Search results for: biology experiments

Authors: Nyeng P. Gyang

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Even though past, current and future trends suggest that multicore and cloud computing systems are increasingly prevalent/ubiquitous, this class of parallel systems is nonetheless underutilized, in general, and barely used for research on employing parallel Delaunay triangulation for parallel surface modeling and generation, in particular. The performances, of actual/physical and virtual/cloud multicore systems/machines, at executing various algorithms, which implement various parallelization strategies of the incremental insertion technique of the Delaunay triangulation algorithm, were evaluated. T-tests were run on the data collected, in order to determine whether various performance metrics differences (including execution time, speedup and efficiency) were statistically significant. Results show that the actual machine is approximately twice faster than the virtual machine at executing the same programs for the various parallelization strategies. Results, which furnish the scalability behaviors of the various parallelization strategies, also show that some of the differences between the performances of these systems, during different runs of the algorithms on the systems, were statistically significant. A few pseudo superlinear speedup results, which were computed from the raw data collected, are not true superlinear speedup values. These pseudo superlinear speedup values, which arise as a result of one way of computing speedups, disappear and give way to asymmetric speedups, which are the accurate kind of speedups that occur in the experiments performed.

Keywords: cloud computing systems, multicore systems, parallel Delaunay triangulation, parallel surface modeling and generation

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

Procedia PDF Downloads 139

Authors: Yonas Lamore, Abebe Beyene, Samuel Fekadu, Moa Megersa

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Unaffordable construction cost of conventional water treatment plant and distribution system in most developing countries makes difficult to provide safe and adequate water for all households, especially for the rural setup. Water treatment at the source can be the best alternative. Solar disinfection is one alternative among point of use treatments. In this study, aqua lens, photovoltaic box and glass bottle were used subsequent to plant coagulants to evaluate microbial reduction potentials. Laboratory- and field-based experiments were conducted from May to August 2016. The Escherichia coli, total coliforms and heterotrophic plate counts were used as indicator organisms. The result indicated that aqua lens (AL), photovoltaic box (PV) and glass bottle (GB) have high inactivation rate subsequently almost for all indicator organisms in short solar exposure time. Total coliforms were inactivated in AL (SD = 15.8 °C, R2 = 0.92) followed by PV inactivation temperature associa- tion (SD = 11.6 C, R2 = 0.90), and the GB concentrator was inactivated (SD = 10.9 °C, R2 = 0.70) at turbidity level of 3.41 NTU. As the study indicated, aqua lens coupled with Moringa oleifera coagulant can be an effective with minimum cost for household water treatment system. The study also concludes heterotrophic bacteria were more resistant than other types of bacteria in SODIS with similar exposure time.

Keywords: acrylic glass, aqua lens, moringa olifera, photovoltaic box, solar disinfection, water treatment

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Authors: Seyed Mohamad Rasool Mirkarimi, David Chiaramonti, Samir Bensaid

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Catalytic methane decomposition (CMD, reaction 4) is a one-step process for hydrogen production where carbon in the methane molecule is sequestered in the form of stable and higher-value carbon materials. Metallic catalysts and carbon-based catalysts are two major types of catalysts utilized for the CDM process. Although carbon-based catalysts have lower activity compared to metallic ones, they are less expensive and offer high thermal stability and strong resistance to chemical impurities such as sulfur. Also, it would require less costly separation methods as some of the carbon-based catalysts may not have an active metal component in them. Since the regeneration of metallic catalysts requires burning of the C on their surfaces, which emits CO/CO2, in some cases, using carbon-based catalysts would be recommended because regeneration can be completely avoided, and the catalyst can be directly used in other processes. This work focuses on the effect of biochar as a carbon-based catalyst for the conversion of methane into hydrogen and carbon. Biochar produced from the pyrolysis of poplar wood and activated biochar are used as catalysts for this process. In order to observe the impact of carbon-based catalysts on methane conversion, methane cracking in the absence and presence of catalysts for a gas stream with different levels of methane concentration should be performed. The results of these experiments prove conversion of methane in the absence of catalysts at 900 °C is negligible, whereas in the presence of biochar and activated biochar, significant growth has been observed. Comparing the results of the tests related to using char and activated char shows the enhancement obtained in BET surface area of the catalyst through activation leads to more than 10 vol.% methane conversion.

