Pub Date : 2023-06-06DOI: 10.37394/232015.2023.19.50
Joseph B. Campit
The study aimed to compare the classification performance of Support Vector Machine (SVM) and Naive Bayes (NB) machine learning models for estimating customer satisfaction utilizing Filipino text. Specifically, it analyzed the characteristics of the customer satisfaction data. It also examined the impact of different model configurations, including n-gram, stop words, and stemming, on the classification performance of the two models. The research employed qualitative and quantitative methods, utilizing text analytics and sentiment analysis to extract and analyze valuable information from unstructured responses from a satisfaction survey of the University President’s leadership performance conducted among PSU personnel and students. The dataset comprised 56,000 Filipino and English-word responses, manually annotated and randomly split into training and testing datasets. The study followed a general framework encompassing data pre-processing, modeling, and model comparison. To validate the classifiers’ classification performance, a 10-fold cross-validation approach was employed. The findings revealed that most personnel and students expressed positive sentiment toward the University President’s leadership performance. SVM outperformed the NB model across all different model configurations. With both stop word removal and stemming, the SVM trigram model achieved the highest classification performance for estimating customer satisfaction, using 75% of the data for training and 25% for testing. The proposed model holds the potential for estimating customer satisfaction using other unstructured customer satisfaction data utilizing Filipino text.
{"title":"Analyzing Customer Satisfaction using Support Vector Machine and Naive Bayes Utilizing Filipino Text","authors":"Joseph B. Campit","doi":"10.37394/232015.2023.19.50","DOIUrl":"https://doi.org/10.37394/232015.2023.19.50","url":null,"abstract":"The study aimed to compare the classification performance of Support Vector Machine (SVM) and Naive Bayes (NB) machine learning models for estimating customer satisfaction utilizing Filipino text. Specifically, it analyzed the characteristics of the customer satisfaction data. It also examined the impact of different model configurations, including n-gram, stop words, and stemming, on the classification performance of the two models. The research employed qualitative and quantitative methods, utilizing text analytics and sentiment analysis to extract and analyze valuable information from unstructured responses from a satisfaction survey of the University President’s leadership performance conducted among PSU personnel and students. The dataset comprised 56,000 Filipino and English-word responses, manually annotated and randomly split into training and testing datasets. The study followed a general framework encompassing data pre-processing, modeling, and model comparison. To validate the classifiers’ classification performance, a 10-fold cross-validation approach was employed. The findings revealed that most personnel and students expressed positive sentiment toward the University President’s leadership performance. SVM outperformed the NB model across all different model configurations. With both stop word removal and stemming, the SVM trigram model achieved the highest classification performance for estimating customer satisfaction, using 75% of the data for training and 25% for testing. The proposed model holds the potential for estimating customer satisfaction using other unstructured customer satisfaction data utilizing Filipino text.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41493114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.37394/232015.2023.19.51
Apriatni E. P., Ngatno Ngatno
The purpose of this study was to examine the impact of the COVID-19 pandemic on the income of microfinance institutions (MFIs) in Indonesia. Using a sample of 181 microfinance institutions using financial report data for 2017–2019 (before the pandemic) and 2020–2021 (during the pandemic). Data were analyzed using a non-parametric test (Wilcoxon signed ranks test). The results show that all elements of income (interest income, fee, and commission income, operating income, and non-operational income) decreased significantly. On the other side of the impact of the COVID-19 pandemic on expenses, several elements of expenses have decreased significantly (interest expense, depreciation, and amortization expense, marketing expense, administration, and general expense, operational expense, and non-operational expense). As for fee and commission expenses, research and development expenses, and an impairment charge on loans, they decrease insignificantly.
