Pub Date : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21103
Van Tuan Pham, Thinh Hoang, Tien Dat Du, VanNguyen Do
Purpose - This paper aims to explore antecedents of ad avoidance with the context in the Vietnam pawnbroking industry. Furthermore, the differences in ad avoidance under personal characteristics will firstly appear in this study. Methodology - A qualitative method from 412 social media users was used to test the proposed model. All data were assessed reliability and validity on SPSS version 26 before conducting into CFA and CB-SEM in AMOS software. Findings - The findings indicate that while ad skepticism and perceptions ad as controversial partially mediates the relationship between ad avoidance and its three determinants (Advertising invasiveness, Perceived Value value and Expectation of Negative), perceived space invasiveness has the most potent effect on pawn ad avoidance. Skeptical customers are more likely to avoid pawnbroking advertisements than those who perceive such ads as controversial. The results also show that ethical judgement moderates both the relationship of perceived controversial ads and ad avoidance and the relationship between ad skepticism and ad avoidance. Implications - Social media platform owners were suggested to reinforce their censoring system and advertising placements. Marketers in this study were convinced to generate advertisements with emotional and informative appeals. Besides, appropriate marketing activities, channels, and ad formats with campaigns should be considered strictly. Originality/value - The mediating role of attitude in the relationship between perception and ad avoidance has been firstly affirmed by qualitative data in this study. Interestingly, researchers explored a new variable - Negative eWOM with a medium impact of ad skepticism. Ethical judgement was demonstrated as a drastically important factor in pawnbroking research.
目的-本文旨在探讨在越南典当行业背景下的广告回避的前因。此外，个人特征下的广告回避差异将首先出现在本研究中。方法-使用来自412名社交媒体用户的定性方法来测试所提出的模型。所有数据在SPSS version 26中进行信度和效度评估，然后在AMOS软件中进行CFA和CB-SEM分析。研究结果-研究结果表明，虽然广告怀疑和认知广告争议在一定程度上调解了广告回避与其三个决定因素(广告侵入性、感知价值价值和负面预期)之间的关系，但感知空间侵入性对pawn广告回避的影响最大。持怀疑态度的顾客比那些认为典当广告有争议的顾客更有可能避开典当广告。结果还表明，道德判断调节了感知争议性广告与广告回避的关系，以及广告怀疑与广告回避的关系。建议社交媒体平台所有者加强审查系统和广告投放。在这项研究中，营销人员被说服制作具有情感和信息吸引力的广告。此外，适当的营销活动、渠道和广告形式应该严格考虑。原创性/价值——本研究首次通过定性数据证实了态度在感知与广告回避关系中的中介作用。有趣的是，研究人员探索了一个新的变量-负edom与广告怀疑的中等影响。在典当业研究中，伦理判断是一个非常重要的因素。
{"title":"Antecedents of Social Media Advertising Avoidance: An Empirical Study in Pawnbroking Industry","authors":"Van Tuan Pham, Thinh Hoang, Tien Dat Du, VanNguyen Do","doi":"10.47059/alinteri/v36i1/ajas21103","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21103","url":null,"abstract":"Purpose - This paper aims to explore antecedents of ad avoidance with the context in the Vietnam pawnbroking industry. Furthermore, the differences in ad avoidance under personal characteristics will firstly appear in this study. Methodology - A qualitative method from 412 social media users was used to test the proposed model. All data were assessed reliability and validity on SPSS version 26 before conducting into CFA and CB-SEM in AMOS software. Findings - The findings indicate that while ad skepticism and perceptions ad as controversial partially mediates the relationship between ad avoidance and its three determinants (Advertising invasiveness, Perceived Value value and Expectation of Negative), perceived space invasiveness has the most potent effect on pawn ad avoidance. Skeptical customers are more likely to avoid pawnbroking advertisements than those who perceive such ads as controversial. The results also show that ethical judgement moderates both the relationship of perceived controversial ads and ad avoidance and the relationship between ad skepticism and ad avoidance. Implications - Social media platform owners were suggested to reinforce their censoring system and advertising placements. Marketers in this study were convinced to generate advertisements with emotional and informative appeals. Besides, appropriate marketing activities, channels, and ad formats with campaigns should be considered strictly. Originality/value - The mediating role of attitude in the relationship between perception and ad avoidance has been firstly affirmed by qualitative data in this study. Interestingly, researchers explored a new variable - Negative eWOM with a medium impact of ad skepticism. Ethical judgement was demonstrated as a drastically important factor in pawnbroking research.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84880266","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21102
