Pub Date : 2022-12-30DOI: 10.35940/ijeat.d3470.1212222
Shanmukha Sai Nikhil Myramuru, Dr. S. Chandra Mohan Reddy, Dr. Gannera Mamatha
NAND Flash Memory has replaced EEPROM and hard drives as Non-volatile. Data is stored in sequential order in NAND Flash Memory. NAND Memory is a type of flash memory widely used in mobile phones and System on Chips (SoC). The Memory controller supports an 8-bit NAND Flash interface and streaming interface towards АXI4. The data transfer between АXI4 and NAND Flash Memory is carried оut by using NAND Flash commands sequences. The AXI4 Interface enables the usage of various рrоtосоls. To improve the flash memory controller's data access speed. This project intends to design, develop, and integrate a NAND Flash memory controller using an AXI4 interface for an open POWER Processor A20 fabless SOC. The Flash Memory Controller includes Finite State Machines (FSM) and AXI4 bridge logic. Using Mentor Graphics® and Xilinx's Vivado design suite, the test results were based on behavioral simulation and synthesis
{"title":"Design and Integration of NAND Flash Memory Controller for Open Power-based Fabless SoC","authors":"Shanmukha Sai Nikhil Myramuru, Dr. S. Chandra Mohan Reddy, Dr. Gannera Mamatha","doi":"10.35940/ijeat.d3470.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.d3470.1212222","url":null,"abstract":"NAND Flash Memory has replaced EEPROM and hard drives as Non-volatile. Data is stored in sequential order in NAND Flash Memory. NAND Memory is a type of flash memory widely used in mobile phones and System on Chips (SoC). The Memory controller supports an 8-bit NAND Flash interface and streaming interface towards АXI4. The data transfer between АXI4 and NAND Flash Memory is carried оut by using NAND Flash commands sequences. The AXI4 Interface enables the usage of various рrоtосоls. To improve the flash memory controller's data access speed. This project intends to design, develop, and integrate a NAND Flash memory controller using an AXI4 interface for an open POWER Processor A20 fabless SOC. The Flash Memory Controller includes Finite State Machines (FSM) and AXI4 bridge logic. Using Mentor Graphics® and Xilinx's Vivado design suite, the test results were based on behavioral simulation and synthesis","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84570786","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 : 2022-12-30DOI: 10.35940/ijeat.b3638.1212222
Islam Asem Salah Abosohyon, G. Aiello, Antonella Certa
Unmanned Aerial Vehicles (UAVs) is an emergent technology with the potential to drastically change the landscape of many civil and industrial activities in the near future. A promising field of application is the inspection and monitoring of industrial plants, where UAVs can be a valid alternative to traditional approaches with a better cost-effectiveness and a higher safety level. Although the disruptive innovative potential of this technology is generally recognized, a consistent methodological approach towards the evaluation of the drawbacks and benefits of employing UAVs in critical industrial operations can hardly be found in the current scientific literature. In such context, this paper proposes a framework for assessing the effectiveness of UAV technology in industrial monitoring applications within a structured multi-objective framework. In particular, the paper compares the traditional ground-based inspection services of Above Ground Storage Tank (AST) with UAV based inspection, by means of the well-known Analytic Hierarchy Process (AHP) method considering time, cost and safety criteria. A case study is also proposed to demonstrate the effectiveness of the approach proposed.
