Search results for: single laboratory validation approach
Commenced in January 2007
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Edition: International
Paper Count: 20288

Search results for: single laboratory validation approach

20018 Using Structured Analysis and Design Technique Method for Unmanned Aerial Vehicle Components

Authors: Najeh Lakhoua

Abstract:

Introduction: Scientific developments and techniques for the systemic approach generate several names to the systemic approach: systems analysis, systems analysis, structural analysis. The main purpose of these reflections is to find a multi-disciplinary approach which organizes knowledge, creates universal language design and controls complex sets. In fact, system analysis is structured sequentially by steps: the observation of the system by various observers in various aspects, the analysis of interactions and regulatory chains, the modeling that takes into account the evolution of the system, the simulation and the real tests in order to obtain the consensus. Thus the system approach allows two types of analysis according to the structure and the function of the system. The purpose of this paper is to present an application of system analysis of Unmanned Aerial Vehicle (UAV) components in order to represent the architecture of this system. Method: There are various analysis methods which are proposed, in the literature, in to carry out actions of global analysis and different points of view as SADT method (Structured Analysis and Design Technique), Petri Network. The methodology adopted in order to contribute to the system analysis of an Unmanned Aerial Vehicle has been proposed in this paper and it is based on the use of SADT. In fact, we present a functional analysis based on the SADT method of UAV components Body, power supply and platform, computing, sensors, actuators, software, loop principles, flight controls and communications). Results: In this part, we present the application of SADT method for the functional analysis of the UAV components. This SADT model will be composed exclusively of actigrams. It starts with the main function ‘To analysis of the UAV components’. Then, this function is broken into sub-functions and this process is developed until the last decomposition level has been reached (levels A1, A2, A3 and A4). Recall that SADT techniques are semi-formal; however, for the same subject, different correct models can be built without having to know with certitude which model is the good or, at least, the best. In fact, this kind of model allows users a sufficient freedom in its construction and so the subjective factor introduces a supplementary dimension for its validation. That is why the validation step on the whole necessitates the confrontation of different points of views. Conclusion: In this paper, we presented an application of system analysis of Unmanned Aerial Vehicle components. In fact, this application of system analysis is based on SADT method (Structured Analysis Design Technique). This functional analysis proved the useful use of SADT method and its ability of describing complex dynamic systems.

Keywords: system analysis, unmanned aerial vehicle, functional analysis, architecture

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20017 The Gradient Complex Protective Coatings for Single Crystal Nickel Alloys

Authors: Evgeniya Popova, Vladimir Lesnikov, Nikolay Popov

Abstract:

High yield complex coatings have been designed for thermally stressed cooled HP turbine blades from single crystal alloys ZHS32-VI-VI and ZHS36 with crystallographic orientation [001]. These coatings provide long-term protection of single crystal blades during operation. The three-layer coatings were prepared as follows: the diffusion barrier layer formation on the alloy surface, the subsequent deposition of the condensed bilayer coatings consisting of an inner layer based on Ni-Cr-Al-Y systems and an outer layer based on the alloyed β-phase. The structure, phase composition of complex coatings and reaction zone interaction with the single-crystal alloys ZHS32-VI and ZHS36-VI were investigated using scanning electron microscope (SEM). The effect of complex protective coatings on the properties of heat-resistant nickel alloys was studied.

Keywords: single crystal nickel alloys, complex heat-resistant coatings, structure, phase composition, properties

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20016 Metropolis-Hastings Sampling Approach for High Dimensional Testing Methods of Autonomous Vehicles

Authors: Nacer Eddine Chelbi, Ayet Bagane, Annie Saleh, Claude Sauvageau, Denis Gingras

Abstract:

As recently stated by National Highway Traffic Safety Administration (NHTSA), to demonstrate the expected performance of a highly automated vehicles system, test approaches should include a combination of simulation, test track, and on-road testing. In this paper, we propose a new validation method for autonomous vehicles involving on-road tests (Field Operational Tests), test track (Test Matrix) and simulation (Worst Case Scenarios). We concentrate our discussion on the simulation aspects, in particular, we extend recent work based on Importance Sampling by using a Metropolis-Hasting algorithm (MHS) to sample collected data from the Safety Pilot Model Deployment (SPMD) in lane-change scenarios. Our proposed MH sampling method will be compared to the Importance Sampling method, which does not perform well in high-dimensional problems. The importance of this study is to obtain a sampler that could be applied to high dimensional simulation problems in order to reduce and optimize the number of test scenarios that are necessary for validation and certification of autonomous vehicles.

