosis since manual examination of lymph node scans is both tedious and oftentimes highly subjective. The usage of AI in the diagnosis process provides a much more straightforward, reliable, and efficient method for medical professionals and would enable faster diagnosis and, therefore, more immediate treatment. The overall approach used was to train a convolution neural network (CNN) based on a set of pathology scan data and use the trained model to binarily classify if a new scan were benign or malignant, outputting a 0 or a 1, respectively. The final model’s prediction accuracy is very high, with 100% for the train set and over 70% for the test set. Being able to have such high accuracy using an AI model is monumental in regard to medical pathology and cancer detection. Having AI as a new tool capable of quick detection will significantly help medical professionals and patients suffering from cancer.

Keywords: breast cancer detection, AI, machine learning, algorithm

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9535 Step Height Calibration Using Hamming Window: Band-Pass Filter

Authors: Dahi Ghareab Abdelsalam Ibrahim

Abstract:

Calibration of step heights with high accuracy is needed for many applications in the industry. In general, step height consists of three bands: pass band, transition band (roll-off), and stop band. Abdelsalam used a convolution of the transfer functions of both Chebyshev type 2 and elliptic filters with WFF of the Fresnel transform in the frequency domain for producing a steeper roll-off with the removal of ripples in the pass band- and stop-bands. In this paper, we used a new method based on the Hamming window: band-pass filter for calibration of step heights in terms of perfect adjustment of pass-band, roll-off, and stop-band. The method is applied to calibrate a nominal step height of 40 cm. The step height is measured first by asynchronous dual-wavelength phase-shift interferometry. The measured step height is then calibrated by the simulation of the Hamming window: band-pass filter. The spectrum of the simulated band-pass filter is simulated at N = 881 and f0 = 0.24. We can conclude that the proposed method can calibrate any step height by adjusting only two factors which are N and f0.

Keywords: optical metrology, step heights, hamming window, band-pass filter

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9534 Vehicle Detection and Tracking Using Deep Learning Techniques in Surveillance Image

Authors: Abe D. Desta

Abstract:

This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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9533 Critical Buckling Load of Carbon Nanotube with Non-Local Timoshenko Beam Using the Differential Transform Method

Authors: Tayeb Bensattalah, Mohamed Zidour, Mohamed Ait Amar Meziane, Tahar Hassaine Daouadji, Abdelouahed Tounsi

Abstract:

In this paper, the Differential Transform Method (DTM) is employed to predict and to analysis the non-local critical buckling loads of carbon nanotubes with various end conditions and the non-local Timoshenko beam described by single differential equation. The equation differential of buckling of the nanobeams is derived via a non-local theory and the solution for non-local critical buckling loads is finding by the DTM. The DTM is introduced briefly. It can easily be applied to linear or nonlinear problems and it reduces the size of computational work. Influence of boundary conditions, the chirality of carbon nanotube and aspect ratio on non-local critical buckling loads are studied and discussed. Effects of nonlocal parameter, ratios L/d, the chirality of single-walled carbon nanotube, as well as the boundary conditions on buckling of CNT are investigated.

Keywords: boundary conditions, buckling, non-local, differential transform method

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9532 Spatiotemporal Neural Network for Video-Based Pose Estimation

Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

Abstract:

Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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9531 Cold Spray Fabrication of Coating for Highly Corrosive Environment

Authors: Harminder Singh

Abstract:

Cold spray is a novel and emerging technology for the fabrication of coating. In this study, coating is successfully developed by this process on superalloy surface. The selected coating composition is already proved as corrosion resistant. The microstructure of the newly developed coating is examined by various characterization techniques, for testing its suitability for high temperature corrosive conditions of waste incinerator. The energy producing waste incinerators are still running at low efficiency, mainly due to their chlorine based highly corrosive conditions. The characterization results show that the developed cold sprayed coating structure is suitable for its further testing in highly aggressive conditions.