{"title":"Drone Based Inspection of Above Ground Storage Tanks. A Multi Criteria Evaluation Approach","authors":"Islam Asem Salah Abosohyon, G. Aiello, Antonella Certa","doi":"10.35940/ijeat.b3638.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3638.1212222","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) is an emergent technology with the potential to drastically change the landscape of many civil and industrial activities in the near future. A promising field of application is the inspection and monitoring of industrial plants, where UAVs can be a valid alternative to traditional approaches with a better cost-effectiveness and a higher safety level. Although the disruptive innovative potential of this technology is generally recognized, a consistent methodological approach towards the evaluation of the drawbacks and benefits of employing UAVs in critical industrial operations can hardly be found in the current scientific literature. In such context, this paper proposes a framework for assessing the effectiveness of UAV technology in industrial monitoring applications within a structured multi-objective framework. In particular, the paper compares the traditional ground-based inspection services of Above Ground Storage Tank (AST) with UAV based inspection, by means of the well-known Analytic Hierarchy Process (AHP) method considering time, cost and safety criteria. A case study is also proposed to demonstrate the effectiveness of the approach proposed.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87402147","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 : 2022-12-30DOI: 10.35940/ijeat.b3926.1212222
Dr. Rene M. Chavez
This research investigated the effectiveness of the mock-up innovation as instructional material for teaching among the third-year automotive technology students at Bukidnon State University, Malaybalay, Bukidnon, during the first semester of the school year 2018-2019. It highlighted the profile of the students considering: academic status (e.g. regular, irregular); program status (e.g. first course, second course); unit load; family income and size; and major subjects. It also evaluated the pre-test and post-test scores in written and practical examinations on the topics of Test and Repair Wiring/AVR Charging Systems; Test and Repair Wiring/IC Charging Systems; and Servicing Car Batteries, as well as their performance during activities and simulations. External evaluations in written and practical examinations were also done on the 3 topics. Finally, it assessed the effects or influence of all the input and process variables on the output variables of the study with the outcome of a trainer model on a Project Development for the Instructional Trainer Innovation for Automatic Voltage Regulator and Integrated Circuit Charging System. A descriptive research method was used, employing the survey questionnaire and written and practical examinations, to gather the data. Findings revealed the academic and socio-economic profile of the respondents; the results of the pre-and post-test in the written and practical evaluation on the 3 topics where improvements in scores are seen in the post-tests after the utilization of the Trainer Model as instructional materials. However, there were no significant effects of the input variables on the written and practical scores of the respondents.
本研究调查了在2018-2019学年第一学期，Bukidnon State University, Malaybalay, Bukidnon的汽车技术三年级学生中，模型创新作为教学材料的有效性。它突出了学生的概况考虑:学术地位(如正规，非正规);课程状态(例如第一课程、第二课程);单位荷载;家庭收入和规模;和主要科目。考试亦评估测试前及测试后有关“测试及维修线路/自动驾驶车辆收费系统”的笔试及实务考试成绩;测试和维修线路/IC充电系统;以及维修汽车电池，以及它们在活动和模拟中的表现。在笔试和实践考试中也对这三个主题进行了外部评价。最后，本文评估了所有输入变量和过程变量对研究输出变量的影响或影响，并在自动电压调节器和集成电路充电系统的教学培训师创新项目开发中建立了培训师模型。采用描述性研究方法，采用调查问卷和书面和实践考试，收集数据。调查结果揭示了受访者的学术和社会经济状况;使用培训师模型作为教学材料后，对三个主题的书面和实践评估的前后测试结果，在测试中可以看到分数的提高。然而，输入变量对被调查者的书面和实践分数没有显著的影响。
{"title":"Instructional Automotive Charging System with Automatic Voltage Regulator and Integrated Circuits","authors":"Dr. Rene M. Chavez","doi":"10.35940/ijeat.b3926.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3926.1212222","url":null,"abstract":"This research investigated the effectiveness of the mock-up innovation as instructional material for teaching among the third-year automotive technology students at Bukidnon State University, Malaybalay, Bukidnon, during the first semester of the school year 2018-2019. It highlighted the profile of the students considering: academic status (e.g. regular, irregular); program status (e.g. first course, second course); unit load; family income and size; and major subjects. It also evaluated the pre-test and post-test scores in written and practical examinations on the topics of Test and Repair Wiring/AVR Charging Systems; Test and Repair Wiring/IC Charging Systems; and Servicing Car Batteries, as well as their performance during activities and simulations. External evaluations in written and practical examinations were also done on the 3 topics. Finally, it assessed the effects or influence of all the input and process