Keywords: automated driving, autonomous emergency braking (AEB), autonomous vehicles, certification, evaluation, importance sampling, metropolis-hastings sampling, tests

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20015 Reduction of False Positives in Head-Shoulder Detection Based on Multi-Part Color Segmentation

Authors: Lae-Jeong Park

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The paper presents a method that utilizes figure-ground color segmentation to extract effective global feature in terms of false positive reduction in the head-shoulder detection. Conventional detectors that rely on local features such as HOG due to real-time operation suffer from false positives. Color cue in an input image provides salient information on a global characteristic which is necessary to alleviate the false positives of the local feature based detectors. An effective approach that uses figure-ground color segmentation has been presented in an effort to reduce the false positives in object detection. In this paper, an extended version of the approach is presented that adopts separate multipart foregrounds instead of a single prior foreground and performs the figure-ground color segmentation with each of the foregrounds. The multipart foregrounds include the parts of the head-shoulder shape and additional auxiliary foregrounds being optimized by a search algorithm. A classifier is constructed with the feature that consists of a set of the multiple resulting segmentations. Experimental results show that the presented method can discriminate more false positive than the single prior shape-based classifier as well as detectors with the local features. The improvement is possible because the presented approach can reduce the false positives that have the same colors in the head and shoulder foregrounds.

Keywords: pedestrian detection, color segmentation, false positive, feature extraction

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20014 DEMs: A Multivariate Comparison Approach

Authors: Juan Francisco Reinoso Gordo, Francisco Javier Ariza-López, José Rodríguez Avi, Domingo Barrera Rosillo

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The evaluation of the quality of a data product is based on the comparison of the product with a reference of greater accuracy. In the case of MDE data products, quality assessment usually focuses on positional accuracy and few studies consider other terrain characteristics, such as slope and orientation. The proposal that is made consists of evaluating the similarity of two DEMs (a product and a reference), through the joint analysis of the distribution functions of the variables of interest, for example, elevations, slopes and orientations. This is a multivariable approach that focuses on distribution functions, not on single parameters such as mean values or dispersions (e.g. root mean squared error or variance). This is considered to be a more holistic approach. The use of the Kolmogorov-Smirnov test is proposed due to its non-parametric nature, since the distributions of the variables of interest cannot always be adequately modeled by parametric models (e.g. the Normal distribution model). In addition, its application to the multivariate case is carried out jointly by means of a single test on the convolution of the distribution functions of the variables considered, which avoids the use of corrections such as Bonferroni when several statistics hypothesis tests are carried out together. In this work, two DEM products have been considered, DEM02 with a resolution of 2x2 meters and DEM05 with a resolution of 5x5 meters, both generated by the National Geographic Institute of Spain. DEM02 is considered as the reference and DEM05 as the product to be evaluated. In addition, the slope and aspect derived models have been calculated by GIS operations on the two DEM datasets. Through sample simulation processes, the adequate behavior of the Kolmogorov-Smirnov statistical test has been verified when the null hypothesis is true, which allows calibrating the value of the statistic for the desired significance value (e.g. 5%). Once the process has been calibrated, the same process can be applied to compare the similarity of different DEM data sets (e.g. the DEM05 versus the DEM02). In summary, an innovative alternative for the comparison of DEM data sets based on a multinomial non-parametric perspective has been proposed by means of a single Kolmogorov-Smirnov test. This new approach could be extended to other DEM features of interest (e.g. curvature, etc.) and to more than three variables

Keywords: data quality, DEM, kolmogorov-smirnov test, multivariate DEM comparison

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20013 Finite Element Simulation of Embankment Bumps at Bridge Approaches, Comparison Study

Authors: F. A. Hassona, M. D. Hashem, R. I. Melek, B. M. Hakeem

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A differential settlement at the end of a bridge near the interface between the abutment and the embankment is a persistent problem for highway agencies. The differential settlement produces the common ‘bump at the end of the bridge’. Reduction in steering response, distraction to the driver, added risk and expense to maintenance operation, and reduction in a transportation agency’s public image are all undesirable effects of these uneven and irregular transitions. This paper attempts to simulate the bump at the end of the bridge using PLAXIS finite element 2D program. PLAXIS was used to simulate a laboratory model called Bridge to Embankment Simulator of Transition (B.E.S.T.) device which was built by others to investigate this problem. A total of six numerical simulations were conducted using hardening- soil model with rational assumptions of missing soil parameters to estimate the bump at the end of the bridge. The results show good agreements between the numerical and the laboratory models. Important factors influencing bumps at bridge ends were also addressed in light of the model results.

