Pub Date : 2021-12-12DOI: 10.21475/ajcs.21.15.12.p3384
Aline Priscilla Gomes da Silva, P. C. Spricigo, Fernanda Bueno Campos, Alana Duarte de Oliveira, Thais Pádua Freitas, A. P. Jacomino
Jabuticaba (Plinia cauliflora) is a native Brazilian Atlantic Rainforest fruit tree. Its fruits are purplish berries with a short shelf life, due to fermentative processes that begin shortly after harvest. Recently, commercial jabuticaba exploitation has intensified, justifying the application of postharvest technologies. In this context, this study aimed to evaluate the chemical characteristics and nutraceutical compounds of “ponhema” jabuticabas stored at room and cold temperatures. Chemical analyzes (soluble solids (SS), titratable acidity (TA), pH, soluble sugars, soluble pectins and pectinamethylesterase (PME) activity), and nutraceutical compounds (total anthocyanins (TA), yellow flavonoids (YF), total phenolic compounds (TFC)) were performed. A completely randomized experimental design was applied. Analyzes were performed every 2 days, at days 0, 2, 4 for the room temperature (25° C) assay and at days 0, 2, 4 and 6 for the cold temperature (13° C) experiment. Fruits stored under cold temperature presented lower acetaldehyde and ethanol contents, as well as high soluble sugar, total anthocyanin, and total phenolic compound levels. Fruits stored at room temperature displayed marked wilting and fermentation on the fifth day of storage, preventing their consumption after this period. Fruits presented a shelf-life gain of up to two days when stored at cold temperature, displaying better characteristic maintenance, such as soluble solids, titratable acidity, pH and soluble sugars, which were verified by the acetaldehyde and ethanol tests. Total anthocyanin and phenolic compound levels were higher in fruits stored at cold temperature
{"title":"Do chemical and nutritional compounds change during the storage of Jabuticaba (Plinia cauliflora)?","authors":"Aline Priscilla Gomes da Silva, P. C. Spricigo, Fernanda Bueno Campos, Alana Duarte de Oliveira, Thais Pádua Freitas, A. P. Jacomino","doi":"10.21475/ajcs.21.15.12.p3384","DOIUrl":"https://doi.org/10.21475/ajcs.21.15.12.p3384","url":null,"abstract":"Jabuticaba (Plinia cauliflora) is a native Brazilian Atlantic Rainforest fruit tree. Its fruits are purplish berries with a short shelf life, due to fermentative processes that begin shortly after harvest. Recently, commercial jabuticaba exploitation has intensified, justifying the application of postharvest technologies. In this context, this study aimed to evaluate the chemical characteristics and nutraceutical compounds of “ponhema” jabuticabas stored at room and cold temperatures. Chemical analyzes (soluble solids (SS), titratable acidity (TA), pH, soluble sugars, soluble pectins and pectinamethylesterase (PME) activity), and nutraceutical compounds (total anthocyanins (TA), yellow flavonoids (YF), total phenolic compounds (TFC)) were performed. A completely randomized experimental design was applied. Analyzes were performed every 2 days, at days 0, 2, 4 for the room temperature (25° C) assay and at days 0, 2, 4 and 6 for the cold temperature (13° C) experiment. Fruits stored under cold temperature presented lower acetaldehyde and ethanol contents, as well as high soluble sugar, total anthocyanin, and total phenolic compound levels. Fruits stored at room temperature displayed marked wilting and fermentation on the fifth day of storage, preventing their consumption after this period. Fruits presented a shelf-life gain of up to two days when stored at cold temperature, displaying better characteristic maintenance, such as soluble solids, titratable acidity, pH and soluble sugars, which were verified by the acetaldehyde and ethanol tests. Total anthocyanin and phenolic compound levels were higher in fruits stored at cold temperature","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84687272","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 : 2021-12-12DOI: 10.21475/ajcs.21.15.12.p3339
Fenelon Lourenço DE Sousa Santos, A. Nascente, M. C. Lacerda, F. Calil, F. C. Araújo
