Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings最新文献
Pub Date : 2022-09-01DOI: 10.21475/ajcs.22.16.09.p3628
Ana Luiza Oliveira Vilela, S. Rosa, S. Coelho, C. Pereira, Ana Cristina de Souza, Fernando Augusto Sales Ribeiro
Coffee seeds rapidly lose viability during storage, which hinders the development of vigorous seedlings for crop establishment. There are reports that seed endosperm is more sensitive to deterioration than embryos, which can be excised and cultivated in vitro. However, a substantial number of plants grown in vitro do not survive during transfer to a greenhouse or field environment. The objective of this study was to evaluate the acclimatization of coffee seedlings of cultivar Catuaí Amarelo IAC 62, developed from zygotic embryos obtained from aged seeds in different substrates and environments, for the production of well-developed seedlings suitable for planting. For this purpose, seedlings were obtained from the in vitro cultivation of embryos obtained from seeds of two quality levels: freshly harvested seeds and artificially aged seeds. Zygotic embryos were extracted from the seeds and cultivated in MS medium. At 60 days, the percentages of normal and abnormal seedlings and dead seeds were evaluated. The good-quality seedlings grown in vitro for 60 days were transplanted into two different substrates (Tropstrato and coconut fiber) and acclimatized in two environments (growth room and greenhouse with a misting system). The plants were evaluated for height, stem diameter, number of leaves, chlorophyll content, and growth rate. The greenhouse environment was better for seedling growth, possibly due to its higher sunlight and temperature. The best substrate was coconut fiber, as it ensured better development of plants from freshly harvested seeds and those from aged seeds. It is possible to develop healthy seedlings from seeds with low viability
{"title":"Acclimatization of coffee seedlings obtained from zygotic embryos of aged seeds","authors":"Ana Luiza Oliveira Vilela, S. Rosa, S. Coelho, C. Pereira, Ana Cristina de Souza, Fernando Augusto Sales Ribeiro","doi":"10.21475/ajcs.22.16.09.p3628","DOIUrl":"https://doi.org/10.21475/ajcs.22.16.09.p3628","url":null,"abstract":"Coffee seeds rapidly lose viability during storage, which hinders the development of vigorous seedlings for crop establishment. There are reports that seed endosperm is more sensitive to deterioration than embryos, which can be excised and cultivated in vitro. However, a substantial number of plants grown in vitro do not survive during transfer to a greenhouse or field environment. The objective of this study was to evaluate the acclimatization of coffee seedlings of cultivar Catuaí Amarelo IAC 62, developed from zygotic embryos obtained from aged seeds in different substrates and environments, for the production of well-developed seedlings suitable for planting. For this purpose, seedlings were obtained from the in vitro cultivation of embryos obtained from seeds of two quality levels: freshly harvested seeds and artificially aged seeds. Zygotic embryos were extracted from the seeds and cultivated in MS medium. At 60 days, the percentages of normal and abnormal seedlings and dead seeds were evaluated. The good-quality seedlings grown in vitro for 60 days were transplanted into two different substrates (Tropstrato and coconut fiber) and acclimatized in two environments (growth room and greenhouse with a misting system). The plants were evaluated for height, stem diameter, number of leaves, chlorophyll content, and growth rate. The greenhouse environment was better for seedling growth, possibly due to its higher sunlight and temperature. The best substrate was coconut fiber, as it ensured better development of plants from freshly harvested seeds and those from aged seeds. It is possible to develop healthy seedlings from seeds with low viability","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84285616","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 : 2022-08-25DOI: 10.36548/jaicn.2022.3.003
Rahul Singhal, S. Srivatsan, Priyabrata Panda
The ability of music to spread joy and excitement across lives, makes it widely acknowledged as the human race's universal language. The phrase "music genre" is frequently used to group several musical styles together as following a shared custom or set of guidelines. According to their unique preferences, people now make playlists based on particular musical genres. Due to the determination and extraction of appropriate audio elements, music genre identification is regarded as a challenging task. Music information retrieval, which extracts meaningful information from music, is one of several real - world applications of machine learning. The objective of this paper is to efficiently categorise songs into various genres based on their attributes using various machine learning approaches. To enhance the outcomes, appropriate feature engineering and data pre-processing techniques have been performed. Finally, using suitable performance assessment measures, the output from each model has been compared. Compared to other machine learning algorithms, Random Forest along with efficient feature selection and hyperparameter tuning has produced better results in classifying music genres.
