Functional Group: IT Operation and Configuration Management

This paper analyzes the current situation and Countermeasures of IT management system, and the necessity of adopting intelligent management in website management, and puts forward the design of open IT operation and maintenance management system based on data mining, so as to improve the system performance by optimizing the system hardware structure and equipment. Based on the development of the existing software and the construction of the information system, combined with the experience of IT operation and maintenance, user needs and advanced IT service management concept, the equipment maintenance management system based on IT operation and maintenance is designed and developed. The system has simple operation and good interactivity. It provides users with the functions of equipment maintenance management and information tracking. It can also query the real-time information according to the actual needs of users, and make the system maintenance The experiment shows that the open IT operation and maintenance management system based on data mining can better meet the needs of users and design requirements.

The impacts on the Operation and Maintenance Process of virtual resources have not been considered in the ITIL processes. Based on the characteristics of the virtual resource management and the process automation method, this paper improves and designs the new IT Operation and Maintenance Processes for virtual resources, includes adding the activities of new event monitoring, event handling, security management, performance and capacity management, and on-line management etc, and also proposed the establishment of the unified IT Operations and Maintenance management team to better support this process. The improved processes have been carried out in the IT Operation and Maintenance management practices of the joint ventures, and greatly improved the efficiency of their IT operations and maintenance works.

Large-scale enterprises face significant challenges in managing and maintaining complex IT infrastructures, especially with the growing adoption of cloud and containerized environments. Configuration management and rehydration processes, crucial for ensuring consistency and rapid recovery, are often time-consuming and error-prone when done manually. This case study explores the transformative impact of Ansible-powered automation on these processes within a large enterprise setting. By leveraging Ansible's agentless architecture, playbook flexibility, and integration capabilities, the organization was able to achieve significant improvements in efficiency, reliability, and scalability. We detail the specific challenges faced, the Ansible-based solutions implemented, and the quantitative results achieved, demonstrating the potential for Ansible to revolutionize configuration management and rehydration practices in modern enterprise IT. The lessons learned and best practices outlined in this study provide valuable insights for organizations seeking to streamline their IT operations and embrace the power of automation.

With the gradual deepening of the influence of artificial intelligence technology on all walks of life, enterprise IT operation and maintenance management is also undergoing changes in a more intelligent and advanced direction. In order to change the practical problems of enterprise IT operation and maintenance management, such as single method and lack of means, this paper analyzes and studies the overall framework of enterprise it intelligent operation and maintenance management technology, and deeply analyzes the key intelligent methods in operation and maintenance management, such as fault prediction, fault analysis, operation and maintenance scheduling, so as to provide support for effectively improving the level of enterprise it intelligent operation and maintenance and systematic support ability.

The evolution of automation in IT operations represents a transformative journey from basic scripting to sophisticated AI-powered solutions, marking a fundamental shift in how organizations approach their technological infrastructure. This article explores the progression through various stages of automation maturity, examining the impact of modern automation frameworks, container orchestration technologies, and artificial intelligence applications in IT operations. The article investigates key developments in configuration management tools, workflow automation, and enterprise implementation strategies across multiple industries, including financial services, healthcare, e-commerce, and telecommunications. Through detailed examination of real-world case studies and implementation patterns, this article highlights the convergence of traditional automation approaches with emerging technologies such as machine learning, predictive analytics, and AIOps. The article encompasses both technical aspects of automation evolution and organizational considerations, including change management strategies, skill development requirements, and governance frameworks necessary for successful automation initiatives in contemporary enterprise environments.

Today, AI is indispensable for driving operational effectiveness in modern organizations. Its pivotal role in successful business operations is widely recognized, significantly enhancing firms‘ competitive edge and reputation. Accurate analysis is imperative before implementing AI initiatives to ensure impactful outcomes. Understanding the current state of AI development is crucial. This article offers a comprehensive review of existing operations management and AI research, shedding light on key domains for future academic exploration. The study's findings furnish valuable insights for operations management and policymaking stakeholders.

This plan describes a configuration management program for K Basins that establishes the systems, processes, and responsibilities necessary for implementation. The K Basins configuration management plan provides the methodology to establish, upgrade, reconstitute, and maintain the technical consistency among the requirements, physical configuration, and documentation. The technical consistency afforded by this plan ensures accurate technical information necessary to achieve the mission objectives that provide for the safe, economic, and environmentally sound management of K Basins and the stored material. The configuration management program architecture presented in this plan is based on the functional model established in the DOE Standard, DOE-STD-1073-93, {open_quotes}Guide for Operational Configuration Management Program{close_quotes}.

