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 : 2022-09-17DOI: 10.36548/jaicn.2022.3.005
C. Anisha, N. Arulanand
Parkinson Disorder (PD) is a neurological disorder which is progressive and degenerative in nature. There are no specific tests pertaining to the diagnosis of PD. The symptoms at an early stage are mild. The early diagnosis of PD is really essential to delay the progression of the disorder. Speech disorder namely dysphonia is experienced by approximately 90% of PD patients. The incorporation of Artificial Intelligence (AI) techniques integrated with non-invasive capture of speech data from patients in diagnosis system aids to provide a robust, reliable and accurate estimation of Unified Parkinson Disease Rating Scale (UPDRS) score which ease the decision-making process effective for healthcare professionals. The proposed system incorporates a novel tuned Homogenous Ensemble Regressor wherein the hyperparameters are chosen and tuned using various experiments. Tuned Extreme Gradient (XgBoost) Regressor and Tuned Random Forest (RF) Regressor are the two homogenous regressor model. The proposed system is compared with the Tuned Linear Regression (LR) model which is the single Regressor model. The proposed system is evaluated using the large database of voice features samples of 42 PD patients. The Mean Absolute Error (MAE) and Mean Squared Error (MAE) values are minimal for the proposed system and it shows that the errors of the proposed system are lower than the single classifier errors and existing similar system.
{"title":"Tuned Homogenous Ensemble Regressor Model for Early Diagnosis of Parkinson Disorder Based on Voice Features Modality","authors":"C. Anisha, N. Arulanand","doi":"10.36548/jaicn.2022.3.005","DOIUrl":"https://doi.org/10.36548/jaicn.2022.3.005","url":null,"abstract":"Parkinson Disorder (PD) is a neurological disorder which is progressive and degenerative in nature. There are no specific tests pertaining to the diagnosis of PD. The symptoms at an early stage are mild. The early diagnosis of PD is really essential to delay the progression of the disorder. Speech disorder namely dysphonia is experienced by approximately 90% of PD patients. The incorporation of Artificial Intelligence (AI) techniques integrated with non-invasive capture of speech data from patients in diagnosis system aids to provide a robust, reliable and accurate estimation of Unified Parkinson Disease Rating Scale (UPDRS) score which ease the decision-making process effective for healthcare professionals. The proposed system incorporates a novel tuned Homogenous Ensemble Regressor wherein the hyperparameters are chosen and tuned using various experiments. Tuned Extreme Gradient (XgBoost) Regressor and Tuned Random Forest (RF) Regressor are the two homogenous regressor model. The proposed system is compared with the Tuned Linear Regression (LR) model which is the single Regressor model. The proposed system is evaluated using the large database of voice features samples of 42 PD patients. The Mean Absolute Error (MAE) and Mean Squared Error (MAE) values are minimal for the proposed system and it shows that the errors of the proposed system are lower than the single classifier errors and existing similar system.","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":"2022-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86013635","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 : 2022-09-16DOI: 10.36548/jitdw.2022.3.006
Dakhole Dipali
Agriculture is the main livelihood in India. Most of the people earn bread and butter through farming, but the farmers are not getting enough profit and the field is facing growth downward due to irregular rainfall, high volatility in agriculture commodity prices and uncertainties in production. The objective of this study is to design and implement an automated crop price prediction system with best suitable machine learning technique, as well as displaying prediction results on website Krishi-Stats designed for easy understanding for Farmers. In this study, three machine-learning (ML) algorithms, ARIMA, VAR and XGBoost are applied on large historical data collected from government website. The ML algorithms compared with their root mean square error values (RMSE). As XGBoost has given optimum RMSE value of 0.94, has been selected as the prediction system engine of our website Krishi-Stats. On website, the crop prediction prices are plotted for all twelve selected crops and visualized using prediction graphs.
