The study provides a systematic literature review (SLR) encompassing industrial wastewater management research from the past decade, examining enablers, challenges, and prevailing practices. Originating from manufacturing, energy production, and diverse industrial processes, industrial wastewater's handling is critical due to its potential to impact the environment and public health. The research aims to comprehend the current state of industrial wastewater management, pinpoint gaps, and outline future research prospects. The SLR methodology involves scouring the Scopus database, yielding an initial pool of 253 articles. Refinement via search code leaves 101 articles, followed by abstract screening that reduces articles to 79, and finally 66 well-focused articles left for thorough full-text examination. Results underscore the significance of regulatory frameworks, technological innovation, and sustainability considerations as cornerstones for effective wastewater management. However, substantial impediments like; inadequate infrastructure, resource constraints and the necessity for stakeholder collaboration still exist. The study highlights emerging research domains, exemplified by advanced technologies like nanotechnology and bioremediation, alongside the pivotal role of circular economy principles in wastewater management. The SLR offers an exhaustive view of contemporary industrial wastewater management, accentuating the imperative of an all-encompassing approach that integrates regulatory, technological, and sustainability facets. Notably, the research identifies gaps and opportunities for forthcoming exploration, advocating for interdisciplinary research and intensified stakeholder collaboration. The study's insights cater to policymakers, practitioners, and researchers, equipping them to address the challenges and capitalize on prospects in industrial wastewater management effectively.
The evolving global landscape for electrical distribution and use created a need area for energy storage systems (ESS), making them among the fastest growing electrical power system products. A key element in any energy storage system is the capability to monitor, control, and optimize performance of an individual or multiple battery modules in an energy storage system and the ability to control the disconnection of the module(s) from the system in the event of abnormal conditions. This management scheme is known as “battery management system (BMS)”, which is one of the essential units in electrical equipment. BMS reacts with external events, as well with as an internal event. It is used to improve the battery performance with proper safety measures within a system. Therefore, a safe BMS is the prerequisite for operating an electrical system. This report analyzes the details of BMS for electric transportation and large-scale (stationary) energy storage. The analysis includes different aspects of BMS covering testing, component, functionalities, topology, operation, architecture, and BMS safety aspects. Additionally, current related standards and codes related to BMS are also reviewed. The report investigates BMS safety aspects, battery technology, regulation needs, and offer recommendations. It further studies current gaps in respect to the safety requirements and performance requirements of BMS by focusing mainly on the electric transportation and stationary application. The report further provides a framework for developing a new standard on BMS, especially on BMS safety and operational risk. In conclusion, four main areas of (1) BMS construction, (2) Operation Parameters, (3) BMS Integration, and (4) Installation for improvement of BMS safety and performance are identified, and detailed recommendations were provided for each area. It is recommended that a technical review of the BMS be performed for transportation electrification and large-scale (stationary) applications. A comprehensive evaluation of the components, architectures, and safety risks applicable to BMS operation is also presented.
Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present article investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal six clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences.
Network slicing has been widely agreed as a promising technique to accommodate diverse services for the Industrial Internet of Things (IIoT). Smart transportation, smart energy, and smart factory/manufacturing are the three key services to form the backbone of IIoT. Network slicing management is of paramount importance in the face of IIoT services with diversified requirements. It is important to have a comprehensive survey on intelligent network slicing management to provide guidance for future research in this field. In this paper, we provide a thorough investigation and analysis of network slicing management in its general use cases as well as specific IIoT services including smart transportation, smart energy and smart factory, and highlight the advantages and drawbacks across many existing works/surveys and this current survey in terms of a set of important criteria. In addition, we present an architecture for intelligent network slicing management for IIoT focusing on the above three IIoT services. For each service, we provide a detailed analysis of the application requirements and network slicing architecture, as well as the associated enabling technologies. Further, we present a deep understanding of network slicing orchestration and management for each service, in terms of orchestration architecture, AI-assisted management and operation, edge computing empowered network slicing, reliability, and security. For the presented architecture for intelligent network slicing management and its application in each IIoT service, we identify the corresponding key challenges and open issues that can guide future research. To facilitate the understanding of the implementation, we provide a case study of the intelligent network slicing management for integrated smart transportation, smart energy, and smart factory. Some lessons learnt include: 1) For smart transportation, it is necessary to explicitly identify service function chains (SFCs) for specific applications along with the orchestration of underlying VNFs/PNFs for supporting such SFCs; 2) For smart energy, it is crucial to guarantee both ultra-low latency and extremely high reliability; 3) For smart factory, resource management across heterogeneous network domains is of paramount importance. We hope that this survey is useful for both researchers and engineers on the innovation and deployment of intelligent network slicing management for IIoT.