Keywords: hydrogen production, catalytic methane decomposition, biochar, activated biochar, carbon-based catalyts

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Authors: Jocelyn B. Barbosa, Angeli L. Magbaril, Mariel T. Sabanal, John Paul T. Galario, Mikka P. Baldovino

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The use of technology has become ubiquitous in different areas of business today. With the advent of digital imaging and database technology, business owners have been motivated to integrate technology to their business operation ranging from small, medium to large enterprises. Technology has been found to have brought many benefits that can make a business grow. Hog or swine raising, for example, is a very popular enterprise in the Philippines, whose challenges in production monitoring can be addressed through technology integration. Swine production monitoring can become a tedious task as the enterprise goes larger. Specifically, problems like delayed and inconsistent reports are most likely to happen if counting of swine per pen of which building is done manually. In this study, we present iCount, which aims to ensure efficient swine detection and counting that hastens the swine production monitoring task. We develop a system that automatically detects and counts swine based on Sobel filter and ellipse fitting model, given the still photos of the group of swine captured in a pen. We improve the Sobel filter detection result through 8-neigbhorhood rule implementation. Ellipse fitting technique is then employed for proper swine detection. Furthermore, the system can generate periodic production reports and can identify the specific consumables to be served to the swine according to schedules. Experiments reveal that our algorithm provides an efficient way for detecting swine, thereby providing a significant amount of accuracy in production monitoring.

Keywords: automatic swine counting, swine detection, swine production monitoring, ellipse fitting model, sobel filter

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Authors: E. Al-Essa, R. Bello-Mendoza, D. G. Wareham

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Anaerobic batch experiments were conducted to investigate the effect of magnetite-supplementation (7 mM) on methane production from digested sludge undergoing two different microbial growth phases, namely fresh sludge (exponential growth phase) and degassed sludge (endogenous decay phase). Three different particle sizes were assessed: small (50 - 150 nm), medium (168 – 490 nm) and large (800 nm - 4.5 µm) particles. Results show that, in the case of the fresh sludge, magnetite significantly enhanced the methane production rate (up to 32%) and reduced the lag phase (by 15% - 41%) as compared to the control, regardless of the particle size used. However, the cumulative methane produced at the end of the incubation was comparable in all treatment and control bottles. In the case of the degassed sludge, only the medium-sized magnetite particles increased significantly the methane production rate (12% higher) as compared to the control. Small and large particles had little effect on the methane production rate but did result in an extended lag phase which led to significantly lower cumulative methane production at the end of the incubation period. These results suggest that magnetite produces a clear and positive effect on methane production only when an active and balanced microbial community is present in the anaerobic digester. It is concluded that, (i) the effect of magnetite particle size on increasing the methane production rate and reducing lag phase duration is strongly influenced by the initial metabolic state of the microbial consortium, and (ii) the particle size would positively affect the methane production if it is provided within the nanometer size range.

Keywords: anaerobic digestion, iron oxide, methanogenesis, nanoparticle

Procedia PDF Downloads 142

Authors: Siwei Chang, Heng Li, Haitao Wu, Xin Fang

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Construction robots are receiving more and more attention as a promising solution to the manpower shortage issue in the construction industry. The development of intelligent control techniques that assist in controlling the robots to avoid transparency and reflected building obstacles is crucial for guaranteeing the adaptability and flexibility of mobile construction robots in complex construction environments. With the boom of computer vision techniques, a number of studies have proposed vision-based methods for transparent obstacle avoidance to improve operation accuracy. However, vision-based methods are also associated with disadvantages such as high computational costs. To provide better perception and value evaluation, this study aims to analyze the performance of vision-based techniques for avoiding transparent building obstacles. To achieve this, commonly used sensors, including a lidar, an ultrasonic sensor, and a USB camera, are equipped on the robotic platform to detect obstacles. A Raspberry Pi 3 computer board is employed to compute data collecting and control algorithms. The turtlebot3 burger is employed to test the programs. On-site experiments are carried out to observe the performance in terms of success rate and detection distance. Control variables include obstacle shapes and environmental conditions. The findings contribute to demonstrating how effectively vision-based obstacle avoidance strategies for transparent building obstacle avoidance and provide insights and informed knowledge when introducing computer vision techniques in the aforementioned domain.

Keywords: construction robot, obstacle avoidance, computer vision, transparent obstacle

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Authors: Divya Vats, Sanjay Mahajani

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The clarification of sugarcane juice plays a pivotal role in the production of non-centrifugal sugar (NCS), profoundly influencing the quality of the final NCS product. In this study, we have investigated the kinetics and mathematical modeling of the batch clarification process. The turbidity of the clarified cane juice (NTU) emerges as the determinant of the end product’s color. Moreover, this parameter underscores the significance of considering other variables as performance indicators for accessing the efficacy of the clarification process. Temperature-controlled experiments were meticulously conducted in a laboratory-scale batch mode. The primary objective was to discern the essential and optimized parameters crucial for augmenting the clarity of cane juice. Additionally, we explored the impact of pH and flocculant loading on the kinetics. Particle Image Velocimetry (PIV) is employed to comprehend the particle-particle and fluid-particle interaction. This technique facilitated a comprehensive understanding, paving the way for the subsequent multiphase computational fluid dynamics (CFD) simulations using the Eulerian-Lagrangian approach in the Ansys fluent. Impressively, these simulations accurately replicated comparable velocity profiles. The final mechanism of this study helps to make a mathematical model and presents a valuable framework for transitioning from the traditional batch process to a continuous process. The ultimate aim is to attain heightened productivity and unwavering consistency in product quality.

