Processing Requirements Research Articles

Building trustworthy smart cities: A systems engineering approach to data engineering at the Smart Metrology Campus

This paper introduces the concept of a Smart Metrology Campus, with its primary objective being to facilitate reliable data science in the realm of smart cities. This is achieved by connecting sensor and meter data with metadata, particularly from the field of metrology. The establishment of a robust data infrastructure, responsible for collecting this data, requires a strategic data engineering approach. The challenge lies in identifying a data engineering approach that is well-suited for design considerations characterized by high demands in scale, complexity, sensitivity, and reliability. To address this challenge, the paper conducts a comprehensive analysis of the applicability of existing guides for data engineering, alongside other guiding processes from related disciplines such as data mining, data science, and systems engineering. As a result, systems engineering is identified as a highly relevant approach for data engineering meeting the needs of smart cities. The subsequent sections explain how this approach can be utilized and adapted for the specific requirements of a data engineering process in smart cities.

A systematic review of machine learning and deep learning techniques for anomaly detection in data mining

The growing use of the internet has increased the threat of cyberattacks. Anomaly detection systems are vital for protecting networks by spotting irregular activities. Various studies investigated anomaly detection techniques without a systematic approach. So far, the existing reviews mainly concerned time series and data streaming methods almost neglected the growing interest in graph-based data mining techniques which are vital in social networks, finance, and IoT domains. Following PRISMA guidelines, this systematic review examines anomaly detection methods applied to time series, data streaming, and graph-based data from 2018 to 2023. A total of 34 papers were selected from four key databases ScienceDirect, Scopus, Web of Science, and IEEE. In addition, this review addressed several issues with existing techniques including low scalability, explainability, and interpretability for real-time anomaly detection systems. In modern applications where data structures are complex, and processing requirements are high these traditional techniques are insufficient for real-time data processing. Finally, our study demanded more advanced, complex methods to address these evolving challenges.

Navigating AAMI ST108 Water Quality Requirements for Safe Processing of Medical Devices.

Water quality plays a critical role in health care, particularly in the processing of medical devices. This article highlights the infection control risks associated with water sources and the regulatory requirements for water management plans in health care facilities. The guidance on water quality has evolved from the initial technical information report provided by the Association for the Advancement of Medical Instrumentation in 2014 to the more recent 2023 publication of the American National Standards Institute and Association for the Advancement of Medical Instrumentation standard for water used in medical device processing. The new standard emphasizes the importance of consistent water and steam quality in instrument processing and outlines the chemical and microbiological parameters for water quality. This article also addresses the challenges of implementing these standards, discusses the implications for patient safety and instrument integrity, and provides strategies for health care teams to ensure compliance.

The Regulatory Landscape of Biobanks In Europe: From Accreditation to Intellectual Property

Biobanks are necessary resources for the storage and management of human biological materials, such as biofluids, tissues, cells, or nucleotides. They play a significant role in the development of new treatments and the advancement of basic and translational research, especially in the field of biomarkers discovery and validation. The regulatory landscape for biobanks, which is necessary to safeguard both privacy and scientific discoveries, exhibits significant heterogeneity across different countries and regions. This article outlines the standards that modern biobanks should fulfill in the European Union (EU), including general, structural, resource, process, and quality requirements. Special attention is given to the importance of transparency and donor consent following the General Data Protection Regulation (GDPR) and the ISO 20387:2018, the international standard specifies general requirements for biobanks. A dedicated section covers the preparation of donor information materials, emphasizing consent for research involvement and personal data processing. The delicate balance between donors' privacy rights and scientific research promotion is also discussed, with a focus on the patenting and economic use of biological material- derived inventions and data. Considering these factors, it would be warranted to refine legal frameworks and foster interdisciplinary collaboration to ethically and responsibly expand biobanking.

