Abstract: The exponential expansion of the Internet of Things (IoT) has fundamentally transformed the way people, machines, and gadgets communicate, resulting in unparalleled levels of interconnectedness. Nevertheless, the growth of IoT has also brought up notable security obstacles, requiring the creation of strong intrusion detection systems to safeguard IoT networks against hostile actions. This study investigates the utilization of fog computing architectures in conjunction with machine learning approaches to improve the security of the IoT. The UNSW-NB15 dataset, containing an extensive range of network traffic characteristics, is used as the basis for training and assessing the machine learning models. The study specifically applies and evaluates the performance of various models, including linear regression, Ridge classifier, SGD classifier, and ensemble learning. Furthermore, the findings indicate that these models are capable of accurately identifying intrusions, with success rates of 94%, 97%, 96.60%, and 96.50%, respectively. The Ridge Classifier demonstrates exceptional accuracy, highlighting its potential for effective implementation in IoT security frameworks. The results emphasize the efficacy of combining machine learning with fog computing to tackle the distinct security obstacles faced by IoT networks. In the future, our work will prioritize optimizing these models for real-time applications, improving their scalability, and investigating more advanced ensemble strategies to enhance detection accuracy. The project intends to enhance these areas to create a comprehensive and scalable intrusion detection system that can offer strong security solutions for the growing IoT environment. This will guarantee the integrity and dependability of linked devices and systems.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In his research, he has established an analysis of the consumption of renewable energy and its impact on CO2 emissions in Peru, 1990-2020. The research employs a quantitative approach and longitudinal non-experimental design, with a multiple linear regression model. It uses time series drawn from the World Bank on renewable energy consumption and energy consumption. A progressive increase was reflected mainly driven by industrial growth, fossil fuel consumption and changes in consumption and production patterns.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: In today's rapidly changing business environment, companies need to be dynamic, adapting their internal processes to respond effectively to external changes. Information Technology has become crucial for businesses to enhance their ability to manage and adapt to change. This study examines East Java manufacturing companies that have heavily invested in sustainable IT systems to enhance their supply chain responsiveness and resilience through improved purchasing strategies and production flexibility. The study collected data from companies that had implemented IT for at least three years, with respondents being permanent employees with a minimum of two years' experience. Analysis of 108 survey responses using SmartPLS 4 revealed significant impacts of IT implementation on purchasing strategy (0.610), production flexibility (0.363), and supply chain responsiveness (0.164). Furthermore, purchasing strategy influenced production flexibility (0.367), supply chain responsiveness (0.348), and resilience (0.166). Production flexibility also affected supply chain responsiveness (0.348) and resilience (0.343), while responsiveness impacted resilience by 0.306. These findings provide a practical contribution for functional managers in companies regarding the importance of IT investment in developing effective purchasing, production, and marketing strategies to meet market demands swiftly. The research contributes to supply chain strategy and resilience theory while highlighting the significance of strong collaboration with external partners for top management.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: An examination of two areas of promotion and assortment planning in an environment is attempted in this paper. Sales promotion is a marketing strategy used by retailers to increase sales and profits by retaining customers and preventing them from switching to their competitors. Various products are available on the market that can substitute each other, so the best product assortment must be determined as well. In order to model the above subject, a nonlinear integer programming problem is proposed. Model solution involves rephrasing the problem as mixed integer linear programming. Small- and medium-sized problems can therefore be solved using MIP solver software. Firefly algorithms are designed to solve large-scale problems. According to the numerical results, determining the best product assortment for stores must also be done simultaneously with finding the optimal promotion. As a matter of fact, the promotion of the products significantly affects the assortment scenarios for the stores. Consequently, the selection of the promotional discount may result in large profit losses if the assortment planning is not taken into consideration. In order to assess the importance and sensitivity of the model parameters, a sensitivity analysis is conducted. The sensitivity analysis demonstrates that the model is able to respond to changes in market demand and competition, and provides an effective tool for chain stores to optimize their promotion and assortment strategies. To further validate the effectiveness of the model, a case study is conducted in Tehran, Iran. The results of the case study demonstrate the ability of the model to effectively optimize promotion and assortment strategies in real-world settings. Overall, the proposed model provides a valuable tool for chain stores to optimize their promotion and assortment strategies, and improve their market competitiveness.