Keywords: bridge approach slabs, bridge bump, hardening-soil, PLAXIS 2D, settlement

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20012 Comparison of Selected Pier-Scour Equations for Wide Piers Using Field Data

Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

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Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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20011 Mediating Role of Burnout in Personality and Marital Satisfaction of Single and Dual Career Couples

Authors: Sara Subhan

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Married couples tend to experience various bio-psycho-social issues that may eventually impact the quality of their marital relationship and mental wellbeing. This study aimed to find out the comparison between the single and dual-career couples’ personality, burnout and marital satisfaction. For that purpose Big Five Inventory, Couple Satisfaction Inventory, and Maslach Burnout Inventory-General Survey was used to measure the relationship between variables. The main study was carried out on 200 samples of single and dual-earner couples with the age range of 23-52 (mean= 34.58; standard deviation= 6.51) by using a purposive sampling strategy. The results showed that burnout tendencies like exhaustion, cynicism and professional efficacy are playing a mediation role between the personality and marital satisfaction of both single and dual career couples. Also, the results revealed that dual-career couples are more likely to have marital satisfaction as compared to single career couples. The results were further discussed in the light of its implications in its cultural context and counseling areas.

Keywords: dual career couples, marital satisfaction, burnout tendencies, personality

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20010 Camera Model Identification for Mi Pad 4, Oppo A37f, Samsung M20, and Oppo f9

Authors: Ulrich Wake, Eniman Syamsuddin

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The model for camera model identificaiton is trained using pretrained model ResNet43 and ResNet50. The dataset consists of 500 photos of each phone. Dataset is divided into 1280 photos for training, 320 photos for validation and 400 photos for testing. The model is trained using One Cycle Policy Method and tested using Test-Time Augmentation. Furthermore, the model is trained for 50 epoch using regularization such as drop out and early stopping. The result is 90% accuracy for validation set and above 85% for Test-Time Augmentation using ResNet50. Every model is also trained by slightly updating the pretrained model’s weights

Keywords: ​ One Cycle Policy, ResNet34, ResNet50, Test-Time Agumentation

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20009 The Effect of Withania Somnifera in Alloxan Induced Diabetic Rabbits

Authors: Farah Ali, Tehreem Fayyaz, Musadiq Idris

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The present work was undertaken to investigate effects of various extracts of withania somnifera for anti-diabetic activity in alloxan induced diabetic rabbits. Rabbits were acclimatized for a week to standard laboratory temperature. Animals were fed according to a strict schedule (8 am, 3 pm and 10 pm) with green fodder (Medicago sativa) and tap water ad libitum. Animals were divided into nine groups of six rabbits each in a random manner. Body weights and physical activities of all rabbits were recorded before start of experiments. The animals of group 1 and 2 were given lactose (250 mg/kg, p.o) and Withania somniferaroot powder (100 mg/kg, p.o) respectively daily from day 1-20. Animals of group 3 were given alloxan (100 mg/kg, i.v) as a single dose on day 1. Powdered root of Withania somnifera in the doses of 100, 150, 200 mg/kg and its aqueous and ethanol extracts (equivalent to 200 mg/kg of crude drug) were given to the treated animals (groups 4-8), respectively by oral route for three weeks (day 1-20o.d), along with alloxan (100 mg/kg, i.v) as a single dose on day 1. Group 9 was treated with metformin (200 mg/kg, p.o) daily from day 1-20, along with a single dose of alloxan (100 mg/ kg, i.v) on day 1. Fasting serum glucose concentration in groups 3-9 was increased significantly (p<0.05) on day 3, with a maximum increase (215.3 mg/dl) in animals of toxic control (TC) group (3) on day 21 of the experiment as compared to normal control (NC) group (1). Effects of different doses (100, 150, 200 mg/kg, p.o) of W. somnifera root powder (WS) decreased the fasting serum glucose concentration as compared to toxic control group, with a maximum decrease (88.3 mg/dl) in group 2 (treated control) on day 21 of the experiment. Metformin (200 mg/kg, p.o) (reference control), aqueous extract (AWS) and ethanol extract (EWS) of W. somnifera (equivalent to 100 mg/kg W.somnifera root, p.o) antagonized the effects of alloxan as compared to toxic control group. These results indicate that the W. somnifera possess significant anti–diabetic activity.

Keywords: diabetes, serum, glucose, blood, sugar, rabbits

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20008 Modeling and Validation of Microspheres Generation in the Modified T-Junction Device

Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

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This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

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20007 Bacteriological Quality of Commercially Prepared Fermented Ogi (AKAMU) Sold in Some Parts of South Eastern Nigeria