Keywords: non-centrifugal sugar, particle image velocimetry, computational fluid dynamics, mathematical modeling, turbidity

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Authors: Christine Y. Yeh, Brian D. Piening, Sarah M. Totten, Kimberly Kukurba, Wenyu Zhou, Kevin P. F. Contrepois, Gucci J. Gu, Sharon Pitteri, Michael Snyder

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Three million deaths worldwide are attributed to obesity. However, the biomolecular mechanisms that describe the link between adiposity and subsequent disease states are poorly understood. Insulin resistance characterizes approximately half of obese individuals and is a major cause of obesity-mediated diseases such as Type II diabetes, hypertension and other cardiovascular diseases. This study makes use of longitudinal quantitative and high-throughput multi-omics (genomics, epigenomics, transcriptomics, glycoproteomics etc.) methodologies on blood samples to develop multigenic and multi-analyte signatures associated with weight gain and insulin resistance. Participants of this study underwent a 30-day period of weight gain via excessive caloric intake followed by a 60-day period of restricted dieting and return to baseline weight. Blood samples were taken at three different time points per patient: baseline, peak-weight and post weight loss. Patients were characterized as either insulin resistant (IR) or insulin sensitive (IS) before having their samples processed via longitudinal multi-omic technologies. This comparative study revealed a wealth of biomolecular changes associated with weight gain after using methods in machine learning, clustering, network analysis etc. Pathways of interest included those involved in lipid remodeling, acute inflammatory response and glucose metabolism. Some of these biomolecules returned to baseline levels as the patient returned to normal weight whilst some remained elevated. IR patients exhibited key differences in inflammatory response regulation in comparison to IS patients at all time points. These signatures suggest differential metabolism and inflammatory pathways between IR and IS patients. Biomolecular differences associated with weight gain and insulin resistance were identified on various levels: in gene expression, epigenetic change, transcriptional regulation and glycosylation. This study was not only able to contribute to new biology that could be of use in preventing or predicting obesity-mediated diseases, but also matured novel biomedical informatics technologies to produce and process data on many comprehensive omics levels.

Keywords: insulin resistance, multi-omics, next generation sequencing, proteogenomics, type ii diabetes

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Authors: Md Omar Faruq Howlader, Tariq Pervez Sattar, Sandra Dudley

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This paper describes the design process of a 200 MHz Ground Penetrating Radar (GPR) and a battery powered concrete vertical concrete surface climbing mobile robot. The key design feature is a miniaturized 200 MHz dipole antenna using additional radiating arms and procedure records a reduction of 40% in length compared to a conventional antenna. The antenna set is mounted in front of the robot using a servo mechanism for folding and unfolding purposes. The robot’s adhesion mechanism to climb the reinforced concrete wall is based on neodymium permanent magnets arranged in a unique combination to concentrate and maximize the magnetic flux to provide sufficient adhesion force for GPR installation. The experiments demonstrated the robot’s capability of climbing reinforced concrete wall carrying the attached prototype GPR system and perform floor-to-wall transition and vice versa. The developed GPR’s performance is validated by its capability of detecting and localizing an aluminium sheet and a reinforcement bar (rebar) of 12 mm diameter buried under a test rig built of wood to mimic the concrete structure environment. The present robotic GPR system proves the concept of feasibility of undertaking inspection procedure on large concrete structures in hazardous environments that may not be accessible to human inspectors.

Keywords: climbing robot, dipole antenna, ground penetrating radar (GPR), mobile robots, robotic GPR

Procedia PDF Downloads 279

Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius

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In general, state-of-the-art Data Acquisition Systems (DAQ) in high energy physics experiments must satisfy high requirements in terms of reliability, efficiency and data rate capability. This paper presents the development and deployment of a debugging tool named DAQ Debugger for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. Utilizing a hardware event builder, the iFDAQ is designed to be able to readout data at the average maximum rate of 1.5 GB/s of the experiment. In complex softwares, such as the iFDAQ, having thousands of lines of code, the debugging process is absolutely essential to reveal all software issues. Unfortunately, conventional debugging of the iFDAQ is not possible during the real data taking. The DAQ Debugger is a tool for identifying a problem, isolating the source of the problem, and then either correcting the problem or determining a way to work around it. It provides the layer for an easy integration to any process and has no impact on the process performance. Based on handling of system signals, the DAQ Debugger represents an alternative to conventional debuggers provided by most integrated development environments. Whenever problem occurs, it generates reports containing all necessary information important for a deeper investigation and analysis. The DAQ Debugger was fully incorporated to all processes in the iFDAQ during the run 2016. It helped to reveal remaining software issues and improved significantly the stability of the system in comparison with the previous run. In the paper, we present the DAQ Debugger from several insights and discuss it in a detailed way.