Intercropping imidazolinone resistance crops, resistant to herbicides imazapyr + imazapic, with forage species may be a viable alternative to recover degraded pasture areas. This practice requires herbicides to slow down development of the forage and avoid reduced rice yield. However, as it is a relatively new technology, the proper management of this herbicide to control forage is not known. The objective of this study was to determine the susceptibility of forages Urochloa ruziziensis, U. brizantha cv. Paiaguás, and U. brizantha cv. Marandu, submitted to the pre-emergence application of the herbicides [imazapyr + imazapic]. The experimental design was completely randomized in a 3×5+3 factorial scheme with five replications. Treatments consisted of the combination of the three species (Urochloa ruziziensis, U. brizantha cv. Paiaguás, and U. brizantha cv. Marandu) and five intervals between herbicide application in the soil and forage sowing (0; 5; 10; 15; and 20 days after its application), in addition to three control treatments, without herbicide application. This study found that application of herbicide on the day of forage sowing for intercropping with imidazolinone resistance crops is not feasible. Increasing the time interval between herbicide application and forage sowing provides increased development of U. brizantha cvs. Marandu and Paiaguás. The species U. ruziziensis is more susceptible to pre-emergence application imazapyr + imazapic. According to the results, U. brizantha cvs. Marandu and Paiaguás are more suitable to be managed by imidazolinone herbicides to recover degraded pasture areas
{"title":"Susceptibility of Urochloa species subjected to pre-emergence application of [imazapyr + imazapic] herbicide","authors":"Fenelon Lourenço DE Sousa Santos, A. Nascente, M. C. Lacerda, F. Calil, F. C. Araújo","doi":"10.21475/ajcs.21.15.12.p3339","DOIUrl":"https://doi.org/10.21475/ajcs.21.15.12.p3339","url":null,"abstract":"Intercropping imidazolinone resistance crops, resistant to herbicides imazapyr + imazapic, with forage species may be a viable alternative to recover degraded pasture areas. This practice requires herbicides to slow down development of the forage and avoid reduced rice yield. However, as it is a relatively new technology, the proper management of this herbicide to control forage is not known. The objective of this study was to determine the susceptibility of forages Urochloa ruziziensis, U. brizantha cv. Paiaguás, and U. brizantha cv. Marandu, submitted to the pre-emergence application of the herbicides [imazapyr + imazapic]. The experimental design was completely randomized in a 3×5+3 factorial scheme with five replications. Treatments consisted of the combination of the three species (Urochloa ruziziensis, U. brizantha cv. Paiaguás, and U. brizantha cv. Marandu) and five intervals between herbicide application in the soil and forage sowing (0; 5; 10; 15; and 20 days after its application), in addition to three control treatments, without herbicide application. This study found that application of herbicide on the day of forage sowing for intercropping with imidazolinone resistance crops is not feasible. Increasing the time interval between herbicide application and forage sowing provides increased development of U. brizantha cvs. Marandu and Paiaguás. The species U. ruziziensis is more susceptible to pre-emergence application imazapyr + imazapic. According to the results, U. brizantha cvs. Marandu and Paiaguás are more suitable to be managed by imidazolinone herbicides to recover degraded pasture areas","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82245867","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 : 2021-12-12DOI: 10.21475/ajcs.21.15.12.p3313
Gustavo Silva Oliveira, R. T. Júnior, Ailson Augusto Loper, Pedro José Steiner Neto, R. Alves
The aim of the study is to analyze the production of round wood from planted forests and the price of pulp and paper and other forestry purposes in southern Brazil, from 2000 to 2019. In this study, we worked with historical series from secondary data collected from the Brazilian Institute of Geography and Statistics IBGE, referring to the produced and traded quantity in forestry (m³), forestry production value (one thousand dollars) and price ($/m³), obtained through the ratio between the production value and the respective produced quantities in each year. The silviculture production value (PV) is a derived variable calculated by the weighted average of quantity and average current price paid to the producer (m³), according to the harvest and commercialization periods of each product. The price evolution (P) was separated according to purpose and obtained through the quotient between the production value and respective quantities produced in each year. The trend models were estimated, in which annual growth rates of the real price and produced quantity were calculated for the two roundwood purposes in the evaluated period. Then, we sought to fit the results according to the possibilities of shift of the supply and demand curves. The results indicate that pulp and paper presented positive rates of produced quantity and price, of 5.8775 and 1.3704, respectively. The nomenclature for other purposes had a positive rate for the produced quantity (4.1929) and a negative rate for price (-0.3203). Thus, logwood for pulp and paper showed a dominant shift in the demand curve to the right, showing a rising market, while for other purposes, there was a dominant shift in supply to the right, corroborating the concept of positive variation in quantity and a negative variation in price. Given these results, it is important to highlight that the study refers to one federative unit in Brazil, which signals the recommendation that other similar studies be carried out in other states to better understand the impact of production and price of these purposes on the Brazilian market