Authors: Alloysius C. Ogodo, Ositadinma C. Ugbogu, Uzochukwu G. Ekeleme

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Food poisoning and infection by bacteria are of public health significance to both developing and developed countries. Samples of ogi (akamu) prepared from white and yellow variety of maize sold in Uturu and Okigwe were analyzed together with the laboratory prepared ogi for microbial quality using the standard microbiological methods. The analyses showed that both white and yellow variety had total bacterial counts (cfu/g) of 4.0 ×107 and 3.9 x 107 for the laboratory prepared ogi while the commercial ogi had 5.2 x 107 and 4.9 x107, 4.9 x107 and 4.5 x107, 5.4 x107 and 5.0 x107 for Eke-Okigwe, Up-gate and Nkwo-Achara market respectively. The Staphylococcal counts ranged from 2.0 x 102 to 5.0 x102 and 1.0 x 102 to 4.0 x102 for the white and yellow variety from the different markets while Staphylococcal growth was not recorded on the laboratory prepared ogi. The laboratory prepared ogi had no Coliform growth while the commercially prepared ogi had counts of 0.5 x103 to 1.6 x 103 for white variety and 0.3 x 103 to 1.1 x103 for yellow variety respectively. The Lactic acid bacterial count of 3.5x106 and 3.0x106 was recorded for the laboratory ogi while the commercially prepared ogi ranged from 3.2x106 to 4.2x106 (white variety) and 3.0 x106 to 3.9 x106 (yellow). The presence of bacteria isolates from the commercial and laboratory fermented ogi showed that Lactobacillus sp, Leuconostoc sp and Citrobacter sp were present in all the samples, Micrococcus sp and Klebsiella sp were isolated from Eke-Okigwe and ABSU-up-gate markets varieties respectively, E. coli and Staphylococcus sp were present in Eke-Okigwe and Nkwo-Achara markets while Salmonella sp were isolated from the three markets. Hence, there are chances of contracting food borne diseases from commercially prepared ogi. Therefore, there is the need for sanitary measures in the production of fermented cereals so as to minimize the rate of food borne pathogens during processing and storage.

Keywords: ogi, fermentation, bacterial quality, lactic acid bacteria, maize

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20006 Wind Turbine Powered Car Uses 3 Single Big C-Section Blades

Authors: K. Youssef, Ç. Hüseyin

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The blades of a wind turbine have the most important job of any wind turbine component; they must capture the wind and convert it into usable mechanical energy. The objective of this work is to determine the mechanical power of single big C-section of vertical wind turbine for wind car in a two-dimensional model. The wind car has a vertical axis with 3 single big C-section blades mounted at an angle of 120°. Moreover, the three single big C-section blades are directly connected to wheels by using various kinds of links. Gears are used to convert the wind energy to mechanical energy to overcome the load exercised on the main shaft under low speed. This work allowed a comparison of drag characteristics and the mechanical power between the single big C-section blades with the previous work on 3 C-section and 3 double C-section blades for wind car. As a result obtained from the flow chart the torque and power curves of each case study are illustrated and compared with each other. In particular, drag force and torque acting on each types of blade was taken at an airflow speed of 4 m/s, and an angular velocity of 13.056 rad/s.

Keywords: blade, vertical wind turbine, drag characteristics, mechanical power

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20005 A Comparative Study of Series-Connected Two-Motor Drive Fed by a Single Inverter

Authors: A. Djahbar, E. Bounadja, A. Zegaoui, H. Allouache

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In this paper, vector control of a series-connected two-machine drive system fed by a single inverter (CSI/VSI) is presented. The two stator windings of both machines are connected in series while the rotors may be connected to different loads, are called series-connected two-machine drive. Appropriate phase transposition is introduced while connecting the series stator winding to obtain decoupled control the two-machines. The dynamic decoupling of each machine from the group is obtained using the vector control algorithm. The independent control is demonstrated by analyzing the characteristics of torque and speed of each machine obtained via simulation under vector control scheme. The viability of the control techniques is proved using analytically and simulation approach.

Keywords: drives, inverter, multi-phase induction machine, vector control

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20004 NanoSat MO Framework: Simulating a Constellation of Satellites with Docker Containers

Authors: César Coelho, Nikolai Wiegand

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The advancement of nanosatellite technology has opened new avenues for cost-effective and faster space missions. The NanoSat MO Framework (NMF) from the European Space Agency (ESA) provides a modular and simpler approach to the development of flight software and operations of small satellites. This paper presents a methodology using the NMF together with Docker for simulating constellations of satellites. By leveraging Docker containers, the software environment of individual satellites can be easily replicated within a simulated constellation. This containerized approach allows for rapid deployment, isolation, and management of satellite instances, facilitating comprehensive testing and development in a controlled setting. By integrating the NMF lightweight simulator in the container, a comprehensive simulation environment was achieved. A significant advantage of using Docker containers is their inherent scalability, enabling the simulation of hundreds or even thousands of satellites with minimal overhead. Docker's lightweight nature ensures efficient resource utilization, allowing for deployment on a single host or across a cluster of hosts. This capability is crucial for large-scale simulations, such as in the case of mega-constellations, where multiple traditional virtual machines would be impractical due to their higher resource demands. This ability for easy horizontal scaling based on the number of simulated satellites provides tremendous flexibility to different mission scenarios. Our results demonstrate that leveraging Docker containers with the NanoSat MO Framework provides a highly efficient and scalable solution for simulating satellite constellations, offering not only significant benefits in terms of resource utilization and operational flexibility but also enabling testing and validation of ground software for constellations. The findings underscore the importance of taking advantage of already existing technologies in computer science to create new solutions for future satellite constellations in space.

