{"title":"Bird Species Recognition System with Fine-Tuned Model","authors":"Ching-Yang Ngo, Lee-Ying Chong, Siew-Chin Chong, Pey-Yun Goh","doi":"10.18517/ijaseit.13.5.19030","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.19030","url":null,"abstract":"","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"206 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135929305","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.18475
Ujang Paman, Saipul Bahri, Agung Pramono
Rice is Indonesia's most important staple food and has become a key indicator of the country's food security. In Kampar Region, most small farmers face challenges in meeting their households’ rice food security under a relatively limited application of mechanization and small farm scale. This study examines the rice food security status of small farmer households under current levels of mechanization in Kampar Region, Indonesia. Field surveys were conducted in two districts, Bangkinang and Kuok in Kampar region in April-June 2020. A total of 72 small farmers were purposively selected for the sample, of which 36 were farmers from each district. Data were collected through interviews using semi-structured questionnaires and analyzed using descriptive-quantitative techniques. As a result, the current mechanization application was classified as intermediate level. At this level, 1.33 tons of rice were produced, and the cultivated area was 0.37 ha on average. Rice productivity averaged 3.56 tons. ha-1 and varied with various farm sizes. The per capita rice consumption was still high, approximately 114.6 kg per year, and it requires a farm size of 0.054 ha to meet annual rice consumption, or 0.27 ha for households with 5 family members. About 46% of small farmers could not meet their rice needs within one year. They could supply rice for less than 12 months and up to 21 percent of them could supply rice for up to 6 months. Therefore, the level of mechanization must be increased to improve rice productivity.
{"title":"Rice Food Security on Small Farmer Households Under Current Mechanization Level in Kampar Region, Indonesia","authors":"Ujang Paman, Saipul Bahri, Agung Pramono","doi":"10.18517/ijaseit.13.5.18475","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.18475","url":null,"abstract":"Rice is Indonesia's most important staple food and has become a key indicator of the country's food security. In Kampar Region, most small farmers face challenges in meeting their households’ rice food security under a relatively limited application of mechanization and small farm scale. This study examines the rice food security status of small farmer households under current levels of mechanization in Kampar Region, Indonesia. Field surveys were conducted in two districts, Bangkinang and Kuok in Kampar region in April-June 2020. A total of 72 small farmers were purposively selected for the sample, of which 36 were farmers from each district. Data were collected through interviews using semi-structured questionnaires and analyzed using descriptive-quantitative techniques. As a result, the current mechanization application was classified as intermediate level. At this level, 1.33 tons of rice were produced, and the cultivated area was 0.37 ha on average. Rice productivity averaged 3.56 tons. ha-1 and varied with various farm sizes. The per capita rice consumption was still high, approximately 114.6 kg per year, and it requires a farm size of 0.054 ha to meet annual rice consumption, or 0.27 ha for households with 5 family members. About 46% of small farmers could not meet their rice needs within one year. They could supply rice for less than 12 months and up to 21 percent of them could supply rice for up to 6 months. Therefore, the level of mechanization must be increased to improve rice productivity.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"60 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808159","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.18570
Ega Asti Anggari, Agus Herawan, Patria Rachman Hakim, Agung Wahyudiono, Sartika Salaswati, Elvira Rachim, Zylshal Zylshal
The LAPAN-A3 is the third microsatellite generation developed by the Research Center for Satellite Technology. The satellite can be used for land classification, agriculture monitoring, drought monitoring, and land use change. This study aims to classify land use and land cover in the research area. The main image used is LAPAN-A3; the compared images are Landsat-8 and Sentinel-2. Three images were taken on the same day and selected on cloud-free terms. The classification process starts with determining the region of interest (ROI) and the class. The classification is divided into six classes: water, forests, rice fields, settlements, open land, and coastal areas. The classification technique uses supervised learning with the maximum likelihood method. This study used Landsat 8 and Sentinel-2 data to compare the results obtained from LAPAN-A3. The accuracy test results for the LAPAN-A3 and Landsat-8 are 84.7042% and 0.783, respectively. While the accuracy test of LAPAN-A3 and Sentinel-2 is 72.2313%, the kappa value is 0.6394. The classification of two comparisons is quite accurate, with an accuracy of more than 70%. The LA3 classification successfully identifies water and coastal areas. The producer and accuracy is substantiated by comparing the results with both Landsat-8 and Sentinel-2 satellite data, which exhibit an accuracy rate exceeding 85%. Finally, LAPAN-A3 has great potential for classifying land use and land cover when compared to Landsat 8 and Sentinel-2 images, but future research should increase the number of datasets and vary the research area to improve the results.