{"title":"Production of round wood from planted forests and price of pulp and paper and other forestry purposes in southern Brazil","authors":"Gustavo Silva Oliveira, R. T. Júnior, Ailson Augusto Loper, Pedro José Steiner Neto, R. Alves","doi":"10.21475/ajcs.21.15.12.p3313","DOIUrl":"https://doi.org/10.21475/ajcs.21.15.12.p3313","url":null,"abstract":"The aim of the study is to analyze the production of round wood from planted forests and the price of pulp and paper and other forestry purposes in southern Brazil, from 2000 to 2019. In this study, we worked with historical series from secondary data collected from the Brazilian Institute of Geography and Statistics IBGE, referring to the produced and traded quantity in forestry (m³), forestry production value (one thousand dollars) and price ($/m³), obtained through the ratio between the production value and the respective produced quantities in each year. The silviculture production value (PV) is a derived variable calculated by the weighted average of quantity and average current price paid to the producer (m³), according to the harvest and commercialization periods of each product. The price evolution (P) was separated according to purpose and obtained through the quotient between the production value and respective quantities produced in each year. The trend models were estimated, in which annual growth rates of the real price and produced quantity were calculated for the two roundwood purposes in the evaluated period. Then, we sought to fit the results according to the possibilities of shift of the supply and demand curves. The results indicate that pulp and paper presented positive rates of produced quantity and price, of 5.8775 and 1.3704, respectively. The nomenclature for other purposes had a positive rate for the produced quantity (4.1929) and a negative rate for price (-0.3203). Thus, logwood for pulp and paper showed a dominant shift in the demand curve to the right, showing a rising market, while for other purposes, there was a dominant shift in supply to the right, corroborating the concept of positive variation in quantity and a negative variation in price. Given these results, it is important to highlight that the study refers to one federative unit in Brazil, which signals the recommendation that other similar studies be carried out in other states to better understand the impact of production and price of these purposes on the Brazilian market","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77189613","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 : 2021-12-10DOI: 10.36548/jaicn.2021.4.006
P. Darney
Automating image-based automobile insurance claims processing is a significant opportunity. In this research work, car damage categorization that is aided by the hybrid convolutional neural network approach is addressed and hence the deep learning-based strategies are applied. Insurance firms may leverage this paper's design and implementation of an automobile damage classification/detection pipeline to streamline car insurance claim policy. Using deep convolutional networks to detect car damage is now possible because of recent improvements in the artificial intelligence sector, mainly due to less computation time and higher accuracy with a hybrid transformation deep learning algorithm. In this paper, multiclass classification proposed to categorize the car damage parts such as broken headlight/taillight, glass fragments, damaged bonnet etc. are compiled into the proposed dataset. This model has been pre-trained on a wide-ranging and benchmark dataset due to the dataset's limited size to minimize overfitting and to understand more common properties of the dataset. To increase the overall proposed model’s performance, the CNN feature extraction model is trained with Resnet architecture with the coco car damage detection datasets and reaches a higher accuracy of 90.82%, which is much better than the previous findings on the comparable test sets.