Energy-Related Assessment of a Hemicellulose-First Concept—Debottlenecking of a Hydrothermal Wheat Straw Biorefinery

A hemicellulose-first approach can offer advantages for biorefineries utilizing wheat straw as it combines lignocellulose fractionation and potentially higher added value from pentose-based hemicellulose. Therefore, a tailored hydrothermal concept for the production of xylooligosaccharides and xylan was investigated. The focus was on assessing the energy requirements and potential improvements based on experimental results. The wheat straw pretreatment and the downstream processing of hemicellulose hydrolysate were modeled at a scale of 30,000 tons of wheat straw dry mass per year. The results confirmed that the hydrothermal concept can be implemented in an energy-efficient manner without the need for additional auxiliaries, due to targeted process design, heat integration and a high solids loading during hydrolysis. The resulting specific energy requirements for pretreatment and hydrolysate processing are 0.28 kWh/kg and 0.13 kWh/kg of wheat straw dry mass, respectively. Compared to thermal hydrolysate processing alone, the combination of a multi-effect evaporator and pressure-driven ultrafiltration can reduce the heating and cooling energy by 29% and 44%, respectively. However, the ultrafiltration requirements (e.g., electrical energy, membrane area and costs) depend heavily on the properties of the hydrolysate and its interactions with the membrane. This work can contribute to the commercially viable ramp-up of wheat straw multi-product biorefineries.

Analysis of Temperature and Stress Fields in the Process of Hot-Rolled Strip Coiling

During the coiling process of a hot-rolled strip, with the increasing layers the temperature and stress distribution inside the coil constantly change and interact with each other. Due to the contact with the sleeve and the transition of the heat exchange state, it is inaccurate to consider the temperature of the whole coil as the coiling temperature set by the process requirement. Meanwhile, due to the periodic interlayer contact in the radial direction, the relation between stress and deformation is nonlinear. For the coiling process, it is difficult to consider the above factors using conventional methods. Therefore, an incremental model has been established to couple the temperature and stress of the coil. In order to obtain the mechanical properties of the strip and radial elastic modulus of the coil, tensile tests and laminated compression experiments are conducted at different temperatures. The effects of changes in strip thickness, coiling tension, and initial temperature of the sleeve on the stress and the temperature inside the coil are studied. Finally, by comparing the model results with measurements and analytical solutions, the effectiveness of the incremental coupled model is verified and the errors caused by the analytical method are analyzed.

Examining the Contours and Challenges of National Cybercrime Reporting Portal in Countering Digital Financial Frauds

Digitalization and ease of financial transactions have spurted a ubiquitous rise in cybercrimes. In 2021, 60.8 per cent of reported cybercrime cases registered were for the motive of fraud. To tackle mounting digital financial fraud complaints, the National Cybercrime Reporting Portal was created by the Indian Cyber Crime Coordination Centre and the Ministry of Home Affairs. The portal is an integrated platform where stakeholders, such as law enforcement agencies, banks, financial intermediaries and others, are connected to prevent the outflow of money from the system, as money once out of the system becomes untraceable and non-retrievable. The portal enables requests to be sent to identified stakeholders by law enforcement authorities to block financial transactions or create a lien on the disputed money while the money is with them. The article has been written against the backdrop of Herbert Packer’s two models of the criminal process, describing two competing goals that underlie criminal legal regimes: the crime-control model and the due process model. As crime is committed in cyberspace and technology is developed to counter it, often the urgency of resolving the crime and the opacity surrounding the technology, blur the lines of permissible and impermissible actions. The article argues that this technical solution created for tackling digital financial frauds is far from perfect, and, at best, a quick fix while larger, looming questions remain unanswered. Through a series of high court cases, the article brings forth how due process requirements are often sidelined in favour of the more immediate goal of crime control in the guise of this PoliceTech, even as questions of the efficiency of the tech remain unaddressed. Nonetheless, the article recommends reforms to ensure the safe deployment of PoliceTech in India, minimize public harm and create accountability for misuse of harms arising from technology.