variables on the output variables of the study with the outcome of a trainer model on a Project Development for the Instructional Trainer Innovation for Automatic Voltage Regulator and Integrated Circuit Charging System. A descriptive research method was used, employing the survey questionnaire and written and practical examinations, to gather the data. Findings revealed the academic and socio-economic profile of the respondents; the results of the pre-and post-test in the written and practical evaluation on the 3 topics where improvements in scores are seen in the post-tests after the utilization of the Trainer Model as instructional materials. However, there were no significant effects of the input variables on the written and practical scores of the respondents.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"88 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84066391","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 : 2022-12-30DOI: 10.35940/ijeat.b3956.1212222
Neha Saini, Prof. Indu Chhabra, Dr. Ajay Guleria
Developing a quality software product is an essential need of the software industry. Software quality comprises of various factors. Therefore, it cannot be measured on the basis of a single variable. Several agile software development methods have evolved all around the world with the passage of time that contribute towards the development of new and improved software methods. The agile processes have started invading the software development industry to provide good quality software in minimal time. As the changes have occurred in the modern day evaluation metrics, the changes have been observed in the agile oriented quality evaluation methods as well. This paper presents a machine learning based approach for evaluating agile based methods for enhancing software quality. This advanced mechanism of processing the data attributes is inspired by SWARA and FDD. The validation and evaluation has been done using statistical and the quantitative parameters.
{"title":"Machine Learning Based Approach for Evaluating Agile Based Methods to Enhance Software Quality","authors":"Neha Saini, Prof. Indu Chhabra, Dr. Ajay Guleria","doi":"10.35940/ijeat.b3956.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3956.1212222","url":null,"abstract":"Developing a quality software product is an essential need of the software industry. Software quality comprises of various factors. Therefore, it cannot be measured on the basis of a single variable. Several agile software development methods have evolved all around the world with the passage of time that contribute towards the development of new and improved software methods. The agile processes have started invading the software development industry to provide good quality software in minimal time. As the changes have occurred in the modern day evaluation metrics, the changes have been observed in the agile oriented quality evaluation methods as well. This paper presents a machine learning based approach for evaluating agile based methods for enhancing software quality. This advanced mechanism of processing the data attributes is inspired by SWARA and FDD. The validation and evaluation has been done using statistical and the quantitative parameters.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89734676","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 : 2022-12-30DOI: 10.35940/ijeat.b3921.1212222
Yao Gnagbolou, M. Agbomahena, G. K. N'Gobi, Dr. Maurel Richy Aza-gnandji
Benin has a large potential (3.5-5.5 kWh/m2 /day) for solar photovoltaic energy production. This daily energy production, which mainly depends on solar radiation, also varies considerably, depending on climatic parameters. The Plateau department is an industrial zone where mainly clinker and cement are mined and processed. In such an environment of dust production, meteorological data are very dynamic and act as input parameters or sometimes disruptors of the photovoltaic energy conversion chain. The aim of this paper is to determine the appropriate location of the photovoltaic field for optimal production of electrical energy, in the plateau department of Benin. The analysis is based on the multicriteria decision-making method (MCDM) and Analytic Hierarchical Process (AHP), using a Geographic Information System (GIS). ArcGIS 10.8 software was used to classify and weight the different vulnerability criteria (Global Horizontal Irradiation, Temperature, Wind Speed, Wind Direction, Precipitation, Relative Humidity, Cloud cover, and Aerosol), in order to determine the optimal photovoltaic power generation area by overlaying the layers. The result shows that solar irradiation is the most important criterion for better production of photovoltaic energy whose weight of 46.06% is the highest, and aerosol (dust), the lowest weight of 2.43%, considerably reduced energy production. The northern zone from 7°35’0″N-7°39’0″N of the commune of Ketou is therefore the best site for optimal production, considering the parameters studied.