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The aim of this study is to assess and rank Anadolu Sigorta Company's sustainability performance between 2018 and 2022 using the hybrid SWARA-MEREC-COBRA model. The sustainability performance evaluation criteria's importance weights were determined using both subjective and objective methods. The SWARA algorithm was used to determine the weights subjectively based on expert opinion, while the MEREC algorithm was used to determine them objectively. The final importance weights were obtained by combining the results of both methods. When evaluating the sustainability performance of Anadolu Sigorta Company, the most important criterion was total paper consumption, while the criterion with the least impact was the number of female employees. The COBRA ranking algorithm was used to rank the alternatives, and it was determined that the company's best sustainability performance was in 2022, while the worst was in 2018. Different sensitivity analyses were used to test the consistency of the proposed model.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study aimed to build a model and set of criteria to evaluate and select business accounting software providers for Truong Son Technology Investment and Development Joint Stock Company. The study helped choose the most suitable supplier that meets the criteria that the company desired. The research proposed the Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) model and was also applied in the case of selecting accounting software suppliers for Truong Son Technology Investment and Development Joint Stock Company. There were 5 business accounting software packages considered: Misa business accounting software, Bravo accounting software, FAST Accounting software, Effect accounting software, and Gamma accounting software. The ranking results of accounting software providers at Truong Son Technology Investment and Development Joint Stock Company were as follows: A1 (Misa Business Accounting Software) was the best supplier, second-ranking was A3 (FAST Accounting software), followed by A2 (Bravo Accounting Software) in third place. The findings of this study could be used as a valuable reference for businesses to choose the best supplier.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The purpose of this research is to explore the relationships between information literacy, digital literacy, media literacy, Attitude toward use, and employability to examine the role of information and digital literacy in influencing employees' intentions to use technology in the workplace. The research sample for Indonesia was 250 respondents and for Malaysia there were 298 respondents. The data collection method uses Google Forms, distributed to respondents through purposive random sampling technique. The research results indicate that in Indonesia, Computer Literacy (CL) on Perceived Usefulness (PU), PU on Attitude towards Use (ATT), and ATT on Employability (EMP) have a big influence. On the other hand, Information Literacy (IL) and CL have a small influence on Employability. Likewise, Perceived Ease of Use (PEOU) has little influence on ATT. Malaysia, which has a big influence is Digital Literacy (DL) on Employability (EMP) and Perceived Ease of Use (PEOU). However, DL has a small influence on PU, as does IL on EMP, PEOU, and PU. Likewise, the influence of PEOU on PU is small.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Poverty is a complex and multidimensional social problem faced by almost all countries including Indonesia. Poverty alleviation efforts require accurate and up-to-date data to ensure that social welfare programs can effectively run and target appropriate beneficiaries. Bekasi Regency, as one of the regions that faces significant challenges in managing poverty, needs the right strategy in updating and utilizing poverty data to support social welfare programs. This study analyzes a policy framework for updating and utilizing the poverty data. The data were collected from focus group discussions with experts and stakeholders who were competent in updating and utilizing the poverty data. MULTIPOL method was used to analyze the data. The results of the study show that the best strategy for updating and utilizing poverty data in the scenario is to integrate scenarios with priority policy with digital budgeting policy, as well as priority actions providing incentives. This study makes an important contribution to regional development planning, especially poverty alleviation strategies based on accurate and integrative data.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Forest masses participate in the hydrological cycle and precipitation patterns. Therefore, the loss of these forest masses has significant implications for atmosphere-surface dynamics. The objective of this article is to determine the influence of forest cover loss on annual rainfall in the departments of Peru during the period 2013-2022. The methodology was quantitative, longitudinal non-experimental design, with panel data and a random-effects model was estimated. The results reveal a positive and statistically significant relationship between tree cover loss and total annual precipitation, specifically, a 1% increase in deforestation is related to an average increase of 0.186% in annual rainfall. The findings contrast with most previous evidence documenting reductions in precipitation due to deforestation, however, they are consistent with some studies. The research concluded that there is a positive relationship between the loss of forest cover and annual rainfall in the departments of Peru during the period studied.