Collaboration modes and advantages in supply chain

This research aims to address supply chain collaboration with a perspective of broader three-dimensional relationship, not a linear two-dimensional relationship discussed broadly in previous research. Case study was adopted for this research, and data collection was mainly conducted via interview. The research results highlighted that supply chain collaborations are common practice across all levels of the pharmaceutical supply chain. The results also indicated that the different strengthen levels of barging power among collaborative partners will influence the achieved advantages at different supply chain levels, including strategic, operational and political levels

Smart manufacturing and supply chain management

In the fourth industrial revolution, smart manufacturing will be characterized by adaptability, resource efficiency and ergonomics as well as the integration of customers and business partners in business and value processes. Business model, operations management, workforce and manufacturing process all face substantial transformations to reasoning the manufacturing process. This paper explores the impacts of smart manufacturing on supply chain management, and develops several propositions to improve supply chain performance under the context of smart manufacturing

Expanding the Horizons of Manufacturing: Towards Wide Integration, Smart Systems and Tools

This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems

Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

Cyber Security

This open access book constitutes the refereed proceedings of the 18th China Annual Conference on Cyber Security, CNCERT 2022, held in Beijing, China, in August 2022. The 17 papers presented were carefully reviewed and selected from 64 submissions. The papers are organized according to the following topical sections: ​​data security; anomaly detection; cryptocurrency; information security; vulnerabilities; mobile internet; threat intelligence; text recognition

The Quality Control of Puerariae Lobatae Radix and Puerariae Thomsonii Radix

Puerariae Lobatae Radix (PLR) and Puerariae Thomsonii Radix (PTR) are traditional Chinese medicines used interchangeably in clinical practice, even though they possess significantly different chemical profiles. The aim of this thesis was to differentiate PLR from PTR using various analytical instruments coupled with chemometrics. Morphological results illustrate PLR possessed distinct macroscopic and microscopic features as compared to PTR. UPLC results reveal isoflavonoids were the major chemical constituents in both species, with the content of puerarin in PLR significantly greater than in PTR. PLS-DA models demonstrate both UPLC and HPTLC chromatographic fingerprints were effective in differentiating PLR from PTR. PLSR coupled with Raman spectra was able to predict the TPC and antioxidant capacities of PLR and PTR. The pharmacological results illustrate PLR possessed significantly greater anti-diabetic, cytoprotective and anti-cancer activities as compared to PTR. In summary, the results reveal the chemical fingerprints coupled with chemometrics was effective in differentiating PLR from PTR, and PLR was morphologically, chemically and pharmacologically different from PTR. This thesis provided further insight into the comprehensive nature of the quality control of two similar species and recommends changes to their descriptions in the pharmacopoeias. This will ultimately improve the quality, safety and efficacy of herbal products

Customer value assessment of Sichuan Mobile

The present research aims to contribute with the evaluation and a segmentation index criterion of the customer group value in order to improve knowledge to the telecommunication industry, in value assessment and in market subdivision based on customer value. This thesis gives practical instrument measure and guiding suggestions to a deeper customer value assessment, combining characteristics of the communication industry in China, based on outstanding domestic and foreign research results and taking the group customers of China Mobile Sichuan Company. A first brief crossing between theoretical backgrounds of customer value assessment, segmentation concept and group customer, allowed the selection and choices of the methodology and the variables that influence group customer value. The following empirical step complemented the development of the assessment index system to calculate the group customer value and the following cluster analysis. The results obtained included the industry experts' experience, which help the identification of the 14 factors that influence the group customer value and the data analysis from 2000 group customers, which has been extracted from the mobile BOSS system. Factor analysis and analytic hierarchy process (AHP) method are used to calculate weights of indexes. Finally, based on current value, potential value, social value and the total value, clusters with typical characteristics are discovered using K-means clustering method. And corresponding marketing strategy is put forward.Esta tese avalia o Valor de grupos de clientes, no âmbito da grande empresa chinesa de telecomunicações móveis, a Sichuan Mobile. O presente estudo contribui para a análise da avaliação e segmentação de grupos de clientes, nomeadamente no mercado das telecomunicações. Este, sugere, ainda, um instrumento prático de medida; um índice de medida do valor de grupo de clientes é proposto e construído com base em análise de dados secundários do sector e do mercado chinês e primários baseados opiniões de peritos do sector e de resposta a um inquérito dos grupos de clientes da China Mobile. Após uma breve revisão do enquadramento teórico de conceitos inseridos na Gestão do Marketing, como Valor do Cliente, Segmentação e cliente-grupo, foram analisadas e seleccionadas as opções metodológicas e as variáveis que podem influenciar a avaliação do valor de um grupo de clientes. O desenvolvimento do índice de ponderação do valor de grupo de clientes foi elaborado após vários passos. Em primeiro lugar foram identificados, junto de peritos do sector, 14 factores que influenciam a avaliação do valor de grupo de clientes; Depois, efectuou-se um inquérito a 2000 grupos de clientes, retirados do sistema móvel BOSS da empresa Sichuan Mobile. Por fim realizou-se à base de dados obtida análises estatísticas como Análise Factorial e de Hierarquia (AHP), métodos que permitiram obter a ponderação do índice. Finalmente, com base no índice de valor corrente, valor potencial, valor social e valor total foram identificados os clusters. A análise destes clusters permitiu ainda sugerir estratégias de marketing em adaptação a cada cluster

