Search results for: statistical monitoring

Authors: B. X. Tchomeni, A. A. Alugongo, L. M. Masu

Abstract:

This paper presents a 4-DOF nonlinear model of a cracked of Laval rotor established based on Energy Principles. The model has been used to simulate coupled torsional-lateral response of the cracked rotor stator-system with multiple parametric excitations, namely, rotor-stator-rub, a breathing transverse crack, unbalanced mass, and an axial force. Nonlinearity due to a “breathing” crack is incorporated by considering a simple hinge model which is suitable for small breathing crack. The vibration response of a cracked rotor passing through its critical speed with rotor-stator interaction is analyzed, and an attempt for crack detection and monitoring explored. Effects of unbalanced eccentricity with phase and acceleration are investigated. By solving the motion equations, steady-state vibration response is obtained in presence of several rotor faults. The presence of a crack is observable in the power spectrum despite the excitation by the axial force and rotor-stator rub impact. Presented results are consistent with existing literature and could be adopted into rotor condition monitoring strategies

Keywords: rotor, crack, rubbing, axial force, non linear

Procedia PDF Downloads 397

Authors: Jasper Kevin C. Dionisio, Denise Mae M. Unsay

Abstract:

In a manufacturing firm, controlling the process ensures that optimum efficiency, productivity, and quality in an organization are achieved. An operation with no standardized procedure yields a poor productivity, inefficiency, and an out of control process. This study focuses on controlling the small intestine processing of a chicken dressing plant through the use of Statistical Process Control (SPC). Since the operation does not employ a standard procedure and does not have an established standard time, the process through the assessment of the observed time of the overall operation of small intestine processing, through the use of X-Bar R Control Chart, is found to be out of control. In the solution of this problem, the researchers conduct a motion and time study aiming to establish a standard procedure for the operation. The normal operator was picked through the use of Westinghouse Rating System. Instead of utilizing the traditional motion and time study, the researchers used the X-Bar R Control Chart in determining the process average of the process that is used for establishing the standard time. The observed time of the normal operator was noted and plotted to the X-Bar R Control Chart. Out of control points that are due to assignable cause were removed and the process average, or the average time the normal operator conducted the process, which was already in control and free form any outliers, was obtained. The process average was then used in determining the standard time of small intestine processing. As a recommendation, the researchers suggest the implementation of the standard time established which is with consonance to the standard procedure which was adopted from the normal operator. With that recommendation, the whole operation will induce a 45.54 % increase in their productivity.

Keywords: motion and time study, process controlling, statistical process control, X-Bar R Control chart

Procedia PDF Downloads 210

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

Procedia PDF Downloads 153

Authors: H. Arzani, Z. Arzani

Abstract:

Every piece of rangeland has a different set of physical and biological characteristics. This requires the manager to synthesis various information for regular monitoring to define changes trend to get wright decision for sustainable management. So range managers need to use computerized technologies to monitor rangeland, and select. The best management practices. There are four examples of computerized technologies that can benefit sustainable management: (1) Photographic method for cover measurement: The method was tested in different vegetation communities in semi humid and arid regions. Interpretation of pictures of quadrats was done using Arc View software. Data analysis was done by SPSS software using paired t test. Based on the results, generally, photographic method can be used to measure ground cover in most vegetation communities. (2) GPS application for corresponding ground samples and satellite pixels: In two provinces of Tehran and Markazi, six reference points were selected and in each point, eight GPS models were tested. Significant relation among GPS model, time and location with accuracy of estimated coordinates was found. After selection of suitable method, in Markazi province coordinates of plots along four transects in each 6 sites of rangelands was recorded. The best time of GPS application was in the morning hours, Etrex Vista had less error than other models, and a significant relation among GPS model, time and location with accuracy of estimated coordinates was found. (3) Application of satellite data for rangeland monitoring: Focusing on the long term variation of vegetation parameters such as vegetation cover and production is essential. Our study in grass and shrub lands showed that there were significant correlations between quantitative vegetation characteristics and satellite data. So it is possible to monitor rangeland vegetation using digital data for sustainable utilization. (4) Rangeland suitability classification with GIS: Range suitability assessment can facilitate sustainable management planning. Three sub-models of sensitivity to erosion, water suitability and forage production out puts were entered to final range suitability classification model. GIS was facilitate classification of range suitability and produced suitability maps for sheep grazing. Generally digital computers assist range managers to interpret, modify, calibrate or integrating information for correct management.