Keywords: containerization, docker containers, NanoSat MO framework, satellite constellation simulation, scalability, small satellites

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20003 Human Action Retrieval System Using Features Weight Updating Based Relevance Feedback Approach

Authors: Munaf Rashid

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For content-based human action retrieval systems, search accuracy is often inferior because of the following two reasons 1) global information pertaining to videos is totally ignored, only low level motion descriptors are considered as a significant feature to match the similarity between query and database videos, and 2) the semantic gap between the high level user concept and low level visual features. Hence, in this paper, we propose a method that will address these two issues and in doing so, this paper contributes in two ways. Firstly, we introduce a method that uses both global and local information in one framework for an action retrieval task. Secondly, to minimize the semantic gap, a user concept is involved by incorporating features weight updating (FWU) Relevance Feedback (RF) approach. We use statistical characteristics to dynamically update weights of the feature descriptors so that after every RF iteration feature space is modified accordingly. For testing and validation purpose two human action recognition datasets have been utilized, namely Weizmann and UCF. Results show that even with a number of visual challenges the proposed approach performs well.

Keywords: relevance feedback (RF), action retrieval, semantic gap, feature descriptor, codebook

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20002 Knowledge and Practices on Waste Disposal Management Among Medical Technology Students at National University – Manila

Authors: John Peter Dacanay, Edison Ramos, Cristopher James Dicang

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Waste management is a global concern due to increasing waste production from changing consumption patterns and population growth. Proper waste disposal management is a critical aspect of public health and environmental protection. In the healthcare industry, medical waste is generated in large quantities, and if not disposed of properly, it poses a significant threat to human health and the environment. Efficient waste management conserves natural resources and prevents harm to human health, and implementing an effective waste management system can save human lives. The study aimed to assess the level of awareness and practices on waste disposal management, highlighting the understanding of proper disposal, potential hazards, and environmental implications among Medical Technology students. This would help to provide more recommendations for improving waste management practices in healthcare settings as well as for better waste management practices in educational institutions. From the collected data, a female of 21 years of age stands out among the respondents. With the frequency and percentage of medical technology students' knowledge of laboratory waste management being high, it indicates that all respondents demonstrated a solid understanding of proper disposal methods, regulations, risks, and handling procedures related to laboratory waste. That said, the findings emphasize the significance of education and awareness programs in equipping individuals involved in laboratory practices with the necessary knowledge to handle and dispose of hazardous and infectious waste properly. Most respondents demonstrate positive practices or are highly mannered in laboratory waste management, including proper segregation and disposal in designated containers. However, there are concerns about the occasional mixing of waste types, emphasizing the reiteration of proper waste segregation. Students show a strong commitment to using personal protective equipment and promptly cleaning up spills. Some students admit to improper disposal due to rushing, highlighting the importance of time management and safety prioritization. Overall, students follow protocols for hazardous waste disposal, indicating a responsible approach. The school's waste management system is perceived as adequate, but continuous assessment and improvement are necessary. Encouraging reporting of issues and concerns is crucial for ongoing improvement and risk mitigation. The analysis reveals a moderate positive relationship between the respondents' knowledge and practices regarding laboratory waste management. The statistically significant correlation with a p-value of 0.26 (p-value 0.05) suggests that individuals with higher levels of knowledge tend to exhibit better practices. These findings align with previous research emphasizing the pivotal role of knowledge in influencing individuals' behaviors and practices concerning laboratory waste management. When individuals possess a comprehensive understanding of proper procedures, regulations, and potential risks associated with laboratory waste, they are more inclined to adopt appropriate practices. Therefore, fostering knowledge through education and training is essential in promoting responsible and effective waste management in laboratory settings.

Keywords: waste disposal management, knowledge, attitude, practices

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20001 Learning in the Virtual Laboratory via Design of Automation Process for Wooden Hammers Marking

Authors: A. Javorova, J. Oravcova, K. Velisek

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The article summarizes the experience of technical subjects teaching methodologies using a number of software products to solve specific assigned tasks described in this paper. Task is about the problems of automation and mechanization in the industry. Specifically, it focuses on introducing automation in the wood industry. The article describes the design of the automation process for marking wooden hammers. Similar problems are solved by students in CA laboratory.