A Diffusion–Attention-Enhanced Temporal (DATE-TM) Model: A Multi-Feature-Driven Model for Very-Short-Term Household Load Forecasting

With the proliferation of smart home devices and the ever-increasing demand for household energy management, very-short-term load forecasting (VSTLF) has become imperative for energy usage optimization, cost saving and for sustaining grid stability. Despite recent advancements, VSTLF in the household scenario still poses challenges. For instance, some characteristics (e.g., high-frequency, noisy and non-stationary) exacerbate the data processing and model training procedures, and the heterogeneity in household consumption patterns causes difficulties for models with the generalization capability. Further, the real-time data processing requirement calls for both the high forecasting accuracy and improved computational efficiency. Thus, we propose a diffusion–attention-enhanced temporal (DATE-TM) model with multi-feature fusion to address the above issues. First, the DATE-TM model could integrate residents’ electricity consumption patterns with climatic factors. Then, it extracts the temporal feature using an encoder and meanwhile models the data uncertainty through a diffusion model. Finally, the decoder, enhanced with the attention mechanism, creates the precise prediction for the household load forecasting. Experimental results reveal that DATE-TM significantly surpasses classical neural networks such as BiLSTM and DeepAR, especially in handling the data uncertainty and long-term dependency.

Synchronized Multi-Augmentation with Multi-Backbone Ensembling for Enhancing Deep Learning Performance

This study introduces a novel technique called Synchronized Multi-Augmentation (SMA) combined with multi-backbone (MB) ensembling to enhance model performance and generalization in deep learning (DL) tasks in real-world scenarios. SMA utilizes synchronously augmented input data for training across multiple backbones, improving the overall feature extraction process. The outputs from these backbones are fused using two distinct strategies: the averaging fusion method, which averages predictions, and the dense fusion method, which averages features through a fully connected network. These methods aim to boost accuracy and reduce computational costs, particularly in Edge Intelligence (EI) systems with limited resources. The proposed SMA technique was evaluated on the CIFAR-10 dataset, highlighting its potential to enhance classification tasks in DL workflows. This study provides a comprehensive analysis of various backbones, their ensemble methods, and the impact of different SMAs on model performance. The results demonstrate that SMAs involving color adjustments, such as contrast and equalization, significantly improve generalization under varied lighting conditions that simulated real-world low-illumination conditions, outperforming traditional spatial augmentations. This approach is particularly beneficial for EI hardware, such as microcontrollers and IoT devices, which operate under strict constraints like limited processing power and memory and real-time processing requirements. This study’s findings suggest that employing SMA and MB ensembling can offer significant improvements in accuracy, generalization, and efficiency, making it a viable solution for deploying DL models on edge devices with constrained resources under real-world practical conditions.

ОРГАНІЗАЦІЯ СИСТЕМИ ЗАХИСТУ ЦИФРОВОЇ ІНФОРМАЦІЇ У ФІНАНОВОМУ ОБЛІКУ

Abstract. Introduction. The constant development of technologies, changing forms of threats and the need to adapt to new conditions will require organizations to constantly improve their security systems. The purpose of this work is to systematize theoretical provisions and substantiate practical recommendations regarding the organization of protection of digital financial accounting data. Methods. In the process of research, the method of induction was used at the stage of collecting, processing and systematization of the received information, the method of analysis and synthesis - to combine the constituent elements of economic phenomena in a single process. Results. The essential characteristics of the concepts of information security, digital security and data cyber security in the context of economic security of the enterprise are revealed. A set of measures in the system of organizing digital security of financial accounting data has been identified. National and international legal acts, standards and recommendations define mandatory requirements for data storage, processing and transmission, thus providing a legal basis for the implementation of information security policies. The main directions of state policy in the field of information security have been determined. The state in which business entities currently work is accompanied by constant cyber-attacks both on the enterprises themselves and on the totality of their digital data in the field of accounting and taxation. The main measures to ensure cyber security for critical infrastructure enterprises have been determined. They singled out the main problems of digital information protection in accounting, namely: data leakage; software attacks; phishing and social engineering; malware. The main methods of preventing cyber threats are summarized. Recommendations on the organization of the system for ensuring the security of digital data in financial accounting have been formed. The actions of the accounting staff of the enterprise or the enterprise of the partner, which may create a threat of information leakage, are singled out. A set of information sources in need of protection has been identified. Conclusions. The digital information protection system should become an element of the company's accounting policy, and its implementation will contribute to the economic security of the business entity.

