Search results for: commuter line vending machine

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

Procedia PDF Downloads 105

Authors: Qurratulain Safdar

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Drought is a temporary aberration in contrast to aridity, as it is a permanent feature of climate. Virtually, it takes place in all types of climatic regions that range from high to low rainfall areas. Due to the wide latitudinal extent of Pakistan, there is seasonal and annual variability in rainfall. The south-central part of the country is arid and hyper-arid. This study focuses on the spatio-temporal analysis of droughts in arid and hyperarid region of Cholistan using the standardized precipitation index (SPI) approach. This study has assessed the extent of recurrences of drought and its temporal vulnerability to drought in Cholistan region. Initially, the paper described the geographic setup of the study area along with a brief description of the drought conditions that prevail in Pakistan. The study also provides a scientific foundation for preparing literature and theoretical framework in-line with the selected parameters and indicators. Data were collected both from primary and secondary data sources. Rainfall and temperature data were obtained from Pakistan Meteorology Department. By applying geostatistical approach, a standardized precipitation index (SPI) was calculated for the study region, and the value of spatio-temporal variability of drought and its severity was explored. As a result, in-depth spatial analysis of drought conditions in Cholistan area was found. Parallel to this, drought-prone areas with seasonal variation were also identified using Kriging spatial interpolation techniques in a GIS environment. The study revealed that there is temporal variation in droughts' occurrences both in time series and SPI values. The paper is finally concluded, and strategic plan was suggested to minimize the impacts of drought.

Keywords: Cholistan desert, climate anomalies, metrological droughts, standardized precipitation index

Procedia PDF Downloads 187

Authors: Anastasios Papathanasiou, George Liontos, Athanasios Katsouras, Vasiliki Liagkou, Euripides Glavas

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Email remains a crucial communication tool due to its efficiency, accessibility and cost-effectiveness, enabling rapid information exchange across global networks. However, the global adoption of email has also made it a prime target for cyber threats, including phishing, malware and Business Email Compromise (BEC) attacks, which exploit its integral role in personal and professional realms in order to perform fraud and data breaches. To combat these threats, this research advocates for a multi-layered defense strategy incorporating advanced technological tools such as anti-spam and anti-malware software, machine learning algorithms and authentication protocols. Moreover, we developed an artificial intelligence model specifically designed to analyze email headers and assess their security status. This AI-driven model examines various components of email headers, such as "From" addresses, ‘Received’ paths and the integrity of SPF, DKIM and DMARC records. Upon analysis, it generates comprehensive reports that indicate whether an email is likely to be malicious or benign. This capability empowers users to identify potentially dangerous emails promptly, enhancing their ability to avoid phishing attacks, malware infections and other cyber threats.

Keywords: email security, artificial intelligence, header analysis, threat detection, phishing, DMARC, DKIM, SPF, ai model

Procedia PDF Downloads 25

Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

Procedia PDF Downloads 322

Authors: Dan Han, Yukun Zhang, Jie Zheng, Rui Zhang

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Making full use of space along transportation infrastructure to develop renewable energy sources, especially solar energy resources, has become a research focus in relevant fields. In recent years, relevant international researches can be classified into three stages of theoretical and technical exploration, exploratory practice as well as planning implementation. Compared with traditional solar energy development mode, the development of solar energy resources in places along the transportation infrastructure has special advantages, which can also bring forth new opportunities for the development of green transportation. 'Road Integrated Photovoltaic', a development model of combining transport and new energy, has been actively studied and applied in developed countries, but it was still in its infancy in China. 'New Silk Road Economic Belt' has great advantage to carry out the 'Road Integrated Photovoltaic' because of the rich solar energy resources in its path, the shortages of renewable energy, the constraints of agricultural land and other reasons. Especially the massive amount of construction of transportation infrastructure brought by Silk Road Economic Belt, large area of developable land along the transportation line will be generated. Abundant solar energy recourses along the Silk Road will provide extremely superb practical opportunities to the land development along transportation infrastructure. We take PVsyst, GIS and Google map software for simulation of its potential by taking Lan-Xin Railway as an example, so potential electrical energy generation can be quantified and further analyzed. Research of 'New Silk Road Economic Belt' combined with 'Road Integrated Photovoltaic' is a creative development for the along transport and energy infrastructure. It not only can make full use of solar radiation and land in its path, but also bring more long-term advantages and benefits.