Keywords: computer, GPS, GIS, remote sensing, photographic method, monitoring, rangeland ecosystem, management, suitability, sheep grazing

Procedia PDF Downloads 363

Authors: Sintija Miļuna, Ričards Melderis, Loreta Briuka, Dagnija Rostoka, Ingus Skadiņš, Juta Kroiča

Abstract:

Objectives Smokeless tobacco products in Latvia become more available and favorable to young adults, especially students and athletes like hockey and floorball players. The aim of the research was to detect visual mucosal changes in the oral cavity in smokeless tobacco users and to evaluate pro - inflammatory and anti - inflammatory cytokine (IL-6, IL-1, IL-8, TNF Alpha) levels in saliva from smokeless tobacco users. Methods A smokeless tobacco group (n=10) and a control group (non-tobacco users) (n=10) were intraorally examined for oral lesions and 5 ml of saliva were collected. Saliva was analysed for Il-6, IL-1, Il-8, TNF Alpha using ELISA Sigma-Aldrich. For statistical analysis IBM Statistics 27 was used (Mann - Whitney U test, Spearman’s Rank Correlation coefficient). This research was approved by the Ethics Committee of Rīga Stradiņš University No.22/28.01.2016. This research has been developed with financing from the European Social Fund and Latvian state budget within the project no. 8.2.2.0/20/I/004 “Support for involving doctoral students in scientific research and studies” at Rīga Stradiņš University. Results IL-1, IL-6, IL-8, TNF Alpha levels were higher in the smokeless tobacco group (IL-1 83.34 pg/ml vs. 74.26 pg/ml; IL-6 195.10 pg/ml vs. 6.16 pg/ml; IL-8 736.34 pg/ml vs. 285.26 pg/ml; TNF Alpha 489.27 pg/ml vs. 200.9 pg/ml), but statistically there is no difference between control group and smokeless tobacco group (IL1 p=0.190, IL6 p=0.052, IL8 p=0.165, TNF alpha p=0.089). There was statistical correlation between IL1 and IL6 (p=0.023), IL6 and TNF alpha (p=0.028), IL8 and IL6 (p=0.005). Conclusions White localized lesions were detected in places where smokeless tobacco users placed sachets. There is a statistical correlation between IL6 and IL1 levels, IL6 and TNF alpha levels, IL8 and IL6 levels in saliva. There are no differences in the inflammatory cytokine levels between control group and smokeless tobacco group.

Keywords: smokeless tobacco, Snus, inflammatory biomarkers, oral lesions, oral pathology

Procedia PDF Downloads 130

Authors: Yaser S. Kishawi, Sadi R. Ali

Abstract:

Part of Palestine, Gaza Strip (365 km2 and 1.8 million inhabitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely cover the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is finding non-conventional water resource from treated wastewater to cover agricultural requirements and serve the population. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line & infiltration basins - IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme – RRS – to capture the spreading plume). Currently, only phase A is functioning. Nearly 23 Mm3 of partially treated wastewater were infiltrated into the aquifer. Phase B and phase C witnessed many delays and this forced a reassessment of the RRS original design. An Environmental Management Plan was conducted from Jul 2013 to Jun 2014 on 13 existing monitoring wells surrounding the project location. This is to measure the efficiency of the SAT system and the spread of the contamination plume with relation to the efficiency of the proposed RRS. Along with the proposed location of the 27 recovery wells as part of the proposed RRS. The results of monitored wells were assessed compared with PWA baseline data. This was put into a groundwater model to simulate the plume to propose the best suitable solution to the delays. The redesign mainly manipulated the pumping rate of wells, proposed locations and functioning schedules (including wells groupings). The proposed simulations were examined using visual MODFLOW V4.2 to simulate the results. The results of monitored wells were assessed based on the location of the monitoring wells related to the proposed recovery wells locations (200m, 500m and 750m away from the IBs). Near the 500m line (the first row of proposed recovery wells), an increase of nitrate (from 30 to 70mg/L) compare to a decrease in Chloride (1500 to below 900mg/L) was found during the monitoring period which indicated an expansion of plume to this distance. On this rate with the required time to construct the recovery scheme, keeping the original design the RRS will fail to capture the plume. Based on that many simulations were conducted leading into three main scenarios. The scenarios manipulated the starting dates, the pumping rate and the locations of recovery wells. A simulation of plume expansion and path-lines were extracted from the model monitoring how to prevent the expansion towards the nearby municipal wells. It was concluded that the location is the most important factor in determining the RRS efficiency. Scenario III was adopted and showed an effective results even with a reduced pumping rates. This scenario proposed adding two additional recovery wells in a location beyond the 750m line to compensate the delays and effectively capture the plume. A continuous monitoring program for current and future monitoring wells should be in place to support the proposed scenario and ensure maximum protection.

Keywords: soil aquifer treatment, recovery and reuse scheme, infiltration basins, north gaza

Procedia PDF Downloads 308

Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

Abstract:

Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis

Procedia PDF Downloads 391

Authors: Ziyda Abunada

Abstract:

In-situ remediation of contaminated land with deep mixing can deliver a multi-technique remedial strategy. A field trail includes permeable reactive barrier (PRB) took place at a severely contaminated site in Yorkshire to the north of the UK through the SMiRT (Soil Mix Remediation Technology) project in May 2011. SMiRT involved the execution of the largest research field trials in the UK to provide field validation. Innovative modified bentonite materials in combination with zeolite and organoclay were used to construct six different walls of a hexagonal PRB. Field monitoring, testing and site cores were collected from the PRB twice: once 2 months after the construction and again in March 2014 (almost 34 months later).This paper presents an overview of the results of the PRB materials’ relative performance with some initial 3-year time-related assessment. Results from the monitoring program and the site cores are presented. Some good correlations are seen together with some clear difference among the materials’ efficiency. These preliminary observations represent a potential for further investigations and highlighted the main lessons learned in a filed scale.