{"title":"Krishi-Stats: A Web-based System for Crop Price Prediction using Machine Learning Approach","authors":"Dakhole Dipali","doi":"10.36548/jitdw.2022.3.006","DOIUrl":"https://doi.org/10.36548/jitdw.2022.3.006","url":null,"abstract":"Agriculture is the main livelihood in India. Most of the people earn bread and butter through farming, but the farmers are not getting enough profit and the field is facing growth downward due to irregular rainfall, high volatility in agriculture commodity prices and uncertainties in production. The objective of this study is to design and implement an automated crop price prediction system with best suitable machine learning technique, as well as displaying prediction results on website Krishi-Stats designed for easy understanding for Farmers. In this study, three machine-learning (ML) algorithms, ARIMA, VAR and XGBoost are applied on large historical data collected from government website. The ML algorithms compared with their root mean square error values (RMSE). As XGBoost has given optimum RMSE value of 0.94, has been selected as the prediction system engine of our website Krishi-Stats. On website, the crop prediction prices are plotted for all twelve selected crops and visualized using prediction graphs.","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":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88082921","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 : 2022-09-15DOI: 10.36548/jaicn.2022.3.004
Kottilingam Kottursamy
One of the biggest threats in the speaker verification system is that of fake audio attacks. Over the years several detection approaches have been introduced that were designed to provide efficient and spoof-proof data-specific scenarios. However, the speaker verification system is still exposed to fake audio threats. Hence to address this issue, several authors have proposed methodologies to retrain and finetune the input data. The drawback with retraining and fine-tuning is that retraining requires high computation resources and time while fine-tuning results in degradation of performance. Moreover, in certain situations, the previous data becomes unavailable and cannot be accessed immediately. In this paper, we have proposed a solution that detects fake without continual-learning based methods and fake detection without forgetting in order to develop a new model which is capable of detecting spoofing attacks in an incremental fashion. In order to retain original model memory, knowledge distillation loss is introduced. In several scenarios, the distribution of genuine voice is said to be very consistent. In several scenarios, there is consistency in distribution of genuine voice hence a similarity loss is embedded additionally to perform a positive sample alignment. The output of the proposed work indicates an error rate reduction of up to 80% as observed and recorded.
{"title":"Deep Learning based DFWF Model for Audio Spoofing Attack Detection","authors":"Kottilingam Kottursamy","doi":"10.36548/jaicn.2022.3.004","DOIUrl":"https://doi.org/10.36548/jaicn.2022.3.004","url":null,"abstract":"One of the biggest threats in the speaker verification system is that of fake audio attacks. Over the years several detection approaches have been introduced that were designed to provide efficient and spoof-proof data-specific scenarios. However, the speaker verification system is still exposed to fake audio threats. Hence to address this issue, several authors have proposed methodologies to retrain and finetune the input data. The drawback with retraining and fine-tuning is that retraining requires high computation resources and time while fine-tuning results in degradation of performance. Moreover, in certain situations, the previous data becomes unavailable and cannot be accessed immediately. In this paper, we have proposed a solution that detects fake without continual-learning based methods and fake detection without forgetting in order to develop a new model which is capable of detecting spoofing attacks in an incremental fashion. In order to retain original model memory, knowledge distillation loss is introduced. In several scenarios, the distribution of genuine voice is said to be very consistent. In several scenarios, there is consistency in distribution of genuine voice hence a similarity loss is embedded additionally to perform a positive sample alignment. The output of the proposed work indicates an error rate reduction of up to 80% as observed and recorded.","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":"2022-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87944925","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}
Jeevanshi Sharma, Rajat Maheshwari, S. Khan, Abid Ali Khan
In this paper, different machine learning and tabular learning classification algorithms have been studied and compared on the acute hand-gesture Electromyogram dataset. The comparative study between different models such as KNN, RandomForest, TabNet, etc. depicts that small datasets can achieve high-level accuracy along with the intuition of high-performing neural net architectures through tabular learning approaches like TabNet. The performed analysis produced an accuracy of 99.9% through TabNet while other conventional classifiers also gave satisfactory results with KNN being at highest achieving accuracy of 97.8 %.