Keywords: DAQ Debugger, data acquisition system, FPGA, system signals, Qt framework

Procedia PDF Downloads 285

Authors: Sheikh Shams Azam, Manoj Raju, Venkatesh Pagidimarri, Vamsi Kasivajjala

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Over the past decade, there has been a steep rise in the data-driven analysis in major areas of medicine, such as clinical decision support system, survival analysis, patient similarity analysis, image analytics etc. Most of the data in the field are well-structured and available in numerical or categorical formats which can be used for experiments directly. But on the opposite end of the spectrum, there exists a wide expanse of data that is intractable for direct analysis owing to its unstructured nature which can be found in the form of discharge summaries, clinical notes, procedural notes which are in human written narrative format and neither have any relational model nor any standard grammatical structure. An important step in the utilization of these texts for such studies is to transform and process the data to retrieve structured information from the haystack of irrelevant data using information retrieval and data mining techniques. To address this problem, the authors present Q-Map in this paper, which is a simple yet robust system that can sift through massive datasets with unregulated formats to retrieve structured information aggressively and efficiently. It is backed by an effective mining technique which is based on a string matching algorithm that is indexed on curated knowledge sources, that is both fast and configurable. The authors also briefly examine its comparative performance with MetaMap, one of the most reputed tools for medical concepts retrieval and present the advantages the former displays over the latter.

Keywords: information retrieval, unified medical language system, syntax based analysis, natural language processing, medical informatics

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Ali A. Ukasha, Majdi F. Elbireki, Mohammad F. Abdullah

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Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression and salt and peppers attacks, bitplanes decomposition, Arnold transform, color image, wavelet transform, lossless image encryption

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Authors: Donludee Jaisut, Norihisa Kato, Thanutchaporn Kumrungsee, Kiyoshi Kawai, Somkiat Prachayawarakorn, Patchalee Tungtrakul

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Jasmine Rice is a principle food of Thai people. However, glycemic index of jasmine rice is in high level, risk of type II diabetes after consuming. Burdock root is a good source of non-starch polysaccharides such as inulin. Inulin acts as prebiotic and helps reduce blood-sugar level. The purpose of this research was to reduce digestion rate of jasmine rice by coating burdock root extract on rice surface, using top-spay fluidized bed coating technique. Coating experiments were performed by spraying burdock root solution onto Jasmine rice kernels (Khao Dawk Mali-105; KDML), which had an initial moisture content of 11.6% wet basis, suspended in the fluidized bed. The experimental conditions were: solution spray rates of 31.7 mL/min, atomization pressure of 1.5 bar, spray time of 10 min, time of drying after spraying of 30 s, superficial air velocity of 3.2 m/s and drying temperatures of 60°C. The coated rice quality was evaluated in terms of the moisture content, texture, whiteness and digestion rate. The results showed that initial and final moisture contents of samples were the same in concentration 8% (v/v) and 10% (v/v). The texture was insignificantly changed from that of uncoated sample. The whiteness values were varied on concentration of burdock root extract. Coated samples were slower digested.

Keywords: burdock root, digestion, drying, rice

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Authors: Ming-Jong Yao, Chin-Sum Shui, Chih-Han Wang

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This paper is developed based on a real-world decision scenario that an industrial gas company that applies the Vendor Managed Inventory model and supplies liquid oxygen with a self-operated heterogeneous vehicle fleet to hospitals in nearby cities. We name it as a Joint Replenishment and Heterogeneous Vehicle Routing Problem with Cyclical Schedule and formulate it as a non-linear mixed-integer linear programming problem which simultaneously determines the length of the planning cycle (PC), the length of the replenishment cycle and the dates of replenishment for each customer and the vehicle routes of each day within PC, such that the average daily operation cost within PC, including inventory holding cost, setup cost, transportation cost, and overtime labor cost, is minimized. A solution method based on genetic algorithm, embedded with an encoding and decoding mechanism and local search operators, is then proposed, and the hash function is adopted to avoid repetitive fitness evaluation for identical solutions. Numerical experiments demonstrate that the proposed solution method can effectively solve the problem under different lengths of PC and number of customers. The method is also shown to be effective in determining whether the company should expand the storage capacity of a customer whose demand increases. Sensitivity analysis of the vehicle fleet composition shows that deploying a mixed fleet can reduce the daily operating cost.