{"title":"Assessing the Accuracy of Land Use Classification Using Multi-spectral Camera From LAPAN-A3, Landsat-8 and Sentinel-2 Satellite: A Case Study in Probolinggo-East Java","authors":"Ega Asti Anggari, Agus Herawan, Patria Rachman Hakim, Agung Wahyudiono, Sartika Salaswati, Elvira Rachim, Zylshal Zylshal","doi":"10.18517/ijaseit.13.5.18570","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.18570","url":null,"abstract":"The LAPAN-A3 is the third microsatellite generation developed by the Research Center for Satellite Technology. The satellite can be used for land classification, agriculture monitoring, drought monitoring, and land use change. This study aims to classify land use and land cover in the research area. The main image used is LAPAN-A3; the compared images are Landsat-8 and Sentinel-2. Three images were taken on the same day and selected on cloud-free terms. The classification process starts with determining the region of interest (ROI) and the class. The classification is divided into six classes: water, forests, rice fields, settlements, open land, and coastal areas. The classification technique uses supervised learning with the maximum likelihood method. This study used Landsat 8 and Sentinel-2 data to compare the results obtained from LAPAN-A3. The accuracy test results for the LAPAN-A3 and Landsat-8 are 84.7042% and 0.783, respectively. While the accuracy test of LAPAN-A3 and Sentinel-2 is 72.2313%, the kappa value is 0.6394. The classification of two comparisons is quite accurate, with an accuracy of more than 70%. The LA3 classification successfully identifies water and coastal areas. The producer and accuracy is substantiated by comparing the results with both Landsat-8 and Sentinel-2 satellite data, which exhibit an accuracy rate exceeding 85%. Finally, LAPAN-A3 has great potential for classifying land use and land cover when compared to Landsat 8 and Sentinel-2 images, but future research should increase the number of datasets and vary the research area to improve the results.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"60 16","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808162","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.19094
Roostita Lobo Balia, Fauzi Rohman, Okta Wismandanu, Lydia Chaidir, - Tyagita, Pranyata T. Waskita, Vesara A. Gatera, Sarasati Windria, Mas Rizky A. A. Syamsunarno, Gemilang L. Utama
Since people and domesticated animals have lived together for a long time, it is possible that diseases could be spread by accident, as happened with SARS-CoV-2. There have been reports of cats in Italy, Spain, and France being exposed to SARS-CoV-2. Not much is known about how farmed animals were exposed to SARS-CoV-2 in Indonesia, which was named the epicenter of COVID-19 in July 2021. The study's goal was to determine if SARS-CoV-2 was present in felines living with people who had COVID-19 in the Bandung, Indonesia, area. Nineteen felines were used in the study. These felines came from seven people who had tested positive for COVID-19. For RT-qPCR testing, samples were taken from the nose, oropharynx, and rectal areas. Blood sera were taken for quick IgM/IgG antibody tests for SARS CoV-2. Using RT-qPCR on nasopharyngeal samples from the felines being studied, it has been seen that four of them have tested positive. But it is interesting to note that only one of these people could be found using a rectal test. There was no clear sign of antibody formation when IgM/IgG rapid test results from blood samples were looked at. The felines that showed positive results were very close to their caretakers and had symptoms that were similar to those of influenza. The results of our study show that there is a chance that SARS-CoV-2 could be passed on to felines who live with people who have COVID-19. Because of this finding, more study needs to be done in this area.