Keywords: land use, silk road economic belt, solar energy, transportation infrastructure

Procedia PDF Downloads 218

Authors: ATM Emdadul Haque

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Phosphorus is an essential nutrient which is regularly consumed with food and exists in the body as phosphate. Phosphate is an important component of cellular structures and needed for bone mineralization. Excessive accumulation of phosphate is an important driving factor of mortality in chronic renal failure patients; of relevance, these patients are usually provided health care by doctors, nurses, and pharmacists. Hence, this study was planned to determine the level of awareness of the future healthcare providers about the phosphate-containing foods and beverages and to access their knowledge on the harmful effects of excess phosphate consumption. A questionnaire was developed and distributed among the year-1 medical, nursing and pharmacy students. 432 medical, nursing and pharmacy students responded with age ranging from 18-24 years. About 70% of the respondents were female with a majority (90.7%) from Malay ethnicity. Among the respondents, 29.9% were medical, 35.4% were the pharmacy and 34.7% were nursing students. 79.2% students knew that phosphate was an important component of the body, but only 61.8% knew that consuming too much phosphate could be harmful to the body. Despite 97% of the students knew that carbonated soda contained high sugar, surprisingly 77% of them did not know the presence of high phosphate in the same soda drinks; in the similar line of observation, 67% did not know the presence of it in the fast food. However, it was encouraging that 94% of the students wanted to know more about the effects of phosphate consumption, 74.3% were willing to give up drinking soda and eating fast food, and 52% considered taking green coconut water instead of soda drinks. It is, therefore, central to take an educational initiative to increase the awareness of the future healthcare providers about phosphate-containing food and its harmful effects in excessive consumptions.

Keywords: high phosphate containing foods and beverages, excessive consumption, future health care providers, phosphorus

Procedia PDF Downloads 354

Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

Procedia PDF Downloads 337

Authors: Arash Sharafat Vaziri, Leila Aghaghazvini, Soodeh Jahangiri, Mohammad Tahami, Roham Borazjani, Mohammad Naghi Tahmasebi, Hamid Rabie, Hesan Jelodari Mamaghani, Fardis Vosoughi, Maryam Salimi

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Aims: It is essential to know the normal extrusion measures in order to detect pathological ones. In this study, we aimed to define some normal reference values for meniscal extrusion in the normal knees during different ranges of motion. Methods: The amount of anterior and posterior portion of meniscal extrusion among twenty-one asymptomatic volunteers (42 knees) were tracked at 0, 45, and 90 degrees of knee flexion using an ultrasound machine. The repeated measures analysis of variance (ANOVA) was used to show the interaction between the amounts of meniscal extrusion and the different degrees of knee flexion. Result: The anterior portion of the lateral menisci at full knee extension (0.59±1.40) and the posterior portion of the medial menisci during 90° flexion (3.06±2.36) showed the smallest and the highest mean amount of extrusion, respectively. The normal average amounts of anterior extrusion were 1.12± 1.17 mm and 0.99± 1.34 mm for medial and lateral menisci, respectively. The posterior meniscal normal extrusions were significantly increasing in both medial and lateral menisci during the survey (F= 20.250 and 11.298; both P-values< 0.001) as they were measured at 2.37± 2.16 mm and 1.53± 2.18 mm in order. Conclusion: The medial meniscus can extrude 1.74± 1.84 mm normally, while this amount was 1.26± 1.82 mm for the lateral meniscus. These measures commonly increased with the rising of knee flexion motion. Likewise, the posterior portion showed more extrusion than the anterior portion on both sides. These measures commonly increased with higher knee flexion.

Keywords: meniscal extrusion, ultrasonography, knee

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Authors: Carol Yue-En Ong, Angelina Hui-Min Tan, Quan Liu, Paul Chi-Lui Ho

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A public general hospital in Singapore has recently implemented an automated unit-dose machine in their inpatient dispensary, Swisslog, with the objective of reducing human error and improving patient safety. However, a concern in stability arises as tablets are removed from their original packaging (bottled loose tablets/capsules) and are repackaged into individual, clear plastic wrappers as unit doses in the system. Drugs that are light-sensitive and hygroscopic would be more susceptible to degradation as the wrapper does not offer full protection. Hence, this study was carried out to study the stability of haloperidol tablets and phenytoin capsules that are light-sensitive and hygroscopic respectively. Validated HPLC-UV assays were first established for quantification of these two compounds. The medications involved were put in the Swisslog and sampled every week for one month. The collected data was analysed and showed no degradation over time. This study also explored an alternative approach for drug stability determination-Raman spectroscopy. The advantage of Raman spectroscopy is its high time efficiency and non-destructive nature. The results suggest that drug degradation can indeed be detected using Raman microscopy, but further research is needed to establish this approach for quantification or qualification of compounds. NanoRam®, a portable Raman spectrocope was also used alongside Raman microscopy but was unsuccessful in detecting degradation in this study.

