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Social and Behavioral Sciences Commons™
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- AI (1)
- Abnormal (1)
- Acceptance (1)
- And Interdependent Learning Processes (1)
- Anomalous (1)
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- Artificial intelligence (AI) (1)
- Automation (1)
- Corona Virus (1)
- Data analysis (1)
- Data augmentation techniques are employed to enhance the variability of the training data (1)
- E-Learning Success Model (1)
- Electronic Health Record system (1)
- International (1)
- Interoperable (1)
- Job automation (1)
- Jobs (1)
- Learning Outcomes (1)
- Machine learning (1)
- Mobile wallets; Technology acceptance model (TAM); Expectation confirmation model (ECM); Covid-19; Perceived Trust; Continued usage intention (1)
- Monitoring (1)
- Pandemic. Statistical Models (1)
- Predictive modeling (1)
- Reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of 100% over the Large-scale fish dataset (1)
- Self-Regulated Learning (1)
- Student Satisfaction (1)
- Suspicious (1)
- Tanzania (1)
- The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture (1)
- This work proposes avenues for future research in the domain of fish classification. (1)
- Which is famous for faster training and lower computational cost. In CCT (1)
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Articles 1 - 8 of 8
Full-Text Articles in Social and Behavioral Sciences
Classification Of Large Scale Fish Dataset By Deep Neural Networks, Priyanka Adapa
Classification Of Large Scale Fish Dataset By Deep Neural Networks, Priyanka Adapa
Electronic Theses, Projects, and Dissertations
The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture, which is famous for faster training and lower computational cost. In CCT, data augmentation techniques are employed to enhance the variability of the training data, reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of …
Analyzing The Impact Of Automation On Employment In Different Us Regions: A Data-Driven Approach, Thejaas Balasubramanian
Analyzing The Impact Of Automation On Employment In Different Us Regions: A Data-Driven Approach, Thejaas Balasubramanian
Electronic Theses, Projects, and Dissertations
Automation is transforming the US workforce with the increasing prevalence of technologies like robotics, artificial intelligence, and machine learning. As a result, it is essential to understand how this shift will impact the labor market and prepare for its effects. This culminating experience project aimed to examine the influence of computerization on jobs in the United States and answer the following research questions: Q1. What factors affect how likely different jobs will be automated? Q2. What are the possible effects of automation on the US workforce across states and industries? Q3. What are the meaningful predictors of the likelihood of …
Human Suspicious Activity Detection, Nilamben Bhuva
Human Suspicious Activity Detection, Nilamben Bhuva
Electronic Theses, Projects, and Dissertations
The detection of suspicious human activity is a crucial aspect of ensuring public safety and security. The aim is to identify suspicious behavior. To accomplish this, we employ the LRCN, a long-term recurrent convolutional network, to detect anomalous activity. It is important to consider the temporal data of the video when classifying suspicious behavior, and the framework uses a combination of CNNs and RNNs to analyze video frames and extract relevant features. The key milestones of this project include conducting research, collecting and pre-processing data, designing and training the model, and evaluating its performance. The resulting detection system can accurately …
Determinants Of Continuance Intention To Use Mobile Wallets Technology In The Post Pandemic Era: Moderating Role Of Perceived Trust, Shailja Tripathi
Determinants Of Continuance Intention To Use Mobile Wallets Technology In The Post Pandemic Era: Moderating Role Of Perceived Trust, Shailja Tripathi
Journal of International Technology and Information Management
The Covid-19 pandemic amplified the volume and importance of mobile payments using digital wallets and placed a basis for their continued adoption. The objective of the study is to formulate and test a comprehensive model by integration of the technology acceptance model (TAM) and expectation confirmation model (ECM) with the addition of three constructs, namely perceived trust, perceived risk, and subjective norm, to identify the determinants of continuance intention to use mobile wallets. Questionnaire-based survey method was used to gather the data from 550 users having experience using mobile wallets for more than six months. The data were analyzed using …
The Need For International Ai Activities Monitoring, Parviz Partow-Navid, Ludwig Slusky
The Need For International Ai Activities Monitoring, Parviz Partow-Navid, Ludwig Slusky
Journal of International Technology and Information Management
This paper focuses primarily on the need to monitor the risks arising from the dual-use of Artificial Intelligence (AI). Dual-use AI technology capability makes it applicable for defense systems and consequently may pose significant security risks, both intentional and unintentional, with the national and international scope of effects. While domestic use of AI remains the prerogative of individual countries, the unregulated and nonmonitored use of AI with international implications presents a specific concern. An international organization tasked with monitoring potential threats of AI activities could help defuse AI-associated risks and promote global cooperation in developing and deploying AI technology. The …
Learning Outcomes And Learner Satisfaction: The Mediating Roles Of Self-Regulated Learning And Dialogues, Sean Eom, Nicholas Jeremy Ashill
Learning Outcomes And Learner Satisfaction: The Mediating Roles Of Self-Regulated Learning And Dialogues, Sean Eom, Nicholas Jeremy Ashill
Journal of International Technology and Information Management
The interdependent learning process is regarded as a crucial part of e-learning success, but it has been largely ignored in e-learning empirical research. Grounded in constructivist and social constructivist theory, we present and test an e-learning success model consisting of eight e-learning critical success factors (CSF) derived from constructivist and social constructivist models. Three hundred seventy-two on-line students from a Midwestern university in the United States participated in the survey. The data collected from the survey was used to examine the partial least squares structural equation model. The results highlight the importance of self-regulated learning and dialogical processes to explain …
Acceptance Of Interoperable Electronic Health Record (Ehrs) Systems: A Tanzanian E-Health Perspective, Emmanuel Mbwambo, Herman Mandari
Acceptance Of Interoperable Electronic Health Record (Ehrs) Systems: A Tanzanian E-Health Perspective, Emmanuel Mbwambo, Herman Mandari
Journal of International Technology and Information Management
The study assessed factors that influence the acceptance of interoperable electronic Health Records (EHRs) Systems in Tanzania Public Hospitals. The study applied a hybrid model that combined the Technology Acceptance Model (TAM) and Technology-Organization-Environment (TOE). Snowball sampling technique was applied and a total of 340 questionnaires were distributed to selected clinics, polyclinics and hospitals, of which 261 (77%) received questionnaires were considered to be valid and reliable for subsequent data analysis. IBM SPSS software version 27.0 was employed for data analysis. Findings indicated that relative advantage, compatibility, management support, organizational competency, training and education, perceived ease of use, perceived usefulness, …
Analysis Of The Impact Of Vaccinations On Pandemic Metrics In The New York Metropolitan Area, Oredola A. Soluade, Heechang Shin, Robert Richardson
Analysis Of The Impact Of Vaccinations On Pandemic Metrics In The New York Metropolitan Area, Oredola A. Soluade, Heechang Shin, Robert Richardson
Journal of International Technology and Information Management
This study evaluates the relationship between pandemic cases and vaccination usage, ICU bed utilization, hospitalizations, and deaths in the New York City metropolitan area. The study includes variables for the lockdown period and confirmed infections. The evaluation addresses three periods: (1) before vaccinations, (2) after vaccinations, and (3) the lockdown period. In addition, the number of vaccines per day for the manufacturers (Pfizer, Moderna, and Johnson & Johnson) are included in the study. Comparisons with New Jersey and Connecticut are used to validate that New York statistics are consistent with other states. The results provide a general model of the …