{"title":"Evaluating Performance of Different Machine Learning Algorithms for the Acute EMG Hand Gesture Datasets","authors":"Jeevanshi Sharma, Rajat Maheshwari, S. Khan, Abid Ali Khan","doi":"10.36548/jei.2022.3.007","DOIUrl":"https://doi.org/10.36548/jei.2022.3.007","url":null,"abstract":"In this paper, different machine learning and tabular learning classification algorithms have been studied and compared on the acute hand-gesture Electromyogram dataset. The comparative study between different models such as KNN, RandomForest, TabNet, etc. depicts that small datasets can achieve high-level accuracy along with the intuition of high-performing neural net architectures through tabular learning approaches like TabNet. The performed analysis produced an accuracy of 99.9% through TabNet while other conventional classifiers also gave satisfactory results with KNN being at highest achieving accuracy of 97.8 %.","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":"2022-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86939708","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}
Biplob Kumar Ray, Angshuman Majumdar, S. Gangopadhyay
An Erbium-Doped Fiber Amplifier (EDFA) is an in-line component in modern all –optical telecommunication infrastructure. Different parametric characteristics of an EDFA express the suitability and excellency of performance in its real field application. Intensities of pump and signal vary with distance from the core-axis along the radius of the fiber which is one of the significant characteristics of an EDFA. Change of behavior of pump and signal intensities along the radius of the fiber in an erbium-doped dual-mode trapezoidal index fiber made amplifier due to Kerr nonlinearity phenomenon originating from launching and transmission of intense light from LASER beam inside the amplifier for the LP_11 mode has been exercised in this case. In the present case, some trapezoidal-index fibers of different normalised frequencies have been opted. This exercise is an implementation of the reliable and easy mathematical instrument, the Chebyshev technique. Results derived in this exercise exhibit a fantastic similarity with those derived by the rigorous finite element method. This study with implementation of such a reliable and easy technique may help the interested optical engineers.
{"title":"Radial Differentiation of Pump and Signal Intensities in Trapezoidal index EDFA for LP11 mode in Kerr nonlinear state","authors":"Biplob Kumar Ray, Angshuman Majumdar, S. Gangopadhyay","doi":"10.36548/jei.2022.3.006","DOIUrl":"https://doi.org/10.36548/jei.2022.3.006","url":null,"abstract":"An Erbium-Doped Fiber Amplifier (EDFA) is an in-line component in modern all –optical telecommunication infrastructure. Different parametric characteristics of an EDFA express the suitability and excellency of performance in its real field application. Intensities of pump and signal vary with distance from the core-axis along the radius of the fiber which is one of the significant characteristics of an EDFA. Change of behavior of pump and signal intensities along the radius of the fiber in an erbium-doped dual-mode trapezoidal index fiber made amplifier due to Kerr nonlinearity phenomenon originating from launching and transmission of intense light from LASER beam inside the amplifier for the LP_11 mode has been exercised in this case. In the present case, some trapezoidal-index fibers of different normalised frequencies have been opted. This exercise is an implementation of the reliable and easy mathematical instrument, the Chebyshev technique. Results derived in this exercise exhibit a fantastic similarity with those derived by the rigorous finite element method. This study with implementation of such a reliable and easy technique may help the interested optical engineers.","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":"2022-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86961686","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}
To contain the chain of Covid-19, taking on the role of Engineering Ambassador of humanity in these dire conditions, this paper develops an electronic equipment referred holistically as “Covid Tunnel” or “Disinfectant Tunnel”. The general thesis from which the whole work has evolved is to make use of temperature control and automation by programming to try to pin the potential host of virus in possible hotspots viz., hospitals, administrative complexes, strategic junctions, etc. The first and foremost import of this benevolent project is the application of Automatic Temperature Control. Arduino Nano Temperature Control is employed for checking the temperature of each entrant at the entrance gate. For instance, if a person entering happens to have a body temperature above 38C, the buzzer goes on indicating a red flag for the entry. The second and equally important process is filtering based on the face mask. Now, a webcam attached right after, which is program-based on Python, Open CV, Tensor Flow etc. provides the necessary input and the program searches for the face mask. If the entrant is unmasked, a voice in Urdu commands for wearing of the face mask. While a masked person enters, the automated sanitizer pops out for sanitizing as a precautionary measure. The sanitizer itself is automated by a DC motor which in turn is driven by MOSFET integrated circuit. Thusly, this paper tries to kick in with the Electronics and Information Technology and helps arrest the spread of the virus in the community, anticipating a Coronavirus-free world.