Keywords: drug stability, haloperidol, HPLC, phenytoin, raman spectroscopy, Swisslog

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Authors: Hashim Isam Jameel Al-Safi, P. Ranjan Sarukkalige

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Climate change is likely to impact the Australian continent by changing the trends of rainfall, increasing temperature, and affecting the accessibility of water quantity and quality. This study investigates the possible impacts of future climate change on the hydrological system of the Harvey River catchment in Western Australia by using the conceptual modelling approach (HBV mode). Daily observations of rainfall and temperature and the long-term monthly mean potential evapotranspiration, from six weather stations, were available for the period (1961-2015). The observed streamflow data at Clifton Park gauging station for 33 years (1983-2015) in line with the observed climate variables were used to run, calibrate and validate the HBV-model prior to the simulation process. The calibrated model was then forced with the downscaled future climate signals from a multi-model ensemble of fifteen GCMs of the CMIP3 model under three emission scenarios (A2, A1B and B1) to simulate the future runoff at the catchment outlet. Two periods were selected to represent the future climate conditions including the mid (2046-2065) and late (2080-2099) of the 21^st century. A control run, with the reference climate period (1981-2000), was used to represent the current climate status. The modelling outcomes show an evident reduction in the mean annual streamflow during the mid of this century particularly for the A1B scenario relative to the control run. Toward the end of the century, all scenarios show a relatively high reduction trends in the mean annual streamflow, especially the A1B scenario, compared to the control run. The decline in the mean annual streamflow ranged between 4-15% during the mid of the current century and 9-42% by the end of the century.

Keywords: climate change impact, Harvey catchment, HBV model, hydrological modelling, GCMs, LARS-WG

Procedia PDF Downloads 241

Authors: Simon Mauma Efange

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The main aims of this research were to describe, in co-relational terms, the relationship, if any, between reading comprehension and academic achievement in science studied at the secondary level and, secondly, to find out possible trends in gender differences, such as whether boys would perform better than girls or vice versa. This research employed a quantitative design. Two kinds of instruments were employed: the Oxford Online Placement Test and the Local Assessment System Test. The Oxford Online Placement Test assesses students' English level quickly and easily. The results of these tests were subjected to statistical analysis using a special statistical software called SPSS. Statistical tools such as mean, standard deviation, percentages, frequencies, t-tests, and Pearson’s coefficient of correlation were used for the analysis of the results. Results of the t-test showed that the means are significantly different. Calculating the p-value revealed that the results were extremely statistically significant at p <.05. The value of r (Pearson correlation coefficient) was 0.2868. Although technically there is a positive correlation, the relationship between the variables is only weak (the closer the value is to zero, the weaker the relationship). However, in conclusion, calculations from the t-test using SPSS revealed that the results were statistically significant at p <.05, confirming a relationship between the two variables, and high scores in reading will give rise to slightly high scores in science. The research also revealed that having a high score in reading comprehension doesn’t necessarily mean having a high score in science or vice versa. Female subjects performed much better than male subjects in both tests, which is in line with the literature reviewed for this research.

Keywords: achievement in science, achievement in English, and bilingual students, relationship