5G/6G Roadmap Creation and Packaging Challenges

Millimeter-wave (mmWave) frequencies unlock the true potential of 5G. The ultra-wide bandwidths enable faster wireless connection speeds and high capacity with low latency, providing the ideal solution to meet increasing industry and government demands. Many mobile network operators started deploying commercial 5G mmWave networks in 2020. All have massive mmWave deployment plans on their roadmaps. In response, 5G chipset, device, and base station makers are ramping up their design and manufacturing powers to bring more 5G mmWave services to market. It should be noted that 5G requires a complex new ecosystemThe key to enabling this architecture is packaging and system integration, especially involving an effective antenna structure and RFIC communication in cost-effective, small form-factor packages. As full speed development, demonstration and qualification of mmWave systems have accelerated in this decade, different design and packaging architectures are emerging. This PDC will cover two major topics: (1) Industry roadmapping activities summarizing the technology needs in materials, material characterization and electrical test and (2) integration and packaging options providing a comprehensive landscape of package development including FOWLP as well as laminate/glass based packaging. The specific requirements of materials and process needs (low dielectric material, copper roughness requirements) will be discussed. Product application spaces ranging from mobile/handheld to network infrastructures and automotive/satellite radars are highlighted. Key aspects and guidelines towards a cost/performance trade-off analysis will be summarized.

Development of the structure of a cyberphysical control system for the process of tailored induction heating of a steel billet

The article is devoted to the development of the structure of a cyberphysical control system for the process of zone induction heating, widely used in modern industrial production during the heat treatment of metal products for various purposes. An analysis of the range of products manufactured using induction heat treatment and the advantages of using induction heating systems has shown a wide range of applications of this method of heat treatment in modern production and great opportunities for automation and optimization of processes associated with induction heating of products. This fact indicates the relevance of the development of various kinds of intelligent control systems in relation to the processes of industrial induction heating of metal blanks and semi-finished products. The article describes the induction method of zone heat treatment of metals, its advantages over flame heat treatment methods and the range of products manufactured using it. A description of the billet-inductor system is presented, for which the structure of a cyberphysical control system for the process of zone induction heating has been developed. The technological requirement for the final temperature distribution on the surface of the workpiece and the factors influencing the deviation of the temperature distribution from that required in the process of zone induction heating are considered. A list of possible disturbing influences is given, requirements for the technological process are formulated, control principles are described and, based on this, the structure of the zone induction heating process control system, which belongs to the class of cyberphysical process control systems, is developed.

Can Reuse of Stormwater Detention Pond Water Meet Community Urban Agriculture Needs?

Urbanization and population growth in coastal communities increase demands on local food and water sectors. Due to this, urban communities are reimagining stormwater pond infrastructure, asking whether the stormwater can be used to irrigate food and grow fish for local consumption. Studies exploring this feasibility are limited in the literature. Driven by a community’s desire to co-locate community gardens with stormwater pond spaces, this research monitored the water quality of a 23.4-hectare stormwater pond located in East Tampa, Florida over one year using the grab sample technique and compared the results with U.S. Environmental Protection Agency (EPA) reuse recommendations, EPA national recommended water quality criteria for aquatic life, and human health. pH and conductivity levels were acceptable for irrigating crops. Heavy metal (arsenic, cadmium, copper, lead, and zinc) concentrations were below the maximum recommended reuse levels (100, 10, 200, 5000 and 2000 µg/L, respectively), while zinc and lead were above the criteria for aquatic life (120 and 2.5 µg/L, respectively). E. coli concentrations ranged from 310 to greater than 200,000 MPN/100 mL, above the 0 CFU/100 mL irrigation requirements for raw food consumption and 200 CFU/100 mL requirements for commercial food processing. Synthetic organic compounds also exceeded criteria for human health.