The advancement in water treatment technology has revolutionized the progress of membrane bioreactor (MBR) technology in the modern era. The large space requirement, low efficiency, and high cost of the traditional activated sludge process have given the necessary space for the MBR system to come into action. The conventional activated sludge (CAS) process and tertiary filtration can be replaced by immersed and side-stream MBR. This article outlines the historical advancement of the MBR process in the treatment of industrial and municipal wastewaters. The structural features and design parameters of MBR, e.g., membrane surface properties, permeate flux, retention time, pH, alkalinity, temperature, cleaning frequency, etc., highly influence the efficiency of the MBR process. The submerged MBR can handle lower permeate flux (requires less power), whereas the side-stream MBR can handle higher permeate flux (requires more power). However, MBR has some operational issues with conventional water treatment technologies. The quality of sludge, equipment requirements, and fouling are major drawbacks of the MBR process. This review paper also deals with the approach to address these constraints. However, given the energy limitations, climatic changes, and resource depletion, conventional wastewater treatment systems face significant obstacles. When compared with CAS, MBR has better permeate quality, simpler operational management, and a reduced footprint requirement. Thus, for sustainable water treatment, MBR can be an efficient tool.
With the rise of Internet of Things (IoT) technology, the seamless connection between the physical and digital worlds has been realized. This review paper aims to conduct a science mapping review of IoT applications in industrial management and to identify mainstream research topics, research gaps, and future research directions. Using VOSviewer as a visualization tool, 142 articles retrieved from the Scopus database were quantitatively discussed using scientometric analysis. Additionally, a follow-up qualitative discussion was focused on mainstream research topics, existing research gaps, and future research directions as the main research goals. The results revealed influential findings for the co-occurrence of keywords, journals, countries, authors, and documents analyses. Moreover, it was found that the existing research mainly focused on four main research topics including (1) application of IoT in manufacturing based on cyber-physical systems, (2) IoT-related technologies on logistics and supply chain management, (3) The impact of IoT on business models, and (4) Industrial IoT (IIoT) in the context of Industry 4.0. On this basis, the existing research gaps and future research directions are proposed. This review paper would help relevant practitioners and researchers to better understand the existing body of knowledge and lay the foundation for further research.
Electric field manipulates the change of droplets wettability on superhydrophobic surfaces, which is widely used in many fields such as electronic zoom microlens and electro wetting displays, and has an important research value. This paper prepared a superhydrophobic acetate film applied electrostatic spinning technique,the maximum contact angle of acetate film is 152.6°, conducted electric field-regulated water droplet wettability change tests, applied voltage to water droplets on acetate film. it was found that the contact angle of the droplets decreased with the increase of the electric field strength, and the electric field regulated the contact angle of the droplets to change in the range of 92.7-142.3°. When the power supply is turned off, the contact angle of the droplet can gradually recover, but not completely restored to the original state.
Zaid Ameen Abduljabbar, Vincent Omollo Nyangaresi, Ahmed Ali Ahmed
et al.
Abstract Vehicular Ad-Hoc Networks (VANETs) have facilitated the massive exchange of real-time traffic and weather conditions, which have helped prevent collisions, reduce accidents, and road congestions. This can effectively enhance driving safety and efficiency in technology-driven transportation systems. However, the transmission of massive and sensitive information across public wireless communication channels exposes the transmitted data to a myriad of privacy as well as security threats. Although past researches has developed many vehicular ad-hoc networks security preservation schemes, several of them are inefficient or susceptible to attacks. This work, introduces an approach that leverages reverse fuzzy extraction, bilinear pairing, and Physically Unclonable Function (PUF) to design an efficient and anonymity-preserving authentication scheme. We conduct an elaborate formal security analysis to demonstrate that the derived session key is secure. The semantic security analyses also demonstrate its resilience against typical VANET attacks such as impersonations, denial of service, and de-synchronization, instilling confidence in its effectiveness. Moreover, our approach incurs the lowest computational overheads at relatively low communication costs. Specifically, our protocol attains a 66.696% reduction in computation costs, and a 70% increment in the supported security functionalities.
In this research, we propose a new numerical method for solving a class of distributed-order fractional partial differential equations, specifically focusing on distributed-order time fractional wave-diffusion equations. The method begins by introducing a novel generalization of Bernoulli wavelets and deriving an exact result for the Riemann–Liouville integral of these new basis functions. Utilizing the Gauss–Legendre quadrature formula and a strategically chosen set of collocation points, along with approximations for the unknown function and its derivatives, we transform the problem into a system of algebraic equations. An error analysis is then conducted for the approximation of a bivariate function using fractional-order Bernoulli wavelets. Finally, three examples are solved to demonstrate the method’s applicability and accuracy, with the numerical results confirming its effectiveness. These findings demonstrate that the parameters of the basis functions can be adjusted to suit the given problem, thereby enhancing the accuracy of the method.