Procedia PDF Downloads 37

Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

Procedia PDF Downloads 137

Authors: Adam Patterson

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This study analyzes the self-reported experiences of virtual reality users to develop insight into an optimal learning path for education within virtual reality. This research uses a sample of 1000 observations to statistically define factors influencing (i) immersion level and (ii) motion sickness rating for virtual reality experience respondents of college age. This paper recommends an efficient duration for each virtual reality session, to minimize sickness and maximize engagement, utilizing modern machine learning methods such as association rules. The goal of this research, in augmentation with previous literature, is to inform logistical decisions relating to implementation of pilot instruction for virtual reality at the collegiate level. Future research will include a Randomized Control Trial (RCT) to quantify the effect of virtual reality education on student learning outcomes and engagement measures. Current research aims to maximize the treatment effect within the RCT by optimizing the learning benefits of virtual reality. Results suggest significant gender heterogeneity amongst likelihood of reporting motion sickness. Females are 1.7 times more likely, than males, to report high levels of motion sickness resulting from a virtual reality experience. Regarding duration, respondents were 1.29 times more likely to select the lowest level of motion sickness after an engagement lasting between 24.3 and 42 minutes. Conversely, respondents between 42 to 60 minutes were 1.2 times more likely to select the higher levels of motion sickness.

Keywords: applications and integration of e-education, practices and cases in e-education, systems and technologies in e-education, technology adoption and diffusion of e-learning

Procedia PDF Downloads 51

Authors: Javad Mohiti-Ardekani, Shabodin Asadii, Ali Moradi

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Introduction: Curcumin, the yellow pigment in turmeric, has been shown as an anti-diabetic agent for centuries but only in recent few years, its mechanism of action has been under investigation. Some studies showed that curcumin might exert its anti-diabetic effect via increasing glucose transporter isotype-4 (GLUT4) gene and glycoprotein contents in cells. To investigate this possibility, we investigate the effects of extract and commercial curcumin with and without insulin on GLUT4 translocation from intracellular compartments of nuclear or endoplasmic reticulum membranes (N/ER) into the cytoplasmic membrane (CM). Methods and Material: C2C12 myoblastic cell line were seeded in DMEM plus 20 % FBS and differentiated to myotubes using 2 % horse serum. After myotubes formation, 40 µmolar Extract and Commercial curcumin, with or without insulin as intervention, and as control 1 % DMSO were added for 3 h. Cells were washed and homogenized followed by ultracentrifuge fractionation, protein separation by SDS-PAGE and GLUT4 detection using semi-quantitative Western blotting. Data analysis was done by two independent samples t-test for comparison of mean ± SD of GLUT4 percent in categories. GLUT4 contents were higher in CM groups curcumin and curcumin with insulin in comparison to 1 % DMSO-treated myotubes control group. Results: As our results have shown extract and commercial curcumin induces GLUT4 translocation from intra-cell into cell surface. The results have also shown synergic effect of curcumin on translocation of GLUT4 from intra-cell into cell surface in the presence of 100 nm insulin. Discussion: We conclude that curcumin may be a choice of type-2 diabetes mellitus treatment because its extract and commercial enhances GLUT4 contents in CM where it facilitates glucose entrance into the cell. However, it is necessary to trace the signaling pathways which are activated by curcumin.

Keywords: Curcumin, insulin, Diabetes type-2, GLUT4

Procedia PDF Downloads 223

Authors: Ewa M. Laskowska, Jorn Vatn

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Industry 4.0 focuses on digital optimization of industrial processes. The idea is to use extracted data in order to build a decision support model enabling use of those data for real time decision making. In terms of predictive maintenance, the desired decision support tool would be a model enabling prognostics of system's health based on the current condition of considered equipment. Within area of system prognostics and health management, a commonly used health indicator is Remaining Useful Lifetime (RUL) of a system. Because the RUL is a random variable, it has to be estimated based on available health indicators. Health indicators can be of different types and come from different sources. They can be process variables, equipment performance variables, data related to number of experienced failures, etc. The aim of this study is the analysis of performance variables of emergency shutdown valves (ESV) used in oil and gas industry. ESV is inspected periodically, and at each inspection torque and time of valve operation are registered. The data will be analyzed by means of machine learning or statistical analysis. The purpose is to investigate whether the available data could be used as a health indicator for a prognostic purpose. The second objective is to examine what is the most efficient way to incorporate the data into predictive model. The idea is to check whether the data can be applied in form of explanatory variables in Markov process or whether other stochastic processes would be a more convenient to build an RUL model based on the information coming from registered data.