Keywords: in-situ remediation, groundwater, permeable reactive barrier, site cores

Procedia PDF Downloads 198

Authors: Mohamad Ghozali Hassan, Abdul Aziz Othman, Mohd Azril Ismail

Abstract:

Adapting quickly to environmental dynamism is essential for an organization to develop outsourcing strategic and management in order to sustain competitive advantage. This research used the Partial Least Squares Structural Equation Modeling (PLS-SEM) tool to investigate the factors of environmental dynamism impact on the strategic outsourcing success among electrical and electronic manufacturing industries in outsourcing management. Statistical results confirm that the inclusion of customer demand, technological change, and competition level as a new combination concept of environmental dynamism, has positive effects on outsourcing success. Additionally, this research demonstrates the acceptability of PLS-SEM as a statistical analysis to furnish a better understanding of environmental dynamism in outsourcing management in Malaysia. A practical finding contributes to academics and practitioners in the field of outsourcing management.

Keywords: environmental dynamism, customer demand, technological change, competition level, outsourcing success

Procedia PDF Downloads 496

Authors: Ahmed Noor Al-Qayyim

Abstract:

During the past decades, the bridge structures are considered very important portions of transportation networks, due to the fast urban sprawling. With the failure of bridges that under operating conditions lead to focus on updating the default bridge inspection methodology. The structures health monitoring (SHM) using the vibration response appeared as a promising method to evaluate the condition of structures. The rapid development in the sensors technology and the condition assessment techniques based on the vibration-based damage detection made the SHM an efficient and economical ways to assess the bridges. SHM is set to assess state and expects probable failures of designated bridges. In this paper, a presentation for Frequency Response function method that uses the captured vibration test information of structures to evaluate the structure condition. Furthermore, the main steps of the assessment of bridge using the vibration information are presented. The Frequency Response function method is applied to the experimental data of a full-scale bridge.

Keywords: bridge assessment, health monitoring, damage detection, frequency response function (FRF), signal processing, structure identification

Procedia PDF Downloads 342

Authors: Elisa Coraggio, Dawei Han, Weiru Liu, Theo Tryfonas

Abstract:

Water is one of the most important resources for human society. The world is currently undergoing a wave of urban growth, and pollution problems are of a great impact. Monitoring water quality is a key task for the future of the environment and human species. In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for environmental monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the artificial intelligence algorithm. This study derives the methodology and demonstrates its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.In recent times, researchers, using Smart Cities technologies are trying to mitigate the problems generated by the population growth in urban areas. The availability of huge amounts of data collected by a pervasive urban IoT can increase the transparency of decision making. Several services have already been implemented in Smart Cities, but more and more services will be involved in the future. Water quality monitoring can successfully be implemented in the urban IoT. The combination of water quality sensors, cloud computing, smart city infrastructure, and IoT technology can lead to a bright future for the environment monitoring. In the past decades, lots of effort has been put on monitoring and predicting water quality using traditional approaches based on manual collection and laboratory-based analysis, which are slow and laborious. The present study proposes a new methodology for implementing a water quality prediction model using artificial intelligence techniques and comparing the results obtained with different algorithms. Furthermore, a 3D numerical model will be created using the software D-Water Quality, and simulation results will be used as a training dataset for the Artificial Intelligence algorithm. This study derives the methodology and demonstrate its implementation based on information and data collected at the floating harbour in the city of Bristol (UK). The city of Bristol is blessed with the Bristol-Is-Open infrastructure that includes Wi-Fi network and virtual machines. It was also named the UK ’s smartest city in 2017.

Keywords: artificial intelligence, hydroinformatics, numerical modelling, smart cities, water quality

Procedia PDF Downloads 182

Authors: Yaser S. Kishawi, Sadi R. Ali

Abstract:

Part of Palestine, Gaza Strip (365 km2 and 1.8 million habitants) is considered a semi-arid zone relies solely on the Coastal Aquifer. The coastal aquifer is only source of water with only 5-10% suitable for human use. This barely covers the domestic and agricultural needs of Gaza Strip. Palestinian Water Authority Strategy is finding non-conventional water resource from treated wastewater to cover agricultural requirements and serve the population. A new WWTP project is to replace the old-overloaded Biet Lahia WWTP. The project consists of three parts; phase A (pressure line and infiltration basins-IBs), phase B (a new WWTP) and phase C (Recovery and Reuse Scheme–RRS– to capture the spreading plume). Currently, only phase A is functioning. Nearly 23 Mm3 of partially treated wastewater were infiltrated into the aquifer. Phase B and phase C witnessed many delays and this forced a reassessment of the RRS original design. An Environmental Management Plan was conducted from Jul 2013 to Jun 2014 on 13 existing monitoring wells surrounding the project location. This is to measure the efficiency of the SAT system and the spread of the contamination plume with relation to the efficiency of the proposed RRS. Along with the proposed location of the 27 recovery wells as part of the proposed RRS. The results of monitored wells were assessed compared with PWA baseline data. This was put into a groundwater model to simulate the plume to propose the best suitable solution to the delays. The redesign mainly manipulated the pumping rate of wells, proposed locations and functioning schedules (including wells groupings). The proposed simulations were examined using visual MODFLOW V4.2 to simulate the results. The results of monitored wells were assessed based on the location of the monitoring wells related to the proposed recovery wells locations (200m, 500m, and 750m away from the IBs). Near the 500m line (the first row of proposed recovery wells), an increase of nitrate (from 30 to 70mg/L) compare to a decrease in Chloride (1500 to below 900mg/L) was found during the monitoring period which indicated an expansion of plume to this distance. On this rate with the required time to construct the recovery scheme, keeping the original design the RRS will fail to capture the plume. Based on that many simulations were conducted leading into three main scenarios. The scenarios manipulated the starting dates, the pumping rate and the locations of recovery wells. A simulation of plume expansion and path-lines were extracted from the model monitoring how to prevent the expansion towards the nearby municipal wells. It was concluded that the location is the most important factor in determining the RRS efficiency. Scenario III was adopted and showed effective results even with a reduced pumping rates. This scenario proposed adding two additional recovery wells in a location beyond the 750m line to compensate the delays and effectively capture the plume. A continuous monitoring program for current and future monitoring wells should be in place to support the proposed scenario and ensure maximum protection.

Keywords: soil aquifer treatment, recovery reuse scheme, infiltration basins, North Gaza

Procedia PDF Downloads 201

Authors: Omar A. A. Shaebi, Matouk M. Elamari, Salaheddin Allid

Abstract:

The Information Computing System of Monitoring (ICSM) for the Research Reactor of Tajoura Nuclear Research Centre (TNRC) stopped working since early 1991. According to the regulations, the computer is necessary to operate the reactor up to its maximum power (10 MW). The fund is secured via IAEA to develop a modern computer based data acquisition system to replace the old computer. This paper presents the development of the Labview based data acquisition system to allow automated measurements using National Instruments Hardware and its labview software. The developed system consists of SCXI 1001 chassis, the chassis house four SCXI 1100 modules each can maintain 32 variables. The chassis is interfaced with the PC using NI PCI-6023 DAQ Card. Labview, developed by National Instruments, is used to run and operate the DAQ System. Labview is graphical programming environment suited for high level design. It allows integrating different signal processing components or subsystems within a graphical framework. The results showed system capabilities in monitoring variables, acquiring and saving data. Plus the capability of the labview to control the DAQ.

Keywords: data acquisition, labview, signal conditioning, national instruments

Procedia PDF Downloads 492

Authors: S. Benessam, T. H. Debieche, S. Amiour, A. Chine, S. Khelili

Abstract:

The metallic trace elements (MTE) are present in water and sediments of the rivers with weak concentrations. Several physicochemical parameters (Eh, pH and oxygen dissolved) and chemical processes (adsorption, absorption, complexation and precipitation) as well as nature of the sediments control their mobility. In order to determine the effect of these factors on the mobility of some MTE (Cd, Cr, Cu, Fe, Pb and Zn) in water of the rivers, a two-monthly monitoring of the physicochemical parameters and chemistry of water and sediments of the Nil wadi (Algeria) was carried out during the period from November 2013 to January 2015. The results show that each MTE has its own conditions of mobility and generally are very influence by the variations of the pH and Eh. Under the natural conditions, neutral pH with basic and medium oxidizing, only the lead presented in water with raised values, indicating its solubility in water and its salting out of the sediments. The other MTE present raised concentrations in the sediments, indicating their trapping by adsorption and/or chemical precipitation. The chemical form of each ETM was given by Eh-pH diagrams. The spatio-temporal monitoring of these ETM shows the effect of the rains, the dry periods and the rejects in the variation of their concentrations.

Keywords: chemistry, metallic trace elements, sediment, water

Procedia PDF Downloads 282

Authors: Marcho Setiawan Handok, Samuel S. Lemma, Abdoulaye Fofana, Naseef Mansoor

Abstract:

This paper is proposing a method to predict the outcome of the National Football League match with data from 2019 to 2022 and compare it with other popular models. The model uses open-source statistical data of each team, such as passing yards, rushing yards, fumbles lost, and scoring. Each statistical data has offensive and defensive. For instance, a data set of anticipated values for a specific matchup is created by comparing the offensive passing yards obtained by one team to the defensive passing yards given by the opposition. We evaluated the model’s performance by contrasting its result with those of established prediction algorithms. This research is using a neural network to predict the score of a National Football League match and then predict the winner of the game.