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study aims to examine the factors affecting Jordanian Islamic banks’ customers’ adoption of electronic banks. The study relied on quantitative methods, where the study designed a questionnaire based on the Technology Acceptance Model (TAM) which derived from the Theory of Reasoned Action (TRA). The study sample consisted of 470 respondents. The study applied the Partial Least Squares Structural Equation Modeling (PLS-SEM), where the results of the Chi-square test and the standardized root mean square residual (SRMR) test showed the validity of the model for analysis. The results showed that usefulness, privacy, and awareness affect the adoption of e-banking, and that ease to use and electronic skills affect the adoption of e-banking through usefulness. The results also show that Infrastructure does not affect the adoption of e-banking, and Convenience does not affect the adoption of e-banking through Intention to use e-banking. The study advises Islamic banks to spread awareness about the importance of electronic banking and design easy-to-use electronic services that enjoy privacy and security.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The current study aims to determine the factors influencing the intention to employ digital libraries among postgraduate students in Jordanian universities. The data were gathered through questionnaires in the format of Google Forms. The questionnaires were distributed to postgraduate students enrolled in Jordanian universities with digital libraries, who were recruited via purposive sampling. A total of 261 responses were received, with 67 deemed unsuitable for the study analysis and subsequently excluded. Resultantly, 194 valid questionnaires were finalized for data analysis. The SMART-partial least squares (PLS) software was utilized to conduct structural equation modelling (SEM) to test the study hypotheses. This study discovered that the variables, namely performance expectancy, effort, and facilitating conditions expectancy, were significantly and positively associated with the outcome variable, which is the intention to employ digital libraries. Meanwhile, social influence was revealed to be insignificant. Performance expectancy also significantly mediated the correlations between technological readiness and the intention to utilize and between online self-efficacy and the intention to utilize. The present study focused only on potential users among postgraduate students at Jordanian universities with digital libraries. The findings contributed valuable insights into the academic sector, especially library management to enhance the rate of digital library or e-library adoption at Jordanian universities. Digital library managers and policymakers could leverage the findings to design pertinent strategies that increase user engagement within digital library environments. The UTAUT model was demonstrated to be capable of predicting users’ intentions of employing digital libraries and corroborated the mediation role of performance expectancy on the associations between technological readiness and the intention to utilize and between online self-efficacy and the intention to use.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This study investigates how key audit matter (KAM) characteristics influence financial statement understandability and subsequent investor decision making. Using Structural Equation Modeling-Variance Based (SEM-VB) through Partial Least Squares (PLS), the analysis was conducted on a diverse global sample of investors from Europe, North America, Asia-Pacific, Africa, and Latin America. The results indicate that KAM accuracy, reliability, audit quality, and financial reporting quality significantly enhance perceived financial statement understandability, which in turn positively impacts investor judgments. The mediating role of understandability is confirmed, emphasizing its crucial influence on investors’ decisions. Additionally, an importance-performance map analysis (IPMA) identified KAM reliability and accuracy as the most critical factors. This study contributes to the theoretical and managerial understanding of audit practices and investor behavior.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Supply chains are vulnerable to various disruption risks that can adversely affect their overall performance and objectives. This study addresses the challenge of designing a resilient and environmentally sustainable mixed open and closed-loop supply chain network that can withstand both operational and disruption risks. The research employs a bi-objective stochastic mathematical model to examine the balance between environmental sustainability and profitability within the SC. To mitigate the impact of disruptions, several resilience strategies are incorporated into the model, significantly reducing their adverse effects. Due to the inherent complexity of the problem, the study introduces a novel hybrid metaheuristic algorithm that combines ant colony optimization with teaching and learning-based optimization, named ACO-TLBO. Additionally, two other enhanced hybrid metaheuristics are proposed. The performance of these solution methods is assessed through various test problems, using specific performance metrics for comparison. Results reveal that the ACO-TLBO algorithm excels in generating high-quality, non-dominated solutions. The model's practical applicability is demonstrated through a case study in the tire industry, validating its effectiveness. The findings indicate that the proposed resilience strategies are crucial for minimizing the negative impacts of disruptions on SC objectives. Furthermore, the results underscore the importance of resilience in maintaining both sustainability and profitability within supply chains.