Agile product management as a catalyst for technological innovation

International Journal of Scientific Research Updates, Journal Year: 2024, Volume and Issue: 7(2), P. 009 - 023

Published: April 13, 2024

Agile Product Management (APM) has emerged as a critical driver of technological innovation, enabling organizations to rapidly adapt changing market dynamics and customer needs. This abstract explores the key principles APM its role in fostering innovation today's fast-paced business environment. At core, is collaborative, iterative approach product development that emphasizes flexibility, feedback, continuous improvement. By breaking down complex projects into manageable tasks delivering value incrementally, enables teams respond quickly feedback evolving requirements. One features emphasis on collaboration. involving customers early often process, can ensure their products meet needs expectations. customer-centric not only drives but also helps stay ahead competition. Another important aspect focus cross-functional teams. bringing together individuals with diverse skills backgrounds, fosters culture creativity innovation. Cross-functional are able experiment new ideas, iterate designs, deliver high-quality faster. In addition manage risk more effectively. smaller, pieces, identify address potential issues reducing likelihood costly delays or failures. Overall, powerful catalyst for embracing collaboration, improvement, drive competition landscape.

Language: Английский

---

Optimization of network topology robustness in IoTs: A systematic review

Computer Networks, Journal Year: 2024, Volume and Issue: 250, P. 110568 - 110568

Published: June 6, 2024

Language: Английский

---

Enhancing Communication Networks in the New Era with Artificial Intelligence: Techniques, Applications, and Future Directions

Network, Journal Year: 2025, Volume and Issue: 5(1), P. 1 - 1

Published: Jan. 6, 2025

Artificial intelligence (AI) transforms communication networks by enabling more efficient data management, enhanced security, and optimized performance across diverse environments, from dense urban 5G/6G to expansive IoT cloud-based systems. Motivated the increasing need for reliable, high-speed, secure connectivity, this study explores key AI applications, including traffic prediction, load balancing, intrusion detection, self-organizing network capabilities. Through detailed case studies, I illustrate AI’s effectiveness in managing bandwidth high-density networks, securing devices edge enhancing security communications through real-time anomaly detection. The findings demonstrate substantial impact on creating adaptive, secure, addressing current future challenges. Key directions work include advancing AI-driven resilience, refining predictive models, exploring ethical considerations deployment management.

Language: Английский

---

AI-Enhanced Traffic Prediction and Congestion Control: A Framework for CNF and VNF Networks

International Journal of Scientific Research in Computer Science Engineering and Information Technology, Journal Year: 2025, Volume and Issue: 11(1), P. 117 - 124

Published: Jan. 3, 2025

This article comprehensively analyzes artificial intelligence-driven approaches to traffic prediction and congestion control in Cloud-Native Functions (CNFs) Virtual Network (VNFs) based networks. examines recent advancements predictive analytics dynamic resource allocation, focusing on implementing deep learning frameworks such as Long Short-Term Memory (LSTM) networks for pattern forecasting. demonstrates how continuous models real-time telemetry data integration enable adaptive network responses fluctuating conditions. indicates that AI-enhanced load balancing shaping techniques significantly improve performance, achieving a more efficient distribution of resources across nodes while maintaining consistent Quality Service (QoS). highlights the transformative potential these innovations meeting demanding requirements 5G beyond, offering insights into cost-effective management strategies scalable solutions. Experimental results show substantial improvements latency reduction utilization efficiency, presenting promising direction next-generation telecom service optimization.

Language: Английский

---

Artificial intelligence advances in anomaly detection for telecom networks

Artificial Intelligence Review, Journal Year: 2025, Volume and Issue: 58(4)

Published: Jan. 25, 2025

Language: Английский

---

The Role of Artificial Intelligence in 6G Networks, Architecture, Protocol, Transmission, and Applications

Advances in wireless technologies and telecommunication book series, Journal Year: 2025, Volume and Issue: unknown, P. 115 - 154

Published: Feb. 7, 2025

The 6G wireless communication technology is the successor to 5G cellular-based technique. It aimed at increased bandwidth and higher dimensions of data transmission with measurement less than one microsecond latency communication. Artificial Intelligence (AI) pivotal in establishing computational intelligence infrastructure, storing, transmission, decision-making. With frequencies 6G, sampling rates will surge beyond those achievable (Fifth Generation). Access points gain capacity serve multiple clients through orthogonal frequency-division access concurrently. expected spectrum using up terahertz (THz). guides Quality Service (QoS) This chapter covers a high-level overview role AI architecture, protocols, technologies, applications.