{"title":"SARS-Corona Virus Type-2 Detection of Cohabiting Feline with COVID-Positive Individuals in Bandung, Indonesia","authors":"Roostita Lobo Balia, Fauzi Rohman, Okta Wismandanu, Lydia Chaidir, - Tyagita, Pranyata T. Waskita, Vesara A. Gatera, Sarasati Windria, Mas Rizky A. A. Syamsunarno, Gemilang L. Utama","doi":"10.18517/ijaseit.13.5.19094","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.19094","url":null,"abstract":"Since people and domesticated animals have lived together for a long time, it is possible that diseases could be spread by accident, as happened with SARS-CoV-2. There have been reports of cats in Italy, Spain, and France being exposed to SARS-CoV-2. Not much is known about how farmed animals were exposed to SARS-CoV-2 in Indonesia, which was named the epicenter of COVID-19 in July 2021. The study's goal was to determine if SARS-CoV-2 was present in felines living with people who had COVID-19 in the Bandung, Indonesia, area. Nineteen felines were used in the study. These felines came from seven people who had tested positive for COVID-19. For RT-qPCR testing, samples were taken from the nose, oropharynx, and rectal areas. Blood sera were taken for quick IgM/IgG antibody tests for SARS CoV-2. Using RT-qPCR on nasopharyngeal samples from the felines being studied, it has been seen that four of them have tested positive. But it is interesting to note that only one of these people could be found using a rectal test. There was no clear sign of antibody formation when IgM/IgG rapid test results from blood samples were looked at. The felines that showed positive results were very close to their caretakers and had symptoms that were similar to those of influenza. The results of our study show that there is a chance that SARS-CoV-2 could be passed on to felines who live with people who have COVID-19. Because of this finding, more study needs to be done in this area.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"60 22","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808156","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.19350
Tuti Widjastuti, Indah Komala, Wiwin Tanwiriah, Leni Nurlaeni
Noni fruit is a herbal plant that has the potential to be used as additional feed to replace Antibiotic Growth Promoters (AGP) and contains bioactive compounds that can increase the absorption of nutrients in the digestive tract. The study aims to determine the effect of adding noni extract with Cu and Zn supplemented in the ration on the performance of Sentul chicken in the developer phase. The research used an experiment method, using 40 female Sentul chickens aged 16 weeks and maintained until 24 weeks of age. The study used an experimental method with an experimental design used was a Completely Randomized Design (CRD). The treatments consisted of P0 = basal ration, P1= basal ration + 0.3%/kg noni fruit extract supplemented with Cu and Zn (ENFm), P2 basal ration + 0.6% /kg ENFm, P3 = basal ration + 0.9% / kg ENFm, P4 = basal ration + 1.2%/kg ENFm. Each treatment was repeated four times, and each repetition consisted of 2 Sentul chickens. The results showed that the P3 (0.9 ENFm) treatment had an influence on body weight gain and feed conversion but did not affect feed consumption and age of sexual maturity, and the addition of 0.6% (P2) level in the ratio could be the best performance on early production of chicken Sentul. This shows that ENFm products can be used as feed additives in Sentul chickens to replace an Antibiotic Growth Promoter (AGP) role.
{"title":"Application of Noni Fruit (Morinda citrifolia L.) Extract with Cu and Zn Supplemented in the Ration on Performance Chicken Sentul of Phase Developer","authors":"Tuti Widjastuti, Indah Komala, Wiwin Tanwiriah, Leni Nurlaeni","doi":"10.18517/ijaseit.13.5.19350","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.19350","url":null,"abstract":"Noni fruit is a herbal plant that has the potential to be used as additional feed to replace Antibiotic Growth Promoters (AGP) and contains bioactive compounds that can increase the absorption of nutrients in the digestive tract. The study aims to determine the effect of adding noni extract with Cu and Zn supplemented in the ration on the performance of Sentul chicken in the developer phase. The research used an experiment method, using 40 female Sentul chickens aged 16 weeks and maintained until 24 weeks of age. The study used an experimental method with an experimental design used was a Completely Randomized Design (CRD). The treatments consisted of P0 = basal ration, P1= basal ration + 0.3%/kg noni fruit extract supplemented with Cu and Zn (ENFm), P2 basal ration + 0.6% /kg ENFm, P3 = basal ration + 0.9% / kg ENFm, P4 = basal ration + 1.2%/kg ENFm. Each treatment was repeated four times, and each repetition consisted of 2 Sentul chickens. The results showed that the P3 (0.9 ENFm) treatment had an influence on body weight gain and feed conversion but did not affect feed consumption and age of sexual maturity, and the addition of 0.6% (P2) level in the ratio could be the best performance on early production of chicken Sentul. This shows that ENFm products can be used as feed additives in Sentul chickens to replace an Antibiotic Growth Promoter (AGP) role.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"60 21","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808157","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.19035
Xian Yang Chan, Tee Connie, Michael Kah Ong Goh
Online learning has gained immense popularity, especially since the COVID-19 pandemic. However, it has also brought its own set of challenges. One of the critical challenges in online learning is the ability to evaluate students' concentration levels during virtual classes. Unlike traditional brick-and-mortar classrooms, teachers do not have the advantage of observing students' body language and facial expressions to determine whether they are paying attention. To address this challenge, this study proposes utilizing facial and body gestures to evaluate students' concentration levels. Common gestures such as yawning, playing with fingers or objects, and looking away from the screen indicate a lack of focus. A dataset containing images of students performing various actions and gestures representing different concentration levels is collected. We propose an enhanced model based on a vision transformer (RViT) to classify the concentration levels. This model incorporates a majority voting feature to maintain real-time prediction accuracy. This feature classifies multiple frames, and the final prediction is based on the majority class. The proposed method yields a promising 92% accuracy while maintaining efficient computational performance. The system provides an unbiased measure for assessing students' concentration levels, which can be useful in educational settings to improve learning outcomes. It enables educators to foster a more engaging and productive virtual classroom environment.