Keywords: CA system, education, simulation, subject

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20000 Copper Sulphate Effect on Cyprinus Carpio Common Fish Parasites

Authors: Jawdhari Abdulhusein, Dan Mihăilescu, Cristian-Emilian Pop, Nicolai Crăciun

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Cyprinus Carpio adult specimens were captured from a single spot location from the Danube River and transported to the Laboratory of Faculty of Biology, University of Bucharest. The specimens were measured, weighed and randomly divided in five groups for later Copper Sulphate (CuSO4) exposure, as well as one control group. From the control group, 3 specimens were immediately sacrificed and microscopically inspected for parasite’s presence in the gills. During the histological inspection of the control group specimens, Ichthyophthiriusmultifiliis, Gyrodactylu ssp., MyxobolusOviforis, and Trichodinacottidarumwere abundantly identified in the gills. The exposure to a single dose of CuSO4 per group took place for 7 days under controlled conditions: water alkalinity ≈ 100 mg/L, temperature 23–24 °C, oxygenation 7.40–7.80 mg/L, and pH 6.10–6.40, the parameters were monitored on an hourly basis and adjusted when needed. After the exposure, all specimens were sacrificed, and the gill tissues were inspected. It was found that concentrations of 0.10, 0.25 and 0.30 ppm of CuSO4 did not affect the presence of parasites, as for 0.40 ppm of CuSO4 it significantly affected onlyIchthyophthiriusmultifiliisandMyxobolusOviforis, while concentration 0.50 ppm of CuSO4 (≈0.20 ppm of Cu2+) eliminated all 4 parasites species previously present in the fish gills, also, there were some histopathological changes to the gills tissue. These findings suggest that low concentrations of CuSO4 treatment for fish parasites are a safe and economical option if used correctly for a brief length of time.

Keywords: copper sulphate, cyprinus carpio, parasites, danube river

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19999 Krill-Herd Step-Up Approach Based Energy Efficiency Enhancement Opportunities in the Offshore Mixed Refrigerant Natural Gas Liquefaction Process

Authors: Kinza Qadeer, Muhammad Abdul Qyyum, Moonyong Lee

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Natural gas has become an attractive energy source in comparison with other fossil fuels because of its lower CO₂ and other air pollutant emissions. Therefore, compared to the demand for coal and oil, that for natural gas is increasing rapidly world-wide. The transportation of natural gas over long distances as a liquid (LNG) preferable for several reasons, including economic, technical, political, and safety factors. However, LNG production is an energy-intensive process due to the tremendous amount of power requirements for compression of refrigerants, which provide sufficient cold energy to liquefy natural gas. Therefore, one of the major issues in the LNG industry is to improve the energy efficiency of existing LNG processes through a cost-effective approach that is 'optimization'. In this context, a bio-inspired Krill-herd (KH) step-up approach was examined to enhance the energy efficiency of a single mixed refrigerant (SMR) natural gas liquefaction (LNG) process, which is considered as a most promising candidate for offshore LNG production (FPSO). The optimal design of a natural gas liquefaction processes involves multivariable non-linear thermodynamic interactions, which lead to exergy destruction and contribute to process irreversibility. As key decision variables, the optimal values of mixed refrigerant flow rates and process operating pressures were determined based on the herding behavior of krill individuals corresponding to the minimum energy consumption for LNG production. To perform the rigorous process analysis, the SMR process was simulated in Aspen Hysys® software and the resulting model was connected with the Krill-herd approach coded in MATLAB. The optimal operating conditions found by the proposed approach significantly reduced the overall energy consumption of the SMR process by ≤ 22.5% and also improved the coefficient of performance in comparison with the base case. The proposed approach was also compared with other well-proven optimization algorithms, such as genetic and particle swarm optimization algorithms, and was found to exhibit a superior performance over these existing approaches.

Keywords: energy efficiency, Krill-herd, LNG, optimization, single mixed refrigerant

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19998 Implications of Optimisation Algorithm on the Forecast Performance of Artificial Neural Network for Streamflow Modelling

Authors: Martins Y. Otache, John J. Musa, Abayomi I. Kuti, Mustapha Mohammed

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The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance.