为了遏制Covid-19链，在这些恶劣条件下承担人类工程大使的角色，本文开发了一种电子设备，统称为“Covid隧道”或“消毒剂隧道”。整个工作发展的一般论点是利用温度控制和自动化编程，试图将病毒的潜在宿主锁定在可能的热点地区，即医院，行政综合体，战略枢纽等。这个慈善项目的第一个也是最重要的是自动温度控制的应用。使用Arduino纳米温度控制器在入口处检查每个进入者的温度。例如，如果一个人进入时体温高于38度，蜂鸣器就会发出红色信号。第二个也是同样重要的过程是基于口罩的过滤。现在，一个基于Python, Open CV, Tensor Flow等程序的网络摄像头提供了必要的输入，程序搜索口罩。如果参赛者没有戴口罩，就会有一个乌尔都语的声音命令他戴上口罩。当戴面具的人进入时，自动消毒机就会跳出来消毒，作为预防措施。消毒机本身由直流电机自动化，直流电机由MOSFET集成电路驱动。因此，本文试图与电子和信息技术相结合，帮助遏制病毒在社区中的传播，期待一个没有冠状病毒的世界。
{"title":"Automatic Temperature Detection and Sanitization with Authorized Entry using Face Mask Detection","authors":"Rukia Rahman","doi":"10.36548/jei.2022.3.005","DOIUrl":"https://doi.org/10.36548/jei.2022.3.005","url":null,"abstract":"To contain the chain of Covid-19, taking on the role of Engineering Ambassador of humanity in these dire conditions, this paper develops an electronic equipment referred holistically as “Covid Tunnel” or “Disinfectant Tunnel”. The general thesis from which the whole work has evolved is to make use of temperature control and automation by programming to try to pin the potential host of virus in possible hotspots viz., hospitals, administrative complexes, strategic junctions, etc. The first and foremost import of this benevolent project is the application of Automatic Temperature Control. Arduino Nano Temperature Control is employed for checking the temperature of each entrant at the entrance gate. For instance, if a person entering happens to have a body temperature above 38C, the buzzer goes on indicating a red flag for the entry. \u0000The second and equally important process is filtering based on the face mask. Now, a webcam attached right after, which is program-based on Python, Open CV, Tensor Flow etc. provides the necessary input and the program searches for the face mask. If the entrant is unmasked, a voice in Urdu commands for wearing of the face mask. While a masked person enters, the automated sanitizer pops out for sanitizing as a precautionary measure. The sanitizer itself is automated by a DC motor which in turn is driven by MOSFET integrated circuit. Thusly, this paper tries to kick in with the Electronics and Information Technology and helps arrest the spread of the virus in the community, anticipating a Coronavirus-free world.","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":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80963799","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 excitement about the 5G wireless network has passed. Mobile network operators (MNO) have begun rolling out 5G networks alongside 4G cellular networks in lower frequency and mid-frequency bands (i.e., 3-6 GHz) all over the world. The mid-frequency band can greatly improve the performance of the current network (i.e., 50 MHz–100 MHz). All we know that the wider spectrum can be provided by the high frequency bands which is required to fulfill the greatest bitrates (20 Gb/s), lowest latencies, and constantly increasing capacity demands. The free space propagation loss rapidly increases as we move to higher frequency bands, that will reduce the individual cell site radius to 100 m for the high frequency band from various distances in 4G. To offer consistent 5G coverage, the MNOs will have significant challenges in precisely planning and acquiring these enormous numbers of new cell site locations. This paper describes about the signal characteristics at 800MHz, 1800MHz for 4G and at 700MHz, 2300MHz, 2600MHz, 3500MHz for 5G and the upgradation of 4G towards 5G in the test environment. The 5G Coverage Planning with three sector cells and its SINR Mapping in advance antenna array will be performed to provide better coverage in 5G environments.