{"title":"Climate Vulnerability of Photovoltaic Energy Systems using GIS: Case of the Plateau Department","authors":"Yao Gnagbolou, M. Agbomahena, G. K. N'Gobi, Dr. Maurel Richy Aza-gnandji","doi":"10.35940/ijeat.b3921.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3921.1212222","url":null,"abstract":"Benin has a large potential (3.5-5.5 kWh/m2 /day) for solar photovoltaic energy production. This daily energy production, which mainly depends on solar radiation, also varies considerably, depending on climatic parameters. The Plateau department is an industrial zone where mainly clinker and cement are mined and processed. In such an environment of dust production, meteorological data are very dynamic and act as input parameters or sometimes disruptors of the photovoltaic energy conversion chain. The aim of this paper is to determine the appropriate location of the photovoltaic field for optimal production of electrical energy, in the plateau department of Benin. The analysis is based on the multicriteria decision-making method (MCDM) and Analytic Hierarchical Process (AHP), using a Geographic Information System (GIS). ArcGIS 10.8 software was used to classify and weight the different vulnerability criteria (Global Horizontal Irradiation, Temperature, Wind Speed, Wind Direction, Precipitation, Relative Humidity, Cloud cover, and Aerosol), in order to determine the optimal photovoltaic power generation area by overlaying the layers. The result shows that solar irradiation is the most important criterion for better production of photovoltaic energy whose weight of 46.06% is the highest, and aerosol (dust), the lowest weight of 2.43%, considerably reduced energy production. The northern zone from 7°35’0″N-7°39’0″N of the commune of Ketou is therefore the best site for optimal production, considering the parameters studied.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"55 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84401589","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 : 2022-12-30DOI: 10.35940/ijeat.b3905.1212222
Dr. Anatoli Nachev
This article presents a case study that provides assessment of access to the Irish healthcare system and the services it provides. We explore factors related to unmet heath care needs using recent survey data. Our approach is based on using support vector machines for building predictive models that analyse and measure those factors. The proposed methodology is novel for the domain. Following the behavioural model for access to medical care, we group factors into three categories: predisposing, enabling, and needs, and analyse each group. Experimental results show and measure the primary causes of imbalances and inequalities of treatment in the Irish healthcare system today.
{"title":"Assessment of Healthcare Services using Models Based on Support Vector Machines","authors":"Dr. Anatoli Nachev","doi":"10.35940/ijeat.b3905.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3905.1212222","url":null,"abstract":"This article presents a case study that provides assessment of access to the Irish healthcare system and the services it provides. We explore factors related to unmet heath care needs using recent survey data. Our approach is based on using support vector machines for building predictive models that analyse and measure those factors. The proposed methodology is novel for the domain. Following the behavioural model for access to medical care, we group factors into three categories: predisposing, enabling, and needs, and analyse each group. Experimental results show and measure the primary causes of imbalances and inequalities of treatment in the Irish healthcare system today.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85680895","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 : 2022-12-30DOI: 10.35940/ijeat.b3915.1212222
Aishat Salau, Prof. Nwojo Agwu Nnanna, Prof. Moussa, Moussa
Health insurance fraud remains a global menace despite the controls implemented to address it; one of such controls is preauthorization. Although, preauthorization promises reduction in fraud, waste and abuse in healthcare, it places undue administrative burden on healthcare service providers and delay in patient care. This limitation has not been thoroughly explored by works of literature in the machine learning domain. In this work, a deep learning model is proposed to learn the preauthorization process for fraud prevention in health insurance for improved process efficacy. In detail, a de-identified HMO preauthorization dataset is used for training the Long Short- Term Memory (LSTM) network. To address class imbalance and avoid data overfitting, the proposed approach utilizes random oversampling and dropout techniques respectively. The experimental results reveal that the proposed model can effectively learn preauthorization request patterns while offering a fraud detection accuracy rate of over 90% with a 2-4% improvement rate in accuracy when compared with previous techniques based on conventional machine learning techniques. The proposed technique is capable of detecting anomalous preauthorization requests based on medical necessity.