{"title":"Impact of the Covid-19 Pandemic on Micro Finance Income","authors":"Apriatni E. P., Ngatno Ngatno","doi":"10.37394/232015.2023.19.51","DOIUrl":"https://doi.org/10.37394/232015.2023.19.51","url":null,"abstract":"The purpose of this study was to examine the impact of the COVID-19 pandemic on the income of microfinance institutions (MFIs) in Indonesia. Using a sample of 181 microfinance institutions using financial report data for 2017–2019 (before the pandemic) and 2020–2021 (during the pandemic). Data were analyzed using a non-parametric test (Wilcoxon signed ranks test). The results show that all elements of income (interest income, fee, and commission income, operating income, and non-operational income) decreased significantly. On the other side of the impact of the COVID-19 pandemic on expenses, several elements of expenses have decreased significantly (interest expense, depreciation, and amortization expense, marketing expense, administration, and general expense, operational expense, and non-operational expense). As for fee and commission expenses, research and development expenses, and an impairment charge on loans, they decrease insignificantly.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46827414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-06DOI: 10.37394/232015.2023.19.52
N. Al-Khalidy
The potential for plumes to affect the safety of aircraft operations is often predicted using MITRE EPA Models. For many projects, key input parameters to MITER EPA are not available and conservative assumptions or models such as OHIO model are used to characterize the combustion and approximate the key input parameters to EPA plume rise model. These assumptions and conservative models lead to inaccurate results of simulations. The current study provides a novel approach to use a combination of Computational Fluid Dynamics (CFD) tool and EPA Models to reliably predict the risk of turbulence and upset being encountered by a range of aircraft types that operate through a rising plume. The main objective of the current study is to develop a Computational Fluid Dynamics (CFD) combustion model and a procedure to determine an improved set of flare inputs for the Air Quality (AQ) and MITER EPA models. A CFD model has been developed to determine flame plume characteristics (Effective Height, Effective Diameter, Temperature and Velocity) from two flare stacks which are part of a trailer-mounted Mobile Purge Burner (MPB) system. A subsequent experimental test of a similar trailer-mounted MPB system has validated the CFD results. Plume temperatures within the combustion zone of the flares were very much in line with the temperatures predicted by the CFD Simulation study. Plume temperatures above the MPB System appear to drop very quickly, such that the plume temperature fell from just under 500°C at 5 m above ground level to around 15-16°C (and close to the ambient temperature) at 22 m above ground. Again, this is consistent with the CFD Study results. The CFD simulations in the current study accounted for the turbulent flow with chemical species mixing and reaction and utilised an advanced radiation model to solve participating radiation in the combusted zones. This study assesses all the parameters that have impact on the accuracy of the numerical model including computational domain, mesh distribution, numerical scheme and flame plume characteristics including ambient conditions (wind speed and temperature) and combustion under various air to fuel ratio scenarios.
{"title":"Determination of Flame Plume Characteristics utilising CFD and Experimental Approaches","authors":"N. Al-Khalidy","doi":"10.37394/232015.2023.19.52","DOIUrl":"https://doi.org/10.37394/232015.2023.19.52","url":null,"abstract":"The potential for plumes to affect the safety of aircraft operations is often predicted using MITRE EPA Models. For many projects, key input parameters to MITER EPA are not available and conservative assumptions or models such as OHIO model are used to characterize the combustion and approximate the key input parameters to EPA plume rise model. These assumptions and conservative models lead to inaccurate results of simulations. The current study provides a novel approach to use a combination of Computational Fluid Dynamics (CFD) tool and EPA Models to reliably predict the risk of turbulence and upset being encountered by a range of aircraft types that operate through a rising plume. The main objective of the current study is to develop a Computational Fluid Dynamics (CFD) combustion model and a procedure to determine an improved set of flare inputs for the Air Quality (AQ) and MITER EPA models. A CFD model has been developed to determine flame plume characteristics (Effective Height, Effective Diameter, Temperature and Velocity) from two flare stacks which are part of a trailer-mounted Mobile Purge Burner (MPB) system. A subsequent experimental test of a similar trailer-mounted MPB system has validated the CFD results. Plume temperatures within the combustion zone of the flares were very much in line with the temperatures predicted by the CFD Simulation study. Plume temperatures above the MPB System appear to drop very quickly, such that the plume temperature fell from just under 500°C at 5 m above ground level to around 15-16°C (and close to the ambient temperature) at 22 m above ground. Again, this is consistent with the CFD Study results. The CFD simulations in the current study accounted for the turbulent flow with chemical species mixing and reaction and utilised an advanced radiation model to solve participating radiation in the combusted zones. This study assesses all the parameters that have impact on the accuracy of the numerical model including computational domain, mesh distribution, numerical scheme and flame plume characteristics including ambient conditions (wind speed and temperature) and combustion under various air to fuel ratio scenarios.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44696781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-26DOI: 10.37394/232015.2023.19.49
Ali Al-Dahoud, M. Fezari, Ahmad A. A. Alkhatib, Mohamed Nadir Soltani, Ahmed Al-Dahoud
Forest fires are one of the most devastating natural disasters that can have a significant impact on the environment, economy, and human lives. Early detection and prompt response are crucial to minimize the damage caused by forest fires. In recent years, Wireless Sensor Networks (WSN) and Internet of Things (IoT) technologies have emerged as promising solutions for forest fire detection due to their low-cost and efficient monitoring capabilities. This paper proposes a low-cost forest fire detection system based on WSN and IoT. The system uses a network of sensor nodes that are strategically placed in the forest to monitor environmental conditions such as temperature, humidity, and smoke. The sensor data is transmitted to a central server, where advanced algorithms are used to detect and predict the occurrence of forest fires. The system provides real-time alerts to forest authorities and users using a mobile application that shows the fire maps and the current updates. The proposed system has been evaluated using based on experiments, and the results show that it can effectively detect forest fires with high accuracy, low false alarms, and low cost. This system has the potential to provide an efficient and cost-effective solution for forest fire detection and can play a vital role in protecting the environment and saving lives.