Keywords: emergency shutdown valves, health indicator, prognostics, remaining useful lifetime, RUL

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Authors: Fasil Wagnew, Kerri Viney, Kefyalew Addis Alene, Matthew Kelly, Darren Gray

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Background: Undernutrition is a risk factor for tuberculosis (TB), including poor treatment outcomes. However, evidence regarding the effect of undernutrition on TB treatment outcomes is not well understood. We aimed to evaluate the effect of undernutrition on sputum culture conversion and treatment outcomes among people with multi-drug resistance (MDR)-TB. Methods: We searched for publications in the Medline, Embase, Scopus, and Web of Science databases without restrictions on geography or year of publication. We conducted a random-effect meta-analysis to estimate the effects of undernutrition on sputum culture conversion and treatment outcomes. Two reviewers independently assessed the study eligibility, extracted the necessary information, and assessed the risk of bias. Depending on the nature of the data, odds ratio (OR) and hazard ratio (HR) with 95% confidence intervals (CIs) were used to summarize the effect estimates. Potential publication bias was checked using funnel plots and Egger’s tests. Results: Of 2358 records screened, 59 studies comprising a total of 31,254 people with MDR-TB were included. Undernutrition was significantly associated with a lower sputum culture conversion rate (HR 0·7, 95% CI 0·6–0·9, I2=67·1%) and a higher rate of mortality (OR 2·9, 95%CI 2·1–3·8, I2=23·7%) and unfavourable treatment outcomes (OR 1·8, 95%CI 1·5–2·0, I2=72·7%). There was no statistically significant publication bias in the included studies. Three studies were low, forty-two studies were moderate, and fourteen studies were high quality. Interpretations: Undernutrition was significantly associated with unfavourable treatment outcomes, including mortality and lower sputum culture conversion among people with MDR-TB. These findings have implications for supporting targeted nutritional interventions alongside standardised second-line TB drugs.

Keywords: undernutrition, MDR-TB, sputum culture conversion, treatment outcomes, meta-analysis

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Authors: Larbi Belagraa, Miloud Beddar, Abderrazak Bouzid

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The needs of the construction sector still increasing for concrete. However, the shortage of natural resources of aggregate could be a problem for the concrete industry, in addition to the negative impact on the environment due to the demolition wastes. Recycling aggregate from construction and demolition (C&D) waste presents a major interest for users and researchers of concrete since this constituent can occupies more than 70% of concrete volume. The aim of the study here in is to assess the effect of sulfate resistant cement combined with the local mineral addition of marble waste fillers on the mechanical behavior of a recycled aggregate concrete (RAC). Physical and mechanical properties of RAC including the density, the flexural and the compressive strength were studied. The non destructive test methods (pulse-velocity, rebound hammer) were performed . The results obtained were compared to crushed aggregate concrete (CAC) using the normal compressive testing machine test method. The optimal content of 5% marble fillers showed an improvement for both used test methods (compression, flexion and NDT). Non-destructive methods (ultrasonic and rebound hammer test) can be used to assess the strength of RAC, but a correction coefficient is required to obtain a similar value to the compressive strength given by the compression tests. The study emphasizes that these waste materials can be successfully and economically utilized as additional inert filler in RAC formulation within similar performances compared to a conventional concrete.

Keywords: marble waste fillers, mechanical strength, natural aggregate, non-destructive testing (NDT), recycled aggregate concrete

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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 119

Authors: Mahmoud Ashraf Farouk

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Shipping transportation is the foremost imperative mode of transportation in universal coordination. At display, more than 2/3 of the full worldwide exchange volume accounts for shipping transportation. Ships are utilized as an implies of marine transportation, introducing large-power diesel motors with exhaust containing nitrogen oxide NOx, sulfur oxide SOx, carbo di-oxide CO₂, particular matter PM10, hydrocarbon HC and carbon mono-oxide CO which are the most dangerous contaminants found in exhaust gas from ships. Ships radiating a large amount of exhaust gases have become a significant cause of pollution in the air in coastal areas, harbors and oceans. Therefore, IMO (the International Maritime Organization) has established rules to reduce this emission. This experiment shows the measurement of the exhaust gases emitted from the Aida IV ship's main engine using marine diesel oil fuel (MDO). The measurement is taken by the Sensonic2000 device on 85% load, which is the main sailing load. Moreover, the paper studies different emission reduction technologies as an alternative fuel, which as liquefied natural gas (LNG) applied to the system and reduction technology which is represented as selective catalytic reduction technology added to the marine diesel oil system (MDO+SCR). The experiment calculated the amount of nitrogen oxide NOx, sulfur oxide SOx, carbon-di-oxide CO₂, particular matter PM10, hydrocarbon HC and carbon mono-oxide CO because they have the most effect on the environment. The reduction technologies are applied on the same ship engine with the same load. Finally, the study found that MDO+SCR is the more efficient technology for the Aida IV ship as a training and supply ship due to low consumption and no need to modify the engine. Just add the SCR system to the exhaust line, which is easy and cheapest. Moreover, the differences between them in the emission are not so big.

