Search results for: General Linear Model
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22307

Search results for: General Linear Model

13337 Direct Blind Separation Methods for Convolutive Images Mixtures

Authors: Ahmed Hammed, Wady Naanaa

Abstract:

In this paper, we propose a general approach to deal with the problem of a convolutive mixture of images. We use a direct blind source separation method by adding only one non-statistical justified constraint describing the relationships between different mixing matrix at the aim to make its resolution easy. This method can be applied, provided that this constraint is known, to degraded document affected by the overlapping of text-patterns and images. This is due to chemical and physical reactions of the materials (paper, inks,...) occurring during the documents aging, and other unpredictable causes such as humidity, microorganism infestation, human handling, etc. We will demonstrate that this problem corresponds to a convolutive mixture of images. Subsequently, we will show how the validation of our method through numerical examples. We can so obtain clear images from unreadable ones which can be caused by pages superposition, a phenomenon similar to that we find every often in archival documents.

Keywords: blind source separation, convoluted mixture, degraded documents, text-patterns overlapping

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13336 An Improved Visible Range Absorption Spectroscopy on Soil Macronutrient

Authors: Suhaila Isaak, Yusmeeraz Yusof, Khairunnisa Mohd Yusof, Ahmad Safuan Abdul Rashid

Abstract:

Soil fertility is commonly evaluated by soil macronutrients such as nitrate, potassium, and phosphorus contents. Optical spectroscopy is an emerging technology which is rapid and simple has been widely used in agriculture to measure soil fertility. For visible and near infrared absorption spectroscopy, the absorbed light level in is useful for soil macro-nutrient measurement. This is because the absorption of light in a soil sample influences sensitivity of the measurement. This paper reports the performance of visible and near infrared absorption spectroscopy in the 400–1400 nm wavelength range using light-emitting diode as the excitation light source to predict the soil macronutrient content of nitrate, potassium, and phosphorus. The experimental results show an improved linear regression analysis of various soil specimens based on the Beer–Lambert law to determine sensitivity of soil spectroscopy by evaluating the absorption of characteristic peaks emitted from a light-emitting diode and detected by high sensitivity optical spectrometer. This would denote in developing a simple and low-cost soil spectroscopy with light-emitting diode for future implementation.

Keywords: macronutrients absorption, optical spectroscopy, soil, absorption

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13335 Design for Safety: Safety Consideration in Planning and Design of Airport Airsides

Authors: Maithem Al-Saadi, Min An

Abstract:

During airport planning and design stages, the major issues of capacity and safety in construction and operation of an airport need to be taken into consideration. The airside of an airport is a major and critical infrastructure that usually consists of runway(s), taxiway system, and apron(s) etc., which have to be designed according to the international standards and recommendations, and local limitations to accommodate the forecasted demands. However, in many cases, airport airsides are suffering from unexpected risks that occurred during airport operations. Therefore, safety risk assessment should be applied in the planning and design of airsides to cope with the probability of risks and their consequences, and to make decisions to reduce the risks to as low as reasonably practicable (ALARP) based on safety risk assessment. This paper presents a combination approach of Failure Modes, Effect, and Criticality Analysis (FMECA), Fuzzy Reasoning Approach (FRA), and Fuzzy Analytic Hierarchy Process (FAHP) to develop a risk analysis model for safety risk assessment. An illustrated example is used to the demonstrate risk assessment process on how the design of an airside in an airport can be analysed by using the proposed safety design risk assessment model.

Keywords: airport airside planning and design, design for safety, fuzzy reasoning approach, fuzzy AHP, risk assessment

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13334 Heat and Mass Transfer of Triple Diffusive Convection in a Rotating Couple Stress Liquid Using Ginzburg-Landau Model

Authors: Sameena Tarannum, S. Pranesh

Abstract:

A nonlinear study of triple diffusive convection in a rotating couple stress liquid has been analysed. It is performed to study the effect of heat and mass transfer by deriving Ginzburg-Landau equation. Heat and mass transfer are quantified in terms of Nusselt number and Sherwood numbers, which are obtained as a function of thermal and solute Rayleigh numbers. The obtained Ginzburg-Landau equation is Bernoulli equation, and it has been elucidated numerically by using Mathematica. The effects of couple stress parameter, solute Rayleigh numbers, and Taylor number on the onset of convection and heat and mass transfer have been examined. It is found that the effects of couple stress parameter and Taylor number are to stabilize the system and to increase the heat and mass transfer.

