Search results for: combined wavelet-artificial neural network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7720

Search results for: combined wavelet-artificial neural network

1570 Effect of Laminating Sequence of MWCNTs and Fe₂O₃ Filled Nanocomposites on Emi Shielding Effectiveness

Authors: Javeria Ahmad, Ayesha Maryam, Zahid Rizwan, Nadeem Nasir, Yasir Nawab, Hafiz Shehbaz Ahmad

Abstract:

Mitigation of electromagnetic interference (EMI) through thin, lightweight, and cost-effective materials is critical for electronic appliances as well as human health. The present research work discusses the design of composites that are suitable to minimize EMI through various stacking sequences. The carbon fibers reinforced composite structures impregnated with dielectric (MWCNTs) and magnetic nanofillers (Fe₂O₃) were developed to investigate their microwave absorption properties. The composite structure comprising a single type of nanofillers, each of MWCNTs & Fe₂O₃, was developed, and then their layers were stacked over each other with various stacking sequences to investigate the best stacking sequence, which presents good microwave absorption characteristics. A vector network analyzer (VNA) was used to analyze the microwave absorption properties of these developed composite structures. The composite structures impregnated with the layers of a dielectric nanofiller and sandwiched between the layers of a magnetic nanofiller show the highest EMI shielding value of 59 dB and a dielectric conductivity of 35 S/cm in the frequency range of 0.1 to 13.6 GHz. The results also demonstrate that the microwave absorption properties of the developed composite structures were dominant over reflection properties. The absence of an external peak in X-ray diffraction (XRD), marked the purity of the added nanofillers.

Keywords: nanocomposites, microwave absorption, EMI shielding, skin depth, reflection loss

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1569 Enhancing Fault Detection in Rotating Machinery Using Wiener-CNN Method

Authors: Mohamad R. Moshtagh, Ahmad Bagheri

Abstract:

Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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1568 Product Separation of Green Processes and Catalyst Recycling of a Homogeneous Polyoxometalate Catalyst Using Nanofiltration Membranes

Authors: Dorothea Voß, Tobias Esser, Michael Huber, Jakob Albert

Abstract:

The growing world population and the associated increase in demand for energy and consumer goods, as well as increasing waste production, requires the development of sustainable processes. In addition, the increasing environmental awareness of our society is a driving force for the requirement that processes must be as resource and energy efficient as possible. In this context, the use of polyoxometalate catalysts (POMs) has emerged as a promising approach for the development of green processes. POMs are bifunctional polynuclear metal-oxo-anion cluster characterized by a strong Brønsted acidity, a high proton mobility combined with fast multi-electron transfer and tunable redox potential. In addition, POMs are soluble in many commonly known solvents and exhibit resistance to hydrolytic and oxidative degradation. Due to their structure and excellent physicochemical properties, POMs are efficient acid and oxidation catalysts that have attracted much attention in recent years. Oxidation processes with molecular oxygen are worth mentioning here. However, the fact that the POM catalysts are homogeneous poses a challenge for downstream processing of product solutions and recycling of the catalysts. In this regard, nanofiltration membranes have gained increasing interest in recent years, particularly due to their relative sustainability advantage over other technologies and their unique properties such as increased selectivity towards multivalent ions. In order to establish an efficient downstream process for the highly selective separation of homogeneous POM catalysts from aqueous solutions using nanofiltration membranes, a laboratory-scale membrane system was designed and constructed. By varying various process parameters, a sensitivity analysis was performed on a model system to develop an optimized method for the recovery of POM catalysts. From this, process-relevant key figures such as the rejection of various system components were derived. These results form the basis for further experiments on other systems to test the transferability to serval separation tasks with different POMs and products, as well as for recycling experiments of the catalysts in processes on laboratory scale.

Keywords: downstream processing, nanofiltration, polyoxometalates, homogeneous catalysis, green chemistry

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1567 The Developing of Knowledge-Based System for the Medical Treatment with Herbs

Authors: Rujijan Vichivanives

Abstract:

This research aims to create a knowledge-based system as a database for self-healthcare analysis, diagnosis of simple illnesses, and the use of Thai herbs instead of modern medicine by using principles of Thai traditional medication theory. These were disseminated by website network programs within Suan Sunandha Rajabhat University. The population used in this study was divided into two groups: the first group consisted of four experts of Thai traditional medication and the second group was 300 website users. The methods used for collecting data were paper questionnaires and poll questionnaires on the website. The statistics used for analyzing data was at an average level. The results were divided into three parts: the first part was the development of a knowledge-based system and the second part was applied programs on website. Both parts could be fulfilled and achieved according to the set goal. The third part was the evaluation of the study: The evaluation of the viewpoints of the experts towards website designs were evaluated at a good level of 4.20. The satisfaction evaluation of the users was found at a good level of average satisfactory level at 4.24. It was found that the young population of those under the age of 16 had less cares about their health than the population of other teenagers, working age adults and those of older age. The research findings should be extended in order to encourage the lifestyle modifications to people of all ages by using the self-healthcare principles.

Keywords: developing, herbs, knowledge-based system, medical treatment

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1566 Polyclonal IgG glycosylation in Patients with Pediatric Appendicitis

Authors: Dalma Dojcsák, Csaba Váradi, Flóra Farkas, Tamás Farkas, János Papp, Béla Viskolcz

Abstract:

Background: Appendicitis is a common acute inflammatory condition in both children and adults, but current laboratory markers such as C-reactive protein (CRP), white blood cell count (WBC), absolute neutrophil count (ANC), and red blood cell count (RNC) lack specificity in detecting appendicitis-related inflammation. N-glycosylation, an asparagine-linked glycosylation process, plays a vital role in cellular interactions, angiogenesis, immune response, and effector functions. Altered N-glycosylation impacts tumor growth and both acute and chronic inflammatory processes. IgG, the second most abundant glycoprotein in serum, shows altered glycosylation patterns during inflammation, suggesting that IgG glycan modifications may serve as potential biomarkers for appendicitis. Specifically, increased levels of agalactosylated IgG glycans are a known feature of various inflammatory conditions, potentially including appendicitis. Identifying pediatric appendicitis remains challenging due to the absence of specific biomarkers, which makes diagnosis reliant on clinical symptoms, imaging such as ultrasound, and nonspecific lab indicators (e.g., CRP, WBC, ANC). In this study, we analyzed the IgG derived N-glycome in pediatric patients with appendicitis compared with healthy controls. Methodology: The N-glycome was analyzed by high-performance liquid-chromatography combined with mass spectrometry. IgG was isolated from serum samples by Protein G column. The IgG derived glycans were released by enzymatic deglycosylation and fluorescent tags were attached to each glycan moiety, which made necessitates the sample clean-up for further reliable quantitation. Overall, 38 controls and 40 serum samples diagnosed with pediatric appendicitis were analyzed by HILIC-MS methods. Multivariate statistical tests were performed with area percentage under the peak data derived from the integrated peaks, which were obtained from the chromatograms. Conclusions: Our results represented the altered N-glycome of IgG in pediatric appendicitis is similar with other observations. The glycosylation pattern reported so far for IgG is characterized by decreased galactosylation and sialylation, and an increase in fucosylation.

Keywords: N-glycosylation, liquid chromatography, mass spectrometry, inflammation, appendicitis, immunoglobulin G

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1565 Optimal Simultaneous Sizing and Siting of DGs and Smart Meters Considering Voltage Profile Improvement in Active Distribution Networks

Authors: T. Sattarpour, D. Nazarpour

Abstract:

This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

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1564 Pinch Technology for Minimization of Water Consumption at a Refinery

Authors: W. Mughees, M. Alahmad

Abstract:

Water is the most significant entity that controls local and global development. For the Gulf region, especially Saudi Arabia, with its limited potable water resources, the potential of the fresh water problem is highly considerable. In this research, the study involves the design and analysis of pinch-based water/wastewater networks. Multiple water/wastewater networks were developed using pinch analysis involving direct recycle/material recycle method. Property-integration technique was adopted to carry out direct recycle method. Particularly, a petroleum refinery was considered as a case study. In direct recycle methodology, minimum water discharge and minimum fresh water resource targets were estimated. Re-design (or retrofitting) of water allocation in the networks was undertaken. Chemical Oxygen Demand (COD) and hardness properties were taken as pollutants. This research was based on single and double contaminant approach for COD and hardness and the amount of fresh water was reduced from 340.0 m3/h to 149.0 m3/h (43.8%), 208.0 m3/h (61.18%) respectively. While regarding double contaminant approach, reduction in fresh water demand was 132.0 m3/h (38.8%). The required analysis was also carried out using mathematical programming technique. Operating software such as LINGO was used for these studies which have verified the graphical method results in a valuable and accurate way. Among the multiple water networks, the one possible water allocation network was developed based on mass exchange.

Keywords: minimization, water pinch, water management, pollution prevention

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1563 Manipulation of Ideological Items in the Audiovisual Translation of Voiced-Over Documentaries in the Arab World

Authors: S. Chabbak

Abstract:

In a widely globalized world, the influence of audiovisual translation on the culture and identity of audiences is unmistakable. However, in the Arab World, there is a noticeable disproportion between this growing influence and the research carried out in the field. As a matter of fact, the voiced-over documentary is one of the most abundantly translated genres in the Arab World that carries lots of ideological elements which are in many cases rendered by manipulation. However, voiced-over documentaries have hardly received any focused attention from researchers in the Arab World. This paper attempts to scrutinize the process of translation of voiced-over documentaries in the Arab World, from French into Arabic in the present case study, by sub-categorizing the ideological items subject to manipulation, identifying the techniques utilized in their translation and exploring the potential extra-linguistic factors that prompt translation agents to opt for manipulative translation. The investigation is based on a corpus of 94 episodes taken from a series entitled 360° GEO Reports, produced by the French German network ARTE in French, and acquired, translated and aired by Al Jazeera Documentary Channel for Arab audiences. The results yielded 124 cases of manipulation in four sub-categories of ideological items, and the use of 10 different oblique procedures in the process of manipulative translation. The study also revealed that manipulation is in most of the instances dictated by the editorial line of the broadcasting channel, in addition to the religious, geopolitical and socio-cultural peculiarities of the target culture.

Keywords: audiovisual translation, ideological items, manipulation, voiced-over documentaries

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1562 Severity Index Level in Effectively Managing Medium Voltage Underground Power Cable

Authors: Mohd Azraei Pangah Pa'at, Mohd Ruzlin Mohd Mokhtar, Norhidayu Rameli, Tashia Marie Anthony, Huzainie Shafi Abd Halim

Abstract:

Partial Discharge (PD) diagnostic mapping testing is one of the main diagnostic testing techniques that are widely used in the field or onsite testing for underground power cable in medium voltage level. The existence of PD activities is an early indication of insulation weakness hence early detection of PD activities can be determined and provides an initial prediction on the condition of the cable. To effectively manage the results of PD Mapping test, it is important to have acceptable criteria to facilitate prioritization of mitigation action. Tenaga Nasional Berhad (TNB) through Distribution Network (DN) division have developed PD severity model name Severity Index (SI) for offline PD mapping test since 2007 based on onsite test experience. However, this severity index recommendation action had never been revised since its establishment. At presence, PD measurements data have been extensively increased, hence the severity level indication and the effectiveness of the recommendation actions can be analyzed and verified again. Based on the new revision, the recommended action to be taken will be able to reflect the actual defect condition. Hence, will be accurately prioritizing preventive action plan and minimizing maintenance expenditure.