Keywords: cyclic inventory routing problem, joint replenishment, heterogeneous vehicle, genetic algorithm

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Authors: Zohreh Fallah, Edward P. L. Roberts

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One of the big challenges for produced water treatment is removing oil from water in the form of emulsified droplets which are not easily separated. An attractive approach is adsorption, as it is a simple and effective process. However, adsorbents must be regenerated in order to make the process cost effective. Several sorbents have been tested for treating oily wastewater. However, some issues such as high energy consumption for activated carbon thermal regeneration have been reported. Due to their significant electrical conductivity, Graphite Intercalation Compounds (GIC) were found to be suitable to be regenerated electrochemically. They are non-porous materials with low surface area and fast adsorptive capacity which are useful for removal of low concentration of organics. An innovative adsorption/regeneration process has been developed at the University of Manchester in which adsorption of organics are done by using a patented GIC adsorbent coupled with subsequent electrochemical regeneration. The oxidation of adsorbed organics enables 100% regeneration so that the adsorbent can be reused over multiple adsorption cycles. GIC adsorbents are capable of removing a wide range of organics and pollutants; however, no comparable report is available for removal of emulsified oil in produced water using abovementioned process. In this study the performance of this technology for the removal of emulsified oil in wastewater was evaluated. Batch experiments were carried out to determine the adsorption kinetics and equilibrium isotherm for both real produced water and model emulsions. The amount of oil in wastewater was measured by using the toluene extraction/fluorescence analysis before and after adsorption and electrochemical regeneration cycles. It was found that oil in water emulsion could be successfully treated by the treatment process and More than 70% of oil was removed.

Keywords: adsorption, electrochemical regeneration, emulsified oil, produced water

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Authors: Sabariah Mohd Yusoff, Qamaruddin Adzeem Muhamad Murad

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This study investigates the impact of car seat design on driver response time, addressing a critical gap in understanding how ergonomic features influence both performance and safety. Controlled driving experiments were conducted with fourteen participants (11 male, 3 female) across three locations chosen for their varying traffic conditions to account for differences in driver alertness. Participants interacted with various seat designs while performing driving tasks, and objective metrics such as braking and steering response times were meticulously recorded. Advanced statistical methods, including regression analysis and t-tests, were employed to identify design factors that significantly affect driver response times. Subjective feedback was gathered through detailed questionnaires—focused on driving experience and knowledge of response time—and in-depth interviews. This qualitative data was analyzed thematically to provide insights into driver comfort and usability preferences. The study aims to identify key seat design features that impact driver response time and to gain a deeper understanding of driver preferences for comfort and usability. The findings are expected to inform evidence-based guidelines for optimizing car seat design, ultimately enhancing driver performance and safety. The research offers valuable implications for automotive manufacturers and designers, contributing to the development of seats that improve driver response time and overall driving safety.

Keywords: car seat design, driver response time, cognitive driving, ergonomics optimization

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Authors: Hyun Kyu Lee, Won Zin Oh, June Hyun Kim, Jin Hee Kim, Sang June Choi, Hak Soo Kim

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The oxidative dissolution of chromium oxide by manganese oxides including permanganate have been widely studied not only for the chemical decontamination of nuclear power plant, but also for the environmental control of the toxic chromate caused by naturally occurring manganese dioxide. However, little attention has been made for the spontaneous reductive decomposition of permanganate in the water, which is a competing reaction with the oxidation of the chromium oxide by permanganate. The objective of this study is to investigate the spontaneous reductive decomposition behavior of permanganate in the water, depending on the variation of acidity, temperature and concentration. Results of the experiments showed that the permanganate reductive decomposition product is manganese dioxide, and this reaction accompanies with the same molar amount of hydrogen ion consumption. Therefore, at the neutral condition (ex. potassium permanganate solution without acidic chemicals), the permanganate do not reduce by itself at any condition of temperature, concentration within the experimental range. From the results, we confirmed that the oxidation reaction for the permanganate reduction is the water oxidation that is accompanying the oxygen evolution. The experimental results on the reductive decomposition behavior of permanganate in the water also showed that the degree and rate of permanganate reduction increases with the temperature, acidity and concentration. The spontaneous decomposition of the permanganates obtained in the studies would become a good reference to select the operational condition, such as temperature, acidity and concentration, for the chemical decontamination of nuclear power plants.

Keywords: permanganate reduction, spontaneous decomposition, water oxidation, acidity, temperature, permanganate concentration, chemical decontamination, nuclear power plant

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Authors: Salwa M. Elmesallamy, Ahmed A. Farag, Magd M. Badr, Dalia S. Fathy, Ahmed Bakry, Mona A. El-Etre

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The term green environment is an international trend. It is become imperative to treat the corrosion of steel with a green coating to protect the environment. From the potential adverse effects of the traditional materials.A series of polybenzoxazine/henna composites (PBZ/henna), with different weight percent (3,5, and 7 wt % (of henna), were prepared for corrosion protection of carbon steel. The structures of the prepared composites were verified using FTIR analysis. The mechanical properties of the resins, such as adhesion, hardness, binding, and tensile strength, were also measured. It was found that the tensile strength increases by henna loading up to 25% higher than the tidy resin. The thermal stability was investigated by thermogravimetric analysis (TGA) the loading of lawsone (henna) molecules into the PBZ matrix increases the thermal stability of the composite. UV stability was tested by the UV weathering accelerator to examine the possibility that henna can also act as an aging UV stabilizer. The effect of henna content on the corrosion resistance of composite coatings was tested using potentiostatic polarization and electrochemical spectroscopy. The presence of henna in the coating matrix enhances the protection efficiency of polybenzoxazine coats. Increasing henna concentration increases the protection efficiency of composites. The quantum chemical calculations for polybenzoxazine/henna composites have resulted that the highest corrosion inhibition efficiency, has the highest EHOMO and lowest ELUMO; which is in good agreement with results obtained from experiments.