{"title":"Classification of Music Genres using Feature Selection and Hyperparameter Tuning","authors":"Rahul Singhal, S. Srivatsan, Priyabrata Panda","doi":"10.36548/jaicn.2022.3.003","DOIUrl":"https://doi.org/10.36548/jaicn.2022.3.003","url":null,"abstract":"The ability of music to spread joy and excitement across lives, makes it widely acknowledged as the human race's universal language. The phrase \"music genre\" is frequently used to group several musical styles together as following a shared custom or set of guidelines. According to their unique preferences, people now make playlists based on particular musical genres. Due to the determination and extraction of appropriate audio elements, music genre identification is regarded as a challenging task. Music information retrieval, which extracts meaningful information from music, is one of several real - world applications of machine learning. The objective of this paper is to efficiently categorise songs into various genres based on their attributes using various machine learning approaches. To enhance the outcomes, appropriate feature engineering and data pre-processing techniques have been performed. Finally, using suitable performance assessment measures, the output from each model has been compared. Compared to other machine learning algorithms, Random Forest along with efficient feature selection and hyperparameter tuning has produced better results in classifying music genres.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85036470","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 : 2022-08-23DOI: 10.36548/jitdw.2022.3.004
M. Dolinsky
The proposed study discusses about the real-time experience of blended teaching for the students of the Faculty of Mathematics and Programming Technologies in the subject "Computer Architecture" based on the use of distance learning instrumental system DL.GSU.BY and special software complexes developed at the F. Skorina State University under the guidance of author. Special software packages include: HLCCAD - software system for designing, modeling and debugging the functional architectures of digital devices; Winter, a software system for developing and debugging programs in assembler and C for various microcontrollers; С-MPDL – firmware description language for computer architecture components; constructor of training and control flash tasks. The proposed method of conducting lectures and practical classes, as well as the organization of students' independent work and an assessment monitoring system that orients students toward a permanent increase in the assessment and quality of knowledge, skills, and abilities throughout the academic semester, are described.
{"title":"Experience of Blended Learning in the Subject - Architecture of Computers","authors":"M. Dolinsky","doi":"10.36548/jitdw.2022.3.004","DOIUrl":"https://doi.org/10.36548/jitdw.2022.3.004","url":null,"abstract":"The proposed study discusses about the real-time experience of blended teaching for the students of the Faculty of Mathematics and Programming Technologies in the subject \"Computer Architecture\" based on the use of distance learning instrumental system DL.GSU.BY and special software complexes developed at the F. Skorina State University under the guidance of author. Special software packages include: HLCCAD - software system for designing, modeling and debugging the functional architectures of digital devices; Winter, a software system for developing and debugging programs in assembler and C for various microcontrollers; С-MPDL – firmware description language for computer architecture components; constructor of training and control flash tasks. The proposed method of conducting lectures and practical classes, as well as the organization of students' independent work and an assessment monitoring system that orients students toward a permanent increase in the assessment and quality of knowledge, skills, and abilities throughout the academic semester, are described.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73229845","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 : 2022-08-20DOI: 10.36548/jitdw.2022.3.003
D. Sasikala, D. Chandrakanth, C. Sai Pranathi Reddy, J. Jitendra Teja
Malign websites effectively endorse the evolution of web illicit events and force the progression of Web services. As an efficient outcome, there is powerful enthusiasm to create systemic resolutions in inhibiting the client from the call onto such Websites. Knowledge-centered Random Forest outfits with XGBoost tactic is recommended for categorizing Websites into 3 categories: Benign, Spam and Malicious. This practice evaluates the Uniform Resource Locator in the situation deprived of accessing the matter of Websites. Thus, it wipes out the run-time expectation and the likelihood of uncovering clients to the browser aimed susceptibilities. As a consequence of involving Random Forest Ensembles with XGBoost, it realizes superior enactment on expansive view and publicity correlated with blacklisting amenity. Preprocessing is performed in order to improve the quality of the data subsequently, analyze certain algorithms, thereby explore the best model are the facts discussed in this research. Work also continues to probe how well this chosen archetypal will operate in the future ahead.