{"title":"Forest Fire Detection System based on Low-Cost Wireless Sensor Network and Internet of Things","authors":"Ali Al-Dahoud, M. Fezari, Ahmad A. A. Alkhatib, Mohamed Nadir Soltani, Ahmed Al-Dahoud","doi":"10.37394/232015.2023.19.49","DOIUrl":"https://doi.org/10.37394/232015.2023.19.49","url":null,"abstract":"Forest fires are one of the most devastating natural disasters that can have a significant impact on the environment, economy, and human lives. Early detection and prompt response are crucial to minimize the damage caused by forest fires. In recent years, Wireless Sensor Networks (WSN) and Internet of Things (IoT) technologies have emerged as promising solutions for forest fire detection due to their low-cost and efficient monitoring capabilities. This paper proposes a low-cost forest fire detection system based on WSN and IoT. The system uses a network of sensor nodes that are strategically placed in the forest to monitor environmental conditions such as temperature, humidity, and smoke. The sensor data is transmitted to a central server, where advanced algorithms are used to detect and predict the occurrence of forest fires. The system provides real-time alerts to forest authorities and users using a mobile application that shows the fire maps and the current updates. The proposed system has been evaluated using based on experiments, and the results show that it can effectively detect forest fires with high accuracy, low false alarms, and low cost. This system has the potential to provide an efficient and cost-effective solution for forest fire detection and can play a vital role in protecting the environment and saving lives.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43501351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-20DOI: 10.37394/232015.2023.19.48
Anyualatha Haridison, Yuwanto Yuwanto, L. Alfirdaus, W. Wijayanto
This manuscript aims to examine the political literature on the pandemic in Indonesia, especially regarding the relationship between politics and the COVID-19 pandemic without leaving the exploration of the views of scholars in the world who address the discussion of this relationship. This study produces several discourses, including, first, countries in the world implement policies depending on the dynamics that exist in that country. The majority implement a lockdown policy or cut off transmission between regions. Indonesia has a somewhat looser policy than other countries, namely large-scale social restrictions (PSBB) while still paying attention to community economic activities. Second, in many cases, electoral trust depends on the successful handling of the pandemic by the ruling regime or even the steps in handling the pandemic by contesting candidates. Third, the election of regional heads simultaneously with the crisis in Indonesia is considered counterfactual. However, the fact is that voter participation has increased from the three previous regional elections. The true form of Indonesian political culture is implied by the actions of the people who respect elections and prioritize health protocols. Fourth, the recommendation of the scholars is the application of political digitization in voting which requires a comprehensive study, especially regarding the readiness of Indonesian technology.