{"title":"Automatic Car Damage detection by Hybrid Deep Learning Multi Label Classification","authors":"P. Darney","doi":"10.36548/jaicn.2021.4.006","DOIUrl":"https://doi.org/10.36548/jaicn.2021.4.006","url":null,"abstract":"Automating image-based automobile insurance claims processing is a significant opportunity. In this research work, car damage categorization that is aided by the hybrid convolutional neural network approach is addressed and hence the deep learning-based strategies are applied. Insurance firms may leverage this paper's design and implementation of an automobile damage classification/detection pipeline to streamline car insurance claim policy. Using deep convolutional networks to detect car damage is now possible because of recent improvements in the artificial intelligence sector, mainly due to less computation time and higher accuracy with a hybrid transformation deep learning algorithm. In this paper, multiclass classification proposed to categorize the car damage parts such as broken headlight/taillight, glass fragments, damaged bonnet etc. are compiled into the proposed dataset. This model has been pre-trained on a wide-ranging and benchmark dataset due to the dataset's limited size to minimize overfitting and to understand more common properties of the dataset. To increase the overall proposed model’s performance, the CNN feature extraction model is trained with Resnet architecture with the coco car damage detection datasets and reaches a higher accuracy of 90.82%, which is much better than the previous findings on the comparable test sets.","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85635595","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 : 2021-12-08DOI: 10.36548/jaicn.2021.4.005
B. Vivekanandam, Balaganesh
The navigation systems available in the present scenario takes into account the path distance for their estimations. In some advanced navigation systems, the road traffic analysis is also considered in the algorithm for their predictions. The proposed work estimates a navigation path with respect to the present pollution level on the roadways. The work suggests an alternate path to avoid additional vehicles to enter the same road which is already impacted by air pollution. A Q-learning (Quality learning) prediction algorithm is trained in the proposed work with a self-made dataset for the estimations. The experimental work presented in the paper explores the accuracy and computational speed of the developed algorithm in comparison to the traditional algorithms.
{"title":"Vehicle Navigation System based on Pollution Metric Analysis with Q-Learning Algorithm","authors":"B. Vivekanandam, Balaganesh","doi":"10.36548/jaicn.2021.4.005","DOIUrl":"https://doi.org/10.36548/jaicn.2021.4.005","url":null,"abstract":"The navigation systems available in the present scenario takes into account the path distance for their estimations. In some advanced navigation systems, the road traffic analysis is also considered in the algorithm for their predictions. The proposed work estimates a navigation path with respect to the present pollution level on the roadways. The work suggests an alternate path to avoid additional vehicles to enter the same road which is already impacted by air pollution. A Q-learning (Quality learning) prediction algorithm is trained in the proposed work with a self-made dataset for the estimations. The experimental work presented in the paper explores the accuracy and computational speed of the developed algorithm in comparison to the traditional algorithms.","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91387785","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}
Engineering has a wide range of applications where more detailed and reliable data are needed, one of which is biomedicine. One of the aims of meshing is to use the Finite Element Approach to solve the problem. By analysing and segmenting raw medical imaging data, meshing aids in a better and more precise understanding of the organs and structures of human body. The main goal of this paper is to collect and review the various available methods in meshing. Also, a comparison study of different meshing techniques that are available in biomedicine is performed.
{"title":"A Review on Meshing Techniques in Biomedicine","authors":"T. V. Smitha, Madhura. S, K. B. Ram, M. M.","doi":"10.36548/jei.2021.4.001","DOIUrl":"https://doi.org/10.36548/jei.2021.4.001","url":null,"abstract":"Engineering has a wide range of applications where more detailed and reliable data are needed, one of which is biomedicine. One of the aims of meshing is to use the Finite Element Approach to solve the problem. By analysing and segmenting raw medical imaging data, meshing aids in a better and more precise understanding of the organs and structures of human body. The main goal of this paper is to collect and review the various available methods in meshing. Also, a comparison study of different meshing techniques that are available in biomedicine is performed.","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91185517","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 : 2021-12-02DOI: 10.36548/jaicn.2021.4.004
Judy Simon
Computer vision research and its applications in the fashion industry have grown popular due to the rapid growth of information technology. Fashion detection is increasingly popular because most fashion goods need detection before they could be worn. Early detection of the human body component of the input picture is necessary to determine where the garment area is and then synthesize it. For this reason, detection is the starting point for most of the in-depth research. The cloth detection of landmarks is retrieved through many feature items that emphasis on fashionate things. The feature extraction can be done for better accuracy, pose and scale transmission. These convolution filters extract the features through many epochs and max-pooling layers in the neural networks. The optimized classification has been done using SVM in this study, for attaining overall high efficiency. This proposed CNN approach fashionate things prediction is combined with SVM for better classification. Furthermore, the classification error is minimized through the evaluation procedure for obtaining better accuracy. Finally, this research work has attained good accuracy and other performance metrics than the different traditional approaches. The benchmark datasets, current methodologies, and performance comparisons are all reorganized for each piece.