Keywords: polybenzoxazine, corrosion, green chemistry, carbon steel

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Authors: N. Z. van Hierden, Q. Yu, F. Gauvin

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Cement manufacturing is, because of its production process, among the highest contributors to CO₂ emissions worldwide. As cement is one of the major components in 3D printed concrete, achieving sustainability and carbon neutrality can be particularly challenging. To improve the sustainability of 3D printed materials, different CO₂-reducing strategies can be used, each one with a distinct level of impact and complexity. In this work, we focus on the development of these sustainable mixtures and finding alternatives. Promising alternatives for cement and clinker replacement include the use of recycled building materials, amongst which (calcined) bricks and roof tiles. To study the potential of recycled clay-based building materials, the application of calcinated clay itself is studied as well. Compared to cement, the calcination temperature of clay-based materials is significantly lower, resulting in reduced CO₂ output. Reusing these materials is therefore a promising solution for utilizing waste streams while simultaneously reducing the cement content in 3D concrete mixtures. In addition, waste streams can be locally sourced, thereby reducing the emitted CO₂ during transportation. In this research, various alternative binders are examined, such as calcined clay blends (LC3) from recycled tiles and bricks, or locally obtained clay resources. Using various experiments, a high potential for mix designs including these resources has been shown with respect to material strength, while sustaining decent printability and buildability. Therefore, the defined strategies are promising and can lead to a more sustainable, low-CO₂ mixture suitable for 3D printing while using accessible materials.

Keywords: cement replacement, 3DPC, circular building materials, calcined clay, CO₂ reduction

Procedia PDF Downloads 87

Authors: B. Karthik Vasan, Rachil Maliwal, Somnath Basu

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Generation of solid waste is a major problem confronting the iron and steel industry around the world. Disposal of untreated wastes is no longer a viable solution in view of the environmental regulations becoming more and more stringent, as well as an increase in community awareness about the long-term hazards of indiscriminate waste disposal. The current work explores the possibility of converting some of the ‘problematic’ solid wastes generated during steel manufacturing operations, viz. dust from primary steelmaking, iron ore handling, and flux calcination processes, into value-added products instead of environmentally hazardous disposal practices. It was possible to develop a synthetic calcium ferrite, which helped to enhance the dissolution of calcined basic fluxes (e.g. CaO) and reduce the overall energy consumption during steel making. This, in turn, increased process efficiency and reduced greenhouse gas emissions. The preliminary results from laboratory-scale experiments clearly demonstrate the potential of utilizing these ‘waste materials’ that are generated in-house in iron and steel manufacturing plants. The energy required for synthesis of the ferrite may be reduced further by partially utilizing the waste heat from the exhaust gases. In the longer run, it would result in significant financial benefits due to reduced dependence on purchased fluxes. The synthesized ferrite is non-hygroscopic and this provides an additional benefit during its storage and transportation, relative to calcined lime (CaO) that is widely used as a basic flux across the steel making industry.

Keywords: calcium ferrite, flux, slag formation, solid waste

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Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

Procedia PDF Downloads 204

Authors: Bong-Su Sin, Jong-Kyu Kim, Se-Il Song, Kwon-Hee Lee

Abstract:

An automobile ball joint is a pivoting element used to allow rotational motion between the parts of the steering and suspension system. And it plays a role in smooth transmission of steering movement, also reduction in impact from the road surface. A ball joint is under various repeated loadings that may cause cracks and abrasion. This damages lead to safety problems of a car, as well as reducing the comfort of the driver's ride, and raise questions about the ball joint procedure and the whole durability of the suspension system. Accordingly, it is necessary to ensure the high durability and reliability of a ball joint. The structural responses of stiffness and pull-out strength were then calculated to check if the design satisfies the related requirements. The analysis was sequentially performed, following the caulking process. In this process, the deformation and stress results obtained from the analysis were saved. Sequential analysis has a strong advantage, in that it can be analyzed by considering the deformed shape and residual stress. The pull-out strength means the required force to pull the ball stud out from the ball joint assembly. The low pull-out strength can deteriorate the structural stability and safety performances. In this study, two design variables and two noise factors were set up. Two design variables were the diameter of a stud and the angle of a socket. And two noise factors were defined as the uncertainties of Young's modulus and yield stress of a seat. The DOE comprises 81 cases using these conditions. Robust design of a ball joint was performed using the DOE. The pull-out strength was generated from the uncertainties in the design variables and the design parameters. The purpose of robust design is to find the design with target response and smallest variation.