{"title":"The Pandemic Politics in Indonesia: A Comparative Perspective","authors":"Anyualatha Haridison, Yuwanto Yuwanto, L. Alfirdaus, W. Wijayanto","doi":"10.37394/232015.2023.19.48","DOIUrl":"https://doi.org/10.37394/232015.2023.19.48","url":null,"abstract":"This manuscript aims to examine the political literature on the pandemic in Indonesia, especially regarding the relationship between politics and the COVID-19 pandemic without leaving the exploration of the views of scholars in the world who address the discussion of this relationship. This study produces several discourses, including, first, countries in the world implement policies depending on the dynamics that exist in that country. The majority implement a lockdown policy or cut off transmission between regions. Indonesia has a somewhat looser policy than other countries, namely large-scale social restrictions (PSBB) while still paying attention to community economic activities. Second, in many cases, electoral trust depends on the successful handling of the pandemic by the ruling regime or even the steps in handling the pandemic by contesting candidates. Third, the election of regional heads simultaneously with the crisis in Indonesia is considered counterfactual. However, the fact is that voter participation has increased from the three previous regional elections. The true form of Indonesian political culture is implied by the actions of the people who respect elections and prioritize health protocols. Fourth, the recommendation of the scholars is the application of political digitization in voting which requires a comprehensive study, especially regarding the readiness of Indonesian technology.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47472659","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-18DOI: 10.37394/232015.2023.19.47
Hicham Riache, M. Pradana
Social Networking Services (SNSs) are online platforms used by end-users that have risen to prominence as a critical means of communication for humans today due to the advancements in the web development domain. The use of these social platforms has always been affected by numerous factors that have helped to shape customers’ behavior in social media over the years. Among these factors are privacy, security, and trust, which significantly affect the consumer’s behavior when it comes to using technologies that have access to the consumer’s data, as they are considered the main pillars that determine the levels of acceptance for these technologies, in our case social networking services. In this article, we focused on exploring the general perception of users towards Meta’s social networking platforms via conducting detailed analyses using data scraping techniques and R programming language.
{"title":"Continuance Intention of Social Networking Services in Indonesia","authors":"Hicham Riache, M. Pradana","doi":"10.37394/232015.2023.19.47","DOIUrl":"https://doi.org/10.37394/232015.2023.19.47","url":null,"abstract":"Social Networking Services (SNSs) are online platforms used by end-users that have risen to prominence as a critical means of communication for humans today due to the advancements in the web development domain. The use of these social platforms has always been affected by numerous factors that have helped to shape customers’ behavior in social media over the years. Among these factors are privacy, security, and trust, which significantly affect the consumer’s behavior when it comes to using technologies that have access to the consumer’s data, as they are considered the main pillars that determine the levels of acceptance for these technologies, in our case social networking services. In this article, we focused on exploring the general perception of users towards Meta’s social networking platforms via conducting detailed analyses using data scraping techniques and R programming language.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49199412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.37394/232015.2023.19.46
Mariarosaria Picone, A. Cartenì
The automotive sector is currently developing advanced autonomous functionalities which are expected to be soon integrated into the vehicles. These vehicles can help to reduce road accidents, ease traffic congestion, improve fuel consumption, and reduce pollutant emissions. By contrast, there are still technological, normative, ethical, and social obstacles to the widespread adoption of self-driving cars, among which users’ acceptance covers a relevant issue. The aim of the paper was to investigate the users’ propensity to use self-driving systems of SAE automation Levels 1 and 2. To do this, an hoc mobility survey was performed in Italy among car drivers, investigating both the presence of these autonomous devices on board the vehicles currently used and their frequency of usage. Survey results show that 41% of the respondents currently have a Level 1 and/or 2 system on-board their car: 54% have only the Cruise Control (Level 1 car), while 46% have both of them (Level 2 car). Furthermore, about 85% of the respondent frequently (medium-high) use the Cruise Control and/or Lane Keeping Assist. More than 86% of the drivers stated that these devices significantly improve both road safety and driving stress (improve the travel experience). The highways are the roads where these self-driving systems are mainly used (more than 70% of the time). These results underline the relevant effort that the automotive industry has performed in the last decades about self-driving. In the last five years within the Italian market was observed an increase of more than 200% of the car standard equipment (no optional) with SAE automation Level 1 or 2 systems.