Keywords: couple stress liquid, Ginzburg-Landau model, rotation, triple diffusive convection

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13333 Adsorptive Desulfurization of Using Cu(I) – Y Zeolite via π-Complexation

Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng, Itumeleng Kohitlhetse

Abstract:

The accelerating requirement to reach 0% sulfur content in liquid fuels demand researchers to seek efficient alternative technologies to challenge the predicament. In this current study, the adsorption capabilities of modified Cu(I)-Y zeolite were tested for the removal of organosulfur compounds (OSC) present in tire pyrolytic oil (TPO). The π-complexation-based adsorbent was obtained by ion exchanging Y-zeolite with Cu+ cation using liquid phase ion exchange (LPIE). Preparation of the adsorbent involved firstly ion exchange between Na-Y zeolite with a Cu(NO₃)₂ aqueous solution of 0.5M for 48 hours followed by reduction of Cu²⁺ to Cu+. Fixed-bed breakthrough studies for TPO in comparison with model diesel comprising of sulfur compounds such as thiophene, benzothiophenes (BT), and dibenzothiophenes (DBT) showed that modified Cu(I)-Y zeolite is an effective adsorbent for removal of OSC in liquid fuels. The effect of operating conditions such as adsorbent dosage and reaction time were studied to optimize the adsorptive desulfurization process. For model diesel fuel, the selectivity for adsorption of sulfur compounds followed the order DBT> BT> Thiophene. The Cu(I)-Y zeolite is fully regeneratable and this is achieved by a simple procedure of blowing the adsorbent with air at 350 °C, followed by reactivation at 450 °C in a rich helium surrounding.

Keywords: adsorption, desulfurization, TPO, zeolite

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13332 Impact of Customer Experience Quality on Loyalty of Mobile and Fixed Broadband Services: Case Study of Telecom Egypt Group

Authors: Nawal Alawad, Passent Ibrahim Tantawi, Mohamed Abdel Salam Ragheb

Abstract:

Providing customers with quality experiences has been confirmed to be a sustainable, competitive advantage with a distinct financial impact for companies. The success of service providers now relies on their ability to provide customer-centric services. The importance of perceived service quality and customer experience is widely recognized. The focus of this research is in the area of mobile and fixed broadband services. This study is of dual importance both academically and practically. Academically, this research applies a new model investigating the impact of customer experience quality on loyalty based on modifying the multiple-item scale for measuring customers’ service experience in a new area and did not depend on the traditional models. The integrated scale embraces four dimensions: service experience, outcome focus, moments of truth and peace of mind. In addition, it gives a scientific explanation for this relationship so this research fill the gap in such relations in which no one correlate or give explanations for these relations before using such integrated model and this is the first time to apply such modified and integrated new model in telecom field. Practically, this research gives insights to marketers and practitioners to improve customer loyalty through evolving the experience quality of broadband customers which is interpreted to suggested outcomes: purchase, commitment, repeat purchase and word-of-mouth, this approach is one of the emerging topics in service marketing. Data were collected through 412 questionnaires and analyzed by using structural equation modeling.Findings revealed that both outcome focus and moments of truth have a significant impact on loyalty while both service experience and peace of mind have insignificant impact on loyalty.In addition, it was found that 72% of the variation occurring in loyalty is explained by the model. The researcher also measured the net prompters score and gave explanation for the results. Furthermore, assessed customer’s priorities of broadband services. The researcher recommends that the findings of this research will extend to be considered in the future plans of Telecom Egypt Group. In addition, to be applied in the same industry especially in the developing countries that have the same circumstances with similar service settings. This research is a positive contribution in service marketing, particularly in telecom industry for making marketing more reliable as managers can relate investments in service experience directly with the performance closest to income for instance, repurchasing behavior, positive word of mouth and, commitment. Finally, the researcher recommends that future studies should consider this model to explain significant marketing outcomes such as share of wallet and ultimately profitability.

Keywords: broadband services, customer experience quality, loyalty, net promoters score

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13331 Nursing Experience in Improving Physical and Mental Well-Being of a Patient with Premature Menopause Osteoporosis and Sarcopenia in Nursing-Led Multi-Discipline Care

Authors: Huang Chiung Chiu

Abstract:

This article is about the nursing experience of assisting an outpatient with premature menopause, osteoporosis and sarcopenia through a multi-discipline care model. The nursing period is from September 22nd, 2020, to December 7th, 2020, collecting data through interviews with the patient, observation, and physical assessment. It was found that the main health problems were insufficient nutrition, less physical need, insomnia, and potentially dangerous falls. As an outpatient nurse, the author observed that in recent years, the age group of women with premature menopause, osteoporosis and sarcopenia had shifted downward. Integrated multi-disciplinary interventions were provided upon the initial diagnosis of osteoporosis and sarcopenia. Under the outpatient care setting, the collaborative team works between the doctors, nutritionists, osteoporosis educators, rehabilitates, physical therapists and other specialized teams were applied to provide individualized, integrated multi-disciplinary care. Through empathy and the establishment of attentive care, companionship and trust, we discussed care plans and treatment guidelines with the case, providing accurate, complete disease information and feedback education to strengthen the patient’s knowledge and motivation for exercise. Nursing guidance regarding the dietary nutrition and adjustment of daily routine was provided to increase the self-care ability, improve the health problems of muscle weakness and insomnia, and prevent falls. For patients with postmenopausal osteoporosis and sarcopenia, it is recommended that the nurses coordinate the multi-discipline integrated care model, adjust patients’ lifestyle and diet, and establish a regular exercise plan so that the cases can be evaluated holistically to improve the quality of care and physical and mental comfort.