Keywords: ball joint, pull-out strength, robust design, design of experiments

Procedia PDF Downloads 422

Authors: Mohamed A. Almoghalis, Osman M. Hegazy, Ibrahim F. Imam, Ali H. Elbastawessy

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This paper presents a new hyperspectral image segmentation scheme with respect to both spatial and spectral contexts. The scheme uses the 8-pixels spatial pattern to build a weight structure that holds the number of outlier bands for each pixel among its neighborhood windows in different directions. The number of outlier bands for a pixel is obtained using bands quartile box plots profile among spatial 8-pixels pattern windows. The quartile box plot weight structure represents the spatial-spectral context in the image. Instead of starting segmentation process by single pixels, the proposed methodology starts by pixels groups that proved to share the same spectral features with respect to their spatial context. As a result, the segmentation scheme starts with Jigsaw pieces that build a mosaic image. The following step builds a model for each Jigsaw piece in the mosaic image. Each Jigsaw piece will be merged with another Jigsaw piece using KNN applied to their bands' quartile box plots profiles. The scheme iterates till required number of segments reached. Experiments use two data sets obtained from Earth Observer 1 (EO-1) sensor for Egypt and France. Initial results qualitative analysis showed encouraging results compared with ground truth. Quantitative analysis for the results will be included in the final paper.

Keywords: hyperspectral image segmentation, image processing, remote sensing, box plot

Procedia PDF Downloads 605

Authors: Yakui Bai, Chen Sun, Ke Wang

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An experimental investigation of environmental effect on fatigue behavior in SA508 Gr.3 Cl.2 Steam Generator Forging CAP1400 nuclear power plant has been carried out. In order to simulate actual loading condition, a range of strain amplitude was applied in different low cycle fatigue (LCF) tests. The current American Society of Mechanical Engineers (ASME) design fatigue code does not take full account of the interactions of environmental, loading, and material's factors. A range of strain amplitude was applied in different low cycle fatigue (LCF) tests at a strain rate of 0.01%s⁻¹. A design fatigue model was constructed by taking environmentally assisted fatigue effects into account, and the corresponding design curves were given for the convenience of engineering applications. The corrosion fatigue experiment was performed in a strain control mode in 320℃ borated and lithiated water environment to evaluate the effects of a mixed environment on fatigue life. Stress corrosion cracking (SCC) in steam generator large forging in primary water of pressurized water reactor was also observed. In addition, it is found that the CF life of SA508 Gr.3 Cl.2 decreases with increasing temperature in the water environment. The relationship between the reciprocal of temperature and the logarithm of fatigue life was found to be linear. Through experiments and subsequent analysis, the mechanisms of reduced low cycle fatigue life have been investigated for steam generator forging.

Keywords: failure behavior, low alloy steel, steam generator forging, stress corrosion cracking

Procedia PDF Downloads 127

Authors: Victor Iorungwa Gwa, Ebenezer Jonathan Ekefan

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Potential of Trichoderma harzianum for biological control of postharvest fungal rot of white yam (Dioscorea rotundata Poir) tubers in storage was studied. Pathogenicity test revealed the susceptibility of healthy looking yam tubers to Aspergillus niger, Botryodiplodia theobromae, and Fusarium oxysporum f. sp. melonganae after fourteen days of inoculation. Treatments comprising A. niger, B. theobromae, and F. oxysporum each paired with T. harzianum and were arranged in completely randomized design and stored for five months. Experiments were conducted between December 2015 and April 2016 and December 2016 and April 2017. Results showed that tubers treated with the pathogenic fungi alone caused mean percentage rot of between 6.67 % (F. oxysporum) and 22.22 % (A. niger) while the paired treatments produced only between 2.22 % (T. harzianum by F. oxysporum) and 6.67 % (T. harzianum by A. niger). In the second year of storage, mean percentage rot was found to be between 13.33 % (F. oxysporum) and 28.89 % (A. niger) while in the paired treatment rot was only between 6.67 % (F. oxysporum) and 8.89% (A. niger). Tubers treated with antagonist alone produced 0.00 % and 2.22 % in the first and second year, respectively. Result revealed that there was a significant difference (P ≤ 0.05) in mean percentage rot between the first year and the second year except where B. theobromae was inoculated alone, A. niger and T. harzianum paired and B. theobromae and T. harzianum paired. The most antagonised fungus in paired treatment for both years was F. oxysporum f. sp. melonganae, while the least antagonised, was A. niger and B. theobromae. It is, therefore, concluded that T. harzianum has potentials to control rot causing pathogens of yam tubers in storage. This can compliment or provide better alternative ways of reducing rot in yam tubers than by the use of chemical fungicides which are not environmentally friendly.