Keywords: partial discharge, severity index, diagnostic testing, medium voltage, power cable

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1561 Profiling Risky Code Using Machine Learning

Authors: Zunaira Zaman, David Bohannon

Abstract:

This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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1560 Assessing Social Sustainability for Biofuels Supply Chains: The Case of Jet Biofuel in Brazil

Authors: Z. Wang, F. Pashaei Kamali, J. A. Posada Duque, P. Osseweijer

Abstract:

Globally, the aviation sector is seeking for sustainable solutions to comply with the pressure to reduce greenhouse gas emissions. Jet fuels derived from biomass are generally perceived as a sustainable alternative compared with their fossil counterparts. However, the establishment of jet biofuels supply chains will have impacts on environment, economy, and society. While existing studies predominantly evaluated environmental impacts and techno-economic feasibility of jet biofuels, very few studies took the social / socioeconomic aspect into consideration. Therefore, this study aims to provide a focused evaluation of social sustainability for aviation biofuels with a supply chain perspective. Three potential jet biofuel supply chains based on different feedstocks, i.e. sugarcane, eucalyptus, and macauba were analyzed in the context of Brazil. The assessment of social sustainability is performed with a process-based approach combined with input-output analysis. Over the supply chains, a set of social sustainability issues including employment, working condition (occupational accident and wage level), labour right, education, equity, social development (GDP and trade balance) and food security were evaluated in a (semi)quantitative manner. The selection of these social issues is based on two criteria: (1) the issues are highly relevant and important to jet biofuel production; (2) methodologies are available for assessing these issues. The results show that the three jet biofuel supply chains lead to a differentiated level of social effects. The sugarcane-based supply chain creates the highest number of jobs whereas the biggest contributor of GDP turns out to be the macauba-based supply chain. In comparison, the eucalyptus-based supply chain stands out regarding working condition. It is also worth noting that biojet fuel supply chain with high level of social benefits could result in high level of social concerns (such as occupational accident, violation of labour right and trade imbalance). Further research is suggested to investigate the possible interactions between different social issues. In addition, the exploration of a wider range of social effects is needed to expand the comprehension of social sustainability for biofuel supply chains.

Keywords: biobased supply chain, jet biofuel, social assessment, social sustainability, socio-economic impacts

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1559 Productivity and Household Welfare Impact of Technology Adoption: A Microeconometric Analysis

Authors: Tigist Mekonnen Melesse

Abstract:

Since rural households are basically entitled to food through own production, improving productivity might lead to enhance the welfare of rural population through higher food availability at the household level and lowering the price of agricultural products. Increasing agricultural productivity through the use of improved technology is one of the desired outcomes from sensible food security and agricultural policy. The ultimate objective of this study was to evaluate the potential impact of improved agricultural technology adoption on smallholders’ crop productivity and welfare. The study is conducted in Ethiopia covering 1500 rural households drawn from four regions and 15 rural villages based on data collected by Ethiopian Rural Household Survey. Endogenous treatment effect model is employed in order to account for the selection bias on adoption decision that is expected from the self-selection of households in technology adoption. The treatment indicator, technology adoption is a binary variable indicating whether the household used improved seeds and chemical fertilizer or not. The outcome variables were cereal crop productivity, measured in real value of production and welfare of households, measured in real per capita consumption expenditure. Results of the analysis indicate that there is positive and significant effect of improved technology use on rural households’ crop productivity and welfare in Ethiopia. Adoption of improved seeds and chemical fertilizer alone will increase the crop productivity by 7.38 and 6.32 percent per year of each. Adoption of such technologies is also found to improve households’ welfare by 1.17 and 0.25 percent per month of each. The combined effect of both technologies when adopted jointly is increasing crop productivity by 5.82 percent and improving welfare by 0.42 percent. Besides, educational level of household head, farm size, labor use, participation in extension program, expenditure for input and number of oxen positively affect crop productivity and household welfare, while large household size negatively affect welfare of households. In our estimation, the average treatment effect of technology adoption (average treatment effect on the treated, ATET) is the same as the average treatment effect (ATE). This implies that the average predicted outcome for the treatment group is similar to the average predicted outcome for the whole population.

Keywords: Endogenous treatment effect, technologies, productivity, welfare, Ethiopia

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1558 An Internet of Things Smart Washroom Framework

Authors: Robin Ratnasingham, Maher Elshakankiri

Abstract:

This research report will look at how to make a smart washroom to increase public hygiene and cleanliness. The system would use IoT devices to pick up various activities in the washroom and notify the appropriate stakeholders or devices to regulate the condition of the washroom. As more people are required to physically go back to the office or school, ensuring a clean and sanitized washroom is even more important now than before. It would help prevent virus outbreaks and safeguard the organization from shutdowns or slowdowns in their business. A framework of the suggested smart washroom was introduced to help reduce the chances of a virus outbreak. Most organizations outsource renovation or implementation to an external party. Using the smart washroom framework, we looked at vendors that provide smart washroom solutions. There are IoT vendors that cannot match the framework, and there are vendors that can support the framework design. This segment is a niche market, and most of the devices are similar in their basic functions. However, all the vendors have unique characteristics to give them a competitive advantage over the rest of the IoT washroom companies. Ultimately, the organization would need to decide if they want to add IoT devices to enable smart capability or renovate the washroom to create a fluid IoT smart washroom design. The report would introduce an IoT smart washroom framework to help organizations design a cohesive preventive measure network for the daily maintenance routine. The framework is designed to help understand how to manage washroom cleanliness more efficiently and to provide guidance in achieving this goal. The leading result is eliminating potential viral outbreaks that could jeopardize the organization.