Keywords: multi-discipline care model, premature menopause, osteoporosis, sarcopenia, insomnia

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13330 Transformation of Industrial Policy towards Industry 4.0 and Its Impact on Firms' Competition

Authors: Arūnas Burinskas

Abstract:

Although Europe is on the threshold of a new industrial revolution called Industry 4.0, many believe that this will increase the flexibility of production, the mass adaptation of products to consumers and the speed of their service; it will also improve product quality and dramatically increase productivity. However, as expected, all the benefits of Industry 4.0 face many of the inevitable changes and challenges they pose. One of them is the inevitable transformation of current competition and business models. This article examines the possible results of competitive conversion from the classic Bertrand and Cournot models to qualitatively new competition based on innovation. Ability to deliver a new product quickly and the possibility to produce the individual design (through flexible and quickly configurable factories) by reducing equipment failures and increasing process automation and control is highly important. This study shows that the ongoing transformation of the competition model is changing the game. This, together with the creation of complex value networks, means huge investments that make it particularly difficult for small and medium-sized enterprises. In addition, the ongoing digitalization of data raises new concerns regarding legal obligations, intellectual property, and security.

Keywords: Bertrand and Cournot Competition, competition model, industry 4.0, industrial organisation, monopolistic competition

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13329 An Efficient Robot Navigation Model in a Multi-Target Domain amidst Static and Dynamic Obstacles

Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

Abstract:

This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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13328 Predicting Loss of Containment in Surface Pipeline using Computational Fluid Dynamics and Supervised Machine Learning Model to Improve Process Safety in Oil and Gas Operations

Authors: Muhammmad Riandhy Anindika Yudhy, Harry Patria, Ramadhani Santoso

Abstract:

Loss of containment is the primary hazard that process safety management is concerned within the oil and gas industry. Escalation to more serious consequences all begins with the loss of containment, starting with oil and gas release from leakage or spillage from primary containment resulting in pool fire, jet fire and even explosion when reacted with various ignition sources in the operations. Therefore, the heart of process safety management is avoiding loss of containment and mitigating its impact through the implementation of safeguards. The most effective safeguard for the case is an early detection system to alert Operations to take action prior to a potential case of loss of containment. The detection system value increases when applied to a long surface pipeline that is naturally difficult to monitor at all times and is exposed to multiple causes of loss of containment, from natural corrosion to illegal tapping. Based on prior researches and studies, detecting loss of containment accurately in the surface pipeline is difficult. The trade-off between cost-effectiveness and high accuracy has been the main issue when selecting the traditional detection method. The current best-performing method, Real-Time Transient Model (RTTM), requires analysis of closely positioned pressure, flow and temperature (PVT) points in the pipeline to be accurate. Having multiple adjacent PVT sensors along the pipeline is expensive, hence generally not a viable alternative from an economic standpoint.A conceptual approach to combine mathematical modeling using computational fluid dynamics and a supervised machine learning model has shown promising results to predict leakage in the pipeline. Mathematical modeling is used to generate simulation data where this data is used to train the leak detection and localization models. Mathematical models and simulation software have also been shown to provide comparable results with experimental data with very high levels of accuracy. While the supervised machine learning model requires a large training dataset for the development of accurate models, mathematical modeling has been shown to be able to generate the required datasets to justify the application of data analytics for the development of model-based leak detection systems for petroleum pipelines. This paper presents a review of key leak detection strategies for oil and gas pipelines, with a specific focus on crude oil applications, and presents the opportunities for the use of data analytics tools and mathematical modeling for the development of robust real-time leak detection and localization system for surface pipelines. A case study is also presented.

Keywords: pipeline, leakage, detection, AI

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13327 Quadratic Convective Flow of a Micropolar Fluid in a Non-Darcy Porous Medium with Convective Boundary Condition

Authors: Ch. Ramreddy, P. Naveen, D. Srinivasacharya

Abstract:

The objective of the present study is to investigate the effect of nonlinear temperature and concentration on the mixed convective flow of micropolar fluid over an inclined flat plate in a non-Darcy porous medium in the presence of convective boundary condition. In order to analyze all the essential features, the transformed nonlinear conservation equations are worked out numerically by spectral method. By insisting the comparison between vertical, horizontal and inclined plates, the physical quantities of the flow and its characteristics are exhibited graphically and quantitatively with various parameters. An increase in the coupling number and inclination of angle tend to decrease the skin friction, mass transfer rate and the reverse change is there in wall couple stress and heat transfer rate. The nominal effect on the wall couple stress and skin friction is encountered whereas the significant effect on the local heat and mass transfer rates are found for high enough values of Biot number.