{"title":"An Efficient Machine Learning based Model for Classification of Wearable Clothing","authors":"Judy Simon","doi":"10.36548/jaicn.2021.4.004","DOIUrl":"https://doi.org/10.36548/jaicn.2021.4.004","url":null,"abstract":"Computer vision research and its applications in the fashion industry have grown popular due to the rapid growth of information technology. Fashion detection is increasingly popular because most fashion goods need detection before they could be worn. Early detection of the human body component of the input picture is necessary to determine where the garment area is and then synthesize it. For this reason, detection is the starting point for most of the in-depth research. The cloth detection of landmarks is retrieved through many feature items that emphasis on fashionate things. The feature extraction can be done for better accuracy, pose and scale transmission. These convolution filters extract the features through many epochs and max-pooling layers in the neural networks. The optimized classification has been done using SVM in this study, for attaining overall high efficiency. This proposed CNN approach fashionate things prediction is combined with SVM for better classification. Furthermore, the classification error is minimized through the evaluation procedure for obtaining better accuracy. Finally, this research work has attained good accuracy and other performance metrics than the different traditional approaches. The benchmark datasets, current methodologies, and performance comparisons are all reorganized for each piece.","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81949137","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 : 2021-11-26DOI: 10.36548/jaicn.2021.4.003
S. Ayyasamy
Recently, the development and integration of various sensor control with smart intelligent unit is used in medical field through IoT. However, there is still a lot of space for growth in the medical and health industry's use of new technology. The traditional nurse care unit is managed through medical staffs, and the expanding medical demands creates the hospital’s patients records to be updated inefficiently. Since this is now an urgent need, developing a realistic, smart medical nursing care unit at low cost with a system capable of facilitating the effective and convenient administration of medical staff has taken a new significance. The proposed framework, conducted in the analysis to monitor medical records and activities of the emergency care unit patients, functions as a nurse and gives patients the nurse care satisfaction. The patients' actual location may be obtained for the first time by cloud computing based smart system. The precise location of the patient is critical to rescue the patient in emergency situation. This research work illustrates that the intelligent nurse care unit is the main phase called Smart Medical Nursing Care (SMNC). It contains several sensor units and by the combination of many sensors in the sensor module, it takes very less reaction time to connect or communicate both sides i.e., between patients and medical staffs.