{"title":"Inhibiting Webshell Attacks by Random Forest Ensembles with XGBoost","authors":"D. Sasikala, D. Chandrakanth, C. Sai Pranathi Reddy, J. Jitendra Teja","doi":"10.36548/jitdw.2022.3.003","DOIUrl":"https://doi.org/10.36548/jitdw.2022.3.003","url":null,"abstract":"Malign websites effectively endorse the evolution of web illicit events and force the progression of Web services. As an efficient outcome, there is powerful enthusiasm to create systemic resolutions in inhibiting the client from the call onto such Websites. Knowledge-centered Random Forest outfits with XGBoost tactic is recommended for categorizing Websites into 3 categories: Benign, Spam and Malicious. This practice evaluates the Uniform Resource Locator in the situation deprived of accessing the matter of Websites. Thus, it wipes out the run-time expectation and the likelihood of uncovering clients to the browser aimed susceptibilities. As a consequence of involving Random Forest Ensembles with XGBoost, it realizes superior enactment on expansive view and publicity correlated with blacklisting amenity. Preprocessing is performed in order to improve the quality of the data subsequently, analyze certain algorithms, thereby explore the best model are the facts discussed in this research. Work also continues to probe how well this chosen archetypal will operate in the future ahead.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81977423","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 : 2022-08-19DOI: 10.36548/jaicn.2022.3.002
K. Krishnan
Reinforcement learning is a well-proven and powerful algorithm for robotic arm manipulation. There are various applications of this in healthcare, such as instrument assisted surgery and other medical interventions where surgeons cannot find the target successfully. Reinforcement learning is an area of machine learning and artificial intelligence that studies how an agent should take actions in an environment so as to maximize its total expected reward over time. It does this by trying different ways through trial-and-error, hoping to be rewarded for the results it achieves. The focus of this paper is to use a deep reinforcement learning neural network to map the raw pixels from a camera to the robot arm control commands for object manipulation.
{"title":"Using Deep Reinforcement Learning For Robot Arm Control","authors":"K. Krishnan","doi":"10.36548/jaicn.2022.3.002","DOIUrl":"https://doi.org/10.36548/jaicn.2022.3.002","url":null,"abstract":"Reinforcement learning is a well-proven and powerful algorithm for robotic arm manipulation. There are various applications of this in healthcare, such as instrument assisted surgery and other medical interventions where surgeons cannot find the target successfully. Reinforcement learning is an area of machine learning and artificial intelligence that studies how an agent should take actions in an environment so as to maximize its total expected reward over time. It does this by trying different ways through trial-and-error, hoping to be rewarded for the results it achieves. The focus of this paper is to use a deep reinforcement learning neural network to map the raw pixels from a camera to the robot arm control commands for object manipulation.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84936534","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}
The Smart Shoe Rack with face recognition is most likely one of the newest projects to have been introduced of its kind. In a Hindu country, temples are almost everywhere, inside the valley as well as outside, where one has to take off his footwear before entering. One of the most common yet overlooked problems is shoe misplacement in crowded temple areas. Therefore, to sort out this major problem, the idea of a Smart Shoe Keeping with face recognition has been proposed in this paper. By the use of microcontrollers, raspberry pi captures face encoding of a person and along with adjusting stepper motors, the shoe can be stacked at one of the sixteen different locations. The use of a clock helps in determining the stepper position at every instance. With face recognition technology, the shoes can be fetched. Once the face is recognized, it is matched with the previously captured person, and the system checks for the available shoe. The position of the stepper is then identified, and the shoe is fetched through the shortest path possible by the step anti/clockwise rotation of the stepper motor. The total time of storage of the footwear displayed in the LCD is then used for charging the amount of money accordingly.