M. Mohanambal, Dr. Prarthana Vardhan
Aim: The study aims to extract features from EEG signals and classify emotion using Support Vector Machine (SVM) and Hidden Markov Model (HMM) classifier. Materials and methods: The study was conducted using the Support Vector Machine (SVM) and Hidden Markov Model (HMM) programs to analyze and compare the recognition of emotions classified under EEG signals. The results were computed using the MATLAB algorithm. For each group, ten samples were used to compare the efficiency of SVM and HMM classifiers. Result: The study’s performance exhibits the HMM classifier’s accuracy over the SVM classifier and the emotion detection from EEG signals computed. The mean value of the HMM classifier is 52.2, and the SVM classifier is 22.4. The accuracy rate of 35% with the data features is found in HMM classifier. Conclusion: This study shows a higher accuracy level of 35% for the HMM classifier when compared with the SVM classifier. In the detection of emotions using the EEG signal. This result shows that the HMM classifier has a higher significant value of P=.001 < P=.005 than the SVM classifier.
目的:利用支持向量机(SVM)和隐马尔可夫模型(HMM)分类器对脑电信号进行特征提取和情绪分类。材料与方法:采用支持向量机(SVM)和隐马尔可夫模型(HMM)程序对脑电信号下分类的情绪识别进行分析比较。利用MATLAB算法对结果进行了计算。每组使用10个样本比较SVM和HMM分类器的效率。结果:该研究的性能表明HMM分类器比SVM分类器和从脑电信号中计算的情绪检测更准确。HMM分类器的均值为52.2,SVM分类器的均值为22.4。HMM分类器对数据特征的准确率达到35%。结论:与SVM分类器相比，HMM分类器的准确率达到了35%。在情绪检测中利用脑电图信号。这表明HMM分类器具有更高的显著值P=。001 < p =。005比SVM分类器。
{"title":"Wavelet based Extraction of Features from EEG Signals and Classification of Novel Emotion Recognition Using SVM and HMM Classifier and to Measure its Accuracy","authors":"M. Mohanambal, Dr. Prarthana Vardhan","doi":"10.47059/alinteri/v36i1/ajas21102","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21102","url":null,"abstract":"Aim: The study aims to extract features from EEG signals and classify emotion using Support Vector Machine (SVM) and Hidden Markov Model (HMM) classifier. Materials and methods: The study was conducted using the Support Vector Machine (SVM) and Hidden Markov Model (HMM) programs to analyze and compare the recognition of emotions classified under EEG signals. The results were computed using the MATLAB algorithm. For each group, ten samples were used to compare the efficiency of SVM and HMM classifiers. Result: The study’s performance exhibits the HMM classifier’s accuracy over the SVM classifier and the emotion detection from EEG signals computed. The mean value of the HMM classifier is 52.2, and the SVM classifier is 22.4. The accuracy rate of 35% with the data features is found in HMM classifier. Conclusion: This study shows a higher accuracy level of 35% for the HMM classifier when compared with the SVM classifier. In the detection of emotions using the EEG signal. This result shows that the HMM classifier has a higher significant value of P=.001 < P=.005 than the SVM classifier.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91347473","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21098
K. Reddy, D. Rani
Aim: The aim of this research work is to determine the presence of hyperthyroidism using modern algorithms, and comparing the accuracy rate between deep learning algorithms and vivo monitoring. Materials and methods: Data collection containing ultrasound images from kaggle's website was used in this research. Samples were considered as (N=23) for Deep learning algorithm and (N=23) for vivo monitoring in accordance to total sample size calculated using clinical.com. The accuracy was calculated by using DPLA with a standard data set. Results: Comparison of accuracy rate is done by independent sample test using SPSS software. There is a statistically indifference between Deep learning algorithm and in vivo monitoring. Deep learning algorithm (87.89%) showed better results in comparison to vivo monitoring (83.32%). Conclusion: Deep learning algorithms appear to give better accuracy than in vivo monitoring to predict hyperthyroidism.