Language: Английский

---

Understanding AI-Driven Threat Detection and Response Systems: A Technical Deep Dive

International Journal of Scientific Research in Computer Science Engineering and Information Technology, Journal Year: 2025, Volume and Issue: 11(1), P. 3074 - 3079

Published: Feb. 18, 2025

This article presents a comprehensive analysis of artificial intelligence-driven threat detection and response systems in modern cybersecurity environments. The examines the evolution security infrastructure through integration advanced machine learning algorithms automated mechanisms. investigates effectiveness multi-tiered architectures detection, behavioral frameworks for user device monitoring, capabilities. demonstrates significant improvements accuracy, times, false positive reduction AI optimization. indicates that quantum computing capabilities promising developments future systems, while maintaining operational efficiency scalability across enterprise deployments.

Language: Английский

---

Optimization Techniques on Quantum and Classical Systems: A Comprehensive Comparative Study

E3S Web of Conferences, Journal Year: 2025, Volume and Issue: 616, P. 02024 - 02024

Published: Jan. 1, 2025

Quantum optimization is a promising field revolutionizing problem-solving across domains. This study compares Particle Swarm Optimization (PSO), Moth Flame (MFO), and Genetic Algorithm (GA) on three platforms : local computer, computer with quantum integration, an IBM machine. Results indicate PSO’s consistent performance all setups, the machine having longer elapsed time. For MFO, optimal solution found using machine, despite its execution Similarly, GA achieves best results These findings suggest that while computers excel in solving complex problems, their time for simpler tasks remains higher than classical setups. Future research should address challenges like noise, limited qubits, high material costs to improve computers’ efficiency availability.

Language: Английский

---

Localized large language model TCNNet 9B for Taiwanese networking and cybersecurity

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: March 20, 2025

Abstract This paper introduces TCNNet-9B, a specialized Traditional Chinese language model developed to address the specific requirements of Taiwanese networking industry. Built upon open-source Yi-1.5-9B architecture, TCNNet-9B underwent extensive pretraining and instruction finetuning utilizing meticulously curated dataset derived from multi-source web crawling. The training data encompasses comprehensive knowledge, DIY assembly guides, equipment recommendations, localized cybersecurity regulations. Our rigorous evaluation through custom-designed benchmarks assessed model’s performance across English, Chinese, Simplified contexts. comparative analysis demonstrated TCNNet-9B’s superior over baseline model, achieving 2.35-fold improvement in Q&A task accuracy, 37.6% increase domain expertise comprehension, 29.5% enhancement product recommendation relevance. practical efficacy was further validated its successful integration into Hi5’s intelligent sales advisor system. research highlights significance domain-specific adaptation localization enhancing large models, providing valuable reference for future developments non-English contexts vertical fields.

Language: Английский

---

Additive Manufacturing for Remedying Supply Chain Disruptions and Building Resilient and Sustainable Logistics Support Systems

Sustainability, Journal Year: 2025, Volume and Issue: 17(6), P. 2783 - 2783

Published: March 20, 2025

Leading industries have implemented various strategic initiatives to enhance the resilience and sustainability of their logistics support systems in response series unforeseen disruptions that significantly impacted supply chains (SCs) incurred substantial costs over past few decades. It is essential assess whether incorporating additive manufacturing (AM) technologies into processes—either as a complementary solution or conjunction with existing strategies—can effectively reduce vulnerabilities modern, complex SCs. AM enable use business models distributed manufacturing, opposed centralized potential create significant change traditional SCs by bringing parts products closer customer. The raw materials necessary for production lower than methods. While this provides cost benefit current structure, there are still challenges, such testing final adjustments printing parameters. shorter delivery times compared methods while also reducing distribution costs. This not only enhances service levels, but lowers inventory across all stages SC. Additionally, can help businesses comply increasingly stringent environmental regulations introduced recent Both AM-based processes it smaller ecological footprints making more sustainable alternative.

Language: Английский

---