Keywords: marine, emissions, reduction, shipping

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Authors: Sridhar Rapuru, D. Mallikarjunreddy, Rajanarendra Sai

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In this reign of the internet, the access of any multimedia file to the users at any time with a superior quality is needed. To achieve this goal, it is very important to have a good network without any interruptions between the satellites along with various earth stations. For that purpose, a high speed inter-satellite optical wireless communication system (IsOWC) is designed with space and polarization diversity techniques. IsOWC offers a high bandwidth, small size, less power requirement and affordable when compared with the present microwave satellite systems. To improve the efficiency and to reduce the propagation delay, inter-satellite link is established between the satellites. High accurate tracking systems are required to establish the reliable connection between the satellites as they have their own orbits. The only disadvantage of this IsOWC system is laser beam width is narrower than the RF because of this highly accurate tracking system to meet this requirement. The satellite uses the 'ephemerides data' for rough pointing and tracking system for fine pointing to the other satellite. In this proposed IsOWC system, laser light is used as a wireless connectedness between the source and destination and free space acts as the channel to carry the message. The proposed system will be designed, simulated and analyzed for 6000km with an improvement of data rate over previously existing systems. The performance parameters of the system are Q-factor, eye opening, bit error rate, etc., The proposed system for Inter-satellite Optical Wireless Communication System Design Using Diversity Techniques finds huge scope of applications in future generation communication purposes.

Keywords: inter-satellite optical wireless system, space and polarization diversity techniques, line of sight, bit error rate, Q-factor

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Authors: A. Elmethnani, A. Jroud

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This coastal crude oil refinery is situated north of a big city west of Tripoli; the city then could be highly prone to downwind refinery emissions where the NNE wind direction is prevailing through most seasons of the year. Furthermore, due to the absence of an air quality monitoring network and scarce emission data available for the neighboring community, nearby residents have serious worries about the impacts of the oil refining operations on local air quality. In responding to these concerns, a short term survey has performed for three consecutive days where a semi-continues mobile monitoring approach has developed effectively in this study; the monitoring station (Compact AQM 65 AeroQual) was mounted on a vehicle to move quickly between locations, measurements of 10 minutes averaging of 60 seconds then been taken at each fixed sampling point. The downwind ambient concentration of CO, H₂S, NOₓ, NO₂, SO₂, PM₁, PM₂.₅ PM₁₀, and TSP were measured at carefully chosen sampling locations, ranging from 200m nearby the fence-line passing through the city center up to 4.7 km east to attain best spatial coverage. Results showed worrying levels of PM₂.₅ PM₁₀, and TSP at one sampling location in the city center, southeast of the refinery site, with an average mean of 16.395μg/m³, 33.021μg/m³, and 42.426μg/m³ respectively, which could be attributed to road traffic. No significant concentrations have been detected for other pollutants of interest over the study area, as levels observed for CO, SO₂, H₂S, NOₓ, and NO₂ haven’t respectively exceeded 1.707 ppm, 0.021ppm, 0.134 ppm, 0.4582 ppm, and 0.0018 ppm, which was at the same sampling locations as well. Although it wasn’t possible to compare the results with the Libyan air quality standards due to the difference in the averaging time period, the technique was adequate for the baseline air quality screening procedure. Overall, findings primarily suggest modeling of dispersion of the refinery emissions to assess the likely impact and spatial-temporal distribution of air pollutants.