{"title":"Smart Shoe Rack with Face Recognition","authors":"Aman Ansari, Gopal Kc, Hasina Dhungel","doi":"10.36548/jei.2022.3.001","DOIUrl":"https://doi.org/10.36548/jei.2022.3.001","url":null,"abstract":"The Smart Shoe Rack with face recognition is most likely one of the newest projects to have been introduced of its kind. In a Hindu country, temples are almost everywhere, inside the valley as well as outside, where one has to take off his footwear before entering. One of the most common yet overlooked problems is shoe misplacement in crowded temple areas. Therefore, to sort out this major problem, the idea of a Smart Shoe Keeping with face recognition has been proposed in this paper. By the use of microcontrollers, raspberry pi captures face encoding of a person and along with adjusting stepper motors, the shoe can be stacked at one of the sixteen different locations. The use of a clock helps in determining the stepper position at every instance. With face recognition technology, the shoes can be fetched. Once the face is recognized, it is matched with the previously captured person, and the system checks for the available shoe. The position of the stepper is then identified, and the shoe is fetched through the shortest path possible by the step anti/clockwise rotation of the stepper motor. The total time of storage of the footwear displayed in the LCD is then used for charging the amount of money accordingly.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81159758","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 : 2022-08-15DOI: 10.48550/arXiv.2208.07322
Ruining Deng, C. Cui, L. W. Remedios, S. Bao, R. M. Womick, S. Chiron, Jia Li, J. T. Roland, K. Lau, Qi Liu, K. Wilson, Yao Wang, Lori A. Coburn, B. Landman, Yuankai Huo
Multi-instance learning (MIL) is widely used in the computer-aided interpretation of pathological Whole Slide Images (WSIs) to solve the lack of pixel-wise or patch-wise annotations. Often, this approach directly applies "natural image driven" MIL algorithms which overlook the multi-scale (i.e. pyramidal) nature of WSIs. Off-the-shelf MIL algorithms are typically deployed on a single-scale of WSIs (e.g., 20× magnification), while human pathologists usually aggregate the global and local patterns in a multi-scale manner (e.g., by zooming in and out between different magnifications). In this study, we propose a novel cross-scale attention mechanism to explicitly aggregate inter-scale interactions into a single MIL network for Crohn's Disease (CD), which is a form of inflammatory bowel disease. The contribution of this paper is two-fold: (1) a cross-scale attention mechanism is proposed to aggregate features from different resolutions with multi-scale interaction; and (2) differential multi-scale attention visualizations are generated to localize explainable lesion patterns. By training ~250,000 H&E-stained Ascending Colon (AC) patches from 20 CD patient and 30 healthy control samples at different scales, our approach achieved a superior Area under the Curve (AUC) score of 0.8924 compared with baseline models. The official implementation is publicly available at https://github.com/hrlblab/CS-MIL.