Cyber Security

This open access book constitutes the refereed proceedings of the 18th China Annual Conference on Cyber Security, CNCERT 2022, held in Beijing, China, in August 2022. The 17 papers presented were carefully reviewed and selected from 64 submissions. The papers are organized according to the following topical sections: ​​data security; anomaly detection; cryptocurrency; information security; vulnerabilities; mobile internet; threat intelligence; text recognition

IoT and Sensor Networks in Industry and Society

The exponential progress of Information and Communication Technology (ICT) is one of the main elements that fueled the acceleration of the globalization pace. Internet of Things (IoT), Artificial Intelligence (AI) and big data analytics are some of the key players of the digital transformation that is affecting every aspect of human's daily life, from environmental monitoring to healthcare systems, from production processes to social interactions. In less than 20 years, people's everyday life has been revolutionized, and concepts such as Smart Home, Smart Grid and Smart City have become familiar also to non-technical users. The integration of embedded systems, ubiquitous Internet access, and Machine-to-Machine (M2M) communications have paved the way for paradigms such as IoT and Cyber Physical Systems (CPS) to be also introduced in high-requirement environments such as those related to industrial processes, under the forms of Industrial Internet of Things (IIoT or I2oT) and Cyber-Physical Production Systems (CPPS). As a consequence, in 2011 the German High-Tech Strategy 2020 Action Plan for Germany first envisioned the concept of Industry 4.0, which is rapidly reshaping traditional industrial processes. The term refers to the promise to be the fourth industrial revolution. Indeed, the first industrial revolution was triggered by water and steam power. Electricity and assembly lines enabled mass production in the second industrial revolution. In the third industrial revolution, the introduction of control automation and Programmable Logic Controllers (PLCs) gave a boost to factory production. As opposed to the previous revolutions, Industry 4.0 takes advantage of Internet access, M2M communications, and deep learning not only to improve production efficiency but also to enable the so-called mass customization, i.e. the mass production of personalized products by means of modularized product design and flexible processes. Less than five years later, in January 2016, the Japanese 5th Science and Technology Basic Plan took a further step by introducing the concept of Super Smart Society or Society 5.0. According to this vision, in the upcoming future, scientific and technological innovation will guide our society into the next social revolution after the hunter-gatherer, agrarian, industrial, and information eras, which respectively represented the previous social revolutions. Society 5.0 is a human-centered society that fosters the simultaneous achievement of economic, environmental and social objectives, to ensure a high quality of life to all citizens. This information-enabled revolution aims to tackle today’s major challenges such as an ageing population, social inequalities, depopulation and constraints related to energy and the environment. Accordingly, the citizens will be experiencing impressive transformations into every aspect of their daily lives. This book offers an insight into the key technologies that are going to shape the future of industry and society. It is subdivided into five parts: the I Part presents a horizontal view of the main enabling technologies, whereas the II-V Parts offer a vertical perspective on four different environments. The I Part, dedicated to IoT and Sensor Network architectures, encompasses three Chapters. In Chapter 1, Peruzzi and Pozzebon analyse the literature on the subject of energy harvesting solutions for IoT monitoring systems and architectures based on Low-Power Wireless Area Networks (LPWAN). The Chapter does not limit the discussion to Long Range Wise Area Network (LoRaWAN), SigFox and Narrowband-IoT (NB-IoT) communication protocols, but it also includes other relevant solutions such as DASH7 and Long Term Evolution MAchine Type Communication (LTE-M). In Chapter 2, Hussein et al. discuss the development of an Internet of Things message protocol that supports multi-topic messaging. The Chapter further presents the implementation of a platform, which integrates the proposed communication protocol, based on Real Time Operating System. In Chapter 3, Li et al. investigate the heterogeneous task scheduling problem for data-intensive scenarios, to reduce the global task execution time, and consequently reducing data centers' energy consumption. The proposed approach aims to maximize the efficiency by comparing