Keywords: coating, cold spray, corrosion, microstructure

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9530 Detection of Chaos in General Parametric Model of Infectious Disease

Authors: Javad Khaligh, Aghileh Heydari, Ali Akbar Heydari

Abstract:

Mathematical epidemiological models for the spread of disease through a population are used to predict the prevalence of a disease or to study the impacts of treatment or prevention measures. Initial conditions for these models are measured from statistical data collected from a population since these initial conditions can never be exact, the presence of chaos in mathematical models has serious implications for the accuracy of the models as well as how epidemiologists interpret their findings. This paper confirms the chaotic behavior of a model for dengue fever and SI by investigating sensitive dependence, bifurcation, and 0-1 test under a variety of initial conditions.

Keywords: epidemiological models, SEIR disease model, bifurcation, chaotic behavior, 0-1 test

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9529 The Priming Effect of Morphology, Phonology, Semantics, and Orthography in Mandarin Chinese: A Prime Paradigm Study

Authors: Bingqing Xu, Wenxing Shuai

Abstract:

This study investigates the priming effects of different Chinese compound words by native Mandarin speakers. There are lots of homonym, polysemy, and synonym in Chinese. However, it is unclear which kind of words have the biggest priming effect. Native Mandarin speakers were tested in a visual-word lexical decision experiment. The stimuli, which are all two-character compound words, consisted of two parts: primes and targets. Five types of relationships were used in all stimuli: morphologically related condition, in which the prime and the target contain the same morpheme; orthographically related condition, in which the target and the prime contain the different morpheme with the same form; phonologically related condition, in which the target and the prime contain the different morpheme with the same phonology; semantically related condition, in which the target and the prime contain the different morpheme with similar meanings; totally unrelated condition. The time since participants saw the target to respond was recorded. Analyses on reaction time showed that the average reaction time of morphologically related targets was much shorter than others, suggesting the morphological priming effect is the biggest. However, the reaction time of the phonologically related conditions was the longest, even longer than unrelated conditions. According to scatter plots analyses, 86.7% of participants had priming effects in morphologically related conditions, only 20% of participants had priming effects in phonologically related conditions. These results suggested that morphologically related conditions had the biggest priming effect. The orthographically and semantically related conditions also had priming effects, whereas the phonologically related conditions had few priming effects.

Keywords: priming effect, morphology, phonology, semantics, orthography

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9528 Investigation of Thermal Comfort Conditions of Vernacular Buildings Taking into Consideration Various Use Patterns: A Case Study

Authors: Christina Kalogirou

Abstract:

The main goal of this paper is to explore the thermal comfort conditions in traditional buildings during all seasons of the year taking into consideration various use patterns. For this purpose a dwelling of vernacular architecture is selected and data regarding the indoor and outdoor air and surface temperature as well as the relative humidity are collected. These measurements are conducted in situ during the period of a year. Also, this building is occupied periodically and a calendar of occupancy was kept (duration of residence, hours of heating system operation, hours of natural ventilation, etc.) in order to correlate the indoor conditions recorded with the use patterns via statistical analysis. Furthermore, the effect of the high thermal inertia of the stone masonry walls and the different orientation of the rooms is addressed. Thus, this paper concludes in some interesting results on the effect of the users in the indoor climate conditions in the case of buildings with high thermal inertia envelops.

Keywords: thermal comfort, in situ measurements, occupant behaviour, vernacular architecture

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9527 Adverse Curing Conditions and Performance of Concrete: Bangladesh Perspective

Authors: T. Manzur

Abstract:

Concrete is the predominant construction material in Bangladesh. In large projects, stringent quality control procedures are usually followed under the supervision of experienced engineers and skilled labors. However, in the case of small projects and particularly at distant locations from major cities, proper quality control is often an issue. It has been found from experience that such quality related issues mainly arise from inappropriate proportioning of concrete mixes and improper curing conditions. In most cases external curing method is followed which requires supply of adequate quantity of water along with proper protection against evaporation. Often these conditions are found missing in the general construction sites and eventually lead to production of weaker concrete both in terms of strength and durability. In this study, an attempt has been made to investigate the performance of general concreting works of the country when subjected to several adverse curing conditions that are quite common in various small to medium construction sites. A total of six different types of adverse curing conditions were simulated in the laboratory and samples were kept under those conditions for several days. A set of samples was also submerged in normal curing condition having proper supply of curing water. Performance of concrete was evaluated in terms of compressive strength, tensile strength, chloride permeability and drying shrinkage. About 37% and 25% reduction in 28-day compressive and tensile strength were observed respectively, for samples subjected to most adverse curing condition as compared to the samples under normal curing conditions. Normal curing concrete exhibited moderate permeability (close to low permeability) whereas concrete under adverse curing conditions showed very high permeability values. Similar results were also obtained for shrinkage tests. This study, thus, will assist concerned engineers and supervisors to understand the importance of quality assurance during the curing period of concrete.

Keywords: adverse, concrete, curing, compressive strength, drying shrinkage, permeability, tensile strength

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9526 Effects of Local Ground Conditions on Site Response Analysis Results in Hungary

Authors: Orsolya Kegyes-Brassai, Zsolt Szilvágyi, Ákos Wolf, Richard P. Ray

Abstract:

Local ground conditions have a substantial influence on the seismic response of structures. Their inclusion in seismic hazard assessment and structural design can be realized at different levels of sophistication. However, response results based on more advanced calculation methods e.g. nonlinear or equivalent linear site analysis tend to show significant discrepancies when compared to simpler approaches. This project's main objective was to compare results from several 1-D response programs to Eurocode 8 design spectra. Data from in-situ site investigations were used for assessing local ground conditions at several locations in Hungary. After discussion of the in-situ measurements and calculation methods used, a comprehensive evaluation of all major contributing factors for site response is given. While the Eurocode spectra should account for local ground conditions based on soil classification, there is a wide variation in peak ground acceleration determined from 1-D analyses versus Eurocode. Results show that current Eurocode 8 design spectra may not be conservative enough to account for local ground conditions typical for Hungary.

Keywords: 1-D site response analysis, multichannel analysis of surface waves (MASW), seismic CPT, seismic hazard assessment

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9525 Recognition of Gene Names from Gene Pathway Figures Using Siamese Network

Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

Abstract:

The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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9524 Optimal Reactive Power Dispatch under Various Contingency Conditions Using Whale Optimization Algorithm

Authors: Khaled Ben Oualid Medani, Samir Sayah

Abstract:

The Optimal Reactive Power Dispatch (ORPD) problem has been solved and analysed usually in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, power system analysis, real power loss minimization, contingency condition, metaheuristic technique, whale optimization algorithm

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9523 Butene Catalytic Cracking to Propylene over Iron and Phosphorus Modified HZSM-5

Authors: Jianwen Li, Hongfang Ma, Haitao Zhang, Qiwen Sun, Weiyong Ying

Abstract:

HZSM-5 zeolites modified by iron and phosphorus were applied in catalytic cracking of butene. N2 adsorption and NH3-TPD were employed to measure the structure and acidity of catalysts. The results indicate that increasing phosphorus loading decreased surface area, pore volume and strong acidity of catalysts. The introduction of phosphorus significantly decreased butene conversion and promoted propylene selectivity. The catalytic performance of catalyst was strongly dependent on the reaction conditions. Appropriate reaction conditions could suppress side reactions and enhance propylene selectivity.