Keywords: streamflow, neural network, optimisation, algorithm

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19997 Comfort Evaluation of Summer Knitted Clothes of Tencel and Cotton Fabrics

Authors: Mona Mohamed Shawkt Ragab, Heba Mohamed Darwish

Abstract:

Context: Comfort properties of garments are crucial for the wearer, and with the increasing demand for cotton fabric, there is a need to explore alternative fabrics that can offer similar or superior comfort properties. This study focuses on comparing the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the aim of identifying fabrics that are more suitable for summer clothes. Research Aim: The aim of this study is to evaluate the comfort properties of tencel/cotton single jersey fabric and cotton single jersey fabric, with the goal of identifying fabrics that can serve as alternatives to cotton, considering their comfort properties for summer clothing. Methodology: An experimental, analytical approach was employed in this study. Two circular knitting machines were used to produce the fabrics, one with a 24 inches gauge and the other with a 28 inches gauge. Both fabrics were knitted with three different loop lengths (3.05 mm, 2.9 mm, and 2.6 mm) to obtain loose, medium, and tight fabrics for evaluation. Various comfort properties, including air permeability, water vapor permeability, wickability, and thermal resistance, were measured for both fabric types. Findings: The study found a significant difference in comfort properties between tencel/cotton single jersey fabric and cotton single jersey fabric. Tencel/cotton fabric exhibited higher air permeability, water vapor permeability, and wickability compared to cotton fabric. These findings suggest that tencel fabric is more suitable for summer clothes due to its superior ventilation and absorption properties. Theoretical Importance: This study contributes to the exploration of alternative fabrics to cotton by evaluating their comfort properties. By identifying fabrics that offer better comfort properties than cotton, particularly in terms of water usage, the study provides valuable insights into sustainable fabric choices for the fashion industry. Data Collection and Analysis Procedures: The comfort properties of the fabrics were measured using appropriate testing methods. Paired comparison t-tests were conducted to determine the significant differences between tencel/cotton fabric and cotton fabric in the measured properties. Correlation coefficients were also calculated to examine the relationships between the factors under study. Question Addressed: The study addresses the question of whether tencel/cotton single jersey fabric can serve as an alternative to cotton fabric for summer clothes, considering their comfort properties. Conclusion: The study concludes that tencel/cotton single jersey fabric offers superior comfort properties compared to cotton single jersey fabric, making it a suitable alternative for summer clothes. The findings also highlight the importance of considering fabric properties, such as air permeability, water vapor permeability, and wickability, when selecting materials for garments to enhance wearer comfort. This research contributes to the search for sustainable alternatives to cotton and provides valuable insights for the fashion industry in making informed fabric choices.

Keywords: comfort properties, cotton fabric, tencel fabric, single jersey

Procedia PDF Downloads 71
19996 Transient Voltage Distribution on the Single Phase Transmission Line under Short Circuit Fault Effect

Authors: A. Kojah, A. Nacaroğlu

Abstract:

Single phase transmission lines are used to transfer data or energy between two users. Transient conditions such as switching operations and short circuit faults cause the generation of the fluctuation on the waveform to be transmitted. Spatial voltage distribution on the single phase transmission line may change owing to the position and duration of the short circuit fault in the system. In this paper, the state space representation of the single phase transmission line for short circuit fault and for various types of terminations is given. Since the transmission line is modeled in time domain using distributed parametric elements, the mathematical representation of the event is given in state space (time domain) differential equation form. It also makes easy to solve the problem because of the time and space dependent characteristics of the voltage variations on the distributed parametrically modeled transmission line.

Keywords: energy transmission, transient effects, transmission line, transient voltage, RLC short circuit, single phase

Procedia PDF Downloads 219
19995 Mathematical Modelling of Different Types of Body Support Surface for Pressure Ulcer Prevention

Authors: Mahbub C. Mishu, Venktesh N. Dubey, Tamas Hickish, Jonathan Cole

Abstract:

Pressure ulcer is a common problem for today's healthcare industry. It occurs due to external load applied to the skin. Also when the subject is immobile for a longer period of time and there is continuous load applied to a particular area of human body,blood flow gets reduced and as a result pressure ulcer develops. Body support surface has a significant role in preventing ulceration so it is important to know the characteristics of support surface under loading conditions. In this paper we have presented mathematical models of different types of viscoelastic materials and also we have shown the validation of our simulation results with experiments.

Keywords: pressure ulcer, viscoelastic material, mathematical model, experimental validation

Procedia PDF Downloads 306
19994 The Effects of Self-Graphing on the Reading Fluency of an Elementary Student with Learning Disabilities

Authors: Matthias Grünke

Abstract:

In this single-case study, we evaluated the effects of a self-graphing intervention to help students improve their reading fluency. Our participant was a 10-year-old girl with a suspected learning disability in reading. We applied an ABAB reversal design to test the efficacy of our approach. The dependent measure was the number of correctly read words from a children’s book within five minutes. Our participant recorded her daily performance using a simple line diagram. Results indicate that her reading rate improved simultaneously with the intervention and dropped as soon as the treatment was suspended. The findings give reasons for optimism that our simple strategy can be a very effective tool in supporting students with learning disabilities to boost their reading fluency.