Keywords: IoT, smart washroom, public hygiene, cleanliness, virus outbreaks, safeguard

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1557 Development of a Fire Analysis Drone for Smoke Toxicity Measurement for Fire Prediction and Management

Authors: Gabrielle Peck, Ryan Hayes

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This research presents the design and creation of a drone gas analyser, aimed at addressing the need for independent data collection and analysis of gas emissions during large-scale fires, particularly wasteland fires. The analyser drone, comprising a lightweight gas analysis system attached to a remote-controlled drone, enables the real-time assessment of smoke toxicity and the monitoring of gases released into the atmosphere during such incidents. The key components of the analyser unit included two gas line inlets connected to glass wool filters, a pump with regulated flow controlled by a mass flow controller, and electrochemical cells for detecting nitrogen oxides, hydrogen cyanide, and oxygen levels. Additionally, a non-dispersive infrared (NDIR) analyser is employed to monitor carbon monoxide (CO), carbon dioxide (CO₂), and hydrocarbon concentrations. Thermocouples can be attached to the analyser to monitor temperature, as well as McCaffrey probes combined with pressure transducers to monitor air velocity and wind direction. These additions allow for monitoring of the large fire and can be used for predictions of fire spread. The innovative system not only provides crucial data for assessing smoke toxicity but also contributes to fire prediction and management. The remote-controlled drone's mobility allows for safe and efficient data collection in proximity to the fire source, reducing the need for human exposure to hazardous conditions. The data obtained from the gas analyser unit facilitates informed decision-making by emergency responders, aiding in the protection of both human health and the environment. This abstract highlights the successful development of a drone gas analyser, illustrating its potential for enhancing smoke toxicity analysis and fire prediction capabilities. The integration of this technology into fire management strategies offers a promising solution for addressing the challenges associated with wildfires and other large-scale fire incidents. The project's methodology and results contribute to the growing body of knowledge in the field of environmental monitoring and safety, emphasizing the practical utility of drones for critical applications.

Keywords: fire prediction, drone, smoke toxicity, analyser, fire management

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1556 A Hybrid Traffic Model for Smoothing Traffic Near Merges

Authors: Shiri Elisheva Decktor, Sharon Hornstein

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Highway merges and unmarked junctions are key components in any urban road network, which can act as bottlenecks and create traffic disruption. Inefficient highway merges may trigger traffic instabilities such as stop-and-go waves, pose safety conditions and lead to longer journey times. These phenomena occur spontaneously if the average vehicle density exceeds a certain critical value. This study focuses on modeling the traffic using a microscopic traffic flow model. A hybrid traffic model, which combines human-driven and controlled vehicles is assumed. The controlled vehicles obey different driving policies when approaching the merge, or in the vicinity of other vehicles. We developed a co-simulation model in SUMO (Simulation of Urban Mobility), in which the human-driven cars are modeled using the IDM model, and the controlled cars are modeled using a dedicated controller. The scenario chosen for this study is a closed track with one merge and one exit, which could be later implemented using a scaled infrastructure on our lab setup. This will enable us to benchmark the results of this study obtained in simulation, to comparable results in similar conditions in the lab. The metrics chosen for the comparison of the performance of our algorithm on the overall traffic conditions include the average speed, wait time near the merge, and throughput after the merge, measured under different travel demand conditions (low, medium, and heavy traffic).

Keywords: highway merges, traffic modeling, SUMO, driving policy

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1555 The Importance of Downstream Supply Chain in Supply Chain Risk Management: Multi-Objective Optimization

Authors: Zohreh Khojasteh-Ghamari, Takashi Irohara

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One of the efficient ways in supply chain risk management is avoiding the interruption in Supply Chain (SC) before it occurs. Although the majority of the organizations focus on their first-tier suppliers to avoid risk in the SC, studies show that in only 60 percent of the disruption cases the reason is first tier suppliers. In the 40 percent of the SC disruptions, the reason is downstream SC, which is the second tier and lower. Due to the increasing complexity and interrelation of modern supply chains, the SC elements have become difficult to trace. Moreover, studies show that there is a vital need to better understand the integration of risk and visibility, especially in the context of multiple objectives. In this study, we propose a multi-objective programming model to avoid disruption in SC. The objective of this study is evaluating the effect of downstream SCV on managing supply chain risk. We propose a multi-objective mathematical programming model with the objective functions of minimizing the total cost and maximizing the downstream supply chain visibility (SCV). The decision variable is supplier selection. We assume there are several manufacturers and several candidate suppliers. For each manufacturer, our model proposes the best suppliers with the lowest cost and maximum visibility in downstream supply chain. We examine the applicability of the model by numerical examples. We also define several scenarios for datasets and observe the tendency. The results show that minimum visibility in downstream SC is needed to have a safe SC network.

Keywords: downstream supply chain, optimization, supply chain risk, supply chain visibility

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1554 Transformation of Periodic Fuzzy Membership Function to Discrete Polygon on Circular Polar Coordinates

Authors: Takashi Mitsuishi

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Fuzzy logic has gained acceptance in the recent years in the fields of social sciences and humanities such as psychology and linguistics because it can manage the fuzziness of words and human subjectivity in a logical manner. However, the major field of application of the fuzzy logic is control engineering as it is a part of the set theory and mathematical logic. Mamdani method, which is the most popular technique for approximate reasoning in the field of fuzzy control, is one of the ways to numerically represent the control afforded by human language and sensitivity and has been applied in various practical control plants. Fuzzy logic has been gradually developing as an artificial intelligence in different applications such as neural networks, expert systems, and operations research. The objects of inference vary for different application fields. Some of these include time, angle, color, symptom and medical condition whose fuzzy membership function is a periodic function. In the defuzzification stage, the domain of the membership function should be unique to obtain uniqueness its defuzzified value. However, if the domain of the periodic membership function is determined as unique, an unintuitive defuzzified value may be obtained as the inference result using the center of gravity method. Therefore, the authors propose a method of circular-polar-coordinates transformation and defuzzification of the periodic membership functions in this study. The transformation to circular polar coordinates simplifies the domain of the periodic membership function. Defuzzified value in circular polar coordinates is an argument. Furthermore, it is required that the argument is calculated from a closed plane figure which is a periodic membership function on the circular polar coordinates. If the closed plane figure is continuous with the continuity of the membership function, a significant amount of computation is required. Therefore, to simplify the practice example and significantly reduce the computational complexity, we have discretized the continuous interval and the membership function in this study. In this study, the following three methods are proposed to decide the argument from the discrete polygon which the continuous plane figure is transformed into. The first method provides an argument of a straight line passing through the origin and through the coordinate of the arithmetic mean of each coordinate of the polygon (physical center of gravity). The second one provides an argument of a straight line passing through the origin and the coordinate of the geometric center of gravity of the polygon. The third one provides an argument of a straight line passing through the origin bisecting the perimeter of the polygon (or the closed continuous plane figure).