{"title":"Deep Learning for Fraud Prediction in Preauthorization for Health Insurance","authors":"Aishat Salau, Prof. Nwojo Agwu Nnanna, Prof. Moussa, Moussa","doi":"10.35940/ijeat.b3915.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3915.1212222","url":null,"abstract":"Health insurance fraud remains a global menace despite the controls implemented to address it; one of such controls is preauthorization. Although, preauthorization promises reduction in fraud, waste and abuse in healthcare, it places undue administrative burden on healthcare service providers and delay in patient care. This limitation has not been thoroughly explored by works of literature in the machine learning domain. In this work, a deep learning model is proposed to learn the preauthorization process for fraud prevention in health insurance for improved process efficacy. In detail, a de-identified HMO preauthorization dataset is used for training the Long Short- Term Memory (LSTM) network. To address class imbalance and avoid data overfitting, the proposed approach utilizes random oversampling and dropout techniques respectively. The experimental results reveal that the proposed model can effectively learn preauthorization request patterns while offering a fraud detection accuracy rate of over 90% with a 2-4% improvement rate in accuracy when compared with previous techniques based on conventional machine learning techniques. The proposed technique is capable of detecting anomalous preauthorization requests based on medical necessity.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74482655","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 : 2022-12-30DOI: 10.35940/ijeat.b3950.1212222
K. Praveena, Prof. Perumalla Naveen Kumar, Prof. D. Krishna Reddy
Ionospheric scintillation is a rapid change in amplitude and phase of an electromagnetic signal in the ionospheric environment. Amplitude scintillations indicated by S4 index and phase scintillations by. Low latitude regions are prone to ionosphere scintillation. Since India is a low latitude region, ionospheric scintillations must be analysed. Indian NavIC or IRNSS planned and implemented by the Indian Space Research Organization (ISRO). In this paper S4 index is investigated for NavIC L5 (1.17645 GHz) and S1 (2.492028 GHz) signals (1B,1C,1D,1E,1F,1G). For the analysis Guntur station (Lat:16.44N, Lon:80.62E) and Hyderabad station (Lat:17°24’28.10″N, Lon: 78°31′4.22″E) IGS receiver data is considered. The S4 index is calculated using carrier to noise ratio of IRNSS L5 and S band signals. From the results it is observed that S4 index is more for L5 band signals compared to S band signals, as ionospheric scintillations are frequency dependent. Guntur station S4 average value is low for all (L5 and S) band satellite signals compared to Hyderabad station satellite signals. Over Indian region, it shows latitude-dependent scintillations.
{"title":"Analysis of Ionospheric Scintillations Measurement on NavIC Signals","authors":"K. Praveena, Prof. Perumalla Naveen Kumar, Prof. D. Krishna Reddy","doi":"10.35940/ijeat.b3950.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3950.1212222","url":null,"abstract":"Ionospheric scintillation is a rapid change in amplitude and phase of an electromagnetic signal in the ionospheric environment. Amplitude scintillations indicated by S4 index and phase scintillations by. Low latitude regions are prone to ionosphere scintillation. Since India is a low latitude region, ionospheric scintillations must be analysed. Indian NavIC or IRNSS planned and implemented by the Indian Space Research Organization (ISRO). In this paper S4 index is investigated for NavIC L5 (1.17645 GHz) and S1 (2.492028 GHz) signals (1B,1C,1D,1E,1F,1G). For the analysis Guntur station (Lat:16.44N, Lon:80.62E) and Hyderabad station (Lat:17°24’28.10″N, Lon: 78°31′4.22″E) IGS receiver data is considered. The S4 index is calculated using carrier to noise ratio of IRNSS L5 and S band signals. From the results it is observed that S4 index is more for L5 band signals compared to S band signals, as ionospheric scintillations are frequency dependent. Guntur station S4 average value is low for all (L5 and S) band satellite signals compared to Hyderabad station satellite signals. Over Indian region, it shows latitude-dependent scintillations.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78807791","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 : 2022-12-30DOI: 10.35940/ijeat.b3861.1212222
Vijaya Kanaparthi
Natural language processing is a branch of artificial intelligence currently being used to classify unstructured data. While natural language processing is found throughout several fields, these algorithms are currently being excelled in the education and healthcare fields. The healthcare industry has found various uses of natural language processing models. These algorithms are capable of analyzing large amounts of unstructured data from clinical notes, making it easier for healthcare professionals to identify at-risk patients and analyze consumer healthcare perception. In the education field, researchers are utilizing natural language processing models to enhance student academic success, reading comprehension, and to evaluate the fairness of student evaluations. Both fields have been able to find use of natural language model processing models. Some business leaders, however, are fearful of natural language processing. This review seeks to explore the various uses of natural language processing in the healthcare and education fields to determine the benefit and disadvantages these models have on both fields.