{"title":"Comparison and Prediction of Hyperthyroidism Accuracy Rate Using Novel Deep Learning Technology and Vivo Monitoring","authors":"K. Reddy, D. Rani","doi":"10.47059/alinteri/v36i1/ajas21098","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21098","url":null,"abstract":"Aim: The aim of this research work is to determine the presence of hyperthyroidism using modern algorithms, and comparing the accuracy rate between deep learning algorithms and vivo monitoring. Materials and methods: Data collection containing ultrasound images from kaggle's website was used in this research. Samples were considered as (N=23) for Deep learning algorithm and (N=23) for vivo monitoring in accordance to total sample size calculated using clinical.com. The accuracy was calculated by using DPLA with a standard data set. Results: Comparison of accuracy rate is done by independent sample test using SPSS software. There is a statistically indifference between Deep learning algorithm and in vivo monitoring. Deep learning algorithm (87.89%) showed better results in comparison to vivo monitoring (83.32%). Conclusion: Deep learning algorithms appear to give better accuracy than in vivo monitoring to predict hyperthyroidism.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80174738","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21101
S. Mahesh, Dr.G. Ramkumar
Aim: Machine learning algorithm plays a vital role in various biometric applications due to its admirable result in detection, recognition and classification. The main objective of this work is to perform comparative analysis on two different machine learning algorithms to recognize the person from low resolution images with high accuracy. Materials & Methods: AlexNet Convolutional Neural Network (ACNN) and Support Vector Machine (SVM) classifiers are implemented to recognize the face in a low resolution image dataset with 20 samples each. Results: Simulation result shows that ACNN achieves a significant recognition rate with 98% accuracy over SVM (89%). Attained significant accuracy ratio (p=0.002) in SPSS statistical analysis as well. Conclusion: For the considered low resolution images ACNN classifier provides better accuracy than SVM Classifier.
{"title":"Smart Face Detection and Recognition in Low Resolution Images Using Alexnet CNN Compare Accuracy with SVM","authors":"S. Mahesh, Dr.G. Ramkumar","doi":"10.47059/alinteri/v36i1/ajas21101","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21101","url":null,"abstract":"Aim: Machine learning algorithm plays a vital role in various biometric applications due to its admirable result in detection, recognition and classification. The main objective of this work is to perform comparative analysis on two different machine learning algorithms to recognize the person from low resolution images with high accuracy. Materials & Methods: AlexNet Convolutional Neural Network (ACNN) and Support Vector Machine (SVM) classifiers are implemented to recognize the face in a low resolution image dataset with 20 samples each. Results: Simulation result shows that ACNN achieves a significant recognition rate with 98% accuracy over SVM (89%). Attained significant accuracy ratio (p=0.002) in SPSS statistical analysis as well. Conclusion: For the considered low resolution images ACNN classifier provides better accuracy than SVM Classifier.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79194928","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21093
M. Madhu, Dr.Kirupa Ganapathy
Aim: Machine learning techniques are rapidly used in the area of medical research due to its impressive results in diagnosis and prediction of diseases. The objective of this study is to evaluate the performance of SVM classifier in identification of liver disorder by comparing it with Naive Bayes algorithm. Methods and Materials: A total of 31619 samples are collected from three liver disease datasets available in kaggle. These samples are divided into training dataset (n = 22133 [70%]) and test dataset (n = 9486 [30%]). Accuracy, precision, specificity and sensitivity values are calculated to quantify the performance of the SVM algorithm. Results: SVM achieved accuracy, precision, sensitivity and specificity of 73.64%, 97.82%, 97.56% and 69.77% respectively compared to 57.31%, 41.39%, 94.87% and 37.20% by Naive Bayes algorithm. Conclusion: In this study it is found that the RBF SVM algorithm performed better than the Naive Bayes algorithm in liver disorder detection of the datasets considered.