Keywords: game prediction, NFL, football, artificial neural network

Procedia PDF Downloads 79

Authors: Zhu Weimin, Allegorico Carmine, Ruggiero Gionata

Abstract:

During decades of Baker Hughes (BH) iCenter experience, it is demonstrated that in addition to conventional insights on equipment steady operation conditions, insights on transient conditions can add significant and exclusive value for anomaly detection, downtime saving, and predictive maintenance. Our work shows examples from the BH iCenter experience to introduce the advantages and features of using transient condition analytics: (i) Operation under critical engine conditions: e.g., high level or high change rate of temperature, pressure, flow, vibration, etc., that would not be reachable in normal operation, (ii) Management of dedicated sub-systems or components, many of which are often bottlenecks for reliability and maintenance, (iii) Indirect detection of anomalies in the absence of instrumentation, (iv) Repetitive sequences: if data is properly processed, the engineering features of transients provide not only anomaly detection but also problem characterization and prognostic indicators for predictive maintenance, (v) Engine variables accounting for fatigue analysis. iCenter has been developing and deploying a series of analytics based on transient conditions. They are contributing to exclusive value adding in the following areas: (i) Reliability improvement, (ii) Startup reliability improvement, (iii) Predictive maintenance, (iv) Repair/overhaul cost down. Illustrative examples for each of the above areas are presented in our study, focusing on challenges and adopted techniques ranging from purely statistical approaches to the implementation of machine learning algorithms. The obtained results demonstrate how the value is obtained using transient condition analytics in the BH iCenter experience.

Keywords: analytics, diagnostics, monitoring, turbomachinery

Procedia PDF Downloads 70

Authors: Mostafa M. Abo Elsoud, Heba I. Elkhouly, Nagwa M. Sidkey

Abstract:

Production of rhamnolipids by Pseudomonas aeruginosa has attracted a growing interest during the last few decades due to its high productivity compared with other microorganisms. In the current work, rhamnolipids production by P. aeruginosa PAO1 was statistically modeled using Taguchi orthogonal array, numerically optimized and validated. Prickly Pear Peel (Opuntia ficus-indica) has been used as a carbon source for production of rhamnolipid. Finally, the optimum conditions for rhamnolipid production were applied in 5L working volume bioreactors at different aerations, agitation and controlled pH for maximum rhamnolipid production. In addition, kinetic studies of rhamnolipids production have been reported. At the end of the batch bioreactor optimization process, rhamnolipids production by P. aeruginosa PAO1 has reached the worldwide levels and can be applied for its industrial production.

Keywords: rhamnolipids, pseudomonas aeruginosa, statistical optimization, tagushi, opuntia ficus-indica

Procedia PDF Downloads 174

Authors: Wilma Coetzee

Abstract:

Statistics lecturers experience that many students who are taking a service course in statistics do not like statistics. Students in these courses tend to struggle and do not perform well. This research takes a look at the student’s perspective, with the aim to determine how to change the teaching of statistics so that students will enjoy it more and perform better. Questionnaires were used to determine the perspectives of first year service statistics students at a South African university. Factors addressed included motivation to study, attitude toward statistics, statistical anxiety, mathematical abilities and tendency to procrastinate. Logistic regression was used to determine what contributes to students performing badly in statistics. The results show that the factors that contribute the most to students performing badly are: statistical anxiety, not being motivated and having had mathematical literacy instead of mathematics in secondary school. Two open ended questions were included in the questionnaire: 'I will enjoy statistics more if…' and 'I will perform better in statistics if…'. The answers to these questions were analyzed using qualitative methods. Frequent themes were identified for each of the questions. A simulation study incorporating bootstrapping was done to determine the saturation of the themes. The majority of the students indicated that they would perform better in statistics if they studied more, managed their time better, had a flare for mathematics and if the lecturer was able to explain difficult concepts better. They also want more active learning. To ensure that students enjoy statistics more, they want an active learning experience. They want fun activities, more interaction with the lecturer and with one another, more computer based problems, and more challenges. They want a better understanding of the subject, want to understand the relevance of statistics to their future career and want excellent lecturers. These findings can be used to direct the improvement of the tuition of statistics.

Keywords: active learning, performance in statistics, statistical anxiety, statistics education

Procedia PDF Downloads 146

Authors: Loubna Tani, Nabih Elouzzani

Abstract:

Crosstalk among interconnects and printed-circuit board (PCB) traces is a major limiting factor of signal quality in high-speed digital and communication equipments especially when fast data buses are involved. Such a bus is considered as a planar multiconductor transmission line. This paper will demonstrate how the finite difference time domain (FDTD) method provides an exact solution of the transmission-line equations to analyze the near end and the far end crosstalk. In addition, this study makes it possible to analyze the rise time effect on the near and far end voltages of the victim conductor. The paper also discusses a statistical analysis, based upon a set of several simulations. Such analysis leads to a better understanding of the phenomenon and yields useful information.