Keywords: convective boundary condition, micropolar fluid, non-darcy porous medium, non-linear convection, spectral method

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13326 Fuzzy-Machine Learning Models for the Prediction of Fire Outbreak: A Comparative Analysis

Authors: Uduak Umoh, Imo Eyoh, Emmauel Nyoho

Abstract:

This paper compares fuzzy-machine learning algorithms such as Support Vector Machine (SVM), and K-Nearest Neighbor (KNN) for the predicting cases of fire outbreak. The paper uses the fire outbreak dataset with three features (Temperature, Smoke, and Flame). The data is pre-processed using Interval Type-2 Fuzzy Logic (IT2FL) algorithm. Min-Max Normalization and Principal Component Analysis (PCA) are used to predict feature labels in the dataset, normalize the dataset, and select relevant features respectively. The output of the pre-processing is a dataset with two principal components (PC1 and PC2). The pre-processed dataset is then used in the training of the aforementioned machine learning models. K-fold (with K=10) cross-validation method is used to evaluate the performance of the models using the matrices – ROC (Receiver Operating Curve), Specificity, and Sensitivity. The model is also tested with 20% of the dataset. The validation result shows KNN is the better model for fire outbreak detection with an ROC value of 0.99878, followed by SVM with an ROC value of 0.99753.

Keywords: Machine Learning Algorithms , Interval Type-2 Fuzzy Logic, Fire Outbreak, Support Vector Machine, K-Nearest Neighbour, Principal Component Analysis

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13325 Use of Analytic Hierarchy Process for Plant Site Selection

Authors: Muzaffar Shaikh, Shoaib Shaikh, Mark Moyou, Gaby Hawat

Abstract:

This paper presents the use of Analytic Hierarchy Process (AHP) in evaluating the site selection of a new plant by a corporation. Due to intense competition at a global level, multinational corporations are continuously striving to minimize production and shipping costs of their products. One key factor that plays significant role in cost minimization is where the production plant is located. In the U.S. for example, labor and land costs continue to be very high while they are much cheaper in countries such as India, China, Indonesia, etc. This is why many multinational U.S. corporations (e.g. General Electric, Caterpillar Inc., Ford, General Motors, etc.), have shifted their manufacturing plants outside. The continued expansion of the Internet and its availability along with technological advances in computer hardware and software all around the globe have facilitated U.S. corporations to expand abroad as they seek to reduce production cost. In particular, management of multinational corporations is constantly engaged in concentrating on countries at a broad level, or cities within specific countries where certain or all parts of their end products or the end products themselves can be manufactured cheaper than in the U.S. AHP is based on preference ratings of a specific decision maker who can be the Chief Operating Officer of a company or his/her designated data analytics engineer. It serves as a tool to first evaluate the plant site selection criteria and second, alternate plant sites themselves against these criteria in a systematic manner. Examples of site selection criteria are: Transportation Modes, Taxes, Energy Modes, Labor Force Availability, Labor Rates, Raw Material Availability, Political Stability, Land Costs, etc. As a necessary first step under AHP, evaluation criteria and alternate plant site countries are identified. Depending upon the fidelity of analysis, specific cities within a country can also be chosen as alternative facility locations. AHP experience in this type of analysis indicates that the initial analysis can be performed at the Country-level. Once a specific country is chosen via AHP, secondary analyses can be performed by selecting specific cities or counties within a country. AHP analysis is usually based on preferred ratings of a decision-maker (e.g., 1 to 5, 1 to 7, or 1 to 9, etc., where 1 means least preferred and a 5 means most preferred). The decision-maker assigns preferred ratings first, criterion vs. criterion and creates a Criteria Matrix. Next, he/she assigns preference ratings by alternative vs. alternative against each criterion. Once this data is collected, AHP is applied to first get the rank-ordering of criteria. Next, rank-ordering of alternatives is done against each criterion resulting in an Alternative Matrix. Finally, overall rank ordering of alternative facility locations is obtained by matrix multiplication of Alternative Matrix and Criteria Matrix. The most practical aspect of AHP is the ‘what if’ analysis that the decision-maker can conduct after the initial results to provide valuable sensitivity information of specific criteria to other criteria and alternatives.

Keywords: analytic hierarchy process, multinational corporations, plant site selection, preference ratings

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13324 Local Government Digital Attention and Green Technology Innovation: Analysis Based on Spatial Durbin Model

Authors: Xin Wang, Chaoqun Ma, Zheng Yao

Abstract:

Although green technology innovation faces new opportunities and challenges in the digital era, its theoretical research remains limited. Drawing on the attention-based view, this study employs the spatial Durbin model to investigate the impact of local government digital attention and digital industrial agglomeration on green technology innovation across 30 Chinese provinces from 2011 to 2021, as well as the spatial spillover effects present. The results suggest that both government digital attention and digital industrial agglomeration positively influence green technology innovation in local and neighboring provinces, with digital industrial agglomeration exhibiting a positive moderating effect on this direct local and indirect spatial spillover relationship. The findings of this study provide a new theoretical perspective for green technology innovation research and hold valuable implications for the advancement of the attention-based view and green technology innovation.