{"title":"Detection of Liver Disorder Using RBF SVM in Comparison with Naïve Bayes to Measure the Accuracy, Precision, Sensitivity and Specificity","authors":"M. Madhu, Dr.Kirupa Ganapathy","doi":"10.47059/alinteri/v36i1/ajas21093","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21093","url":null,"abstract":"Aim: Machine learning techniques are rapidly used in the area of medical research due to its impressive results in diagnosis and prediction of diseases. The objective of this study is to evaluate the performance of SVM classifier in identification of liver disorder by comparing it with Naive Bayes algorithm. Methods and Materials: A total of 31619 samples are collected from three liver disease datasets available in kaggle. These samples are divided into training dataset (n = 22133 [70%]) and test dataset (n = 9486 [30%]). Accuracy, precision, specificity and sensitivity values are calculated to quantify the performance of the SVM algorithm. Results: SVM achieved accuracy, precision, sensitivity and specificity of 73.64%, 97.82%, 97.56% and 69.77% respectively compared to 57.31%, 41.39%, 94.87% and 37.20% by Naive Bayes algorithm. Conclusion: In this study it is found that the RBF SVM algorithm performed better than the Naive Bayes algorithm in liver disorder detection of the datasets considered.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77304040","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21095
Koneti Sairam, A. Sivagami
Aim: This project aims to improve the electrical characteristics in the polymer tandem solar cell by changing polymers with thickness to increase the efficiency. Methods and Materials: The PEDOT: PSS and P3HT Polymer was chosen as a group having 20 samples in each respectively. The electrical characteristics are stimulated by varying the polymer with thickness. Changing the polymer material leads to improved efficiency in the tandem solar cell. Results: The Independent T test was done which reveals that the P3HT (P = 0.553) was found to be statistically significantly compared with PEDOT: PSS polymer material. Conclusion: The analysis we found P3HT appeared to have better efficiency than PEDOT: PSS polymer tandem solar cell from Green energy. While P3HT(p=0.583) having the better significance compared with PEDOT: PSS (p=0.883).
{"title":"Comparison the Electrical Characteristics of PEDOT: PSS Tandem Solar Cell and P3HT Tandem Solar Cell by Varying Thickness","authors":"Koneti Sairam, A. Sivagami","doi":"10.47059/alinteri/v36i1/ajas21095","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21095","url":null,"abstract":"Aim: This project aims to improve the electrical characteristics in the polymer tandem solar cell by changing polymers with thickness to increase the efficiency. Methods and Materials: The PEDOT: PSS and P3HT Polymer was chosen as a group having 20 samples in each respectively. The electrical characteristics are stimulated by varying the polymer with thickness. Changing the polymer material leads to improved efficiency in the tandem solar cell. Results: The Independent T test was done which reveals that the P3HT (P = 0.553) was found to be statistically significantly compared with PEDOT: PSS polymer material. Conclusion: The analysis we found P3HT appeared to have better efficiency than PEDOT: PSS polymer tandem solar cell from Green energy. While P3HT(p=0.583) having the better significance compared with PEDOT: PSS (p=0.883).","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76963174","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}
This scientific article focuses on the analysis of a certain level of contribution of agricultural production to the positive changes in the national economy of the republic in 2018-2019. There is a general approach to the role of the industry in strengthening the food security of products, as well as in the supply of raw materials for light industry and solving the problem of unemployment in the country.