Keywords: butene catalytic cracking, HZSM-5, modification, reaction conditions

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9522 Emergency Condition Discrimination for Single People Using a CO2 Sensor and Body Detectors

Authors: Taiyo Matsumura, Kota Funabashi, Nobumichi Sakai, Takashi Ono

Abstract:

The purpose of this research is to construct a watching system that monitors human activity in a room and detects abnormalities at an early stage to prevent unattended deaths of people living alone. In this article, we propose a method whereby highly urgent abnormal conditions of a person are determined by changes in the concentration of CO2 generated from activity and respiration in a room. We also discussed the effects the amount of activity has on the determination. The results showed that this discrimination method is not dependent on the amount of activity and is effective in judging highly urgent abnormal conditions.

Keywords: abnormal conditions, multiple sensors, people living alone, respiratory arrest, unattended death, watching system

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9521 Measurement of Liquid Film Thickness in a Vertical Annular Two Phase Flow Changing the Gas-Liquid Density Ratio

Authors: Shoji Mori, Kunito Okuyama

Abstract:

Annular two phase flow is encountered in many industrial equipments, including flow near nuclear fuel rods in boiling water reactor (BWR). Especially, disturbance waves play important roles in the pressure drop, the generation of entrainments, and the dryout of the liquid film. Therefore, it is important to clarify the behavior of disturbance waves and base film. However, most of the previous studies have been performed under atmospheric pressure conditions that provides the properties of liquid and gas which are significantly different from those of a BWR. Therefore, the effect of properties in gas and liquid on liquid film characteristics should be clarified. In this paper we focus on the effect of gas-liquid density ratio on liquid film thickness characteristics. The experiments have been conducted at four density ratio conditions (ρL/ρG =763, 451, 231, and 31). As a result, it is found that and interfacial shear stress collapse not only tF ave but also tF max and tF min successfully under the same liquid mass flow rate conditions irrespective of ρL/ρG, and moreover a non-dimensional parameter tends to collapse tF max,tF ave,and tF min in the wide range of experimental conditions (ρL/ρG:31~763,We:10~1800,ReL:500 ~ 2200).

Keywords: two phase flow, liquid film, annular flow, disturbance wave

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9520 Experimental Study on the Effect of Storage Conditions on Thermal Hazard of Nitrocellulose

Authors: Hua Chai, Qiangling Duan, Huiqi Cao, Mi Li, Jinhua Sun

Abstract:

Nitrocellulose (NC), a kind of energetic material, has been widely used in the industrial and military fields. However, this material can also cause serious social disasters due to storage conditions. Thermal hazard of nitrocellulose (NC) was experimentally investigated using the CALVET heat flux calorimeter C80, and three kinds of storage conditions were considered in the experiments: (1) drying time, (2) moisture content, (3) cycles. The results showed that the heat flow curves of NC moved to the low-temperature direction firstly and then slightly moved back by increasing the drying hours. Moisture that was responsible for the appearance of small exothermic peaks was proven to be the unfavorable safety factor yet it could increase the onset temperature of the main peak to some extent. And cycles could both lower the onset temperature and the maximum heat flow but enlarged the peak temperature. Besides, relevant kinetic parameters such as the heat of reaction (ΔH) and the activation energy (Ea) were obtained and compared. It was found that all the three conditions could reduce the values of Ea and most of them produced larger reaction heat. In addition, the critical explosion temperature (Tb) of the NC samples were derived. It was clear that not only the drying time but also the cycles would increase the thermal hazard of the NC. Yet, the right amount of water helped to reduce the thermal hazard.

Keywords: C80, nitrocellulose, storage conditions, the critical explosion temperature, thermal hazard

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9519 Theory and Practice of Wavelets in Signal Processing

Authors: Jalal Karam

Abstract:

The methods of Fourier, Laplace, and Wavelet Transforms provide transfer functions and relationships between the input and the output signals in linear time invariant systems. This paper shows the equivalence among these three methods and in each case presenting an application of the appropriate (Fourier, Laplace or Wavelet) to the convolution theorem. In addition, it is shown that the same holds for a direct integration method. The Biorthogonal wavelets Bior3.5 and Bior3.9 are examined and the zeros distribution of their polynomials associated filters are located. This paper also presents the significance of utilizing wavelets as effective tools in processing speech signals for common multimedia applications in general, and for recognition and compression in particular. Theoretically and practically, wavelets have proved to be effective and competitive. The practical use of the Continuous Wavelet Transform (CWT) in processing and analysis of speech is then presented along with explanations of how the human ear can be thought of as a natural wavelet transformer of speech. This generates a variety of approaches for applying the (CWT) to many paradigms analysing speech, sound and music. For perception, the flexibility of implementation of this transform allows the construction of numerous scales and we include two of them. Results for speech recognition and speech compression are then included.