{"title":"Users’ Propensity to Use Self-Driving Systems of SAE Automation Level 1 and 2 Cars: Results of an Italian Survey","authors":"Mariarosaria Picone, A. Cartenì","doi":"10.37394/232015.2023.19.46","DOIUrl":"https://doi.org/10.37394/232015.2023.19.46","url":null,"abstract":"The automotive sector is currently developing advanced autonomous functionalities which are expected to be soon integrated into the vehicles. These vehicles can help to reduce road accidents, ease traffic congestion, improve fuel consumption, and reduce pollutant emissions. By contrast, there are still technological, normative, ethical, and social obstacles to the widespread adoption of self-driving cars, among which users’ acceptance covers a relevant issue. The aim of the paper was to investigate the users’ propensity to use self-driving systems of SAE automation Levels 1 and 2. To do this, an hoc mobility survey was performed in Italy among car drivers, investigating both the presence of these autonomous devices on board the vehicles currently used and their frequency of usage. Survey results show that 41% of the respondents currently have a Level 1 and/or 2 system on-board their car: 54% have only the Cruise Control (Level 1 car), while 46% have both of them (Level 2 car). Furthermore, about 85% of the respondent frequently (medium-high) use the Cruise Control and/or Lane Keeping Assist. More than 86% of the drivers stated that these devices significantly improve both road safety and driving stress (improve the travel experience). The highways are the roads where these self-driving systems are mainly used (more than 70% of the time). These results underline the relevant effort that the automotive industry has performed in the last decades about self-driving. In the last five years within the Italian market was observed an increase of more than 200% of the car standard equipment (no optional) with SAE automation Level 1 or 2 systems.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42085014","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-16DOI: 10.37394/232015.2023.19.44
Sonya Damyanova, V. Dimitrova
The research was carried out in four beech communities in two mountains, Stara Planina and Vitosha in Western Bulgaria. The object of the study was dead beech wood. The aim was to determine the chemical composition and stocks of nutrients in different parts of dead wood in both mountains. The content of macro- and micronutrients in different fractions (stumps, standing, and lying dead wood) of dead wood was determined. The elements carbon (C), hydrogen (H), and nitrogen (N) were in the largest quantities of all the chemical elements studied. Next in order were Ca, Mg, K, and P. Micronutrients were arranged as follows in descending order of their content in the dead wood: Mn, Fe, Zn, Na, Pb, Cu. The calculated stocks of these elements showed that Stara Planina had a larger stock of elements than Vitosha mountain due to the greater amount of dead wood. The results proved that the dead wood is primarily a carbon reservoir, stored mainly in the lying dead wood fraction. The average carbon stock was 983 kg/ha for Vitosha and 4635 kg/ha for Stara Planina. The stocks of all other elements that are contained were several times less in quantity.
这项研究是在保加利亚西部的Stara Planina和Vitosha两座山上的四个山毛榉群落中进行的。研究的对象是枯死的山毛榉木材。目的是测定两座山枯木不同部位的化学成分和营养物质储量。测定了枯木不同部分（树桩、直立枯木和躺着枯木）中宏观和微量营养素的含量。在所研究的所有化学元素中，碳（C）、氢（H）和氮（N）的数量最多。其次是Ca、Mg、K和P。微量元素在枯木中的含量按降序排列如下：Mn、Fe、Zn、Na、Pb、Cu。这些元素的计算储量表明，由于枯木的数量较多，Plana Stara Planina的元素储量大于Vitosha mountain。结果表明，枯木主要是一个碳库，主要储存在躺着的枯木部分。Vitosha和Stara Planina的平均碳储量分别为983千克/公顷和4635千克/公顷。所含所有其他元素的库存数量都减少了数倍。
{"title":"Chemical Composition and Stocks of Nutrients in Dead Wood of Beech (Fagus Sylvatica L.) Forests","authors":"Sonya Damyanova, V. Dimitrova","doi":"10.37394/232015.2023.19.44","DOIUrl":"https://doi.org/10.37394/232015.2023.19.44","url":null,"abstract":"The research was carried out in four beech communities in two mountains, Stara Planina and Vitosha in Western Bulgaria. The object of the study was dead beech wood. The aim was to determine the chemical composition and stocks of nutrients in different parts of dead wood in both mountains. The content of macro- and micronutrients in different fractions (stumps, standing, and lying dead wood) of dead wood was determined. The elements carbon (C), hydrogen (H), and nitrogen (N) were in the largest quantities of all the chemical elements studied. Next in order were Ca, Mg, K, and P. Micronutrients were arranged as follows in descending order of their content in the dead wood: Mn, Fe, Zn, Na, Pb, Cu. The calculated stocks of these elements showed that Stara Planina had a larger stock of elements than Vitosha mountain due to the greater amount of dead wood. The results proved that the dead wood is primarily a carbon reservoir, stored mainly in the lying dead wood fraction. The average carbon stock was 983 kg/ha for Vitosha and 4635 kg/ha for Stara Planina. The stocks of all other elements that are contained were several times less in quantity.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46320796","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-16DOI: 10.37394/232015.2023.19.43