{"title":"The Role and Importance of Agriculture in the Development of the National Economy of the Republic of Uzbekistan","authors":"Soxadaliyev Abdurashid Mamadaliyevich, Mahmudov Baxriddin Jurayevich","doi":"10.47059/alinteri/v36i1/ajas21106","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21106","url":null,"abstract":"This scientific article focuses on the analysis of a certain level of contribution of agricultural production to the positive changes in the national economy of the republic in 2018-2019. There is a general approach to the role of the industry in strengthening the food security of products, as well as in the supply of raw materials for light industry and solving the problem of unemployment in the country.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80878410","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21104
Bui Thi Thom, D. Huy, T. Phùng
Thanapongtharm (2016) stated that in Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Also detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems. Pig farming is very important in Vietnam, esp. In Thai Nguyen city and Northern provinces, pork products are suitable for people's taste. At present, most pig breeds are selected and raised in accordance with local conditions, especially wild boar and hybrids are very popular with people, the demand for products is increasing day by day. Lander et al (2020) pointed Pigs have played a central role in the subsistence and culture of China for millennia. The close relationship between pigs and people began when humans gradually domesticated wild pigs over 8,000 years ago. While pigs initially foraged around settlements, population growth led people to pen their pigs, which made them household trash processors and fertilizer producers. Study results show for instance, For commercial cross-bred wild boar farming, a diet with a protein level of 16-14% and a metabolic energy level of 3000-2900 kcal/kg of feed in the diet for growth and fattening most appropriate, which has both the growth ability of hybrid wild pigs and economic efficiency under semi-wild breeding conditions in Thai Nguyen ecological environment. Last but not least authors present food processing of wild pigs into delicious stir-dried pork.
{"title":"Improving Yield and Quality of Wild Pork and Pigs in Thai Nguyen, Vietnam - and Solutions to Enhance Competitiveness to Thailand and China","authors":"Bui Thi Thom, D. Huy, T. Phùng","doi":"10.47059/alinteri/v36i1/ajas21104","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21104","url":null,"abstract":"Thanapongtharm (2016) stated that in Thailand, pig production intensified significantly during the last decade, with many economic, epidemiological and environmental implications. Also detailed geographical analysis of the different production systems will be used to spatially-inform planning decisions for pig farming accounting for the specific health, environment and economical implications of the different pig production systems. Pig farming is very important in Vietnam, esp. In Thai Nguyen city and Northern provinces, pork products are suitable for people's taste. At present, most pig breeds are selected and raised in accordance with local conditions, especially wild boar and hybrids are very popular with people, the demand for products is increasing day by day. Lander et al (2020) pointed Pigs have played a central role in the subsistence and culture of China for millennia. The close relationship between pigs and people began when humans gradually domesticated wild pigs over 8,000 years ago. While pigs initially foraged around settlements, population growth led people to pen their pigs, which made them household trash processors and fertilizer producers. Study results show for instance, For commercial cross-bred wild boar farming, a diet with a protein level of 16-14% and a metabolic energy level of 3000-2900 kcal/kg of feed in the diet for growth and fattening most appropriate, which has both the growth ability of hybrid wild pigs and economic efficiency under semi-wild breeding conditions in Thai Nguyen ecological environment. Last but not least authors present food processing of wild pigs into delicious stir-dried pork.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85937990","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21090
M. Reddy, P. Dass
Aim: The aim of this work is to construct an innovative pMos logic based comparator and analyze the power consumption and compare with the nMos logic based comparator. Material and methods: The comparator is designed by using the Tanner tool version 16.01 for simulation and verification. By varying the length of a transistors in a circuit the power values were obtained. This experiment is performed for 20 different values of length. Results: The power consumption of a pMos logic based comparator was minimum (2.2656 ± 0.37933), followed by the nMos logic based comparator (7.7494 ± 0.41603), the less power consumption seen in pMos logic based comparator significance (.955). Conclusion: The consumption of power by the constructed pMos logic based comparator appears to have less power consumption than the nMos logic based comparator.