Keywords: continuous wavelet transform, biorthogonal wavelets, speech perception, recognition and compression

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9518 Estimation of Probabilistic Fatigue Crack Propagation Models of AZ31 Magnesium Alloys under Various Load Ratio Conditions by Using the Interpolation of a Random Variable

Authors: Seon Soon Choi

Abstract:

The essential purpose is to present the good fatigue crack propagation model describing a stochastic fatigue crack growth behavior in a rolled magnesium alloy, AZ31, under various load ratio conditions. Fatigue crack propagation experiments were carried out in laboratory air under four conditions of load ratio, R, using AZ31 to investigate the crack growth behavior. The stochastic fatigue crack growth behavior was analyzed using an interpolation of random variable, Z, introduced to an empirical fatigue crack propagation model. The empirical fatigue models used in this study are Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was found that the random variable is useful in describing the stochastic fatigue crack growth behaviors under various load ratio conditions. The good probabilistic model describing a stochastic fatigue crack growth behavior under various load ratio conditions was also proposed.

Keywords: magnesium alloys, fatigue crack propagation model, load ratio, interpolation of random variable

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9517 Experimental Chevreul’s Salt Production Methods on Copper Recovery

Authors: Turan Çalban, Oral Laçin, Abdüsselam Kurtbaş

Abstract:

The experimental production methods Chevreul’s salt being a intermediate stage product for copper recovery were investigated by dealing with the articles written on this topic. Chevreul’s salt, Cu2SO3.CuSO3.2H2O, being a mixed valence copper sulphite compound has been obtained by using different methods and reagents. Chevreul’s salt has a intense brick-red color. It is a highly stable and expensive salt. The production of Chevreul’s salt plays a key role in hiydrometallurgy. In recent years, researchs on this compound have been intensified. Silva et al. reported that this salt is thermally stable up to 200oC. Çolak et al. precipitated the Chevreul’s salt by using ammonia and sulphur dioxide. Çalban et al. obtained at the optimum conditions by passing SO2 from leach solutions with NH3-(NH4)2SO4. Yeşiryurt and Çalban investigated the optimum precipitation conditions of Chevreul’s salt from synthetic CuSO4 solutions including Na2SO3. Çalban et al. achieved the precipitation of Chevreul’s salt at the optimum conditions by passing SO2 from synthetic CuSO4 solutions. Çalban et al. examined the precipitation conditions of Chevreul’s salt using (NH4)2SO3 from synthetic aqueous CuSO4 solutions. In light of these studies, it can be said that Chevreul’s salt can be produced practically from both a leach solutions including copper and synthetic CuSO4 solutions.

Keywords: Chevreul’s salt, ammonia, copper sulpfite, sodium sülfite, optimum conditions

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9516 The Prototype of the Solar Energy Utilization for the Finding Sustainable Conditions in the Future: The Solar Community with 4000 Dwellers 960 Families, equal to 480 Solar Dwelling Houses and 32 Mansion Buildings (480 Dwellers)

Authors: Kunihisa Kakumoto

Abstract:

This technical paper is for the prototype of solar energy utilization for finding sustainable conditions. This model has been simulated under the climate conditions in Japan. At the beginning of the study, the solar model house was built up on site. And the concerned data was collected in this model house for several years. On the basis of these collected data, the concept on the solar community was built up. For the finding sustainable conditions, the amount of the solar energy generation and its reduction of carbon dioxide and the reduction of carbon dioxide by the green planting and the amount of carbon dioxide according to the normal daily life in the solar community and the amount of the necessary water for the daily life in the solar community and the amount of the water supply by the rainfall on-site were calculated. These all values were taken into consideration. The relations between each calculated result are shown in the expression of inequality. This solar community and its consideration for finding sustainable conditions can be one prototype to do the feasibility study for our life in the future

Keywords: carbon dioxide, green planting, smart city, solar community, sustainable condition, water activity

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9515 Renewed Urban Waterfront: Spatial Conditions of a Contemporary Urban Space Typology

Authors: Beate Niemann, Fabian Pramel

Abstract:

The formerly industrially or militarily used Urban Waterfront is a potential area for urban development. Extensive interventions in the urban space come along with the development of these previously inaccessible areas in the city. The development of the Urban Waterfront in the European City is not subject to any recognizable urban paradigm. In this study, the development of the Urban Waterfront as a new urban space typology is analyzed by case studies of Urban Waterfront developments in European Cities. For humans, perceptible spatial conditions are categorized and it is identified whether the themed Urban Waterfront Developments are congruent or incongruent urban design interventions and which deviations the Urban Waterfront itself induce. As congruent urban design, a design is understood, which fits in the urban fabric regarding its similar spatial conditions to the surrounding. Incongruent urban design, however, shows significantly different conditions in its shape. Finally, the spatial relationship of the themed Urban Waterfront developments and their associated environment are compared in order to identify contrasts between new and old urban space. In this way, conclusions about urban design paradigms of the new urban space typology are tried to be drawn.

Keywords: composition, congruence, identity, paradigm, spatial condition, urban design, urban development, urban waterfront

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9514 Optimising Light Conditions for Recombinant Protein Production in the Microalgal Chlamydomonas reinhardtii Chloroplast

Authors: Saskya E. Carrera P., Ben Hankamer, Melanie Oey

Abstract:

The green alga C. reinhardtii provides a platform for the cheap, scalable, and safe production of complex proteins. Despite gene expression in photosynthetic organisms being tightly regulated by light, most expression studies have analysed chloroplast recombinant protein production under constant light. Here the influence of illumination time and intensity on GFP and a GFP-PlyGBS (bacterial-lysin) fusion protein expression was investigated. The expression of both proteins was strongly influenced by the light regime (6-24 hr illumination per day), the light intensity (0-450 E m⁻²s⁻¹) and growth condition (photoautotrophic, mixotrophic and heterotrophic). Heterotrophic conditions resulted in relatively low recombinant protein yields per unit volume, despite high protein yields per cell, due to low growth rates. Mixotrophic conditions exhibited the highest yields at 6 hrs illumination at 200µE m⁻²s⁻¹ and under continuous low light illumination (13-16 mg L⁻¹ GFP and 1.2-1.6 mg L⁻¹ GFP-PlyGBS), as these conditions supported good cell growth and cellular protein yields. A ~23-fold increase in protein accumulation per cell and ~9-fold increase L⁻¹ culture was observed compared to standard constant 24 hr illumination for GFP-PlyGBS. The highest yields under photoautotrophic conditions were obtained under 9 hrs illumination (6 mg L⁻¹ GFP and 2.1 mg L⁻¹ GFP-PlyGBS). This represents a ~4-fold increase in cellular protein accumulation for GFP-PlyGBS. On a volumetric basis the highest yield was at 15 hrs illumination (~2-fold increase L⁻¹ over the constant light for GFP-PlyGBS). Optimising illumination conditions to balance growth and protein expression can thus significantly enhance overall recombinant protein production in C. reinhardtii cultures.