{"title":"5G Coverage Planning for Urban Area at Kathmandu City, Nepal","authors":"Nirmala Sharma, S. Shakya","doi":"10.36548/jei.2022.3.004","DOIUrl":"https://doi.org/10.36548/jei.2022.3.004","url":null,"abstract":"The excitement about the 5G wireless network has passed. Mobile network operators (MNO) have begun rolling out 5G networks alongside 4G cellular networks in lower frequency and mid-frequency bands (i.e., 3-6 GHz) all over the world. The mid-frequency band can greatly improve the performance of the current network (i.e., 50 MHz–100 MHz). All we know that the wider spectrum can be provided by the high frequency bands which is required to fulfill the greatest bitrates (20 Gb/s), lowest latencies, and constantly increasing capacity demands. The free space propagation loss rapidly increases as we move to higher frequency bands, that will reduce the individual cell site radius to 100 m for the high frequency band from various distances in 4G. To offer consistent 5G coverage, the MNOs will have significant challenges in precisely planning and acquiring these enormous numbers of new cell site locations. This paper describes about the signal characteristics at 800MHz, 1800MHz for 4G and at 700MHz, 2300MHz, 2600MHz, 3500MHz for 5G and the upgradation of 4G towards 5G in the test environment. The 5G Coverage Planning with three sector cells and its SINR Mapping in advance antenna array will be performed to provide better coverage in 5G environments.","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":"2022-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74329892","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 Intelligent Electronic Devices (IEDs) are widely used to control the power circuits through an automated control device. The main motive of IEDs is to monitor the power flow, enable the control process and meter the changes. In some cases, the IEDs are employed as an electronic circuit breaker for providing a reliable operation. It is achieved by operating the relays through digital signals. The traditional methods have been using a mechanical system for operating the circuit breakers, which requires a manual operation for resting the breakers. The modern IEDs are developed to reset the operation by its own but such systems are heavily affected through data intrusions. Therefore, a programmed IED is developed in the proposed work to analyze if the decisions made by the IEDs are original or fake in a simulated observation. It is done with a mathematical averaging algorithm with respect to time for estimating a threshold. The experimental outcome indicates that the performance of the customized IED is better over the traditional IEDs. Moreover, the proposed device saves the energy distribution in a power system by avoiding the fake operations created in the IEDs through external intrusions.
{"title":"Design of a Customized Intelligent Electronic Device for Power Circuit Safety","authors":"P. Ebby Darney","doi":"10.36548/jei.2022.3.003","DOIUrl":"https://doi.org/10.36548/jei.2022.3.003","url":null,"abstract":"The Intelligent Electronic Devices (IEDs) are widely used to control the power circuits through an automated control device. The main motive of IEDs is to monitor the power flow, enable the control process and meter the changes. In some cases, the IEDs are employed as an electronic circuit breaker for providing a reliable operation. It is achieved by operating the relays through digital signals. The traditional methods have been using a mechanical system for operating the circuit breakers, which requires a manual operation for resting the breakers. The modern IEDs are developed to reset the operation by its own but such systems are heavily affected through data intrusions. Therefore, a programmed IED is developed in the proposed work to analyze if the decisions made by the IEDs are original or fake in a simulated observation. It is done with a mathematical averaging algorithm with respect to time for estimating a threshold. The experimental outcome indicates that the performance of the customized IED is better over the traditional IEDs. Moreover, the proposed device saves the energy distribution in a power system by avoiding the fake operations created in the IEDs through external intrusions.","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":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81913813","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}
Recently, the printing technologies for mass producing flexible and elastic electronics might significantly broaden the range of uses for electronics and transform the way people think about them. This document offers a summary of the most current research in this area. The structure that allows for the transmission of data involves the transfer of information from one channel to another by way of a very flexible film model transistor assisted by an integrated circuit procedure. The semiconductor industry makes extensive use of wall-based carbon nanotubes for the purpose of developing models with improved efficiency. This study provides a comprehensive explanation of single and multi-channel field-effect transistors, both of which are used for the process of data transmission using flexible carbon nanotube transistors in applications such as hearing aid equipment. This research work go through all the recent tweaks to the printing process for sensing and transmitting data from one to another source. All of these modifications are ideal for the mass-production of stretchy and flexible electronics.
