Publications

[Overview of patents on targeted genome editing technologies and their implications for innovation and entrepreneurship education in universities].

Zinc finger nuclease, transcription activator-like effector nuclease, and clustered regularly interspaced short palindromic repeats/Cas9 nuclease are important targeted genome editing technologies. They have great significance in scientific research and applic

Research on Information Development of Innovation and Entrepreneurship Education for University Students Based on Wireless Communication

Wireless communication and innovation and entrepreneurship education is undoubtedly one of the current hot issues in the field of human resource development and education. One emphasizes the change of educational technology, means and methods from the micro le

Emerging Technologies in Digital Learning Ecosystems: Implications for Online Education and Business Innovation

The integration of emerging digital technologies into online learning platforms has significantly transformed modern education systems and business operations worldwide. Online platform learning has evolved from a supplementary educational method into a primar

Standardization as emerging content in technology education at all levels of education

Integration of standardization into different levels of technology education has surfaced as a critical issue for educational practitioners and policy makers at national and regional (APEC, EU) level. In this paper, we describe and analyze empirical data colle

Study of fidelity of synthetic imagery for artificial intelligence (AI) and machine learning (ML) problems

Computer Security with Artificial Intelligence, Machine Learning, and Data Science Combination

Implementation of Data Mining Algorithm for Clustering of Palm Oil Harvested Data

Palm oil is one of the plantation commodities that has a strategic role in Indonesia's economic development. In this study, we will discuss oil palm yields at PPKS Marihat, one of the Oil Palm Research Center branches located in Simalungun Regency, Medan, Nort

Predicting Mandibular Bone Growth Using Artificial Intelligence and Machine Learning: A Systematic Review

Introduction The accurate prediction of mandibular bone growth is crucial in orthodontics and maxillofacial surgery, impacting treatment planning and patient outcomes. Traditional methods often fall short due to their reliance on linear models and clinician ex

Applications of Machine Learning and Artificial Intelligence in Intelligent Transportation System: A Review

Analysis of K-Means Algorithm for Clustering of Covid-19 Social Assistance Recipients

During the Covid-19 pandemic, the government provided assistance distributed through each sub-district throughout the province of Indonesia, one of which was the Pahlawan Village in the East Siantar District Pematangsiantar City. So far, the assistance provide

Navigating Technical Debt in the Evolving Landscape of Machine Learning and Artificial Intelligence

Role of Artificial Intelligence and Machine Learning for Climate Disaster Management and Earth Resource Management

Appendix B: Introduction to TF 2

CHALLENGES AND OPPORTUNITIES OF IMPLEMENTING ARTIFICIAL INTELLIGENCE(AI) AND MACHINE LEARNING IN NIGERIAN LIBRARIES

Machine Learning and Artificial Intelligence in Credit Scoring and Fraud Detection

Probabilistic Models

Leveraging Artificial Intelligence and Machine Learning to Profile Internet Users through Media Content

Artificial Intelligence-Driven Cybersecurity Framework for Enterprise Threat Detection: A Machine Learning Approach

The increasing complexity of cyber threats has exposed the limitations of traditional signature-based intrusion detection systems, creating a need for intelligent and adaptive cybersecurity solutions. This study proposes an artificial intelligence-driven cyber

Assessing Technology Readiness for Artificial Intelligence and Machine Learning based Innovations

Usage of Machine Learning Methods for Cause-Effect Graph Feasibility Prediction

Cause-effect graphs (CEGs) are usually applied for black-box testing of complex industrial systems. The specification process is time-consuming and can result in many errors. In this work, machine learning methods were applied for predicting the feasibility of