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Asset Liability Management (ALM) can be overseen using financial ratios derived from financial statements. These statements provide a comprehensive picture of a company's status and necessitate analysis to evaluate performance. This research aims to analyze financial ratios to describe the financial condition, measure business development over time, and evaluate the achievement of the company's objectives. An optimization analysis of financial ratios is performed using the Weighted Goal Programming (WGP) model, which addresses multiple objectives by applying weights based on their priorities. The Best-Worst Method (BWM) was used to determine the priority weights of deviation variables from each financial ratio target. Financial ratios were selected based on their impact on profit using factor analysis. The constructed WGP model aims to minimize deviations in Return on Assets, Operating Ratios, Operating Income Ratio, Total Assets Turnover, and Current Ratio. Computational calculations to solve the WGP model are performed using Python, with pseudocode provided. A case study on a company in the garment and textile sector was conducted and found that the Operating Ratio, Return on Assets, Operating Income Ratio, and Current Ratio still need improvement by developing strategies to achieve the targets. Sensitivity analysis was also employed to assess the resilience of the model in response to alterations in data.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: This research attempts to investigate the effect of types of AI systems (assisted, augmented, and autonomous) on internal auditing in Saudi Arabia. A questionnaire was used to collect data from 150 internal auditors in Riyadh City. To confirm that the study's goals were met, the descriptive analytical method was used. The questionnaire data is analyzed, and hypotheses are tested, using the Smart pls application. The study’s results show that there is a clear positive effect of AI systems, but different impacts vary according to the kind of AI systems, which is high in augmented systems, moderate in autonomous systems, and weak in assistive intelligence systems. Further studies on this subject can be conducted with larger sample sizes, especially if they are conducted globally. Based on these findings, future research can concentrate on national and cultural conditions. Additionally, companies should adopt more comprehensive involvement methods in internal auditing issues and the development of AI adoption in all company activities.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Communication is essential for humanity today and in the past. However, some individuals lack verbal communication due to their innate disability and physical losses from accidents. There are sign-language communication methods developed for such people to communicate. Artificial intelligence solutions are offered to remove the disadvantaged situations of people with disabilities due to communication in daily life. Nowadays, rapidly developing image processing and artificial intelligence methods are proper solutions for the problem focused on in this study. Convolution neural network techniques, which have become very popular recently, offer solutions to many problems. On the other hand, the YOLO algorithm shows very high performance in real-time object detection. In this study, we proposed a method for identifying the alphabets which each gesture delivers. This work studied hand detection on images and classification according to hand movements. The American Sign Language (ASL) standard was used as the sign language. The most recent version of YOLO, known as YOLOv5x, is used for gesture detection. Concentrating on the Static Sign-language problem, a study was conducted on the definition of hand movements. The letters “J” and “Z” are not included in the data set because movable hand signals are required. Apart from these two letters, a total number of 24 letters are classified. The proposed model achieved a training performance of 99.45% mAP@.5. Moreover, the proposed model has a performance of 97.9% mAP@.5 on the test dataset. The results demonstrate that the model's object detection performance is excellent. A statistical analysis of the training time shows that the training time has been drastically decreased, 4.5 hours with the current model as compared to the existing models in the literature.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The aim of the research is to identify the determinants of investment decisions of individual investors - the empirical evidence of Hanoi, Vietnam. Conducting a survey of 210 individual investors and using quantitative analysis through SPSS software, the research results showed that market stability and project profitability have the greatest impact on investment decisions. Research results also showed that corporate image and investor psychology have no impact on individual investment decisions. However, research results confirmed the positive impact of business growth on investment decisions, so growing businesses have many advantages for investors, so they have many opportunities to attract financial resources from investors to expand production and business.