Keywords: biological control, fungal rot, postharvest, Trichoderma harzianum, white yam

Procedia PDF Downloads 164

Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

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Over the past decade, the non-elective admissions in the UK have increased significantly. Taking into account limited resources (i.e. beds), the related service managers are obliged to manage their resources effectively due to the non-elective admissions which are mostly admitted to inpatient specialities via A&E departments. Geriatric medicine is one of specialities that have long length of stay for the non-elective admissions. This study aims to develop a discrete event simulation model to understand how possible increases on non-elective demand over the next 12 months affect the bed occupancy rate and to determine required number of beds in a geriatric medicine speciality in a UK hospital. In our validated simulation model, we take into account observed frequency distributions which are derived from a big data covering the period April, 2009 to January, 2013, for the non-elective admission and the length of stay. An experimental analysis, which consists of 16 experiments, is carried out to better understand possible effects of case studies and scenarios related to increase on demand and number of bed. As a result, the speciality does not achieve the target level in the base model although the bed occupancy rate decreases from 125.94% to 96.41% by increasing the number of beds by 30%. In addition, the number of required beds is more than the number of beds considered in the scenario analysis in order to meet the bed requirement. This paper sheds light on bed management for service managers in geriatric medicine specialities.

Keywords: bed management, bed occupancy rate, discrete event simulation, geriatric medicine, non-elective admission

Procedia PDF Downloads 225

Authors: Marian Sagat, Mariana Remesikova

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In civil engineering, there is a problem how to industrially produce tensile membrane structures that are non-developable surfaces. Nondevelopable surfaces can only be developed with a certain error and we want to minimize this error. To that goal, the non-developable surfaces are cut into plates along to the geodesic curves. We propose a numerical algorithm for finding approximations of open geodesics on meshes and surfaces based on geodesic curvature flow. For practical reasons, it is important to automatize the choice of the time step. We propose a method for automatic setting of the time step based on the diagonal dominance criterion for the matrix of the linear system obtained by discretization of our partial differential equation model. Practical experiments show reliability of this method. Because approximation of the model is made by numerical method based on classic derivatives, it is necessary to solve obstacles which occur for meshes with sharp corners. We solve this problem for big family of meshes with sharp corners via special rotations which can be seen as partial unfolding of the mesh. In practical applications, it is required that the approximation of geodesic has its vertices only on the edges of the mesh. This problem is solved by a specially designed pointing tracking algorithm. We also partially solve the problem of finding geodesics on meshes with holes. We implemented the whole algorithm in Rhinoceros (commercial 3D computer graphics and computer-aided design software ). It is done by using C# language as C# assembly library for Grasshopper, which is plugin in Rhinoceros.

Keywords: geodesic, geodesic curvature flow, mesh, Rhinoceros software

Procedia PDF Downloads 154

Authors: Xiaoyu Li, Wenchuan Ding, Yujia Yia

Abstract:

As the nanoscale zinc oxide particles (nano-ZnO) accumulate in the landfill, nano-ZnO will enter the landfill leachate and come into contact with the heavy metal ions in leachate, which will change their transport process in the landfill and, furthermore, affect each other's environmental fate and toxicity. In this study, we explored the transport of co-existing nano-ZnO, Cu(II) and Cr(VI) ions by column experiments under different stages of landfill leachate conditions (flow rate, pH, ionic strength, humic acid). The results show that Cu(II) inhibits the transport of nano-ZnO in the quartz sand column by increasing the surface potential of nano-ZnO, and nano-ZnO increases the retention of Cu(II) in the quartz sand column by adsorbing Cu(II) ions. Cr(VI) promotes the transport of nano-ZnO in the quartz sand column by neutralizing the surface potential of the nano-ZnO which reduces electrostatic attraction between nZnO and quartz sand, but the nano-ZnO has no effect on the transport of Cr(VI). The nature of landfill leachates such as flow rate, pH, ionic strength (IS) and humic acid (HA) has a certain effect on the transport of coexisting nano-ZnO and heavy metal ions. For leachate containing Cu(II) and Cr(VI) ions, at the initial stage of landfilling, the pH of leachate is acidic, ionic strength value is high, the humic acid concentration is low, and the transportability of nano-ZnO is weak. As the landfill age increased, the pH value in the leachate gradually increases, when the ions are raised to alkaline, these ions are trending to precipitated or adsorbed to the solid wastes in landfill, which resulting in low IS value of leachate. At the same time, more refractory organic matter gradually increases such as HA, which provides repulsive steric effects, so the nano-ZnO is more likely to migrate. Overall, the Cr(VI) can promote the transport of nano-ZnO more than Cu(II).

Keywords: heavy metal ions, landfill leachate, nano-ZnO, transport

Procedia PDF Downloads 137