{"title":"Smart Medical Nursing Care Unit based on Internet of Things for Emergency Healthcare","authors":"S. Ayyasamy","doi":"10.36548/jaicn.2021.4.003","DOIUrl":"https://doi.org/10.36548/jaicn.2021.4.003","url":null,"abstract":"Recently, the development and integration of various sensor control with smart intelligent unit is used in medical field through IoT. However, there is still a lot of space for growth in the medical and health industry's use of new technology. The traditional nurse care unit is managed through medical staffs, and the expanding medical demands creates the hospital’s patients records to be updated inefficiently. Since this is now an urgent need, developing a realistic, smart medical nursing care unit at low cost with a system capable of facilitating the effective and convenient administration of medical staff has taken a new significance. The proposed framework, conducted in the analysis to monitor medical records and activities of the emergency care unit patients, functions as a nurse and gives patients the nurse care satisfaction. The patients' actual location may be obtained for the first time by cloud computing based smart system. The precise location of the patient is critical to rescue the patient in emergency situation. This research work illustrates that the intelligent nurse care unit is the main phase called Smart Medical Nursing Care (SMNC). It contains several sensor units and by the combination of many sensors in the sensor module, it takes very less reaction time to connect or communicate both sides i.e., between patients and medical staffs.","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84669425","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 : 2021-11-26DOI: 10.36548/jaicn.2021.4.002
Seyed Omid Mohammadi, A. Kalhor
The rapid progress of computer vision, machine learning, and artificial intelligence combined with the current growing urge for online shopping systems opened an excellent opportunity for the fashion industry. As a result, many studies worldwide are dedicated to modern fashion-related applications such as virtual try-on and fashion synthesis. However, the accelerated evolution speed of the field makes it hard to track these many research branches in a structured framework. This paper presents an overview of the matter, categorizing 110 relevant articles into multiple sub-categories and varieties of these tasks. An easy-to-use yet informative tabular format is used for this purpose. Such hierarchical application-based multi-label classification of studies increases the visibility of current research, promotes the field, provides research directions, and facilitates access to related studies.
{"title":"Smart Fashion: A Review of AI Applications in Virtual Try-On & Fashion Synthesis","authors":"Seyed Omid Mohammadi, A. Kalhor","doi":"10.36548/jaicn.2021.4.002","DOIUrl":"https://doi.org/10.36548/jaicn.2021.4.002","url":null,"abstract":"The rapid progress of computer vision, machine learning, and artificial intelligence combined with the current growing urge for online shopping systems opened an excellent opportunity for the fashion industry. As a result, many studies worldwide are dedicated to modern fashion-related applications such as virtual try-on and fashion synthesis. However, the accelerated evolution speed of the field makes it hard to track these many research branches in a structured framework. This paper presents an overview of the matter, categorizing 110 relevant articles into multiple sub-categories and varieties of these tasks. An easy-to-use yet informative tabular format is used for this purpose. Such hierarchical application-based multi-label classification of studies increases the visibility of current research, promotes the field, provides research directions, and facilitates access to related studies.","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86142895","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 : 2021-11-22DOI: 10.36548/jaicn.2021.4.001
S. Shakya
A building automation system is a centralized intelligent system, which controls the operation of energy, security, water, and safety by the help of hardware and software modules. The general software modules employed for automation process have an algorithm with pre-determined decisions. However, such pre-determined decision algorithms won’t work in a proper manner at all situations like a human brain. Therefore a human biological inspired algorithms are developed in recent days and termed as neural network algorithms. The Probabilistic Neural Network (PNN) is a kind of artificial neural network algorithm which has the ability to take decisions same as like of human brains in an efficient way. Hence a building automation system is proposed in the work based on PNN for verifying the effectiveness of neural network algorithms over the traditional pre-determined decision making algorithms. The experimental work is further extended to verify the performances of the basic neural network algorithm called Convolution Neural Network (CNN).
{"title":"Probabilistic Neural Network based Managing Algorithm for Building Automation System","authors":"S. Shakya","doi":"10.36548/jaicn.2021.4.001","DOIUrl":"https://doi.org/10.36548/jaicn.2021.4.001","url":null,"abstract":"A building automation system is a centralized intelligent system, which controls the operation of energy, security, water, and safety by the help of hardware and software modules. The general software modules employed for automation process have an algorithm with pre-determined decisions. However, such pre-determined decision algorithms won’t work in a proper manner at all situations like a human brain. Therefore a human biological inspired algorithms are developed in recent days and termed as neural network algorithms. The Probabilistic Neural Network (PNN) is a kind of artificial neural network algorithm which has the ability to take decisions same as like of human brains in an efficient way. Hence a building automation system is proposed in the work based on PNN for verifying the effectiveness of neural network algorithms over the traditional pre-determined decision making algorithms. The experimental work is further extended to verify the performances of the basic neural network algorithm called Convolution Neural Network (CNN).","PeriodicalId":10994,"journal":{"name":"December 2021","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91420435","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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