Keywords: chlamydomonas reinhardtii, light, mixotrophic, recombinant protein

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9513 Glycine Betaine Affects Antioxidant Response and Lipid Peroxidation in Wheat Genotypes under Water-Deficit Conditions

Authors: S. K. Thind, Neha Gupta

Abstract:

Glycine betaine (N, N’, N’’– trimethyl glycine), (GB) as aqueous solution (100 mM) containing 0.1% TWEEN-20 (Ploythylene glycol sorbitan monolaurate) was sprayed on selected nineteen wheat genotypes at maximum tillering and anthesis stages. Water-deficit conditions resulted in lipid peroxidation. GB applications reduced lipid peroxidation in all wheat genotypes at both the stages. Catalase (CAT) activity was recorded more in control than under stressed conditions in selected wheat genotypes at both the stages; GB had no effect. The ascorbic acid content in leaves of selected genotypes increased under water deficit. A genotypic variability in Ascorbate peroxidase (APx) activity was recorded and GB treatment decreased it. Superoxide dismutase (SOD) activity was increased significantly under water-deficit at both stages in all genotypes. In present study, prolonged water-deficit conditions caused CAT deficiency/suppression which was compensated by APX and SOD; and GB exogenous application mitigated negative effect of water-deficit stress on lipid peroxidation.

Keywords: glycine-betaine, lipid peroxidation, ROS, water deficit stress

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9512 Design and Implementation of Image Super-Resolution for Myocardial Image

Authors: M. V. Chidananda Murthy, M. Z. Kurian, H. S. Guruprasad

Abstract:

Super-resolution is the technique of intelligently upscaling images, avoiding artifacts or blurring, and deals with the recovery of a high-resolution image from one or more low-resolution images. Single-image super-resolution is a process of obtaining a high-resolution image from a set of low-resolution observations by signal processing. While super-resolution has been demonstrated to improve image quality in scaled down images in the image domain, its effects on the Fourier-based technique remains unknown. Super-resolution substantially improved the spatial resolution of the patient LGE images by sharpening the edges of the heart and the scar. This paper aims at investigating the effects of single image super-resolution on Fourier-based and image based methods of scale-up. In this paper, first, generate a training phase of the low-resolution image and high-resolution image to obtain dictionary. In the test phase, first, generate a patch and then difference of high-resolution image and interpolation image from the low-resolution image. Next simulation of the image is obtained by applying convolution method to the dictionary creation image and patch extracted the image. Finally, super-resolution image is obtained by combining the fused image and difference of high-resolution and interpolated image. Super-resolution reduces image errors and improves the image quality.

Keywords: image dictionary creation, image super-resolution, LGE images, patch extraction

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9511 A TgCNN-Based Surrogate Model for Subsurface Oil-Water Phase Flow under Multi-Well Conditions

Authors: Jian Li

Abstract:

The uncertainty quantification and inversion problems of subsurface oil-water phase flow usually require extensive repeated forward calculations for new runs with changed conditions. To reduce the computational time, various forms of surrogate models have been built. Related research shows that deep learning has emerged as an effective surrogate model, while most surrogate models with deep learning are purely data-driven, which always leads to poor robustness and abnormal results. To guarantee the model more consistent with the physical laws, a coupled theory-guided convolutional neural network (TgCNN) based surrogate model is built to facilitate computation efficiency under the premise of satisfactory accuracy. The model is a convolutional neural network based on multi-well reservoir simulation. The core notion of this proposed method is to bridge two separate blocks on top of an overall network. They underlie the TgCNN model in a coupled form, which reflects the coupling nature of pressure and water saturation in the two-phase flow equation. The model is driven by not only labeled data but also scientific theories, including governing equations, stochastic parameterization, boundary, and initial conditions, well conditions, and expert knowledge. The results show that the TgCNN-based surrogate model exhibits satisfactory accuracy and efficiency in subsurface oil-water phase flow under multi-well conditions.

Keywords: coupled theory-guided convolutional neural network, multi-well conditions, surrogate model, subsurface oil-water phase

Procedia PDF Downloads 60