{"title":"Cross-scale Attention Guided Multi-instance Learning for Crohn's Disease Diagnosis with Pathological Images","authors":"Ruining Deng, C. Cui, L. W. Remedios, S. Bao, R. M. Womick, S. Chiron, Jia Li, J. T. Roland, K. Lau, Qi Liu, K. Wilson, Yao Wang, Lori A. Coburn, B. Landman, Yuankai Huo","doi":"10.48550/arXiv.2208.07322","DOIUrl":"https://doi.org/10.48550/arXiv.2208.07322","url":null,"abstract":"Multi-instance learning (MIL) is widely used in the computer-aided interpretation of pathological Whole Slide Images (WSIs) to solve the lack of pixel-wise or patch-wise annotations. Often, this approach directly applies \"natural image driven\" MIL algorithms which overlook the multi-scale (i.e. pyramidal) nature of WSIs. Off-the-shelf MIL algorithms are typically deployed on a single-scale of WSIs (e.g., 20× magnification), while human pathologists usually aggregate the global and local patterns in a multi-scale manner (e.g., by zooming in and out between different magnifications). In this study, we propose a novel cross-scale attention mechanism to explicitly aggregate inter-scale interactions into a single MIL network for Crohn's Disease (CD), which is a form of inflammatory bowel disease. The contribution of this paper is two-fold: (1) a cross-scale attention mechanism is proposed to aggregate features from different resolutions with multi-scale interaction; and (2) differential multi-scale attention visualizations are generated to localize explainable lesion patterns. By training ~250,000 H&E-stained Ascending Colon (AC) patches from 20 CD patient and 30 healthy control samples at different scales, our approach achieved a superior Area under the Curve (AUC) score of 0.8924 compared with baseline models. The official implementation is publicly available at https://github.com/hrlblab/CS-MIL.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89573749","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 : 2022-08-12DOI: 10.36548/jaicn.2022.3.001
D. Sasikala, K. Venkatesh Sharma
Agriculture is a noteworthy and vibrant domain in the fiscal evolution of the globe. With populationin progress, climatic situation and assets, and agriculture turn out dazed to be a crucial task to realize the necessities of the future population. Intelligent precision agriculture/intelligent smart farming has transpired as an innovative tool to tackle hovers of the future ahead in automated agricultural sustainability by leading Artificial Intelligence (AI) in agriculture automation.AI unravels critical farm labor challenges by improving or reducing work and lessening the necessity of numerous workers. Agricultural AI aids in reaping harvests quicker than human employees at a greater quantity, further precise in categorizing and eradicating unwanted plants, also dropping cost and menace. This process motivates the cutting-edge technologies capitulating the machine capability to learn by sourcing Bootstrapped Meta-learning also reinforcing with rewards as maximum crop yields and minimum resource utilizations as well as within time limits. AI empowered farm machinery is the key constituent of the future agriculture revolution ahead. In this exploratory work, an efficient automation of AI application in the field of agriculture sustenance is ensured for receipt of the most obtainable aids as outcomes and inhibiting the applied assets. Fixing the precise real-time issues trailed by unravelling it for agricultural augmentation or amplification thereby leads to the global best future agriculture.
{"title":"Future Intelligent Agriculture with Bootstrapped Meta-Learning andє-greedy Q-learning","authors":"D. Sasikala, K. Venkatesh Sharma","doi":"10.36548/jaicn.2022.3.001","DOIUrl":"https://doi.org/10.36548/jaicn.2022.3.001","url":null,"abstract":"Agriculture is a noteworthy and vibrant domain in the fiscal evolution of the globe. With populationin progress, climatic situation and assets, and agriculture turn out dazed to be a crucial task to realize the necessities of the future population. Intelligent precision agriculture/intelligent smart farming has transpired as an innovative tool to tackle hovers of the future ahead in automated agricultural sustainability by leading Artificial Intelligence (AI) in agriculture automation.AI unravels critical farm labor challenges by improving or reducing work and lessening the necessity of numerous workers. Agricultural AI aids in reaping harvests quicker than human employees at a greater quantity, further precise in categorizing and eradicating unwanted plants, also dropping cost and menace. \u0000This process motivates the cutting-edge technologies capitulating the machine capability to learn by sourcing Bootstrapped Meta-learning also reinforcing with rewards as maximum crop yields and minimum resource utilizations as well as within time limits. AI empowered farm machinery is the key constituent of the future agriculture revolution ahead. In this exploratory work, an efficient automation of AI application in the field of agriculture sustenance is ensured for receipt of the most obtainable aids as outcomes and inhibiting the applied assets. Fixing the precise real-time issues trailed by unravelling it for agricultural augmentation or amplification thereby leads to the global best future agriculture.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84189676","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 : 2022-08-08DOI: 10.36548/jitdw.2022.3.002
Arun Agarwal, Kishan Ray, B. Pradhan, Vishaka Kumari
Traditional notice boards are very difficult to maintain and involves very tedious process to change notice every time. This also is accompanied by waste of paper, ink, time, and manpower as well. This research work presents a low-cost new concept of digital wireless electronic notice board based on Global System for Mobile communications (GSM) modem whereby the required notice to be displayed will be sent through Short Message Service (SMS). This transmission of information is done by Radio Frequency wireless technique. In this device, a message or notice is sent to the display device like Liquid Crystal Display (LCD), and this message can be easily modified and sent from any part of the world, just by using the SMS facility in GSM cellular devices. Whatever notice to be displayed on the board is sent using suffix and prefix, and the message sent is displayed on the 16*2 display built on the wireless notice board. This work is very useful in schools, cinema halls, railway stations, colleges, offices etc. where the notice can be changed from anywhere, at any moment and as many times it needs to be modified.
