Research Paper
Economics
Mobasshira Zaman
Abstract
The COVID-19 pandemic has caused unprecedented disruption to the global economic structure, resulting in significant changes in spending patterns for households worldwide. Developed countries like the United States have been affected as well, struggling to return to pre-pandemic stable economic situations. ...
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The COVID-19 pandemic has caused unprecedented disruption to the global economic structure, resulting in significant changes in spending patterns for households worldwide. Developed countries like the United States have been affected as well, struggling to return to pre-pandemic stable economic situations. This study focuses on the impact of the pandemic on household expenditure in the United States, using ANOVA to compare household expenses between the pre-COVID period in 2018 and the post-COVID period in 2021. The results of the study showed a significant increase in all types of household expenditure from pre-COVID to post-COVID periods, highlighting the correlation between the pandemic and changes in spending habits. This trend is further fueled by price increases in daily necessities, inflation of the dollar, and scarcity of goods. The analysis also revealed that the trend was increasing, emphasizing the need for immediate policy interventions to address the issue. Further research is needed to identify the specific types of expenditure driving this increase and the underlying reasons behind it. The implications of the study are significant for policymakers and economists as they underscore the need for effective interventions to stabilize household expenditure and promote economic recovery in the wake of the pandemic. The findings also highlight the importance of utilizing statistical methods such as ANOVA to evaluate complex economic systems and guide evidence-based policy interventions. As future research continues to explore the impact of the pandemic on economic structures worldwide, this study provides valuable insights into the specific changes in household expenditure in the United States, emphasizing the urgent need for targeted policy interventions to address these changes.
Review Paper
Total quality management and quality engineering
Supriyati Supriyati Supriyati
Abstract
SMEs is one of the pillars that can improve people's lives and is very meaningful for the government. In order for SMEs to continue to develop, even increase, it is necessary to measure service quality and customer satisfaction so that SMEs can identify weaknesses in their business as evaluation ...
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SMEs is one of the pillars that can improve people's lives and is very meaningful for the government. In order for SMEs to continue to develop, even increase, it is necessary to measure service quality and customer satisfaction so that SMEs can identify weaknesses in their business as evaluation material. The research method begins by reviewing the literature related to the SMEs service industry, classifying, choosing what is appropriate for this research. The results of the research show that several methods can be used to measure, analyze, evaluate, and develop products. The KANO method with functional dysfunction assessment to identify customer desires based on attributes can have a significant influence on customer satisfaction. Servqual with a 5 gap analysis model for customer satisfaction analysis, IPA can be used to measure, test, analyze and determine service priority improvements, while QFD is broader. In addition to evaluating the quality of services and products, it is also for development or innovation and is not limited to the service industry but can be used to develop products for the manufacturing industry. Every business needs to be evaluated to improve performance, several approaches such as KANO, Servqual, IPA, QFD can be used as a reference for measuring, evaluating and developing to continue to improve and develop the business.
Research Paper
Design of Mechanical and Thermal Systems
Aniekan Essienubong Ikpe; Akanimo Udofia Ekpenyong
Abstract
Cooling refrigeration systems ingest prime energy and contribute to universal negative impacts due to ecologically unfavorable working fluids used. Hence, the quests to improve the performance of VCRS with more efficient and eco-friendly refrigerant such as nanoparticles is imperative. In this study, ...