Kisang Kwon, Eun-Ryeong Lee, Kyung-Hee Kang, Seung-Whan Kim, Hyewon Park, Junghae Kim, A. Lee, O. Kwon
Cyclophilin A (CypA), a cytosolic binding protein of cyclosporine A, is an immunosuppressive drug. In this study, CypA cDNA was cloned from the two-spotted cricket Gryllus bimaculatus (gCypA). The protein encoded by gCypA comprises 165 amino acids with a molecular mass of 19.23 kDa and an isoelectric point of 9.38 and possesses three N-glycosylation sites and 17 phosphorylation sites. The secondary and tertiary structures of gCypA were identified, and homology analysis revealed that it shares around 73%-81% sequence identities with other CypA proteins. When the researchers analyzed the expression levels of gCypA mRNA in various tissues, they found that the foregut exhibited nearly the same expression level as that of the dorsal longitudinal flight muscle (the control). However, gCypA mRNA expression in the fat body, Malpighian tubes, and midgut was less than half of that in the dorsal longitudinal flight muscle. Under endoplasmic reticulum stress conditions, gCypA mRNA expression was highest in Malpighian tubules (about two times higher than the expression in the control). Under starvation conditions, gCypA mRNA expression increased to three times that of the dorsal longitudinal flight muscle 6 days after starvation. Nonetheless, its expression levels decreased in Malpighian tubules under all starvation conditions. This study provides insights into the physiological role of gCypA in G. bimaculatus.
{"title":"Identification and Expression Analysis of a cDNA Encoding Cyclophilin A from Gryllus bimaculatus (Orthoptera: Gryllidae)","authors":"Kisang Kwon, Eun-Ryeong Lee, Kyung-Hee Kang, Seung-Whan Kim, Hyewon Park, Junghae Kim, A. Lee, O. Kwon","doi":"10.37394/232015.2023.19.43","DOIUrl":"https://doi.org/10.37394/232015.2023.19.43","url":null,"abstract":"Cyclophilin A (CypA), a cytosolic binding protein of cyclosporine A, is an immunosuppressive drug. In this study, CypA cDNA was cloned from the two-spotted cricket Gryllus bimaculatus (gCypA). The protein encoded by gCypA comprises 165 amino acids with a molecular mass of 19.23 kDa and an isoelectric point of 9.38 and possesses three N-glycosylation sites and 17 phosphorylation sites. The secondary and tertiary structures of gCypA were identified, and homology analysis revealed that it shares around 73%-81% sequence identities with other CypA proteins. When the researchers analyzed the expression levels of gCypA mRNA in various tissues, they found that the foregut exhibited nearly the same expression level as that of the dorsal longitudinal flight muscle (the control). However, gCypA mRNA expression in the fat body, Malpighian tubes, and midgut was less than half of that in the dorsal longitudinal flight muscle. Under endoplasmic reticulum stress conditions, gCypA mRNA expression was highest in Malpighian tubules (about two times higher than the expression in the control). Under starvation conditions, gCypA mRNA expression increased to three times that of the dorsal longitudinal flight muscle 6 days after starvation. Nonetheless, its expression levels decreased in Malpighian tubules under all starvation conditions. This study provides insights into the physiological role of gCypA in G. bimaculatus.","PeriodicalId":53713,"journal":{"name":"WSEAS Transactions on Environment and Development","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43693135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-16DOI: 10.37394/232015.2023.19.45
Ahmad Al-dahoud, M. Fezari, A. Aldahoud
The objective of this study is to develop an automatic cleaning system for Photovoltaic (PV) solar panels using machine learning algorithms. The experiment includes two phases. Phase one is to perform testing and reading of the sensor in 4 different classes which include no-dust, little dust, dusty, and very dusty during day and night time. The reading was taken using a visual inspection of the solar panel and the sensor reading using a multimeter. Phase two uses supervised learning to test and calibrate the sensor using the KNN algorithm. The classification was done using the data gathered from the sensor with one of the main classes identified. A total of 800 readings were taken. The results show the sensor reading taken during the night was more stable and accurate due to the sensor’s sensitivity to noise which includes: heat and light during the daytime. Secondly, using machine learning (KNN algorithm) we get a 95% (with K=5) correct classification for the four main classes which determines the level of cleaning needed for the solar panel.
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