{"title":"Construction of pMos Logic based Low Power High Speed Comparator Compare with nMos Logic","authors":"M. Reddy, P. Dass","doi":"10.47059/alinteri/v36i1/ajas21090","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21090","url":null,"abstract":"Aim: The aim of this work is to construct an innovative pMos logic based comparator and analyze the power consumption and compare with the nMos logic based comparator. Material and methods: The comparator is designed by using the Tanner tool version 16.01 for simulation and verification. By varying the length of a transistors in a circuit the power values were obtained. This experiment is performed for 20 different values of length. Results: The power consumption of a pMos logic based comparator was minimum (2.2656 ± 0.37933), followed by the nMos logic based comparator (7.7494 ± 0.41603), the less power consumption seen in pMos logic based comparator significance (.955). Conclusion: The consumption of power by the constructed pMos logic based comparator appears to have less power consumption than the nMos logic based comparator.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78073344","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 : 2021-06-29DOI: 10.47059/alinteri/v36i1/ajas21107
Raafat A. Abu - Almaaly, A. T. Al-Musawi
The study was conducted to show the effect of adding different percentages of Sea Salt solution and aqueous extracts of green pepper and thyme individually or in combination, it reduces the Acrylamide content in the potato chips product when exposed to high temperatures during processing, potato slices were treated by soaking before frying with C1 (0.1, 0.2, 0.3) % Sea Salt solution and the aqueous extract of Green Pepper C2 and thyme C3 in proportions (1, 2,3)% and a mixture of the three additives C4, the treatment C was left to be the control, High performance liquid chromatography technology (HPLC) was used to estimate the concentration of acrylamide in the treatments, sensory evaluation to the parameters of taste, color, odor, texture and general acceptance was conducted, the results showed a clear decrease in the acrylamide concentration in the potato chips treatments by increasing the concentration of the additives, C4 treatment with the synergistic action of Sea Salt, thyme and Green Pepper outperformed all other treatments in decreasing the acrylamide concentration, The results were descending C4 > C2- 3% C3- 3% > C1- 3% amounting to 0.013, 0.024, 0.034 and 0.084, respectively, compared to the control treatment 0.522, the results of sensory evaluation recorded the highest degree of receptivity to the treatments by increasing the percentage of additives, and the results were descending C4 > C3> C2 compared to the control treatment.
{"title":"Reducing the Acrylamide Concentration in the Potato Chips Product by Using Sea Salt, Green Pepper and Thyme","authors":"Raafat A. Abu - Almaaly, A. T. Al-Musawi","doi":"10.47059/alinteri/v36i1/ajas21107","DOIUrl":"https://doi.org/10.47059/alinteri/v36i1/ajas21107","url":null,"abstract":"The study was conducted to show the effect of adding different percentages of Sea Salt solution and aqueous extracts of green pepper and thyme individually or in combination, it reduces the Acrylamide content in the potato chips product when exposed to high temperatures during processing, potato slices were treated by soaking before frying with C1 (0.1, 0.2, 0.3) % Sea Salt solution and the aqueous extract of Green Pepper C2 and thyme C3 in proportions (1, 2,3)% and a mixture of the three additives C4, the treatment C was left to be the control, High performance liquid chromatography technology (HPLC) was used to estimate the concentration of acrylamide in the treatments, sensory evaluation to the parameters of taste, color, odor, texture and general acceptance was conducted, the results showed a clear decrease in the acrylamide concentration in the potato chips treatments by increasing the concentration of the additives, C4 treatment with the synergistic action of Sea Salt, thyme and Green Pepper outperformed all other treatments in decreasing the acrylamide concentration, The results were descending C4 > C2- 3% C3- 3% > C1- 3% amounting to 0.013, 0.024, 0.034 and 0.084, respectively, compared to the control treatment 0.522, the results of sensory evaluation recorded the highest degree of receptivity to the treatments by increasing the percentage of additives, and the results were descending C4 > C3> C2 compared to the control treatment.","PeriodicalId":42396,"journal":{"name":"Alinteri Journal of Agriculture Sciences","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88087926","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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