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: Our research used a SVAR to analyze the underlying copper price shocks, that is, a commodity shock for the Junín department in Peru. The results of a short- and long-run SVAR were based on traditional matrix constraints that capture the fact that domestic shocks do not affect international prices. The main conclusion is that before the pandemic a shock in the international price of copper decreases economic growth and inflation in the department of Junín in Peru, after the pandemic the opposite happens. As a result of the model, the short and long-run effects of the international copper price on the main macroeconomic variables of Junín in Peru are statistically significant. Before the pandemic, the dynamics of the international copper price reflected the existence of the curse of mining resources in copper institutions. Before the pandemic, a percentage increase in the international price of copper decreased economic growth, reflecting the existence of the mining resource curse in copper institutions. After the pandemic, a percentage increase in the price of copper increases economic growth by up to 0.0488%, then decreases over time, noting the transitory effect of economic recovery and poor management of mineral resources.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The issue of integrated scheduling and sequencing operation of unloading and loading equipment in container ports has been one of the most important issues concerning time efficiency. In addition, with the emergence of green harbor concepts, the inclusion of criteria for minimizing energy consumption, fuel and emission reduction are among the other issues that have been noticed by planners in the field of energy efficiency. Furthermore, due to the complexity and scope of activities of a container terminal, uncertainty in operational parameters such as transportation time, time of readiness and entry of work into the system and the velocity of the transportation fleet are inevitable in this operational environment. Therefore, this research with the aim of sharing trucks among loading and unloading equipment, proposes a robust multi-objective integer programming model for the synchronized scheduling of truck operations with other handling equipment to decrease the fuel consumption of trucks and the flow time of containers, considering the uncertainty in operational parameters as fuzzy numbers. To find the Pareto solutions for this model, the ε-Constraint technique is employed. Finally, the performance of the model in deterministic and uncertain modes is evaluated, compared and analyzed employing the inputs gathered from Shahid Rajaei port. The findings demonstrate that using this model will result in a substantial decrease in both fuel consumption and flow time of containers in comparison to the current procedure. Additionally, results will demonstrate the extent to which the terminal's fuel and time consumption will increase under conditions of uncertainty in operational parameters when the optimal plans derived from the robust model are implemented.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)

Abstract: The expansion of tourism locations that are both creative and of high quality is a significant contributor to the expansion of the economy. The stages of tourism development that are influenced by the progression of information technology are represented by the term "smart tourism" in the context of the ecosystem of smart villages. Integrating micro-enterprises with tourist practices is one of the ways that may be utilised to speed up the development of villages. By implementing the concept of smart tourism, tourism integrated with information and communication technology (ICT) can potentially improve both the economics and the services provided by the tourism industry. This research aims to analyse the clustering of smart tourism potential possibilities within the Kemang sub-district. These areas' clustering depends on some variables, including infrastructure (access for tourists), innovation, technology, local wisdom, distinctiveness, and economic conditions. The Fuzzy C-Means (FCM) clustering approach is utilised. A Geographic Information System (GIS) is utilised to facilitate the process of determining which villages are included in each cluster. This is done to describe potential areas better. The value of the cluster evaluation using the Davies Boulding Index (DBI) obtained is 0.3819, and the number of clusters with the best performance is 3. There is a very potential cluster in Cluster 3, comprising two villages (Kemang and Atangsanjaya). A potential cluster was also detected in Cluster 2, comprising three villages (Tegal, Pondokudik, and Parakanjaya). Furthermore, a fairly potential cluster was detected in Cluster 1, consisting of three villages (Jampang, Pabuaran, and Bojong). Specifically, in the Kemang sub-district, it is anticipated that the findings of this study will provide an overview of possible sites for implementing environmentally conscious tourism.

	© 2010 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the license. Creative Commons Attribution (CC-BY)