Keywords: single-case study, learning disabilities, elementary education, reading problems, reading fluency

Procedia PDF Downloads 106
19993 Urban Laboratory for Community Involvement in Urban Design Process

Authors: Anja Jutraz, Tadeja Zupancic

Abstract:

This article explores urban laboratory, which presents a combination of different physical and digital methods and tools for public participation in urban design. The city consists of built and unbuilt environments, which can be defined as a community of people, who live there. Communities should have the option to express opinions and decide about the future of their city, from the early stages of the design process onwards. In this paper, we presented the possibility of involving community into renewal of Banska Štiavnica in Slovakia (more exactly the old mining shaft and lake Michal Štolna) and the methods to promote the community building. As a case study we presented the eTHNo project, Education about Technical, Historical and Natural opportunities of Michal Štolna. Moreover, we discussed the possibility of using virtual digital tools for public participation in urban design, where we especially focused on Virtual Urban Laboratory, VuLab.

Keywords: community building, digital tools, public participation, urban design

Procedia PDF Downloads 569
19992 Author Name Disambiguation for Biomedical Literature

Authors: Parthiban Srinivasan

Abstract:

PubMed provides online access to the National Library of Medicine database (MEDLINE) and other publications, which contain close to 25 million scientific citations from 1865 to the present. There are close to 80 million author name instances in those close to 25 million citations. For any work of literature, a fundamental issue is to identify the individual(s) who wrote it, and conversely, to identify all of the works that belong to a given individual. Due to the lack of universal standards for name information, there are two aspects of name ambiguity: name synonymy (a single author with multiple name representations), and name homonymy (multiple authors sharing the same name representation). In this talk, we present some results from our extensive work in author name disambiguation for PubMed citations. Information will be presented on the effectiveness and shortcomings of different aspects of successful name disambiguation such as parsing, validation, standardization and normalization.

Keywords: disambiguation, normalization, parsing, PubMed

Procedia PDF Downloads 294
19991 An Integrated DEMATEL-QFD Model for Medical Supplier Selection

Authors: Mehtap Dursun, Zeynep Şener

Abstract:

Supplier selection is considered as one of the most critical issues encountered by operations and purchasing managers to sharpen the company’s competitive advantage. In this paper, a novel fuzzy multi-criteria group decision making approach integrating quality function deployment (QFD) and decision making trial and evaluation laboratory (DEMATEL) method is proposed for supplier selection. The proposed methodology enables to consider the impacts of inner dependence among supplier assessment criteria. A house of quality (HOQ) which translates purchased product features into supplier assessment criteria is built using the weights obtained by DEMATEL approach to determine the desired levels of supplier assessment criteria. Supplier alternatives are ranked by a distance-based method.

Keywords: DEMATEL, group decision making, QFD, supplier selection

Procedia PDF Downloads 431
19990 An Automatic Large Classroom Attendance Conceptual Model Using Face Counting

Authors: Sirajdin Olagoke Adeshina, Haidi Ibrahim, Akeem Salawu

Abstract:

large lecture theatres cannot be covered by a single camera but rather by a multicamera setup because of their size, shape, and seating arrangements. Although, classroom capture is achievable through a single camera. Therefore, a design and implementation of a multicamera setup for a large lecture hall were considered. Researchers have shown emphasis on the impact of class attendance taken on the academic performance of students. However, the traditional method of carrying out this exercise is below standard, especially for large lecture theatres, because of the student population, the time required, sophistication, exhaustiveness, and manipulative influence. An automated large classroom attendance system is, therefore, imperative. The common approach in this system is face detection and recognition, where known student faces are captured and stored for recognition purposes. This approach will require constant face database updates due to constant changes in the facial features. Alternatively, face counting can be performed by cropping the localized faces on the video or image into a folder and then count them. This research aims to develop a face localization-based approach to detect student faces in classroom images captured using a multicamera setup. A selected Haar-like feature cascade face detector trained with an asymmetric goal to minimize the False Rejection Rate (FRR) relative to the False Acceptance Rate (FAR) was applied on Raspberry Pi 4B. A relationship between the two factors (FRR and FAR) was established using a constant (λ) as a trade-off between the two factors for automatic adjustment during training. An evaluation of the proposed approach and the conventional AdaBoost on classroom datasets shows an improvement of 8% TPR (output result of low FRR) and 7% minimization of the FRR. The average learning speed of the proposed approach was improved with 1.19s execution time per image compared to 2.38s of the improved AdaBoost. Consequently, the proposed approach achieved 97% TPR with an overhead constraint time of 22.9s compared to 46.7s of the improved Adaboost when evaluated on images obtained from a large lecture hall (DK5) USM.

Keywords: automatic attendance, face detection, haar-like cascade, manual attendance

Procedia PDF Downloads 66
19989 Improving Cell Type Identification of Single Cell Data by Iterative Graph-Based Noise Filtering

Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

Abstract:

Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

Procedia PDF Downloads 108