The development of digital technology has brought about a substantial evolution in the multimedia field.The use of generative technologies to produce digital multimedia material is one of the newer developments in thi...The development of digital technology has brought about a substantial evolution in the multimedia field.The use of generative technologies to produce digital multimedia material is one of the newer developments in this field.The“Digital Generative Multimedia Tool Theory”(DGMTT)is therefore presented in this theoretical postulation by Timothy Ekeledirichukwu Onyejelem and Eric Msughter Aondover.It discusses and describes the principles behind the development and deployment of generative tools in multimedia creation.The DGMTT offers an all-encompassing structure for comprehending and evaluating the fundamentals and consequences of generative tools in the production of multimedia content.It provides information about the creation and use of these instruments,thereby promoting developments in the digital media industry.These tools create dynamic and interactive multimedia content by utilizing machine learning,artificial intelligence,and algorithms.This theory emphasizes how crucial it is to comprehend the fundamental ideas and principles of generative tools in order to use them efficiently when creating digital media content.A wide range of industries,including journalism,advertising,entertainment,education,and the arts,can benefit from the practical use of DGMTT.It gives artists the ability to use generative technologies to create unique and customized multimedia content for its viewers.展开更多
This study investigates the learning curve of commercial banks regarding the efficiency of credit and value creation.However,current empirical methods for accessing the learning curve in organizations are not suitable...This study investigates the learning curve of commercial banks regarding the efficiency of credit and value creation.However,current empirical methods for accessing the learning curve in organizations are not suitable for use in financial institutions.Considering bank-specific characteristics,we introduce a dynamic learning curve using a cost function adjusted to capture learning-by-doing in banks.Using the model,we test several hypotheses on the impact of bank intermediary experience(learning)on the efficiency of credit and value creation in Japanese commercial banks.The findings show that bank intermediary learning significantly improves the cost efficiency gain in the gross value created,total credit created,and investment.However,bank intermediary experience has no significant effect on the efficiency of the economic value created for all the banks analyzed.These findings have practical implications for evaluating cost dynamics in bank credit and value creation,risk management,lending to the real sector,and shareholder value creation.展开更多
Cyber-Physical System(CPS)involves the combination of physical processes with computation and communication systems.The recent advancementsmade in cloud computing,Wireless Sensor Network(WSN),healthcare sensors,etc.te...Cyber-Physical System(CPS)involves the combination of physical processes with computation and communication systems.The recent advancementsmade in cloud computing,Wireless Sensor Network(WSN),healthcare sensors,etc.tend to develop CPS as a proficient model for healthcare applications especially,home patient care.Though several techniques have been proposed earlier related to CPS structures,only a handful of studies has focused on the design of CPS models for health care sector.So,the proposal for a dedicated CPS model for healthcare sector necessitates a significant interest to ensure data privacy.To overcome the challenges,the current research paper designs a Deep Learning-based Intrusion Detection and Image Classification for Secure CPS(DLIDIC-SCPS)model for healthcare sector.The aim of the proposed DLIDIC-SCPS model is to achieve secure image transmission and image classification process for CPS in healthcare sector.Primarily,data acquisition takes place with the help of sensors and detection of intrusions is performed using Fuzzy Deep Neural Network(FDNN)technique.Besides,Multiple Share Creation(MSC)approach is used to create several shares of medical image so as to accomplish security.Also,blockchain is employed as a distributed data storage entity to create a ledger that provides access to the client.For image classification,Inception v3 with Fuzzy Wavelet Neural Network(FWNN)is utilized that diagnose the disease from the applied medical image.Finally,Salp Swarm Algorithm(SSA)is utilized to fine tune the parameters involved in WNN model,thereby boosting its classification performance.A wide range of simulations was carried out to highlight the superiority of the proposed DLIDIC-SCPS technique.The simulation outcomes confirm that DLIDIC-SCPS approach demonstrates promising results in terms of security,privacy,and image classification outcomes over recent state-of-the-art techniques.展开更多
This paper explores the benefits of using literature to improve freshmen＇s language skills in English. Teaching strategies of literature instruction encouraged peer collaboration and constructing meaning with other s...This paper explores the benefits of using literature to improve freshmen＇s language skills in English. Teaching strategies of literature instruction encouraged peer collaboration and constructing meaning with other students prior to class, in class and after class. Various activities, such as group discussion on guided questions, presentation of reading diary and peer correction of reflection poems were applied to enhance students＇ learning interests. Four intact advanced-level classes of 162 freshmen participated in the study. They answered a questionnaire and took an English proficiency pre/post test. Descriptive statistics, ANOVA, Scheffe post-Hoc test, independent t-test and a paired t-test were used to analyze data. Results showed literature instruction effectively promoted students＇ English skills and their awareness of cultural differences. Watching the adaptation of the novel on DVD before they read the book helped students＇ comprehension. Finally, there was a significant improvement in both students＇ reading and listening exam grades. Future studies may consider looking for participants from different levels of English proficiency and extending the instruction time from one semester to two semesters.展开更多
文摘The development of digital technology has brought about a substantial evolution in the multimedia field.The use of generative technologies to produce digital multimedia material is one of the newer developments in this field.The“Digital Generative Multimedia Tool Theory”(DGMTT)is therefore presented in this theoretical postulation by Timothy Ekeledirichukwu Onyejelem and Eric Msughter Aondover.It discusses and describes the principles behind the development and deployment of generative tools in multimedia creation.The DGMTT offers an all-encompassing structure for comprehending and evaluating the fundamentals and consequences of generative tools in the production of multimedia content.It provides information about the creation and use of these instruments,thereby promoting developments in the digital media industry.These tools create dynamic and interactive multimedia content by utilizing machine learning,artificial intelligence,and algorithms.This theory emphasizes how crucial it is to comprehend the fundamental ideas and principles of generative tools in order to use them efficiently when creating digital media content.A wide range of industries,including journalism,advertising,entertainment,education,and the arts,can benefit from the practical use of DGMTT.It gives artists the ability to use generative technologies to create unique and customized multimedia content for its viewers.