Keywords: defuzzification, fuzzy membership function, periodic function, polar coordinates transformation

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1553 Prevalence of Adverse Events in Children and Adolescents on Antiretroviral Therapy: Examining the Pediatric Cohort in the Eastern Cape

Authors: Shannon Glaspy, Gerald Boon, Jack Lambert

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Studies on AE of highly active antiretroviral therapy (HAART) in children and adolescents are rare. The aim of this study is to observe the frequency of treatment limiting adverse drug reactions against years on ARVs and specific ARV regimen. Methods: A retrospective cohort study was conducted in East London, South Africa. All patient files in the pediatric (0 – 18 years) ARV cohort were examined, selecting only those patients started on HAART. ARV regimen changes explicitly due to AE, age on ARV treatment onset, age of AE onset, and gender were extrapolated. Eligible subjects were obtained from patient folders, anonymized and cross-referenced with data obtained from electronic records. A total of 1120 patients [592 male (52.9%) and 528 female (47.1%)] were charted by incidence and year. Additional information was extrapolated in cases where the patient experienced lipodystrophy and lipoatrophy to include the number of years on ARVs prior to the onset of the AE. Results: Of the 1120 HIV infected children of the hospital cohort, a total of 105 (9.37%) AE (53.3% male) observed were deemed eligible for the study due to completeness of medical history and agreement between electronic records and paper files. The AE cited were as follows: lipoatrophy 62 (5.53% of all subjects), lipodystrophy 27 (2.41%), neuropathy 9 (0.8%), anemia 2 (0.17%), Steven Johnsons Syndrome 1 (0.08%), elevated LFTs 1 (0.8%), breast hypertrophy (0.08%), gastritis 1 (0.08%) and rash 1 (0.08%). The most prevalence ARV regimens associated with the onset of the AE are: D4T/3TC/EFV 72 cases (64.86% of all AE), D4T/3TC/LOPr 24 cases (21.62%). Lipoatrophy and lipodystrophy combined represent 84.76% (89 cases) of all adverse events documented in this cohort. Within the 60 cases of lipoatrophy, the average number of years on ARVs associated with an AE is 3.54, with 14 cases experiencing an AE between 0-2 years of HAART. Within the 29 cases of lipodystrophy, the average number of years on ARVs associated with an AE is 3.89, with 4 cases experiencing an AE between 0-2 years on HAART. The regimen D4T/3TC/EFV is associated with 43 cases (71.66%) of lipoatrophy and 21 cases (72.41%) of lipodystrophy. D4T/3TC/LOPr is associated with 15 cases (25%) of lipoatrophy and 7 cases (24.14%) of lipodystrophy. The frequency of AE associated with ARV regimens could be misrepresented due to prevalence of different 1st line regimens which were not captured in this study, particularly with the systematic change of 1st line drugs from D4T to ABC in 2010. Conclusion: In this descriptive study we found a 9.37% prevalence of AE were significant enough to be treatment limiting among our cohort. Lipoatrophy accounted for 59.04% of all documented AE. Overall, D4T/3TC/EFV was associated with 64.86% of all AE, 71.66% of lipoatrophy cases and 72.41% of lipodystrophy cases.

Keywords: ARV, adverse events, HAART, pediatric

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1552 Enhancing Information Technologies with AI: Unlocking Efficiency, Scalability, and Innovation

Authors: Abdal-Hafeez Alhussein

Abstract:

Artificial Intelligence (AI) has become a transformative force in the field of information technologies, reshaping how data is processed, analyzed, and utilized across various domains. This paper explores the multifaceted applications of AI within information technology, focusing on three key areas: automation, scalability, and data-driven decision-making. We delve into how AI-powered automation is optimizing operational efficiency in IT infrastructures, from automated network management to self-healing systems that reduce downtime and enhance performance. Scalability, another critical aspect, is addressed through AI’s role in cloud computing and distributed systems, enabling the seamless handling of increasing data loads and user demands. Additionally, the paper highlights the use of AI in cybersecurity, where real-time threat detection and adaptive response mechanisms significantly improve resilience against sophisticated cyberattacks. In the realm of data analytics, AI models—especially machine learning and natural language processing—are driving innovation by enabling more precise predictions, automated insights extraction, and enhanced user experiences. The paper concludes with a discussion on the ethical implications of AI in information technologies, underscoring the importance of transparency, fairness, and responsible AI use. It also offers insights into future trends, emphasizing the potential of AI to further revolutionize the IT landscape by integrating with emerging technologies like quantum computing and IoT.

Keywords: artificial intelligence, information technology, automation, scalability

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1551 Soft Robotic System for Mechanical Stimulation of Scaffolds During Dynamic Cell Culture

Authors: Johanna Perdomo, Riki Lamont, Edmund Pickering, Naomi C. Paxton, Maria A. Woodruff

Abstract:

Background: Tissue Engineering (TE) has combined advanced materials, such as biomaterials, to create affordable scaffolds and dynamic systems to generate stimulation of seeded cells on these scaffolds, improving and maintaining the cellular growth process in a cell culture. However, Few TE skin products have been clinically translated, and more research is required to produce highly biomimetic skin substitutes that mimic the native elasticity of skin in a controlled manner. Therefore, this work will be focused on the fabrication of a novel mechanical system to enhance the TE treatment approaches for the reparation of damaged tissue skin. Aims: To archive this, a soft robotic device will be created to emulate different deformation of skin stress. The design of this soft robot will allow the attachment of scaffolds, which will then be mechanically actuated. This will provide a novel and highly adaptable platform for dynamic cell culture. Methods: Novel, low-cost soft robot is fabricated via 3D printed moulds and silicone. A low cost, electro-mechanical device was constructed to actuate the soft robot through the controlled combination of positive and negative air pressure to control the different state of movements. Mechanical tests were conducted to assess the performance and calibration of each electronic component. Similarly, pressure-displacement test was performed on scaffolds, which were attached to the soft robot, applying various mechanical loading regimes. Lastly, digital image correlation test was performed to obtain strain distributions over the soft robot’s surface. Results: The control system can control and stabilise positive pressure changes for long hours. Similarly, pressure-displacement test demonstrated that scaffolds with 5µm of diameter and wavy geometry can displace at 100%, applying a maximum pressure of 1.5 PSI. Lastly, during the inflation state, the displacement of silicone was measured using DIC method, and this showed a parameter of 4.78 mm and strain of 0.0652. Discussion And Conclusion: The developed soft robot system provides a novel and low-cost platform for the dynamic actuation of tissue scaffolds with a target towards dynamic cell culture.