Keywords: air quality, mobil monitoring, oil refinery

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Authors: Ahmed H. Elkholy

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An elastic analysis is developed to obtain the distribution of stresses, strains, bending moment and deformation for a thin hollow, variable thickness cylindrical specimen when subjected to different biaxial loadings. The specimen was subjected to a combination of internal pressure, axial tensile loading and external pressure. Several axial to circumferential stress ratios were investigated in detail. The analytical model was then validated using experimental results obtained from a test rig using several biaxial loadings. Based on the preliminary results obtained, the specimen was then modified geometrically to ensure uniform strain distribution through its wall thickness and along its gauge length. The new design of the specimen has a higher buckling strength and a maximum value of equivalent stress according to the maximum distortion energy theory. A cyclic function generator of the standard servo-controlled, electro-hydraulic testing machine is used to generate a specific signal shape (sine, square,…) at a certain frequency. The two independent controllers of the electronic circuit cause an independent movement to each servo-valve piston. The movement of each piston pressurizes the upper and lower sides of the actuators alternately. So, the specimen will be subjected to axial and diametral loads independent of each other. The hydraulic system has two different pressures: one pressure will be responsible for axial stress produced in the specimen and the other will be responsible for the tangential stress. Changing the two pressure ratios will change the stress ratios accordingly. The only restriction on the maximum stress obtained is the capacity of the testing system and specimen instability due to buckling.

Keywords: biaxial, fatigue, stress, testing

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Authors: Jeries Khoury

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The use of legendary, folkloric and religious symbols is one of the most important phenomena in modern Arabic poetry. Interestingly enough, most of the modern Arabic poetry’s pioneers were so fascinated by the biblical symbols and they managed to use many modern techniques to make these symbols adequate for their personal life from one side and fit to their Islamic beliefs from the other. One of the most famous poets to do so was al-Sayya:b. The way he employed one of these symbols ‘job’, the new features he adds to this character and the link between this character and his personal life will be discussed in this study. Besides, the study will examine the influence of al-Sayya:b on another modern poet Saadi Yusuf, who, following al-Sayya:b, used the character of Job in a special way, by mixing its features with al-Sayya:b’s personal features and in this way creating a new mixed character. A semantic, cultural and comparative analysis of the poems written by al-Sayya:b himself and the other poets who evoked the mixed image of al-Sayya:b-Job, can reveal the changes Arab poets made to the original biblical figure of Job to bring it closer to Islamic culture. The paper will make an intensive use of intertextuality idioms in order to shed light on the network of relations between three kinds of texts (indeed three ‘palimpsests’: 1- biblical- the primary text; 2- poetic- al-Syya:b’s secondary version; 3- re-poetic- Sa’di Yusuf’s tertiary version). The bottom line in this paper is that that al-Sayya:b was directly influenced by the dramatic biblical story of Job more than the brief Quranic version of the story. In fact, the ‘new’ character of Job designed by al-Sayya:b himself differs from the original one in many aspects that we can safely say it is the Sayyabian-Job that cannot be found in the poems of any other poets, unless they are evoking the own tragedy of al-Sayya:b himself, like what Saadi Yusuf did.

Keywords: Arabic poetry, intertextuality, job, meter, modernism, symbolism

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Authors: Aanh Eduardo Dimate-Garcia, Diana Carolina Rodriguez-Romero, Edna Yuliana Gonzalez Rincon, Diana Marcela Pardo Lopez, Yessica Garibello Cubillos

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Musculoskeletal disorders (MD) are the new epidemic of chronic diseases, are multifactorial and affect the different productive sectors. Although there are multiple instruments to evaluate the static and dynamic load, the method of repetitive occupational action (OCRA) seems to be an attractive option. Objective: It is aimed to analyze the use of the OCRA method and the prevalence of MD in workers of various productive sectors according to the literature (2007-2018). Materials and Methods: A literature review (following the PRISMA statement) of studies aimed at assessing the level of biomechanical risk (OCRA) and the prevalence of MD in the databases Scielo, Science Direct, Scopus, ProQuest, Gale, PubMed, Lilacs and Ebsco was realized; 7 studies met the selection criteria; the majority are quantitative (cross section). Results: it was evidenced (gardening and flower-growers) in this review that 79% of the conditions related to the task require physical requirements and involve repetitive movements. In addition, of the high appearance of DM in the high-low back, upper and lower extremities that are produced by the frequency of the activities carried out (footwear production). Likewise, there was evidence of 'very high risks' of developing MD (salmon industry) and a medium index (OCRA) for repetitive movements that require special care (U-Assembly line). Conclusions: the review showed the limited use of the OCRA method for the detection of MD in workers from different sectors, and this method can be used for the detection of biomechanical risk and the appearance of MD.