Keywords: multiconductor transmission line, crosstalk, finite difference time domain (FDTD), printed-circuit board (PCB), rise time, statistical analysis

Procedia PDF Downloads 428

Authors: Chiu-Pin Wei

Abstract:

This research aims to explore the impact of music preferences on the emotional well-being of military academy students, recognizing the potential long-term implications for their high-stress careers post-graduation. Given the significance of positive emotion regulation in military personnel, this study focuses on understanding the types of music preferred by military cadets and analyzing how these preferences correlate with their emotional states. The study employs a quantitative approach, utilizing the Music Category Scale and Mood Scale to collect data. Statistical tools, such as Statistical Product and Service Solutions (SPSS), are employed for inferential analysis, including t-tests for emotional responses to instrumental and vocal music, one-way variance analysis for different demographic factors (grades, genders, and music listening frequencies), and Pearson's correlation to examine the relationship between music preferences and moods of military students.

Keywords: music preference, emotional regulation, military academic students, SPASS

Procedia PDF Downloads 64

Authors: Daniel Dahis, Haim Azhari

Abstract:

Noninvasive image-guided intracranial treatments using high intensity focused ultrasound (HIFU) are on the course of translation into clinical applications. They include, among others, tumor ablation, hyperthermia, and blood-brain-barrier (BBB) penetration. Since many of these procedures are associated with local temperature elevation, thermal monitoring is essential. MRI constitutes an imaging method with high spatial resolution and thermal mapping capacity. It is the currently leading modality for temperature guidance, commonly under the name MRgHIFU (magnetic-resonance guided HIFU). Nevertheless, MRI is a very expensive non-portable modality which jeopardizes its accessibility. Ultrasonic thermal monitoring, on the other hand, could provide a modular, cost-effective alternative with higher temporal resolution and accessibility. In order to assess the feasibility of ultrasonic brain thermal monitoring, this study investigated the usage of brain tissue attenuation coefficient (AC) temporal changes as potential estimators of thermal changes. Newton's law of cooling describes a temporal exponential decay behavior for the temperature of a heated object immersed in a relatively cold surrounding. Similarly, in the case of cerebral HIFU treatments, the temperature in the region of interest, i.e., focal zone, is suggested to follow the same law. Thus, it was hypothesized that the AC of the irradiated tissue may follow a temporal exponential behavior during cool down regime. Three ex-vivo bovine brain tissue specimens were inserted into plastic containers along with four thermocouple probes in each sample. The containers were placed inside a specially built ultrasonic tomograph and scanned at room temperature. The corresponding pixel-averaged AC was acquired for each specimen and used as a reference. Subsequently, the containers were placed in a beaker containing hot water and gradually heated to about 45ᵒC. They were then repeatedly rescanned during cool down using ultrasonic through-transmission raster trajectory until reaching about 30ᵒC. From the obtained images, the normalized AC and its temporal derivative as a function of temperature and time were registered. The results have demonstrated high correlation (R² > 0.92) between both the brain AC and its temporal derivative to temperature. This indicates the validity of the hypothesis and the possibility of obtaining brain tissue temperature estimation from the temporal AC thermal changes. It is important to note that each brain yielded different AC values and slopes. This implies that a calibration step is required for each specimen. Thus, for a practical acoustic monitoring of the brain, two steps are suggested. The first step consists of simply measuring the AC at normal body temperature. The second step entails measuring the AC after small temperature elevation. In face of the urging need for a more accessible thermal monitoring technique for brain treatments, the proposed methodology enables a cost-effective high temporal resolution acoustical temperature estimation during HIFU treatments.

Keywords: attenuation coefficient, brain, HIFU, image-guidance, temperature

Procedia PDF Downloads 160

Authors: Mustapha Benssalah, Mustapha Djeddou, Karim Drouiche

Abstract:

The random number generation (RNG) presents a significant importance for the security and the privacy of numerous applications, such as RFID technology and smart cards. Since, the quality of the generated bit sequences is paramount that a weak internal generator for example, can directly cause the entire application to be insecure, and thus it makes no sense to employ strong algorithms for the application. In this paper, we propose a new pseudo random number generator (PRNG), suitable for cryptosystems ECC-based, constructed by randomly selecting points from several elliptic curves randomly selected. The main contribution of this work is the increasing of the generator internal states by extending the set of its output realizations to several curves auto-selected. The quality and the statistical characteristics of the proposed PRNG are validated using the Chi-square goodness of fit test and the empirical Special Publication 800-22 statistical test suite issued by NIST.

Keywords: PRNG, security, cryptosystem, ECC

Procedia PDF Downloads 441

Authors: Sitarrine Thongpussawal, Dasarath Jayasuriya, Thanaroj Woraratprasert, Sakawtree Prajamwong

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Thailand grapples with recurrent floods causing substantial repercussions on its economy, society, and environment. In 2021, the economic toll of these floods amounted to an estimated 53,282 million baht, primarily impacting the agricultural sector. The existing flood monitoring system in Thailand suffers from inaccuracies and insufficient information, resulting in delayed warnings and ineffective communication to the public. The Office of the National Water Resources (OWNR) is tasked with developing and integrating data and information systems for efficient water resources management, yet faces challenges in monitoring accuracy, forecasting, and timely warnings. This study endeavors to evaluate the viability of enhancing Thailand's Flood Forecasting and Warning (FFW) systems. Additionally, it aims to formulate a comprehensive work package grounded in international best practices to enhance the country's FFW systems. Employing qualitative research methodologies, the study conducted in-depth interviews and focus groups with pertinent agencies. Data analysis involved techniques like note-taking and document analysis. The study substantiates the feasibility of developing and enhancing FFW systems in Thailand. Implementation of international best practices can augment the precision of flood forecasting and warning systems, empowering local agencies and residents in high-risk areas to prepare proactively, thereby minimizing the adverse impact of floods on lives and property. This research underscores that Thailand can feasibly advance its FFW systems by adopting international best practices, enhancing accuracy, and improving preparedness. Consequently, the study enriches the theoretical understanding of flood forecasting and warning systems and furnishes valuable recommendations for their enhancement in Thailand.