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Cooling refrigeration systems ingest prime energy and contribute to universal negative impacts due to ecologically unfavorable working fluids used. Hence, the quests to improve the performance of VCRS with more efficient and eco-friendly refrigerant such as nanoparticles is imperative. In this study, performance analysis of Hybrid Nanofluids-Zeotropic Mixtures in a VCRS were experimentally investigated to determine the best operating optimum performance using exergy based approach. To achieve this, varying concentrated mixtures were selected using ternary graph. Results revealed that all the designated ratios of the mixed refrigerant with different fractions achieved good performance improvement with the optimum values obtained at (011) zero gram of TiO2, 7.5g-Al2O3/CuO. All the selected hybrid mixtures led to an improved outcome in terms of Coefficient of Performance (COP), less power consumption and high performance exergetic efficiency, with COP values ranging from 0.31 % to 3.10 % and exergetic efficiency from 0.32 % to 1.43 %. The values for thermal conductivity, dynamic viscosity, density and specific heat were found to be highest (0.0958 W/m.K; 0.00164 W/m.K; 686.82 kg/m3 and 359.82 kJ/kg.K) at the same concentration of zero grams TiO2 in the mixtures. Comparison made from the performance characteristics curve (with global parameters) indicated that maximum power coefficient and cooling capacity for the various concentrations were found at (001) 7.5g-TiO2, zero grams Al2O3/CuO equal to 2.2 kW, and the minimum value at concentration 5 was 0.61 % at (111) 5g-TiO2/Al2O3/CuO, and 0.87 % for (121). An increase was observed in the maximum power coefficient, cooling capacity and COP increased by 13.51 %, 5.78 % and 10.33 %. It was observed that hybrid nanofluid-zeotropic refrigerant worked seamlessly with VRCS, making it a sustainable, green and clean as well as eco-friendly alternative with near-zero to zero negative effects on public health safety and environment.
Short Communication
Computational Intelligence
Mobasshira Zaman
Abstract
This research paper presents a comprehensive SWOT analysis of ChatGPT in healthcare, examining its strengths, weaknesses, opportunities, and threats. The paper highlights the potential benefits of ChatGPT, such as improved patient engagement and support for medical education, as well as its limitations, ...
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This research paper presents a comprehensive SWOT analysis of ChatGPT in healthcare, examining its strengths, weaknesses, opportunities, and threats. The paper highlights the potential benefits of ChatGPT, such as improved patient engagement and support for medical education, as well as its limitations, including the risk of inaccurate data and inability to summarize non-text reports. The paper also identifies opportunities for ChatGPT, such as enabling personalized healthcare delivery and supporting remote patient monitoring. However, the paper also highlights potential threats, such as self-treatment among patients and the risk of an AI-driven infodemic. The significance of this research paper lies in its valuable insights into the ethical and safe use of ChatGPT in healthcare, providing healthcare professionals and policymakers with important considerations for its use. The SWOT analysis also serves as a framework for future research and development of ChatGPT and other large language models in healthcare. This research paper is a significant contribution to the ongoing discussion on the use of ChatGPT in healthcare and its potential impact on patient care and public health.
Research Paper
Decision analysis and methods
Ahmed El-Araby
Abstract
Multiple criteria decision making (MCDM) methods are used widely by researchers to make decisions in the presence of numerous criteria. It is essential to make the right decision for the most of engineering applications which makes the decision making process more complex and requires further analysis. ...
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Multiple criteria decision making (MCDM) methods are used widely by researchers to make decisions in the presence of numerous criteria. It is essential to make the right decision for the most of engineering applications which makes the decision making process more complex and requires further analysis. A major issue of MCDM methods that they suffer from the rank reversal phenomenon (RRP). Another drawback to MCDM methods that they produce different ranking when evaluating the same problem. Thus, researcher tend to develop new methods to overcome these problems. This paper explores the applicability of a new MCDM approach namely measurement alternatives and ranking according to compromise solution (MARCOS) by solving four different engineering problems. The results of MARCOS method are analyzed throughout a comparison with the results of other MCDM methods. The rank reversal test is explored for each problem to check the robustness of the method. The two phases of analysis indicate that the method is robust and applicable for different types of engineering applications.
Research Paper
Data Envelopment Analysis, DEA
Amir Reza Bazargan; Seyyed Esmaeil Najafi; Farhad Hosseinzadeh Lotfi; Mohammad Fallah
Abstract
The data envelopment analysis method is commonly used to measure efficiency. An estimate of the relative efficiency of this model is derived by calculating the ratio between inputs and outputs. Data envelopment analysis models can also be applied to network structures due to the extension of these models. ...
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The data envelopment analysis method is commonly used to measure efficiency. An estimate of the relative efficiency of this model is derived by calculating the ratio between inputs and outputs. Data envelopment analysis models can also be applied to network structures due to the extension of these models. Supply chain management is a novel approach that governed production management in recent years. In complex and dynamic environments, the petrochemical industry requires an investigation system similar to those used by other organizations to inform about its activity's desirability, especially in complex and dynamic environments. This research focused on the petrochemical company supply chain. Laboratory studies, experts, and visits to petrochemical sites were used to identify production processes and determine indicators. After that, they were evaluated with an envelopment model and a coefficient corresponding to the identified petrochemical supply chain structure. The aggregate and componentwise efficiency of the studied units in petrochemical were also examined from 2016 to 2019.