Keywords: local government digital attention, digital industrial agglomeration, green technology innovation, attention-based view

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13323 Iraqi Short Term Electrical Load Forecasting Based on Interval Type-2 Fuzzy Logic

Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

Abstract:

Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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13322 The Entrepreneurial Journey of Students: An Identity Perspective

Authors: J. Marchand

Abstract:

While university dropout entrepreneurs are celebrated in the practitioner literature, students’ intentions of becoming entrepreneurs have increasingly been the focus of student entrepreneur studies. However, students who are already running a business have rarely been examined. The experience of these students is a phenomenon that requires further research. Entrepreneurial identity represents a gap in the organisational studies literature. This paper utilises studentpreneurs’ self-narratives of their entrepreneurial journey. More specifically, the aim is to answer the following question: what are the types of identity work that individuals go through to build their entrepreneurial identity during that journey? Through long interviews, this paper studies the lived experience of 14 studentpreneurs who have achieved $54,000 in income and who participated publicly in entrepreneurial competitions. A general inductive analysis is performed on their narrative. With its focus on the journey, this paper makes a contribution to the literature on identity work and the entrepreneurial journey. A key contribution is the study of identity work on the journey to becoming an (established) entrepreneur in contrast to routine identity work.

Keywords: entrepreneurial identity, student entrepreneur, identity work, student entrepreneurship

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13321 Detection of Intravenous Infiltration Using Impedance Parameters in Patients in a Long-Term Care Hospital

Authors: Ihn Sook Jeong, Eun Joo Lee, Jae Hyung Kim, Gun Ho Kim, Young Jun Hwang

Abstract:

This study investigated intravenous (IV) infiltration using bioelectrical impedance for 27 hospitalized patients in a long-term care hospital. Impedance parameters showed significant differences before and after infiltration as follows. First, the resistance (R) after infiltration significantly decreased compared to the initial resistance. This indicates that the IV solution flowing from the vein due to infiltration accumulates in the extracellular fluid (ECF). Second, the relative resistance at 50 kHz was 0.94 ± 0.07 in 9 subjects without infiltration and was 0.75 ± 0.12 in 18 subjects with infiltration. Third, the magnitude of the reactance (Xc) decreased after infiltration. This is because IV solution and blood components released from the vein tend to aggregate in the cell membrane (and acts analogously to the linear/parallel circuit), thereby increasing the capacitance (Cm) of the cell membrane and reducing the magnitude of reactance. Finally, the data points plotted in the R-Xc graph were distributed on the upper right before infiltration but on the lower left after infiltration. This indicates that the infiltration caused accumulation of fluid or blood components in the epidermal and subcutaneous tissues, resulting in reduced resistance and reactance, thereby lowering integrity of the cell membrane. Our findings suggest that bioelectrical impedance is an effective method for detection of infiltration in a noninvasive and quantitative manner.

Keywords: intravenous infiltration, impedance, parameters, resistance, reactance

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13320 Determination of Chemical and Adsorption Kinetics: An Investigation of a Petrochemical Wastewater Treatment Utilizing GAC

Authors: Leila Vafajoo, Feria Ghanaat, Alireza Mohmadi Kartalaei, Amin Ghalebi

Abstract:

Petrochemical industries are playing an important role in producing wastewaters. Nowadays different methods are employed to treat these materials. The goal of the present research was to reduce the COD of a petrochemical wastewater via adsorption technique using a commercial granular activated carbon (GAC) as adsorbent. In the current study, parameters of kinetic models as well as; adsorption isotherms were determined through utilizing the Langmuir and Freundlich isotherms. The key parameters of KL= 0.0009 and qm= 33.33 for the former and nf=0.5 and Kf= 0.000004 for the latter isotherms resulted. Moreover, a correlation coefficient of above 90% for both cases proved logical use of such isotherms. On the other hand, pseudo-first and -second order kinetics equations were implemented. These resulted in coefficients of k1=0.005 and qe=2018 as well as; K2=0.009 and qe=1250; respectively. In addition, obtaining the correlation coefficients of 0.94 and 0.68 for these 1st and 2nd order kinetics; respectively indicated advantageous use of the former model. Furthermore, a significant experimental reduction of the petrochemical wastewater COD revealed that, using GAC for the process undertaken was an efficient mean of treatment. Ultimately, the current investigation paved down the road for predicting the system’s behavior on industrial scale.