Keywords: flooding, forecasting, warning, monitoring, communication, Thailand

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Authors: Swetha Priya Darshini Thammadi, Sateesh Kumar Pisini, Sanjay Kumar Shukla

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Source apportionment using Dispersion model depends primarily on the quality of Emission Inventory. In the present study, a CMB receptor model has been used to identify the sources of PM_2.5, while the AERMOD dispersion model has been used to account for missing sources of PM_2.5 in the Emission Inventory. A statistical approach has been developed to quantify the missing sources not considered in the Emission Inventory. The inventory of each grid was improved by adjusting emissions based on road lengths and deficit in measured and modelled concentrations. The results showed that in CMB analyses, fugitive sources - soil and road dust - contribute significantly to ambient PM_2.5 pollution. As a result, AERMOD significantly underestimated the ambient air concentration at most locations. The revised Emission Inventory showed a significant improvement in AERMOD performance which is evident through statistical tests.

Keywords: CMB, GIS, AERMOD, PM₂.₅, fugitive, emission inventory

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Authors: Sadia Afroza, Rakiba Rouf

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Road safety and associated behaviors have received significant attention in recent years, reflecting general public concern. This paper portrays a statistical scenario of the young drivers in UAE with emphasis on various concern points of young driver’s behavior and license issuance. Although there are many factors contributing to road accidents, statistically it is evident that age plays a major role in road accidents. Despite ensuring strict road safety laws enforced by the UAE government, there is a staggering correlation among road accidents and young driver’s at UAE. However, private organizations like BMW and RoadSafetyUAE have extended its support on conducting surveys on driver’s behavior with an aim to ensure road safety. Various strategies such as road safety law enforcement, license issuance, adapting new technologies like safety cameras and raising awareness can be implemented to improve the road safety concerns among young drivers.

Keywords: driving behavior, Graduated Driver Licensing System (GLDS), road safety, UAE drivers, young drivers

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Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

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The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: data mining, Korean linguistic feature, literary fiction, relationship extraction

Procedia PDF Downloads 374

Authors: John Mark Payawal, Francis Aldrine Uy, John Paul Carreon

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This paper shows the application of Structural Health Monitoring, SHM into bridges. Bridges are structures built to provide passage over a physical obstruction such as rivers, chasms or roads. The Philippines has a total of 8,166 national bridges as published on the 2015 atlas of the Department of Public Works and Highways (DPWH) and only 2,924 or 35.81% of these bridges are in good condition. As a result, PHP 30.464 billion of the 2016 budget of DPWH is allocated on roads and/or bridges maintenance alone. Intensive spending is owed to the present practice of outdated manual inspection and assessment, and poor structural health monitoring of Philippine infrastructures. As the School of Civil, Environmental, & Geological Engineering of Mapua Institute of Technology (MIT) continuous its well driven passion in research based projects, a partnership with the Department of Science and Technology (DOST) and the DPWH launched the application of Structural Health Monitoring, (SHM) in Padre Jacinto Zamora Flyover. The flyover is located along Nagtahan Boulevard in Sta. Mesa, Manila that connects Brgy. 411 and Brgy. 635. It gives service to vehicles going from Lacson Avenue to Mabini Bridge passing over Legarda Flyover. The flyover is chosen among the many located bridges in Metro Manila as the focus of the pilot testing due to its site accessibility, and complete structural built plans and specifications necessary for SHM as provided by the Bureau of Design, BOD department of DPWH. This paper focuses on providing a method to calibrate theoretical readings from STAAD Vi8 Pro and sync the data to actual MEMS accelerometer readings. It is observed that while the design standards used in constructing the flyover was reflected on the model, actual readings of MEMS accelerometer display a large difference compared to the theoretical data ran and taken from STAAD Vi8 Pro. In achieving a true seismic response of the modeled bridge or hence syncing the theoretical data to the actual sensor reading also called as the independent variable of this paper, analysis using single degree of freedom (SDOF) of the flyover under free vibration without damping using STAAD Vi8 Pro is done. The earthquake excitation and bridge responses are subjected to earthquake ground motion in the form of ground acceleration or Peak Ground Acceleration, PGA. Translational acceleration load is used to simulate the ground motion of the time history analysis acceleration record in STAAD Vi8 Pro.