Keywords: soft robot, tissue engineering, mechanical stimulation, dynamic cell culture, bioreactor

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1550 Technologic Information about Photovoltaic Applied in Urban Residences

Authors: Stephanie Fabris Russo, Daiane Costa Guimarães, Jonas Pedro Fabris, Maria Emilia Camargo, Suzana Leitão Russo, José Augusto Andrade Filho

Abstract:

Among renewable energy sources, solar energy is the one that has stood out. Solar radiation can be used as a thermal energy source and can also be converted into electricity by means of effects on certain materials, such as thermoelectric and photovoltaic panels. These panels are often used to generate energy in homes, buildings, arenas, etc., and have low pollution emissions. Thus, a technological prospecting was performed to find patents related to the use of photovoltaic plates in urban residences. The patent search was based on ESPACENET, associating the keywords photovoltaic and home, where we found 136 patent documents in the period of 1994-2015 in the fields title and abstract. Note that the years 2009, 2010, 2011, 2012, 2013 and 2014 had the highest number of applicants, with respectively, 11, 13, 23, 29, 15 and 21. Regarding the country that deposited about this technology, it is clear that China leads with 67 patent deposits, followed by Japan with 38 patents applications. It is important to note that most depositors, 50% are companies, 44% are individual inventors and only 6% are universities. On the International Patent classification (IPC) codes, we noted that the most present classification in results was H02J3/38, which represents provisions in parallel to feed a single network by two or more generators, converters or transformers. Among all categories, there is the H session, which means Electricity, with 70% of the patents.

Keywords: photovoltaic, urban residences, technology forecasting, prospecting

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1549 Utilizing Experiential Teaching Strategies to Reduce the Incidence of Falls in Patients in Orthopedic Wards

Authors: Yu-Shi Ye, Jia-Min Wu, Jhih-Ci Li

Abstract:

Background: Most orthopedic inpatients and primary caregivers are elderly, and patients are at high risk of falls. We set up a quality control team to analyze the root cause and found the following issues: 1. The nursing staff did not conduct cognitive assessments of patients and their primary caregivers to ensure that health education content was understood. 2. Nurses prefer to use spoken language in health education but lack the skills to use diverse teaching materials. 3. Newly recruited nurses have insufficient awareness of fall prevention. Methods: The study subjects were 16 nurses in the orthopedic ward of a teaching hospital in central Taiwan. We implemented the following strategies: 1. Developed a fall simulation teaching plan and conducted teaching courses and assessments in the morning meeting; 2. Designed and used a "fall prevention awareness card" to improve the prevention awareness of elderly patients; 3. All staff (including new staff) received experiential education training. Results: In 2021, 40% of patients in the orthopedic wards were aged 60-79 years (792/1979) with a high risk of falls. According to data collection, the incidence of falls in hospitalized patients was 0.04% (5/12651), which exceeded the threshold of 0.02% in our ward. After completing the on-the-job education training in October, the nursing staff expressed that they were more aware of the special situation of fall prevention. Through practical sharing and drills, combined with experiential teaching strategies, nurses can reconstruct the safety awareness of fall prevention and deepen their cognitive memory. Participants scored between 30 and 80 on the pretest (16 students, mean: 72.6) and between 90 and 100 on the post-test (16 students, mean: 92.6), resulting in a 73.8% improvement in overall scores. We have a total of 4 new employees who have all completed the first 3 months of compulsory PGY courses. From January to April 2022, the incidence of falls in hospitalized patients was 0.025% (1/3969). We have made good improvements and will continue to track the outcome. Discussion: In addition to enhancing the awareness of falls among nursing staff, how-to guide patients and primary caregivers to prevent falls is also the focus of improvement. The proper way of health education can be better understood through practical exercises and case sharing.

Keywords: experiential teaching strategies, fall prevention, cognitive card, elderly patients, orthopedic wards

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1548 Timing and Probability of Presurgical Teledermatology: Survival Analysis

Authors: Felipa de Mello-Sampayo

Abstract:

The aim of this study is to undertake, from patient’s perspective, the timing and probability of using teledermatology, comparing it with a conventional referral system. The dynamic stochastic model’s main value-added consists of the concrete application to patients waiting for dermatology surgical intervention. Patients with low health level uncertainty must use teledermatology treatment as soon as possible, which is precisely when the teledermatology is least valuable. The results of the model were then tested empirically with the teledermatology network covering the area served by the Hospital Garcia da Horta, Portugal, links the primary care centers of 24 health districts with the hospital’s dermatology department via the corporate intranet of the Portuguese healthcare system. Health level volatility can be understood as the hazard of developing skin cancer and the trend of health level as the bias of developing skin lesions. The results of the survival analysis suggest that the theoretical model can explain the use of teledermatology. It depends negatively on the volatility of patients' health, and positively on the trend of health, i.e., the lower the risk of developing skin cancer and the younger the patients, the more presurgical teledermatology one expects to occur. Presurgical teledermatology also depends positively on out-of-pocket expenses and negatively on the opportunity costs of teledermatology, i.e., the lower the benefit missed by using teledermatology, the more presurgical teledermatology one expects to occur.