基金supported by JSPS KAKENHI Grant Number 19J10715.
文摘This study investigates the learning curve of commercial banks regarding the efficiency of credit and value creation.However,current empirical methods for accessing the learning curve in organizations are not suitable for use in financial institutions.Considering bank-specific characteristics,we introduce a dynamic learning curve using a cost function adjusted to capture learning-by-doing in banks.Using the model,we test several hypotheses on the impact of bank intermediary experience(learning)on the efficiency of credit and value creation in Japanese commercial banks.The findings show that bank intermediary learning significantly improves the cost efficiency gain in the gross value created,total credit created,and investment.However,bank intermediary experience has no significant effect on the efficiency of the economic value created for all the banks analyzed.These findings have practical implications for evaluating cost dynamics in bank credit and value creation,risk management,lending to the real sector,and shareholder value creation.
文摘Cyber-Physical System(CPS)involves the combination of physical processes with computation and communication systems.The recent advancementsmade in cloud computing,Wireless Sensor Network(WSN),healthcare sensors,etc.tend to develop CPS as a proficient model for healthcare applications especially,home patient care.Though several techniques have been proposed earlier related to CPS structures,only a handful of studies has focused on the design of CPS models for health care sector.So,the proposal for a dedicated CPS model for healthcare sector necessitates a significant interest to ensure data privacy.To overcome the challenges,the current research paper designs a Deep Learning-based Intrusion Detection and Image Classification for Secure CPS(DLIDIC-SCPS)model for healthcare sector.The aim of the proposed DLIDIC-SCPS model is to achieve secure image transmission and image classification process for CPS in healthcare sector.Primarily,data acquisition takes place with the help of sensors and detection of intrusions is performed using Fuzzy Deep Neural Network(FDNN)technique.Besides,Multiple Share Creation(MSC)approach is used to create several shares of medical image so as to accomplish security.Also,blockchain is employed as a distributed data storage entity to create a ledger that provides access to the client.For image classification,Inception v3 with Fuzzy Wavelet Neural Network(FWNN)is utilized that diagnose the disease from the applied medical image.Finally,Salp Swarm Algorithm(SSA)is utilized to fine tune the parameters involved in WNN model,thereby boosting its classification performance.A wide range of simulations was carried out to highlight the superiority of the proposed DLIDIC-SCPS technique.The simulation outcomes confirm that DLIDIC-SCPS approach demonstrates promising results in terms of security,privacy,and image classification outcomes over recent state-of-the-art techniques.
文摘This paper explores the benefits of using literature to improve freshmen＇s language skills in English. Teaching strategies of literature instruction encouraged peer collaboration and constructing meaning with other students prior to class, in class and after class. Various activities, such as group discussion on guided questions, presentation of reading diary and peer correction of reflection poems were applied to enhance students＇ learning interests. Four intact advanced-level classes of 162 freshmen participated in the study. They answered a questionnaire and took an English proficiency pre/post test. Descriptive statistics, ANOVA, Scheffe post-Hoc test, independent t-test and a paired t-test were used to analyze data. Results showed literature instruction effectively promoted students＇ English skills and their awareness of cultural differences. Watching the adaptation of the novel on DVD before they read the book helped students＇ comprehension. Finally, there was a significant improvement in both students＇ reading and listening exam grades. Future studies may consider looking for participants from different levels of English proficiency and extending the instruction time from one semester to two semesters.