{"title":"Facial and Body Gesture Recognition for Determining Student Concentration Level","authors":"Xian Yang Chan, Tee Connie, Michael Kah Ong Goh","doi":"10.18517/ijaseit.13.5.19035","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.19035","url":null,"abstract":"Online learning has gained immense popularity, especially since the COVID-19 pandemic. However, it has also brought its own set of challenges. One of the critical challenges in online learning is the ability to evaluate students' concentration levels during virtual classes. Unlike traditional brick-and-mortar classrooms, teachers do not have the advantage of observing students' body language and facial expressions to determine whether they are paying attention. To address this challenge, this study proposes utilizing facial and body gestures to evaluate students' concentration levels. Common gestures such as yawning, playing with fingers or objects, and looking away from the screen indicate a lack of focus. A dataset containing images of students performing various actions and gestures representing different concentration levels is collected. We propose an enhanced model based on a vision transformer (RViT) to classify the concentration levels. This model incorporates a majority voting feature to maintain real-time prediction accuracy. This feature classifies multiple frames, and the final prediction is based on the majority class. The proposed method yields a promising 92% accuracy while maintaining efficient computational performance. The system provides an unbiased measure for assessing students' concentration levels, which can be useful in educational settings to improve learning outcomes. It enables educators to foster a more engaging and productive virtual classroom environment.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"60 18","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808160","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.19210
- Iswoyo, Juni Sumarmono, Triana Setyawardani
Indonesia Batur local lamb meat has emerged as a promising meat source for the production of emulsion-type sausages. However, the manufacturing process of this sausage typically requires high-fat content to achieve the desired quality characteristics. To address this issue, this study investigates utilizing microbial transglutaminase (MTGase) enzyme to improve local lamb meat sausage's physicochemical, textural, and microstructure features. This research aimed to develop emulsion sausages using local lamb meat by incorporating the MTGase enzyme. The experimental design encompassed various treatments, including a control group, the addition of 10% tapioca, and incremental amounts of MTGase (ranging from 0.2% to 1.0%). The sausages were evaluated comprehensively: pH value, color, tenderness, texture, and microstructure. The statistical analysis, employing ANOVA, demonstrated a significant improvement in pH, firmness, toughness, cohesiveness, and gumminess with the addition of MTGase, while also influencing the color of the sausages (P<0.05) that can be attributed to the MTGase enzyme's capacity to bind myofibrillar proteins through cross-linking reactions, enhancing texture and tenderness. Nevertheless, it was noticed that the presence of MTGase led to a* and b* values reduction due to the denaturation of globin and carotenoid pigments; however, these values remained within an acceptable range. Notably, the incorporation of 0.8% and 1.0% MTGase resulted in forming an ordered and homogeneous network microstructure, exhibiting fewer voids within the sausages. Overall, the findings of this study demonstrate the successful enhancement of the quality of sausages, thereby significantly increasing the acceptability of the final product.