the cost between remote task execution and data migration. The II Part is dedicated to Industry 4.0, and includes two Chapters. In Chapter 4, Grecuccio et al. propose a solution to integrate IoT devices by leveraging a blockchain-enabled gateway based on Ethereum, so that they do not need to rely on centralized intermediaries and third-party services. As it is better explained in the paper, where the performance is evaluated in a food-chain traceability application, this solution is particularly beneficial in Industry 4.0 domains. Chapter 5, by De Fazio et al., addresses the issue of safety in workplaces by presenting a smart garment that integrates several low-power sensors to monitor environmental and biophysical parameters. This enables the detection of dangerous situations, so as to prevent or at least reduce the consequences of workers accidents. The III Part is made of two Chapters based on the topic of Smart Buildings. In Chapter 6, Petroșanu et al. review the literature about recent developments in the smart building sector, related to the use of supervised and unsupervised machine learning models of sensory data. The Chapter poses particular attention on enhanced sensing, energy efficiency, and optimal building management. In Chapter 7, Oh examines how much the education of prosumers about their energy consumption habits affects power consumption reduction and encourages energy conservation, sustainable living, and behavioral change, in residential environments. In this Chapter, energy consumption monitoring is made possible thanks to the use of smart plugs. Smart Transport is the subject of the IV Part, including three Chapters. In Chapter 8, Roveri et al. propose an approach that leverages the small world theory to control swarms of vehicles connected through Vehicle-to-Vehicle (V2V) communication protocols. Indeed, considering a queue dominated by short-range car-following dynamics, the Chapter demonstrates that safety and security are increased by the introduction of a few selected random long-range communications. In Chapter 9, Nitti et al. present a real time system to observe and analyze public transport passengers' mobility by tracking them throughout their journey on public transport vehicles. The system is based on the detection of the active Wi-Fi interfaces, through the analysis of Wi-Fi probe requests. In Chapter 10, Miler et al. discuss the development of a tool for the analysis and comparison of efficiency indicated by the integrated IT systems in the operational activities undertaken by Road Transport Enterprises (RTEs). The authors of this Chapter further provide a holistic evaluation of efficiency of telematics systems in RTE operational management. The book ends with the two Chapters of the V Part on Smart Environmental Monitoring. In Chapter 11, He et al. propose a Sea Surface Temperature Prediction (SSTP) model based on time-series similarity measure, multiple pattern learning and parameter optimization. In this strategy, the optimal parameters are determined by means of an improved Particle Swarm Optimization method. In Chapter 12, Tsipis et al. present a low-cost, WSN-based IoT system that seamlessly embeds a three-layered cloud/fog computing architecture, suitable for facilitating smart agricultural applications, especially those related to wildfire monitoring. We wish to thank all the authors that contributed to this book for their efforts. We express our gratitude to all reviewers for the volunteering support and precious feedback during the review process. We hope that this book provides valuable information and spurs meaningful discussion among researchers, engineers, businesspeople, and other experts about the role of new technologies into industry and society

Artificial Neural Networks in Agriculture

Modern agriculture needs to have high production efficiency combined with a high quality of obtained products. This applies to both crop and livestock production. To meet these requirements, advanced methods of data analysis are more and more frequently used, including those derived from artificial intelligence methods. Artificial neural networks (ANNs) are one of the most popular tools of this kind. They are widely used in solving various classification and prediction tasks, for some time also in the broadly defined field of agriculture. They can form part of precision farming and decision support systems. Artificial neural networks can replace the classical methods of modelling many issues, and are one of the main alternatives to classical mathematical models. The spectrum of applications of artificial neural networks is very wide. For a long time now, researchers from all over the world have been using these tools to support agricultural production, making it more efficient and providing the highest-quality products possible