Leveraging Microalgae to Achieve Zero Hunger: Enhancing Livestock Feed for Nutritional Security

Achieving “Zero Hunger” (SDG 2) requires overcoming complex challenges, especially in vulnerable communities in developing countries. Livestock plays a key role in food security, but limited resources threaten productivity, prompting interest in innovative solutions like microalgae supplementation in ruminant diets. Microalgae offer potential benefits by enhancing productivity and nutrition while addressing local protein deficiencies. However, barriers such as economic costs, processing requirements, and resistance to changing traditional feeding practices present challenges. This review examines the feasibility of microalgae-based livestock feed as a sustainable strategy to improve food security, particularly in arid, climate-affected regions. Biomass yield estimates suggest that small-scale cultivation can meet livestock nutritional needs; for example, a 22-goat herd would require approximately 88 g of microalgae per day to enrich meat with polyunsaturated fatty acids. Semi-continuous production systems could enable smallholders to cultivate adequate biomass, using local agricultural resources efficiently. This approach supports food security, improves meat quality, and strengthens community resilience. Collaboration among researchers, extension services, and local farmers is essential to ensure the effective adoption of microalgae feed systems, contributing to a sustainable future for livestock production in vulnerable regions.

Development of a Novel Retrofit Framework Considering Industry 4.0 Concepts: A Case Study of a Modular Production System

Retrofitting legacy systems provides significant advantages by addressing compatibility issues with new devices and technologies, meeting current process requirements, and increasing security and regulatory compliance. The process starts by collecting requirements and evaluating the legacy system’s attributes and limitations, followed by integrating modern technologies to improve efficiency, streamline processes, and enhancing performance and interoperability while leveraging existing facilities to reduce costs. A systematic approach ensures that updates align with modern technological standards, with performance evaluations conducted via qualitative and quantitative methods and system maturity assessed according to the Reference Architecture Model for Industries 4.0 (RAMI 4.0 model’s) criteria for intelligent factories. By incorporating digital twin (DT) capabilities, which replicate the physical state of systems and provide real-time data updates, the retrofit strategy aligns the physical system with Industry 4.0 contexts, facilitating continuous improvement and seamless integration with modern processes. The goal is to advance the legacy system technologically to ensure seamless integration with contemporary processes, validated through RAMI criteria analysis for smart factories. As part of this process, digital twin architecture was built. This architecture was the basis for building and operating digital twins in the process. The methodology was used to enhance and transform legacy systems, creating the foundation for creating a fully digital twin. Using this method, these systems can be updated to meet the requirements of Industry 4.0. This ensures that they can work with new systems and share data in real time, which improves general operations.

Comprehensive Analysis of Milling Performance and Multi-Objective Parameter Optimization for YG6C Milling Tool

Numerous conflicting objectives exist in the engineering field, and resolving these conflicts to reduce costs constitutes a problem that demands top-priority consideration. A model for tool wear and a multi-quadratic regression model for milling forces were developed to accurately predict the trends of wear on the rake face of the milling tool and the variations in milling forces. The influence of milling parameters (spindle speed, n; feed rate, vf; axial milling depth, ap) on both the wear of the rake face and milling force was analyzed by means of orthogonal experiments. The findings indicated that the impact of these parameters on the wear ranked in the following order: n > vf > ap. In contrast, for milling force, F, the ranking was ap > vf > n. Utilizing MATLAB’s genetic algorithm, an optimization procedure was conducted with multiple objectives including the wear of the rake face, milling force, and material removal rate; subsequently, a Pareto optimal solution set was generated for milling parameters based on practical processing requirements.

Multi-objective mixed-model assembly line balancing with hierarchical worker assignment: A case study of gear reducer manufacturing operations

Assembly lines, generally speaking, can reduce production costs, shorten cycle times, and achieve higher quality levels. Since the current market is characterized by increasing product variability, mixed-model assembly lines, in which similar product models can be assembled simultaneously, are more suitable to respond to varied market demands than traditional single-model assembly lines. In addition, in an assembly line, tasks often differ in processing requirements, and workers may have different qualification levels. This study, therefore, aims to construct models for the multi-objective mixed-model assembly line balancing problem with hierarchical worker assignment (MO-MALBP-HW). The goal is to generate a suitable plan for a mixed-model assembly line balancing problem considering the constraint of a hierarchical workforce, the cost of a hierarchical workforce, and production cycle time. When the problem is simple, it can be solved by a mixed integer programming (MIP) model. When the problem becomes complex, it can be solved by a multi-objective genetic algorithm (MOGA) and a non-dominated sorting genetic algorithm II (NSGA-II) to obtain a near-optimal solution. The implementation of this model can effectively manage the multi-objective mixed-model assembly line balancing plan, thereby improving plant efficiency and reducing cost.