Keywords: teledermatology, wait time, uncertainty, opportunity cost, survival analysis

Procedia PDF Downloads 126
1547 Distributed Coordination of Connected and Automated Vehicles at Multiple Interconnected Intersections

Authors: Zhiyuan Du, Baisravan Hom Chaudhuri, Pierluigi Pisu

Abstract:

In connected vehicle systems where wireless communication is available among the involved vehicles and intersection controllers, it is possible to design an intersection coordination strategy that leads the connected and automated vehicles (CAVs) travel through the road intersections without the conventional traffic light control. In this paper, we present a distributed coordination strategy for the CAVs at multiple interconnected intersections that aims at improving system fuel efficiency and system mobility. We present a distributed control solution where in the higher level, the intersection controllers calculate the road desired average velocity and optimally assign reference velocities of each vehicle. In the lower level, every vehicle is considered to use model predictive control (MPC) to track their reference velocity obtained from the higher level controller. The proposed method has been implemented on a simulation-based case with two-interconnected intersection network. Additionally, the effects of mixed vehicle types on the coordination strategy has been explored. Simulation results indicate the improvement on vehicle fuel efficiency and traffic mobility of the proposed method.

Keywords: connected vehicles, automated vehicles, intersection coordination systems, multiple interconnected intersections, model predictive control

Procedia PDF Downloads 356
1546 The Investment Decision-Making Principles in Regional Tourism

Authors: Evgeni Baratashvili, Giorgi Sulashvili, Malkhaz Sulashvili, Bela Khotenashvili, Irma Makharashvili

Abstract:

The most investment decision-making principle of regional travel firm's management and its partner is the formulation of the aims of investment programs. The investments can be targeted in order to reduce the firm's production costs and to purchase good transport equipment. In attractive region, in order to develop firm’s activities, the investment program can be targeted for increasing of provided services. That is the case where the sales already have been used in the market. The investment can be directed to establish the affiliate firms, branches, to construct new hotels, to create food and trade enterprises, to develop entertainment enterprises, etc. Economic development is of great importance to regional development. International experience shows that inclusive economic growth largely depends on not only the national, but also regional development planning and implementation of a strong and competitive regions. Regional development is considered as the key factor in achieving national success. Establishing a modern institute separate entities if the pilot centers will constitute a promotion, international best practice-based public-private partnership to encourage the use of models. Regional policy directions and strategies adopted in accordance with the successful implementation of major importance in the near future specific action plans for inclusive development and implementation, which will be provided in accordance with the effective monitoring and evaluation tools and measurable indicators combined. All of these above-mentioned investments are characterized by different levels, which are related to the following fact: How successful tourism marketing service is, whether it is able to determine the proper market's reaction according to the particular firm's actions. In the sphere of regional tourism industry and in the investment decision possible variants it can be developed the some specter of models. Each of the models can be modified and specified according to the situation, and characteristic skills of the existing problem that must be solved. Besides, while choosing the proper model, the process is affected by the regulation system of economic processes. Also, it is influenced by liberalization quality and by the level of state participation.

Keywords: net income of travel firm, economic growth, Investment profitability, regional development, tourist product, tourism development

Procedia PDF Downloads 260
1545 Improving Rural Access to Specialist Emergency Mental Health Care: Using a Time and Motion Study in the Evaluation of a Telepsychiatry Program

Authors: Emily Saurman, David Lyle

Abstract:

In Australia, a well serviced rural town might have a psychiatrist visit once-a-month with more frequent visits from a psychiatric nurse, but many have no resident access to mental health specialists. Access to specialist care, would not only reduce patient distress and benefit outcomes, but facilitate the effective use of limited resources. The Mental Health Emergency Care-Rural Access Program (MHEC-RAP) was developed to improve access to specialist emergency mental health care in rural and remote communities using telehealth technologies. However, there has been no current benchmark to gauge program efficiency or capacity; to determine whether the program activity is justifiably sufficient. The evaluation of MHEC-RAP used multiple methods and applied a modified theory of access to assess the program and its aim of improved access to emergency mental health care. This was the first evaluation of a telepsychiatry service to include a time and motion study design examining program time expenditure, efficiency, and capacity. The time and motion study analysis was combined with an observational study of the program structure and function to assess the balance between program responsiveness and efficiency. Previous program studies have demonstrated that MHEC-RAP has improved access and is used and effective. The findings from the time and motion study suggest that MHEC-RAP has the capacity to manage increased activity within the current model structure without loss to responsiveness or efficiency in the provision of care. Enhancing program responsiveness and efficiency will also support a claim of the program’s value for money. MHEC-RAP is a practical telehealth solution for improving access to specialist emergency mental health care. The findings from this evaluation have already attracted the attention of other regions in Australia interested in implementing emergency telepsychiatry programs and are now informing the progressive establishment of mental health resource centres in rural New South Wales. Like MHEC-RAP, these centres will provide rapid, safe, and contextually relevant assessments and advice to support local health professionals to manage mental health emergencies in the smaller rural emergency departments. Sharing the application of this methodology and research activity may help to improve access to and future evaluations of telehealth and telepsychiatry services for others around the globe.

Keywords: access, emergency, mental health, rural, time and motion

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1544 Intelligent Minimal Allocation of Capacitors in Distribution Networks Using Genetic Algorithm

Authors: S. Neelima, P. S. Subramanyam

Abstract:

A distribution system is an interface between the bulk power system and the consumers. Among these systems, radial distributions system is popular because of low cost and simple design. In distribution systems, the voltages at buses reduces when moved away from the substation, also the losses are high. The reason for a decrease in voltage and high losses is the insufficient amount of reactive power, which can be provided by the shunt capacitors. But the placement of the capacitor with an appropriate size is always a challenge. Thus, the optimal capacitor placement problem is to determine the location and size of capacitors to be placed in distribution networks in an efficient way to reduce the power losses and improve the voltage profile of the system. For this purpose, in this paper, two stage methodologies are used. In the first stage, the load flow of pre-compensated distribution system is carried out using ‘dimension reducing distribution load flow algorithm (DRDLFA)’. On the basis of this load flow the potential locations of compensation are computed. In the second stage, Genetic Algorithm (GA) technique is used to determine the optimal location and size of the capacitors such that the cost of the energy loss and capacitor cost to be a minimum. The above method is tested on IEEE 9 and 34 bus system and compared with other methods in the literature.