Keywords: petrochemical wastewater, adsorption, granular activated carbon, equilibrium isotherm, kinetic model

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13319 Sequence Component-Based Adaptive Protection for Microgrids Connected Power Systems

Authors: Isabelle Snyder

Abstract:

Microgrid protection presents challenges to conventional protection techniques due to the low induced fault current. Protection relays present in microgrid applications require a combination of settings groups to adjust based on the architecture of the microgrid in islanded and grid-connected mode. In a radial system where the microgrid is at the other end of the feeder, directional elements can be used to identify the direction of the fault current and switch settings groups accordingly (grid connected or microgrid connected). However, with multiple microgrid connections, this concept becomes more challenging, and the direction of the current alone is not sufficient to identify the source of the fault current contribution. ORNL has previously developed adaptive relaying schemes through other DOE-funded research projects that will be evaluated and used as a baseline for this research. The four protection techniques in this study are the following: (1) Adaptive Current only Protection System (ACPS), Intentional (2) Unbalanced Control for Protection Control (IUCPC), (3) Adaptive Protection System with Communication Controller (APSCC) (4) Adaptive Model-Driven Protective Relay (AMDPR). The first two methods focus on identifying the islanded mode without communication by monitoring the current sequence component generated by the system (ACPS) or induced with inverter control during islanded mode (IUCPC) to identify the islanding condition without communication at the relay to adjust the settings. These two methods are used as a backup to the APSCC, which relies on a communication network to communicate the islanded configuration to the system components. The fourth method relies on a short circuit model inside the relay that is used in conjunction with communication to adjust the system configuration and computes the fault current and adjusts the settings accordingly.

Keywords: adaptive relaying, microgrid protection, sequence components, islanding detection, communication controlled protection, integrated short circuit model

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13318 Application of Mathematical Models for Conducting Long-Term Metal Fume Exposure Assessments for Workers in a Shipbuilding Factory

Authors: Shu-Yu Chung, Ying-Fang Wang, Shih-Min Wang

Abstract:

To conduct long-term exposure assessments are important for workers exposed to chemicals with chronic effects. However, it usually encounters with several constrains, including cost, workers' willingness, and interference to work practice, etc., leading to inadequate long-term exposure data in the real world. In this study, an integrated approach was developed for conducting long-term exposure assessment for welding workers in a shipbuilding factory. A laboratory study was conducted to yield the fume generation rates under various operating conditions. The results and the measured environmental conditions were applied to the near field/far field (NF/FF) model for predicting long term fume exposures via the Monte Carlo simulation. Then, the predicted long-term concentrations were used to determine the prior distribution in Bayesian decision analysis (BDA). Finally, the resultant posterior distributions were used to assess the long-term exposure and serve as basis for initiating control strategies for shipbuilding workers. Results show that the NF/FF model was a suitable for predicting the exposures of metal contents containing in welding fume. The resultant posterior distributions could effectively assess the long-term exposures of shipbuilding welders. Welders' long-term Fe, Mn and Pb exposures were found with high possibilities to exceed the action level indicating preventive measures should be taken for reducing welders' exposures immediately. Though the resultant posterior distribution can only be regarded as the best solution based on the currently available predicting and monitoring data, the proposed integrated approach can be regarded as a possible solution for conducting long term exposure assessment in the field.

Keywords: Bayesian decision analysis, exposure assessment, near field and far field model, shipbuilding industry, welding fume

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13317 Using Power Flow Analysis for Understanding UPQC’s Behaviors

Authors: O. Abdelkhalek, A. Naimi, M. Rami, M. N. Tandjaoui, A. Kechich

Abstract:

This paper deals with the active and reactive power flow analysis inside the unified power quality conditioner (UPQC) during several cases. The UPQC is a combination of shunt and series active power filter (APF). It is one of the best solutions towards the mitigation of voltage sags and swells problems on distribution network. This analysis can provide the helpful information to well understanding the interaction between the series filter, the shunt filter, the DC bus link and electrical network. The mathematical analysis is based on active and reactive power flow through the shunt and series active power filter. Wherein series APF can absorb or deliver the active power to mitigate a swell or sage voltage where in the both cases it absorbs a small reactive power quantity whereas the shunt active power absorbs or releases the active power for stabilizing the storage capacitor’s voltage as well as the power factor correction. The voltage sag and voltage swell are usually interpreted through the DC bus voltage curves. These two phenomena are introduced in this paper with a new interpretation based on the active and reactive power flow analysis inside the UPQC. For simplifying this study, a linear load is supposed in this digital simulation. The simulation results are carried out to confirm the analysis done.

Keywords: UPQC, Power flow analysis, shunt filter, series filter.

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13316 Climate Change Impact on Mortality from Cardiovascular Diseases: Case Study of Bucharest, Romania

Authors: Zenaida Chitu, Roxana Bojariu, Liliana Velea, Roxana Burcea

Abstract:

A number of studies show that extreme air temperature affects mortality related to cardiovascular diseases, particularly among elderly people. In Romania, the summer thermal discomfort expressed by Universal Thermal Climate Index (UTCI) is highest in the Southern part of the country, where Bucharest, the largest Romanian urban agglomeration, is also located. The urban characteristics such as high building density and reduced green areas enhance the increase of the air temperature during summer. In Bucharest, as in many other large cities, the effect of heat urban island is present and determines an increase of air temperature compared to surrounding areas. This increase is particularly important during heat wave periods in summer. In this context, the researchers performed a temperature-mortality analysis based on daily deaths related to cardiovascular diseases, recorded between 2010 and 2019 in Bucharest. The temperature-mortality relationship was modeled by applying distributed lag non-linear model (DLNM) that includes a bi-dimensional cross-basis function and flexible natural cubic spline functions with three internal knots in the 10th, 75th and 90th percentiles of the temperature distribution, for modelling both exposure-response and lagged-response dimensions. Firstly, this study applied this analysis for the present climate. Extrapolation of the exposure-response associations beyond the observed data allowed us to estimate future effects on mortality due to temperature changes under climate change scenarios and specific assumptions. We used future projections of air temperature from five numerical experiments with regional climate models included in the EURO-CORDEX initiative under the relatively moderate (RCP 4.5) and pessimistic (RCP 8.5) concentration scenarios. The results of this analysis show for RCP 8.5 an ensemble-averaged increase with 6.1% of heat-attributable mortality fraction in future in comparison with present climate (2090-2100 vs. 2010-219), corresponding to an increase of 640 deaths/year, while mortality fraction due to the cold conditions will be reduced by 2.76%, corresponding to a decrease by 288 deaths/year. When mortality data is stratified according to the age, the ensemble-averaged increase of heat-attributable mortality fraction for elderly people (> 75 years) in the future is even higher (6.5 %). These findings reveal the necessity to carefully plan urban development in Bucharest to face the public health challenges raised by the climate change. Paper Details: This work is financed by the project URCLIM which is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by Ministry of Environment, Romania with co-funding by the European Union (Grant 690462). A part of this work performed by one of the authors has received funding from the European Union’s Horizon 2020 research and innovation programme from the project EXHAUSTION under grant agreement No 820655.

Keywords: cardiovascular diseases, climate change, extreme air temperature, mortality

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13315 Modeling of Polyethylene Particle Size Distribution in Fluidized Bed Reactors

Authors: R. Marandi, H. Shahrir, T. Nejad Ghaffar Borhani, M. Kamaruddin

Abstract:

In the present study, a steady state population balance model was developed to predict the polymer particle size distribution (PSD) in ethylene gas phase fluidized bed olefin polymerization reactors. The multilayer polymeric flow model (MPFM) was used to calculate the growth rate of a single polymer particle under intra-heat and mass transfer resistance. The industrial plant data were used to calculate the growth rate of polymer particle and the polymer PSD. Numerical simulations carried out to describe the influence of effective monomer diffusion coefficient, polymerization rate and initial catalyst size on the catalyst particle growth and final polymer PSD. The results present that the intra-heat and mass limitation is important for the ethylene polymerization, the growth rate of particle and the polymer PSD in the fluidized bed reactor. The effect of the agglomeration on the PSD is also considered. The result presents that the polymer particle size distribution becomes broader as the agglomeration exits.

Keywords: population balance, olefin polymerization, fluidized bed reactor, particle size distribution, agglomeration

Procedia PDF Downloads 319
13314 An Analysis of Sequential Pattern Mining on Databases Using Approximate Sequential Patterns

Authors: J. Suneetha, Vijayalaxmi

Abstract:

Sequential Pattern Mining involves applying data mining methods to large data repositories to extract usage patterns. Sequential pattern mining methodologies used to analyze the data and identify patterns. The patterns have been used to implement efficient systems can recommend on previously observed patterns, in making predictions, improve usability of systems, detecting events, and in general help in making strategic product decisions. In this paper, identified performance of approximate sequential pattern mining defines as identifying patterns approximately shared with many sequences. Approximate sequential patterns can effectively summarize and represent the databases by identifying the underlying trends in the data. Conducting an extensive and systematic performance over synthetic and real data. The results demonstrate that ApproxMAP effective and scalable in mining large sequences databases with long patterns.

Keywords: multiple data, performance analysis, sequential pattern, sequence database scalability

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13313 Democracy Leadership and Good Governance in Nigerias Fourth Republic

Authors: Salisu Adamu Abdullahi, Yusuf Abdullahi Manu

Abstract:

Nigeria returned to a democratically elected government on May 29, 1999. This signaled the beginning of the journey into the Fourth Republic. The return has received popular endorsement by the electorates as the level of enthusiasm was high due to the yearnings and expectations by the electorate that democracy will bring about the much-desired change required by the general mass. As democracy would allow for popular participation through periodic elections and so on. The paper examines democracy, leadership, and challenges of good governance in Nigerias Fourth Republic. It utilizes secondary source of data and content analysis as a methodology. It argues that Nigerias practice of democracy over the years is marred by flagrant abuse of the principles of good governance by the ruling elite. This has posed threats to the survival of democracy due to non-adherence to one of the cardinal principles of democracy which is good governance. The paper recommends among others that the anti-corruption law is amended in such a way that death penalties be issued to those found wanting by the law.