Keywords: accelerometer, analysis using single degree of freedom, micro electro mechanical system, peak ground acceleration, structural health monitoring

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Authors: Dian Zhang, Brendan Heery, Maria O’Neill, Ciprian Briciu-Burghina, Noel E. O’Connor, Fiona Regan

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Recent developments in sensors, wireless data communication and the cloud computing have brought the sensor web to a whole new generation. The introduction of the concept of ‘Internet of Thing (IoT)’ has brought the sensor research into a new level, which involves the developing of long lasting, low cost, environment friendly and smart sensors; new wireless data communication technologies; big data analytics algorithms and cloud based solutions that are tailored to large scale smart sensor network. The next generation of smart sensor network consists of several layers: physical layer, where all the smart sensors resident and data pre-processes occur, either on the sensor itself or field gateway; data transmission layer, where data and instructions exchanges happen; the data process layer, where meaningful information is extracted and organized from the pre-process data stream. There are many definitions of smart sensor, however, to summarize all these definitions, a smart sensor must be Intelligent and Adaptable. In future large scale sensor network, collected data are far too large for traditional applications to send, store or process. The sensor unit must be intelligent that pre-processes collected data locally on board (this process may occur on field gateway depends on the sensor network structure). In this case study, three smart sensing methods, corresponding to simple thresholding, statistical model and machine learning based MoPBAS method, are introduced and their strength and weakness are discussed as an introduction to the smart sensing concept. Data fusion, the integration of data and knowledge from multiple sources, are key components of the next generation smart sensor network. For example, in the water level monitoring system, weather forecast can be extracted from external sources and if a heavy rainfall is expected, the server can send instructions to the sensor notes to, for instance, increase the sampling rate or switch on the sleeping mode vice versa. In this paper, we describe the deployment of 11 affordable water level sensors in the Dublin catchment. The objective of this paper is to use the deployed river level sensor network at the Dodder catchment in Dublin, Ireland as a case study to give a vision of the next generation of a smart sensor network for flood monitoring to assist agencies in making decisions about deploying resources in the case of a severe flood event. Some of the deployed sensors are located alongside traditional water level sensors for validation purposes. Using the 11 deployed river level sensors in a network as a case study, a vision of the next generation of smart sensor network is proposed. Each key component of the smart sensor network is discussed, which hopefully inspires the researchers who are working in the sensor research domain.

Keywords: smart sensing, internet of things, water level sensor, flooding

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Eyob Seife

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Immunization is a life-saving intervention which prevents needless suffering through sickness, disability, and death. Emphasis on data quality and use will become even stronger with the development of the immunization agenda 2030 (IA2030). Quality of data is a key factor in generating reliable health information that enables monitoring progress, financial planning, vaccine forecasting capacities, and making decisions for continuous improvement of the national immunization program. However, ensuring data of sufficient quality and promoting an information-use culture at the point of the collection remains critical and challenging, especially in hard-to-reach and pastoralist areas where Degehabur district is selected based on a hypothesis of ‘there is no difference in reported and recounted immunization data consistency. Data quality is dependent on different factors where organizational, behavioral, technical, and contextual factors are the mentioned ones. A cross-sectional quantitative study was conducted on September 2022 in the Degehabur district. The study used the world health organization (WHO) recommended data quality self-assessment (DQS) tools. Immunization tally sheets, registers, and reporting documents were reviewed at 5 health facilities (2 health centers and 3 health posts) of primary health care units for one fiscal year (12 months) to determine the accuracy ratio. The data was collected by trained DQS assessors to explore the quality of monitoring systems at health posts, health centers, and the district health office. A quality index (QI) was assessed, and the accuracy ratio formulated were: the first and third doses of pentavalent vaccines, fully immunized (FI), and the first dose of measles-containing vaccines (MCV). In this study, facility-level results showed both over-reporting and under-reporting were observed at health posts when computing the accuracy ratio of the tally sheet to health post reports found at health centers for almost all antigens verified where pentavalent 1 was 88.3%, 60.4%, and 125.6% for Health posts A, B, and C respectively. For first-dose measles-containing vaccines (MCV), similarly, the accuracy ratio was found to be 126.6%, 42.6%, and 140.9% for Health posts A, B, and C, respectively. The accuracy ratio for fully immunized children also showed 0% for health posts A and B and 100% for health post-C. A relatively better accuracy ratio was seen at health centers where the first pentavalent dose was 97.4% and 103.3% for health centers A and B, while a first dose of measles-containing vaccines (MCV) was 89.2% and 100.9% for health centers A and B, respectively. A quality index (QI) of all facilities also showed results between the maximum of 33.33% and a minimum of 0%. Most of the verified immunization data accuracy ratios were found to be relatively better at the health center level. However, the quality of the monitoring system is poor at all levels, besides poor data accuracy at all health posts. So attention should be given to improving the capacity of staff and quality of monitoring system components, namely recording, reporting, archiving, data analysis, and using information for decision at all levels, especially in pastoralist areas where such kinds of study findings need to be improved beside to improving the data quality at root and health posts level.

Keywords: accuracy ratio, Degehabur District, regular childhood immunization program, quality of monitoring system, Somali Region-Ethiopia

Procedia PDF Downloads 100