{"title":"Examining Natural Language Processing Techniques in the Education and Healthcare Fields","authors":"Vijaya Kanaparthi","doi":"10.35940/ijeat.b3861.1212222","DOIUrl":"https://doi.org/10.35940/ijeat.b3861.1212222","url":null,"abstract":"Natural language processing is a branch of artificial intelligence currently being used to classify unstructured data. While natural language processing is found throughout several fields, these algorithms are currently being excelled in the education and healthcare fields. The healthcare industry has found various uses of natural language processing models. These algorithms are capable of analyzing large amounts of unstructured data from clinical notes, making it easier for healthcare professionals to identify at-risk patients and analyze consumer healthcare perception. In the education field, researchers are utilizing natural language processing models to enhance student academic success, reading comprehension, and to evaluate the fairness of student evaluations. Both fields have been able to find use of natural language model processing models. Some business leaders, however, are fearful of natural language processing. This review seeks to explore the various uses of natural language processing in the healthcare and education fields to determine the benefit and disadvantages these models have on both fields.","PeriodicalId":13981,"journal":{"name":"International Journal of Engineering and Advanced Technology","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74417639","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 : 2022-12-30DOI: 10.35940/ijeat.b3917.1212222
A. C, A. B.
The Performance of an Aerobic Bio-Reactor (ABR) for the behavior of synthetic sago processing wastewater was investigated. The system with 13.3 liters of working volume was accomplished by attached as well as suspended growth process. The experimental analysis was carried out with the influent Chemical Oxygen Demand of 3920 mg/l, 4360 mg/l and 4640 mg/l at Hydraulic Retention Times (HRT) of 11, 14, 17, 21, 28, 42, 84 and 141 hours. During the experiment, pH plays an important role and the Dissolved Oxygen was maintained within the permissible limit continuously. In an ABR, the maximum COD removal efficiency was attained 91.20% with an Organic Loading Rate (OLR) of 1.518 kg COD/m3. To achieve the goal of reusing the wastewater, again the treated effluent was analyzed by the technology of adsorption process using zinc oxide nano powder as a Chemisorbent and the maximum COD removal efficiency of 100% was observed with 0.75 g of dosage content at the pH of 6 at the contact time of 180 minutes.
研究了好氧生物反应器(ABR)处理合成西米加工废水的性能。采用附着生长和悬浮生长两种方法，制备出工作体积为13.3 l的系统。实验分析在水力停留时间(HRT)为11、14、17、21、28、42、84和141 h时，进水化学需氧量分别为3920、4360和4640 mg/l。在实验过程中，pH起着重要的作用，溶解氧一直保持在允许的范围内。在ABR中，COD去除率最高可达91.20%，有机负荷率(OLR)为1.518 kg COD/m3。为达到废水回用的目的，再次采用氧化锌纳米粉作为化学吸附剂的吸附工艺对处理后的出水进行分析，在pH = 6、接触时间为180 min、投加量为0.75 g时，COD去除率最高可达100%。
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