{"title":"Future Trends for Carbon Nanotube Transistors in Sensing and Transmitting Data","authors":"G. Rajakumar","doi":"10.36548/jei.2022.3.002","DOIUrl":"https://doi.org/10.36548/jei.2022.3.002","url":null,"abstract":"Recently, the printing technologies for mass producing flexible and elastic electronics might significantly broaden the range of uses for electronics and transform the way people think about them. This document offers a summary of the most current research in this area. The structure that allows for the transmission of data involves the transfer of information from one channel to another by way of a very flexible film model transistor assisted by an integrated circuit procedure. The semiconductor industry makes extensive use of wall-based carbon nanotubes for the purpose of developing models with improved efficiency. This study provides a comprehensive explanation of single and multi-channel field-effect transistors, both of which are used for the process of data transmission using flexible carbon nanotube transistors in applications such as hearing aid equipment. This research work go through all the recent tweaks to the printing process for sensing and transmitting data from one to another source. All of these modifications are ideal for the mass-production of stretchy and flexible electronics.","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":"2022-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77505063","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 : 2022-09-02DOI: 10.36548/jitdw.2022.3.005
Pascal Muam Mah, Iwona Skalna, John Muzam, Lilian Kuyiena Song
FinTech is a digital innovation technology that aims to educate and enable the world on how to create utility values in every activity. Natural language processing is one of the umbrella systems that has unite other innovative technologies behind FinTech. Technological system drivers regarded as "ABCDE" of FinTech consist of Artificial intelligence, Blockchain, Cloud computing, big data, and the internet of things. As communication took the lead in the second half of the 21st century, most companies are moving remotely, leading to much-needed innovation in FinTech. The study presents how natural language processing enables different technologies and advances the technology behind FinTech. The study aims to identify areas of the modern world that can be transformed into a source of finance using the FinTechs drivers of "ABCDE”. The study observed FinTech as a digital Economics that integrates with different aspects of modern technology to create utility values. The study uses the 5 C's of credit as the source of finance for innovative ideas and the 5 P's of marketing as innovative network to reach ultimate FinTech utility values. Results based on the demand and supply analysis indicate that a combination of 5 C's and 5 P's is the bond behind FinTech with the support of the drivers of "ABCDE". Also that the increased demand for goods and services in every economy indicates a fall in the request for credit and vice versa. The study concluded that a well-structured 5 C's and 5 P's is the best route to FinTech technology which is financial freedom to the world.
{"title":"Analysis of Natural Language Processing in the FinTech Models of Mid-21st Century","authors":"Pascal Muam Mah, Iwona Skalna, John Muzam, Lilian Kuyiena Song","doi":"10.36548/jitdw.2022.3.005","DOIUrl":"https://doi.org/10.36548/jitdw.2022.3.005","url":null,"abstract":"FinTech is a digital innovation technology that aims to educate and enable the world on how to create utility values in every activity. Natural language processing is one of the umbrella systems that has unite other innovative technologies behind FinTech. Technological system drivers regarded as \"ABCDE\" of FinTech consist of Artificial intelligence, Blockchain, Cloud computing, big data, and the internet of things. As communication took the lead in the second half of the 21st century, most companies are moving remotely, leading to much-needed innovation in FinTech. The study presents how natural language processing enables different technologies and advances the technology behind FinTech. The study aims to identify areas of the modern world that can be transformed into a source of finance using the FinTechs drivers of \"ABCDE”. \u0000The study observed FinTech as a digital Economics that integrates with different aspects of modern technology to create utility values. The study uses the 5 C's of credit as the source of finance for innovative ideas and the 5 P's of marketing as innovative network to reach ultimate FinTech utility values. Results based on the demand and supply analysis indicate that a combination of 5 C's and 5 P's is the bond behind FinTech with the support of the drivers of \"ABCDE\". Also that the increased demand for goods and services in every economy indicates a fall in the request for credit and vice versa. The study concluded that a well-structured 5 C's and 5 P's is the best route to FinTech technology which is financial freedom to the world.","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":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77123554","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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