Business process management (BPM) is an approach focused on the continuous improvement of business processes, providing for this a collection of best practices. These best practices enable the redesign of business processes to meet the desired performance. IT service management (ITSM) defines the management of IT operations as a service. There are several ITSM frameworks available, consisting in best practices that propose standardizing these processes for the respective operations. By adopting these frameworks, organisations can align IT with their business objectives. The constant need for change, competitiveness and innovation in organisations compels managers to analyse its business processes and find improvement opportunities. Therefore, the objective of this research is to understand how BPM can be used to improve of ITSM processes. An exploratory case study in a multinational company based in Lisbon, Portugal, is conducted for the improvement of the time performance of an incident management process. Data were gained through documentation, archival records, interviews and focus groups with a team involved in IT support service. The results of this study demonstrate how BPM highlighted the current incident management process incongruences. The preliminary evidences of this research indicate that with the application of the remain BPM lifecycle phases may be possible to improve incident management process. During the next months the authors intend to identify the main problems and simulate the appropriate BPM heuristics to understand the impact in the business organisation.

In modern IT infrastructure projects, optimizing system performance and security is crucial for ensuring reliability, efficiency, and compliance. This study explores the role of business analytics in improving IT infrastructure performance and mitigating cybersecurity risks. By utilizing real-world datasets rather than literature-based models, this research applies predictive analytics, machine learning algorithms, and business intelligence tools to enhance IT operations. The findings reveal a 26.7% reduction in CPU usage, 25% improvement in memory utilization, and a 29.2% decrease in network latency, demonstrating the effectiveness of data-driven performance optimization. Additionally, cybersecurity risk assessments using machine learning models resulted in a 14% improvement in threat detection accuracy, a 4% false positive rate, and a 75% reduction in compliance breach risks, ensuring better adherence to security frameworks like ISO 27001 and NIST. The integration of business intelligence dashboards (Tableau, Power BI) enables real-time monitoring of IT risks, enhancing decision-making and proactive threat mitigation. This study contributes to the field by providing a scalable, analytics-driven framework for IT performance enhancement and cybersecurity resilience, bridging the gap between operational efficiency and security risk management. Future research should explore advanced AI-driven automation and real-time adaptive security measures to further strengthen IT infrastructure

The IoT devices are typically shipped with default insecure configurations and vulnerable software stacks rendering host networks exposed to attacks, especially small networks with no administration. We present a network system model for device configuration and operations management. Using this model, we design and implement an autonomous network management platform with device classification and traffic characterization functions integrated in a network gateway. We evaluate the system using a connected home testbed that combines IoT and general-purpose devices.

With the continuous development of information and communication network technology, the number of devices in the network and the running data are increasing geometrically, which brings certain challenges to network configuration, operation and maintenance and management. At present, with the vigorous development of artificial intelligence technology, the concept of intelligent operation and maintenance came into being. The construction of hybrid network knowledge graph is an important part of intelligent operation and maintenance, and hybrid network entity extraction is a key step in its construction. Therefore, in order to effectively identify hybrid network entities, this paper proposes hybrid network entity extraction algorithm based on attention mechanism. Using the multi-head attention mechanism combined with the bidirectional long and short-term memory network and CRF, the accuracy of the neural network model is further improved. In order to verify the effectiveness of the method, we compare the improved algorithm in this paper with the existing classical algorithms and literature algorithms. The experiments show that the algorithm in this paper has certain effectiveness and superiority.

Despite significant advancements in the field of breast cancer therapy (such as chemotherapy or radiotherapy), still, several women fail while having these treatments and die. To overcome certain side effects, nanoparticles (NPs) proved to be a powerful tool as drug delivery vehicles. The major factors that contribute to achieving this target include small size, more drug accumulation, non-toxicity, efficiency, bioavailability, and studies such as optimum pH, temperature, drug release profile, cytotoxicity tests, etc. The arena of nanotechnology has allowed countless researchers to address the role of NPs in the delivery of numerous drugs into breast cancer cells. The NPs synthesized by any of the methods can be tuned to various sizes and shapes. They can also be modified with chemical reagents to contain certain functional groups followed by linkage to drugs via covalent or non-covalent interactions. The present chapter is focused on types of NPs - properties and challenges which are in use for breast cancer therapy. The reported studies clearly indicate that NPs have prospective importance in the controlled release of drugs and refining the lifespan of patients.

Chapter 4 - Factors contributing to nanoparticle toxicity

In the present chapter, we turn our attention to a detailed description of the following two processes that belong to the IT SUPPORT functional group:

Industrial effluents from textile, paper, pharmaceutical and food processing industry are contaminated with high concentration of various dyes. Most of the dyes are aromatic with azo (–N=N–) and nitro (–NO2) functional groups. The effluents containing dyes can affect aquatic life, human health and environment due to toxic, non-biodegradable and carcinogenic nature of dyes. Advanced oxidation processes (AOPs) are known to decolourize and degrade dye effluents. However, a single AOP or any other physicochemical process alone is ineffective for complete degradation of the dye. Therefore, hybrid treatment technologies comprising a combination of AOPs or physicochemical processes have gained recognition in the recent decade for the removal of recalcitrant compounds. In the present chapter, an in-depth evaluation of potential hybrid technologies is performed with a focus on previous literature on hybrid treatment methods for the degradation of dye in wastewater. In addition, limitations of the different hybrid systems are discussed for their better application during wastewater treatment.KeywordsAdvanced oxidation processesDye wastewaterHybrid treatment systemsIndustrial wastewater treatmentPhysicochemical treatment