Keywords: democracy, democratic consolidation, challenges, good governance

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13312 The Impact of Artificial Intelligence on the Behavior of Children and Autism

Authors: Sara Fayez Fawzy Mikhael

Abstract:

Inclusive education services for students with Autism remains in its early developmental stages in Thailand. Despite many more children with autism are attending schools since the Thai government introduced the Education Provision for People with Disabilities Act in 2008, the services students with autism and their families receive are generally lacking. This quantitative study used Attitude and Preparedness to Teach Students with Autism Scale (APTSAS) to investigate 110 primary school teachers’ attitude and preparedness to teach students with autism in the general education classroom. Descriptive statistical analysis of the data found that student behavior was the most significant factor in building teachers’ negative attitudes students with autism. The majority of teachers also indicated that their pre-service education did not prepare them to meet the learning needs of children with autism in particular, those who are non-verbal. The study is significant and provides direction for enhancing teacher education for inclusivity in Thailand.

Keywords: attitude, autism, teachers, thailandsports activates, movement skills, motor skills

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13311 Unsteady Heat and Mass Transfer in MHD Flow of Nanofluids over Stretching Sheet with a Non Uniform Heat Source/Sink

Authors: Bandari Shankar, Yohannes Yirga

Abstract:

In this paper, the problem of heat and mass transfer in unsteady MHD boundary-layer flow of nanofluids over stretching sheet with a non uniform heat source/sink is considered. The unsteadiness in the flow and temperature is caused by the time-dependent stretching velocity and surface temperature. The unsteady boundary layer equations are transformed to a system of non-linear ordinary differential equations and solved numerically using Keller box method. The velocity, temperature, and concentration profiles were obtained and utilized to compute the skin-friction coefficient, local Nusselt number, and local Sherwood number for different values of the governing parameters viz. solid volume fraction parameter, unsteadiness parameter, magnetic field parameter, Schmidt number, space-dependent and temperature-dependent parameters for heat source/sink. A comparison of the numerical results of the present study with previously published data revealed an excellent agreement

Keywords: unsteady, heat and mass transfer, manetohydrodynamics, nanofluid, non-uniform heat source/sink, stretching sheet

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13310 Selection of Social and Sustainability Criteria for Public Investment Project Evaluation in Developing Countries

Authors: Pintip Vajarothai, Saad Al-Jibouri, Johannes I. M. Halman

Abstract:

Public investment projects are primarily aimed at achieving development strategies to increase national economies of scale and overall improvement in a country. However, experience shows that public projects, particularly in developing countries, struggle or fail to fulfill the immediate needs of local communities. In many cases, the reason for that is that projects are selected in a subjective manner and that a major part of the problem is related to the evaluation criteria and techniques used. The evaluation process is often based on a broad strategic economic effects rather than real benefits of projects to society or on the various needs from different levels (e.g. national, regional, local) and conditions (e.g. long-term and short-term requirements). In this paper, an extensive literature review of the types of criteria used in the past by various researchers in project evaluation and selection process is carried out and the effectiveness of such criteria and techniques is discussed. The paper proposes substitute social and project sustainability criteria to improve the conditions of local people and in particular the disadvantaged groups of the communities. Furthermore, it puts forward a way for modelling the interaction between the selected criteria and the achievement of the social goals of the affected community groups. The described work is part of developing a broader decision model for public investment project selection by integrating various aspects and techniques into a practical methodology. The paper uses Thailand as a case to review what and how the various evaluation techniques are currently used and how to improve the project evaluation and selection process related to social and sustainability issues in the country. The paper also uses an example to demonstrates how to test the feasibility of various criteria and how to model the interaction between projects and communities. The proposed model could be applied to other developing and developed countries in the project evaluation and selection process to improve its effectiveness in the long run.

Keywords: evaluation criteria, developing countries, public investment, project selection methodology

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13309 Design of Wireless and Traceable Sensors for Internally Illuminated Photoreactors

Authors: Alexander Sutor, David Demetz

Abstract:

We present methods for developing wireless and traceable sensors for photobioreactors or photoreactors in general. The main focus of application are reactors which are wirelessly powered. Due to the promising properties of the propagation of magnetic fields under water we implemented an inductive link with an on/off switched hartley-oscillator as transmitter and an LC-tank as receiver. For this inductive link we used a carrier frequency of 298 kHz. With this system we performed measurements to demonstrate the independence of the magnetic field from water or salty water. In contrast we showed the strongly reduced range of RF-transmitter-receiver systems at higher frequencies (433 MHz and 2.4 GHz) in water and in salty water. For implementing the traceability of the sensors, we performed measurements to show the well defined orientation of the magnetic field of a coil. This information will be used in future work for implementing an inductive link based traceability system for our sensors.

Keywords: wireless sensors, photoreactor, internal illumination, wireless power

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13308 A Statistical Study on Young UAE Driver’s Behavior towards Road Safety

Authors: Sadia Afroza, Rakiba Rouf

Abstract:

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

Procedia PDF Downloads 246