{"title":"GSM Based Smart Digital Wireless Electronic Notice Board","authors":"Arun Agarwal, Kishan Ray, B. Pradhan, Vishaka Kumari","doi":"10.36548/jitdw.2022.3.002","DOIUrl":"https://doi.org/10.36548/jitdw.2022.3.002","url":null,"abstract":"Traditional notice boards are very difficult to maintain and involves very tedious process to change notice every time. This also is accompanied by waste of paper, ink, time, and manpower as well. This research work presents a low-cost new concept of digital wireless electronic notice board based on Global System for Mobile communications (GSM) modem whereby the required notice to be displayed will be sent through Short Message Service (SMS). This transmission of information is done by Radio Frequency wireless technique. In this device, a message or notice is sent to the display device like Liquid Crystal Display (LCD), and this message can be easily modified and sent from any part of the world, just by using the SMS facility in GSM cellular devices. Whatever notice to be displayed on the board is sent using suffix and prefix, and the message sent is displayed on the 16*2 display built on the wireless notice board. This work is very useful in schools, cinema halls, railway stations, colleges, offices etc. where the notice can be changed from anywhere, at any moment and as many times it needs to be modified.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83707556","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 : 2022-07-29DOI: 10.36548/jitdw.2022.3.001
B. Radhika
Sharing information has become very important in the proper use of information assets, and the reason for this is that sharing information can be considered the most important part of an organization because information from organizations must be transferred and participated in order to be known and understood, wherein a clear and unambiguous information is considered a key criterion. To stimulate creativity, information sharing or integration is used to bring disparate pieces of knowledge together. Many current information sharing practices, such as training and development programs, IT systems, reports, official documents, and hard-working groups, are examples of integrating information. By integrating information everywhere to improve the quality of products and services, increases responsiveness to customer needs, develop new capabilities, and improve every aspect of the environment. This study reviews the ground-breaking theory behind information sharing in an organization. From the author’s perspective, this is the first study which gives a complete overview about knowledge representation.
{"title":"Ground-breaking Theory of Knowledge Representation Practices for Information Sharing in IT Organization","authors":"B. Radhika","doi":"10.36548/jitdw.2022.3.001","DOIUrl":"https://doi.org/10.36548/jitdw.2022.3.001","url":null,"abstract":"Sharing information has become very important in the proper use of information assets, and the reason for this is that sharing information can be considered the most important part of an organization because information from organizations must be transferred and participated in order to be known and understood, wherein a clear and unambiguous information is considered a key criterion. To stimulate creativity, information sharing or integration is used to bring disparate pieces of knowledge together. Many current information sharing practices, such as training and development programs, IT systems, reports, official documents, and hard-working groups, are examples of integrating information. By integrating information everywhere to improve the quality of products and services, increases responsiveness to customer needs, develop new capabilities, and improve every aspect of the environment. This study reviews the ground-breaking theory behind information sharing in an organization. From the author’s perspective, this is the first study which gives a complete overview about knowledge representation.","PeriodicalId":74231,"journal":{"name":"Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78822953","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}
Multiscale multimodal medical imaging : Third International Workshop, MMMI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings
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