Keywords: dimension reducing distribution load flow algorithm, DRDLFA, genetic algorithm, electrical distribution network, optimal capacitors placement, voltage profile improvement, loss reduction

Procedia PDF Downloads 390
1543 Effect of Weave on Cotton Fabric to Improve the Durable Press Finish Rating

Authors: Mayur Kudale, Priyanka Panchal

Abstract:

Cellulose fibres, mainly cotton, are the most important kind of fibre used for manufacturing shirting fabric. However, to overcome its main disadvantage, that is it gets wrinkled after washing, is to use special kind of finish which is resin finish. This finish provides a resistance against shrinkage along with improved wet and dry wrinkle recovery to cellulosic textiles. The Durable Press (DP) finish uses a mechanism of cross-linking with polymers or resin to inhibit the easy movement of the cellulose chains. The purpose of these experimentations on the weave is to observe and compare the variations in properties after DP finish without adverse effect on strength of the fabric. In this work, we have prepared three types of fabric weaves viz. Plain, Twill and Sateen with their construction parameters intact. To get the projected results, this work uses three types of variables viz. concentration of Resin, Temperature and Time. Resultant of these variables is only change in weave or construction on DP finish which further opens the possibilities of improvement of DP either of mentioned weaves. The combined effect of such various parametric resin finish methodology will give the best method to improve the DP. However, the DP finish can cause a side effect of reduction in elasticity and flexibility of cellulosic fibres. The natural cellulose could loss abrasion resistance along with tear and tensile strength by applying DP finish. In this work, it is taken care that the tear strength of fabric will not drop below certain limit otherwise the fabric will tear down easily. In this work, it is found that there is a significant drop in tearing and tensile strength with the improvement of DP finish. Later on, it is also found that the twill weave has more percentage drop in tearing strength as compared to plain and sateen weave. There is major kind of observations obtained after this work. First, the mixing of cotton should be done properly to achieve the higher DP rating in plain weave. Second, the careful combination of warp, weft and fabric construction must be decided to avoid the high drop in tear and tensile strength in a twill weave. Third, the sateen weave has a good sheen and DP rating hence it can be used in shirting of gents and ladies dress materials. This concludes that to achieve higher DP ratings, use plain weave construction than twill and sateen because it has the lowest tear and tensile strength drop.

Keywords: concentration of resin, cross-linking, durable press (DP) finish, sheen, tear and tensile strength, weave

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1542 Storage Method for Parts from End of Life Vehicles' Dismantling Process According to Sustainable Development Requirements: Polish Case Study

Authors: M. Kosacka, I. Kudelska

Abstract:

Vehicle is one of the most influential and complex product worldwide, which affects people’s life, state of the environment and condition of the economy (all aspects of sustainable development concept) during each stage of lifecycle. With the increase of vehicles’ number, there is growing potential for management of End of Life Vehicle (ELV), which is hazardous waste. From one point of view, the ELV should be managed to ensure risk elimination, but from another point, it should be treated as a source of valuable materials and spare parts. In order to obtain materials and spare parts, there are established recycling networks, which are an example of sustainable policy realization at the national level. The basic object in the polish recycling network is dismantling facility. The output material streams in dismantling stations include waste, which very often generate costs and spare parts, that have the biggest potential for revenues creation. Both outputs are stored into warehouses, according to the law. In accordance to the revenue creation and sustainability potential, it has been placed a strong emphasis on storage process. We present the concept of storage method, which takes into account the specific of the dismantling facility in order to support decision-making process with regard to the principles of sustainable development. The method was developed on the basis of case study of one of the greatest dismantling facility in Poland.

Keywords: dismantling, end of life vehicles, sustainability, storage

Procedia PDF Downloads 270
1541 Impulsivity Leads to Compromise Effect

Authors: Sana Maidullah, Ankita Sharma

Abstract:

The present study takes naturalistic decision-making approach to examine the role of personality in information processing in consumer decision making. In the technological era, most of the information comes in form of HTML or similar language via the internet; processing of this situation could be ambiguous, laborious and painful. The present study explores the role of impulsivity in creating an extreme effect on consumer decision making. Specifically, the study explores the role of impulsivity in extreme effect, i.e., extremeness avoidance (compromise effect) and extremeness seeking; the role of demographic variables, i.e. age and gender, in the relation between impulsivity and extreme effect. The study was conducted with the help of a questionnaire and two experiments. The experiment was designed in the form of two shopping websites with two product types: Hotel choice and Mobile choice. Both experimental interfaces were created with the Xampp software, the frontend of interfaces was HTML CSS JAVASCRIPT and backend was PHP MySQL. The mobile experiment was designed to measure the extreme effect and hotel experiment was designed to measure extreme effect with alignability of attributes. To observe the possibilities of the combined effect of individual difference and context effects, the manipulation of price, a number of alignable attributes and number of the non-alignable attributes is done. The study was conducted on 100 undergraduate and post-graduate engineering students within the age range of 18-35. The familiarity and level of use of internet and shopping website were assessed and controlled in the analysis. The analysis was done by using a t-test, ANOVA and regression analysis. The results indicated that the impulsivity leads to compromise effect and at the same time it also increases the relationship between alignability of attribute among choices and the compromise effect. The demographic variables were found to play a significant role in the relationship. The subcomponents of impulsivity were significantly influencing compromise effect, but the cognitive impulsivity was significant for women, and motor impulsivity was significant for males only. The impulsivity was significantly positively predicted by age, though there were no significant gender differences in impulsivity. The results clearly indicate the importance of individual factors in decision making. The present study, with precise and direct results, provides a significant suggestion for market analyst and business providers.

Keywords: impulsivity, extreme effect, personality, alignability, consumer decision making

Procedia PDF Downloads 189