Keywords: checklist, cumulative trauma disorders, musculoskeletal diseases, repetitive movements

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Authors: Lal Hussain, Wajid Aziz, Imtiaz Ahmed Awan, Sharjeel Saeed

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Multiscale entropy analysis (MSE) is a useful technique recently developed to quantify the dynamics of physiological signals at different time scales. This study is aimed at investigating the electroencephalogram (EEG) signals to analyze the background activity of alcoholic and control subjects by inspecting various coarse-grained sequences formed at different time scales. EEG recordings of alcoholic and control subjects were taken from the publically available machine learning repository of University of California (UCI) acquired using 64 electrodes. The MSE analysis was performed on the EEG data acquired from all the electrodes of alcoholic and control subjects. Mann-Whitney rank test was used to find significant differences between the groups and result were considered statistically significant for p-values<0.05. The area under receiver operator curve was computed to find the degree separation between the groups. The mean ranks of MSE values at all the times scales for all electrodes were higher control subject as compared to alcoholic subjects. Higher mean ranks represent higher complexity and vice versa. The finding indicated that EEG signals acquired through electrodes C3, C4, F3, F7, F8, O1, O2, P3, T7 showed significant differences between alcoholic and control subjects at time scales 1 to 5. Moreover, all electrodes exhibit significance level at different time scales. Likewise, the highest accuracy and separation was obtained at the central region (C3 and C4), front polar regions (P3, O1, F3, F7, F8 and T8) while other electrodes such asFp1, Fp2, P4 and F4 shows no significant results.

Keywords: electroencephalogram (EEG), multiscale sample entropy (MSE), Mann-Whitney test (MMT), Receiver Operator Curve (ROC), complexity analysis

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Authors: Khairul Zahreen Mohd Arof, Rahimah Muhamad

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Oil palm fiber (OPF) is a fibrous material produced from the waste of palm oil industry which is suitable to be used in construction industry. The applications of OPF in concrete can reduce the material costs and enhance concrete behavior. Dog-bone test provides significant results for investigating the behavior of fiber reinforced concrete under tensile loading. It is able to provide stress-strain profile, modulus of elasticity, stress at cracking point and total crack width. In this research, dog-bone tests have been conducted to analyze total crack width, stress-strain profile, and modulus of elasticity of OPFC. Specimens are in a dog-bone shape with a long notch in the middle as compared to the end, to ensure cracks occur only within the notch. Tests were instrumented using a universal testing machine Shimadzu 300kN, a linear variable differential transformer and two strain gauges. A total of nine specimens with different fibers at fiber volume fractions of 0.75%, 1.00%, and 1.25% have been tested to analyze the behavior under tensile loading. Also, three specimens of plain concrete fiber have been tested as control specimens. The tensile test of all specimens have been carried out for concrete age exceed 28 days. It shows that OPFC able to reduce total crack width. In addition, OPFC has higher cracking stress than plain concrete. The study shows plain concrete can be improved with the addition of OPF.

Keywords: cracks, crack width, dog-bone test, oil palm fiber concrete

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Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

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Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

Procedia PDF Downloads 142

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: H. Hakim, C. Kibert, C. Fabre, S. Monadizadeh

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Construction industry is an industry saddled with chronic problems of high waste generation. Waste management that is to ensure materials are utilized in an efficient manner would make a major contribution to mitigating the negative environmental impacts of construction waste including finite resources depletion and growing occupied landfill areas to name a few. Furthermore, ‘material resource efficiency’ has been found an economically smart approach specially when considered during the design phase. One effective strategy is to utilizing off-site construction process which includes a series of prefabricated systems such as mobile, modular, and HUD construction (Department of Housing and Urban Development manufactured buildings). These types of buildings are by nature material and resource-efficient. Despite conventional construction that is exposed to adverse weather conditions, manufactured construction production line is capable of creating repetitive units in a factory controlled environment. A factory can have several parallel projects underway with a high speed and in a timely manner which simplifies the storage of excess materials and re-allocating to the next projects. The literature reports that prefabricated construction significantly helps reduce errors, site theft, rework, and delayed problems and can ultimately lead to a considerable waste reduction. However, there is not sufficient data to quantify this reduction when it comes to a regular modular house in the U.S. Therefore, this manuscript aims to provide an analysis of waste originated from a manufactured factory trend. The analysis was made possible with several visits and data collection of Homes of Merits, a Florida Manufactured and Modular Homebuilder. The results quantify and verify a noticeable construction waste reduction.

Keywords: construction waste, modular construction, prefabricated buildings, waste management

Procedia PDF Downloads 249