Research Paper
Management Sciences
Yaser Hamidavi Nasab; Maghsoud Amiri; Amirreza Keyghobadi; Kiamars Fathi Hafshejani; Hessam Zandhessami
Abstract
All organizations inevitably have to deal with various critical situations. This requires providing necessary resilience-building infrastructure and facilities. A review of the research literature reveals that scholars have examined factors affecting organizational resilience(OR) from different perspectives. ...
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All organizations inevitably have to deal with various critical situations. This requires providing necessary resilience-building infrastructure and facilities. A review of the research literature reveals that scholars have examined factors affecting organizational resilience(OR) from different perspectives. To gain an in-depth understanding and provide a list of effacing factors to organizations on their improvement practices related to OR, this paper aims to compile and synthesize qualitative findings of previous researches. Conducting systematic literature review 98 articles were selected for final analysis. The data were analyzed, summarized and synthesized in a step-by-step coding process, where 14 themes were identified as factors influencing OR. The identified factors included flexibility, control, redundancy and resources, planning and preparedness, decision making, social capital, resilience policymaking, organizational culture, staff, financial and economic viability, collaboration, customers and markets, modernization discourse and learning. Through a meta-synthesis of qualitative findings, this study is one of the first to forms novel perspective for offering a holistic understanding affecting factors for providing evidence to support improvement practices over OR.
Research Paper
Data Envelopment Analysis, DEA
reza rasi nojehdehi; hadi bagherzadeh valami
Abstract
Network DEA models deal with measurements of relative efficiency of Decision-Making Units when the insight of their internal structures is available. In network models, sub-processes are connected by links or intermediate products. Links have the dual role of output from one division or sub-process and ...
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Network DEA models deal with measurements of relative efficiency of Decision-Making Units when the insight of their internal structures is available. In network models, sub-processes are connected by links or intermediate products. Links have the dual role of output from one division or sub-process and input to another one. Therefore, improving the efficiency score of one division by increasing its output may reduce the score of another division because of increasing its input. To address this conflict, in the present paper we proposed a new approach in SBM framework which provides deeper insights regarding the sources of inefficiency. The proposed approach is a Two-Phase procedure in which Phase-I determine the role of intermediate measures by solving a linear program and partitions the intermediate measures into three groups of “input type”, “output type” and “fixed-flows” and Phase-II measures the scores of the DMUs under evaluation. Providing a classification for intermediate products and account their excesses or shortfalls in efficiency calculation while the continuity of link flows between subunits are kept, are the advantages of the proposed approach.
Research Paper
Medical and pharmaceutical applications
FARZANEH SALAMI; Ali Bozorgi-Amiri; Reza Tavakkoli-Moghaddam
Abstract
Feature selection is the process of picking the most effective feature among a considerable number of features in the dataset. However, choosing the best subset that gives a higher performance in classification is challenging. This study constructs and validates multiple meta-heuristic algorithms to ...
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Feature selection is the process of picking the most effective feature among a considerable number of features in the dataset. However, choosing the best subset that gives a higher performance in classification is challenging. This study constructs and validates multiple meta-heuristic algorithms to optimize machine learning models in diagnosing Alzheimers. This study aims to classify cognitively normal, mild cognitive impairment, and Alzheimers by selecting the best features. The features include Freesurfer features extracted from MRI images and clinical data. We use well-known machine learning algorithms for classifying, and after that, we use multiple meta-heuristic methods for feature selection and optimizing the objective function of the classification. We consider the objective function a macro-average F1 score because of the imbalanced data. Our procedure not only reduces the irreverent features but also increases the classification performance. Results show that metheuristic algorithms can improve the performance of machine learning methods in diagnosing Alzheimers by 20%. We find that classification performance can be significantly enhanced by using appropriate meta-heuristic algorithms. Meta-heuristic algorithms can help find the best features for medical classification problems, especially Alzheimers.