A Novel 49-Level Inverter Topology with Reduced Component Count and Total Standing Voltage for PV Energy Systems

This paper introduces a novel 49 Level (49-L) inverter topology designed to overcome the limitations of traditional inverters in photovoltaic (PV) renewable energy systems. This design focuses on minimizing component count and total standing voltage (TSV) at high output levels, making it versatile for various applications. The proposed inverter incorporates a modified packed H-Bridge unit and basic units to optimize component usage and reduce switch voltage stress. Mathematical formulations for calculating switching angles are provided, simplifying switching signal generation and reducing processing requirements. The 49-level inverter undergoes rigorous testing under different load conditions, with analysis emphasizing key performance metrics such as total harmonic distortion (THD), switch voltage stress, TSV, and efficiency. Its suitability for PV system integration - particularly in standalone systems - is demonstrated, highlighting its potential for renewable energy applications. The obtained results unveil that the proposed inverter achieves low THD for voltage and current, meeting IEEE 519 standards. The voltage THD is found to be at the value of 1.66% under all loads. The current THD is found to be at 1.66% under resistive load and ranges from 0.11% to 0.14% under RL loads. Moreover, the inverter's efficiency - depending on load conditions - is found to range from 96% to 98%. Additionally, the proposed inverter performs well under dynamic conditions, with smooth transitions during changes in irradiation levels and load types. Furthermore, this topology is the most cost-effective compared to other recent multilevel inverter (MLI) designs. Finally, the proposed 49-level inverter offers a promising solution for PV renewable energy systems, delivering high power quality, efficiency, and flexibility.

Research Progress in the Field of MapReduce Framework Based on Serverless Computing

In recent years, big data technology has presented a rapid development trend with each passing day, and its application in all walks of life is becoming more and more extensive and in-depth. At the same time, traditional computing frameworks are gradually showing serious challenges in performance bottlenecks and scalability in the face of massive data processing requirements, making it difficult to meet the growing needs of data processing and highly concurrent access scenarios. Firstly, this paper introduces MapReduce framework and serverless platforms, and then introduces the MapReduce framework model based on serverless platforms from several parts of implementation, application scenarios and technical principles. This paper argues that the serverless-based MapReduce framework will provide a more efficient and flexible solution for big data processing and analyzing, which is of great significance in promoting the development of data-driven decision-making and intelligent applications. The main content of this paper will be introduced from the basic overview of MapReduce computing framework and serverless platform, the implementation of serverless-based MapReduce computing framework, technical principles and application scenarios.

Sustainable ballistic solutions for recycling silkworm cocoon waste into high-performance bulletproof materials

ABSTRACT This study aims to develop a method for producing ballistic panels meeting NIJ Level IIIA standards by integrating silkworm cocoon waste (SCW) as reinforcement and utilizing bias fabric through cold pressing. Various SCW quantities (100 g designated as P2, 150 g designated as P3, and 225 g designated as P4) alongside 50 g of resin and 230 g of bias fabric were used, comparing six (type I) and three (type II) layer patterns. Panels with SCW exhibit enhanced mechanical properties, particularly in type II layouts, which show superior performance in tensile, impact, and flexural resistance. Ballistic impact tests reveal that only type I-P3, I-P4, II-P3, and II-P4 composite panels effectively stop bullet penetration, with BFS measurements ranging from 10.6–14.6 mm, below the 44 mm NIJ standard limit. Consequently, the study indicates that II-P3 is selected for producing bulletproof armor compliant with NIJ Level IIIA standards, supported by the method's simplicity, cost-effectiveness, and consistent outcomes. The decision to use II-P3 for producing ballistic panels is made due to its simplified processing requirements. Upon calculating the total component cost for panels sized at 150 × 150 mm, it is established that each panel has a cost of $1.5.