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Development of Quantum Noise-Based Quantum Random Number Generator (QRNG) Xiang, Yang; Jing, Wang; Wei, Sun
Journal of Tecnologia Quantica Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v1i4.1682

Abstract

The background of this research focuses on the development of a quantum noise-based Quantum Random Number Generator (QRNG) to generate random numbers that are safer and more efficient compared to conventional methods. Quantum fluctuation-based QRNG has the potential to generate more unpredictable numbers, improving security in cryptographic and simulation applications. The purpose of this research is to develop a QRNG system that can generate high-quality random numbers with various experimental settings and conditions. The method used is an experiment measuring quantum fluctuations through a photon detector to generate a random number based on quantum noise, followed by statistical testing to test the quality of the randomness. The results show that quantum noise-based QRNG is able to generate random numbers with better quality than conventional random number generators, with p-values that indicate very high random uncertainty. In addition, these QRNGs can operate at various photon intensities without compromising the random quality produced. The conclusion of this study is that quantum noise-based QRNG offers a safer and more efficient solution in generating random numbers for applications that require high randomness. Further research is needed to improve efficiency and overcome implementation obstacles in the real world.
AI-Augmented Creative Writing: Evaluating Machine-Human Collaboration in Narrative Innovation Dara, Ardi Azhar; Li, Zhang; Jing, Wang
Journal of Loomingulisus ja Innovatsioon Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/innovatsioon.v2i3.2357

Abstract

This study examines how artificial intelligence (AI) can augment human creativity in the field of narrative writing through a collaborative approach. The research addresses the growing influence of AI-based tools in creative industries and the need to understand their role in enhancing innovation rather than replacing human authorship. The study aims to evaluate the effectiveness of machine-human collaboration in generating original and innovative storylines. Using a mixed-methods design, twenty creative writing teams were engaged in structured workshops combining generative AI tools with traditional writing processes. Data were collected from narrative outputs, participant observations, and post-workshop interviews, and analyzed using thematic coding and comparative quality assessment. Findings indicate that AI-assisted teams produced more diverse narrative structures and demonstrated a significant increase in creative risk-taking compared to control groups. The results suggest that AI can serve as a valuable co-creator when guided by intentional human direction. This research concludes that rather than replacing writers, AI technologies can strengthen creative processes, supporting a hybrid model where human judgment shapes and refines machine-generated contributions.  
Polymers and Composites for Energy Storage Applications Mei, Chen; Jing, Wang; Wei, Sun
Research of Scientia Naturalis Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v1i4.1576

Abstract

The increasing demand for efficient energy storage solutions has driven research into polymers and composites. These materials offer unique advantages, such as lightweight properties, flexibility, and tunable conductivity, making them ideal candidates for energy storage applications. The exploration of innovative polymers and composites is essential for improving energy density and cycle life in storage devices. This research aims to evaluate the performance of various polymers and composites in energy storage applications. The focus is on understanding their electrochemical properties and how modifications can enhance their performance in batteries and supercapacitors. A systematic review of recent advancements in polymer and composite materials was conducted, alongside experimental assessments of selected materials. Performance metrics such as conductivity, energy density, and stability were evaluated using electrochemical testing methods, including cyclic voltammetry and galvanostatic charge-discharge tests. The findings indicate that specific polymers and composites exhibit enhanced performance in energy storage applications. Notable improvements in conductivity and energy density were observed, particularly with the incorporation of conductive fillers. Additionally, the stability of the materials under cycling conditions showed promising results, suggesting their potential for practical applications.The research highlights the significant potential of polymers and composites in advancing energy storage technologies. Continued exploration and optimization of these materials can lead to the development of more efficient and durable energy storage solutions, addressing the growing demands for sustainable energy systems.
Surface Modification of Gold Nanoparticles to Improve Cancer Cell Targeting Mei, Chen; Jing, Wang; Yang, Liu
Journal of Biomedical and Techno Nanomaterials Vol. 1 No. 4 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v1i4.1809

Abstract

Gold nanoparticles (AuNPs) are promising agents for cancer therapy due to their unique properties, but effective targeting remains a challenge. Surface modification with specific ligands can enhance targeting efficiency. To develop and optimize surface-modified AuNPs to improve targeting of cancer cells, enhancing therapeutic outcomes while minimizing side effects. The study employed theoretical modeling, laboratory experiments, and in vivo testing. Cancer cell lines (MCF-7, A549, PC-3) and mouse models with human tumors were used to evaluate targeting efficiency. Instruments included TEM, SEM, DLS, zeta potential analysis, and HPLC. Surface-modified AuNPs showed an 80% increase in cancer cell binding compared to unmodified AuNPs. In vivo studies demonstrated a 70% reduction in tumor volume in treated mice. Stability tests indicated consistent performance under various biological conditions. Surface modification of AuNPs with specific ligands significantly enhances their targeting ability and therapeutic efficacy against cancer cells. Further clinical trials are necessary to validate these findings for clinical application.  
Creative Content Monetization: Case Studies on Digital Platforms Kadeni, Kadeni; Santoso, Ekbal; Jing, Wang
Journal of Social Entrepreneurship and Creative Technology Vol. 2 No. 2 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jseact.v2i2.2059

Abstract

The rise of digital platforms has transformed the way creative content is produced, shared, and consumed, opening up new avenues for content creators to monetize their work. However, despite the rapid growth of digital content, challenges persist in understanding the most effective strategies for monetization. This research aims to explore the various monetization models used by content creators on digital platforms, focusing on case studies across YouTube, Patreon, Instagram, and TikTok. The goal is to identify key factors that contribute to successful content monetization and to analyze the potential for these models to be applied across different types of creative content. A qualitative research approach was used, with in-depth case studies of five content creators from various creative fields, including music, visual arts, and writing. Data were collected through interviews, content analysis, and platform performance metrics. The findings indicate that a combination of audience engagement, consistent content production, and platform-specific strategies (such as ads, subscriptions, and merchandise) were critical to successful monetization. Additionally, creators who diversified their revenue streams were more likely to achieve long-term financial sustainability. The research concludes that the future of creative content monetization lies in the development of personalized, audience-centric models and the integration of emerging technologies like AI and blockchain. These findings provide valuable insights for content creators seeking to optimize their monetization strategies in the ever-evolving digital landscape.