{"title":"Enhancing the Sausage Quality of Indonesian Local Lamb Meat with Microbial Transglutaminase Enzyme: Physicochemical, Textural, and Microstructure Properties","authors":"- Iswoyo, Juni Sumarmono, Triana Setyawardani","doi":"10.18517/ijaseit.13.5.19210","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.19210","url":null,"abstract":"Indonesia Batur local lamb meat has emerged as a promising meat source for the production of emulsion-type sausages. However, the manufacturing process of this sausage typically requires high-fat content to achieve the desired quality characteristics. To address this issue, this study investigates utilizing microbial transglutaminase (MTGase) enzyme to improve local lamb meat sausage's physicochemical, textural, and microstructure features. This research aimed to develop emulsion sausages using local lamb meat by incorporating the MTGase enzyme. The experimental design encompassed various treatments, including a control group, the addition of 10% tapioca, and incremental amounts of MTGase (ranging from 0.2% to 1.0%). The sausages were evaluated comprehensively: pH value, color, tenderness, texture, and microstructure. The statistical analysis, employing ANOVA, demonstrated a significant improvement in pH, firmness, toughness, cohesiveness, and gumminess with the addition of MTGase, while also influencing the color of the sausages (P<0.05) that can be attributed to the MTGase enzyme's capacity to bind myofibrillar proteins through cross-linking reactions, enhancing texture and tenderness. Nevertheless, it was noticed that the presence of MTGase led to a* and b* values reduction due to the denaturation of globin and carotenoid pigments; however, these values remained within an acceptable range. Notably, the incorporation of 0.8% and 1.0% MTGase resulted in forming an ordered and homogeneous network microstructure, exhibiting fewer voids within the sausages. Overall, the findings of this study demonstrate the successful enhancement of the quality of sausages, thereby significantly increasing the acceptability of the final product.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"73 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808319","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.19041
Siti Musliha Aishah Musa, Asrul Izam Azmi, Siti Azlida Ibrahim, Raja Kamarulzaman Raja Ibrahim
This research investigates fiber Bragg grating (FBG) temperature sensing performance in monitoring non—uniformity of non-thermal plasma (NTP) formation in a packed-bed reactor using FBG operating at atmospheric pressure. Two FBGs made from germanium doped fiber were embedded inside and outside the PBNTP reactor to allow for comparison between the temperatures inside and outside of the reactor to be made. Each FBG comes with three grating series, which allow the reactor temperatures at three different locations inside or outside the reactor to be measured and compared. Two types of plasma, namely nitrogen (N2) and argon (Ar) were generated in the reactor at a gas flow rate in the range of 2 - 7 L/min and applied voltage in the range of l - 20 kV. It was found that the PBNTP reactor temperature varies up to 20 oC at different positions inside and up to 40 oC outside of the reactor. This finding shows the non-uniformity of plasma formation and the nature of the plasma's localized thermodynamic equilibrium (LTE). The sensitivity of the FBG temperature sensor used in this study is estimated at 10.36 - 10.50 pm/oC.
{"title":"Non-Uniformity of Non-Thermal Plasma Formation: Using FBG as Temperature Sensors","authors":"Siti Musliha Aishah Musa, Asrul Izam Azmi, Siti Azlida Ibrahim, Raja Kamarulzaman Raja Ibrahim","doi":"10.18517/ijaseit.13.5.19041","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.19041","url":null,"abstract":"This research investigates fiber Bragg grating (FBG) temperature sensing performance in monitoring non—uniformity of non-thermal plasma (NTP) formation in a packed-bed reactor using FBG operating at atmospheric pressure. Two FBGs made from germanium doped fiber were embedded inside and outside the PBNTP reactor to allow for comparison between the temperatures inside and outside of the reactor to be made. Each FBG comes with three grating series, which allow the reactor temperatures at three different locations inside or outside the reactor to be measured and compared. Two types of plasma, namely nitrogen (N2) and argon (Ar) were generated in the reactor at a gas flow rate in the range of 2 - 7 L/min and applied voltage in the range of l - 20 kV. It was found that the PBNTP reactor temperature varies up to 20 oC at different positions inside and up to 40 oC outside of the reactor. This finding shows the non-uniformity of plasma formation and the nature of the plasma's localized thermodynamic equilibrium (LTE). The sensitivity of the FBG temperature sensor used in this study is estimated at 10.36 - 10.50 pm/oC.","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"73 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135808320","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}
{"title":"Modification of Surface Charges on Ex-Gold Mining Soil Ameliorated with Activation of Sub-Bituminous Coal - NaOH","authors":"Teguh Budi Prasetyo, Amsar Maulana, Mimien Harianti, Aresta Leo Lita, - Herviyanti","doi":"10.18517/ijaseit.13.5.18429","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.18429","url":null,"abstract":"","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"38 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135929302","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 : 2023-10-31DOI: 10.18517/ijaseit.13.5.18284
Purba Daru Kusuma, Meta Kallista
{"title":"Adaptive Cone Algorithm","authors":"Purba Daru Kusuma, Meta Kallista","doi":"10.18517/ijaseit.13.5.18284","DOIUrl":"https://doi.org/10.18517/ijaseit.13.5.18284","url":null,"abstract":"","PeriodicalId":14471,"journal":{"name":"International Journal on Advanced Science, Engineering and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135929304","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}
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