This paper presents a novel approach to enhancing the security and reliability of drone communications through the integration of Quantum Random Number Generators (QRNG) in Frequency Hopping Spread Spectrum (FHSS) systems. We propose a multi-drone framework that leverages QRNG technology to generate truly random frequency hopping sequences, significantly improving resistance against jamming and interception attempts. Our method introduces a concurrent access protocol for multiple drones to share a QRNG device efficiently, incorporating robust error handling and a shared memory system for random number distribution. The implementation includes secure communication protocols, ensuring data integrity and confidentiality through encryption and Hash-based Message Authentication Code (HMAC) verification. We demonstrate the system’s effectiveness through comprehensive simulations and statistical analyses, including spectral density, frequency distribution, and autocorrelation studies of the generated frequency sequences. The results show a significant enhancement in the unpredictability and uniformity of frequency distributions compared to traditional pseudo-random number generator-based approaches. Specifically, the frequency distributions of the drones exhibited a relatively uniform spread across the available spectrum, with minimal discernible patterns in the frequency sequences, indicating high unpredictability. Autocorrelation analyses revealed a sharp peak at zero lag and linear decrease to zero values for other lags, confirming a general absence of periodicity or predictability in the sequences, which enhances resistance to predictive attacks. Spectral analysis confirmed a relatively flat power spectral density across frequencies, characteristic of truly random sequences, thereby minimizing vulnerabilities to spectral-based jamming. Statistical tests, including Chi-squared and Kolmogorov-Smirnov, further confirm the unpredictability of the frequency sequences generated by QRNG, supporting enhanced security measures against predictive attacks. While some short-term correlations were observed, suggesting areas for improvement in QRNG technology, the overall findings confirm the potential of QRNG-based FHSS systems in significantly improving the security and reliability of drone communications. This work contributes to the growing field of quantum-enhanced wireless communications, offering substantial advancements in security and reliability for drone operations. The proposed system has potential applications in military, emergency response, and secure commercial drone operations, where enhanced communication security is paramount.
<p>This study aims to investigate the unique features of the food supply chain, examining the impact of food supply chain integration, consisting of internal integration, supplier and customer, the quality of food products and product innovation capability. Managers need to understand the importance of supplier and customer integration when responding to supply chain risk and company uncertainty. The data were collected from 168 managers active in the food industry in Tehran province. The partial least squares tool (SmartPLS 3.0) was used to analyze the data using Structural Equation Modeling (SEM) technique. The results show that there is a strong relationship between uncertainty and supply chain integration including customer, supplier and internal integration. The findings indicate that customer integration and supplier integration are critical factors in improving product quality in the food supply chain. The results can be related to the prominent role of customer relations and contact in the development of innovation capabilities in manufactured products, which has also been approved by some previous studies. Additionally, analyzing the various dimensions of supply chain integration separately revealed that internal integration is a capability factor for external integration. This study can help businesses in the food industry understand the value-creating roles of food supply chain integration and provide valuable guidance for them to decide how to meet the various challenges and manage food supply chain integration in order to improve product quality and product innovation capability.</p>
Abstract Catastrophic forgetting in neural networks is a common problem, in which neural networks lose information from previous tasks after training on new tasks. Although adopting a regularization method that preferentially retains the parameters important to the previous task to avoid catastrophic forgetting has a positive effect; existing regularization methods cause the gradient to be near zero because the loss is at the local minimum. To solve this problem, we propose a new continuous learning method with Bayesian parameter updating and weight memory (CL-BPUWM). First, a parameter updating method based on the Bayes criterion is proposed to allow the neural network to gradually obtain new knowledge. The diagonal of the Fisher information matrix is then introduced to significantly minimize computation and increase parameter updating efficiency. Second, we suggest calculating the importance weight by observing how changes in each network parameter affect the model prediction output. In the process of model parameter updating, the Fisher information matrix and the sensitivity of the network are used as the quadratic penalty terms of the loss function. Finally, we apply dropout regularization to reduce model overfitting during training and to improve model generalizability. CL-BPUWM performs very well in continuous learning for classification tasks on CIFAR-100 dataset, CIFAR-10 dataset, and MNIST dataset. On CIFAR-100 dataset, it is 0.8%, 1.03% and 0.75% higher than the best performing regularization method (EWC) in three task partitions. On CIFAR-10 dataset, it is 2.25% higher than the regularization method (EWC) and 0.7% higher than the scaled method (GR). It is 0.66% higher than the regularization method (EWC) on the MNIST dataset. When the CL-BPUWM method was combined with the brain-inspired replay model under the CIFAR-100 and CIFAR-10 datasets, the classification accuracy was 2.35% and 5.38% higher than that of the baseline method, BI-R + SI.
Electronic computers. Computer science, Information technology
Nowadays, people live amidst the smart home domain, business opportunities in the industrial smart city and health care, though, along with concerns about security. Security is central for IoT systems to protect sensitive data and infrastructure, whilst security issues become increasingly expensive, in particular in Industrial Internet of Things (IIoT) domains. Nonetheless, there are some key challenges for dealing with those security issues in IoT domains: Applications operate in distributed environments such as Blockchain, varied smart objects are used, and sensors are limited in what comes to machine resources. In this way, traditional security does not fit in IoT systems. In this vein, the issue of cyber security has become paramount to the Internet of Things (IoT) and Industrial Internet of Things (IIoT) in mitigating cyber security risk for organizations and end users. New cyber security technologies / applications present improvements for IoT security management. Nevertheless, there is a gap on the effectiveness of IoT cyber risk solutions. This review article discusses the, trends around opportunities and threats in cyber security for IIoT.
Elías Jordan Karmach-Sánchez, Carlos Leandro Delgado-Fuentealba, Paola Giuliana Zerega-Tallia
et al.
Para los jóvenes, la elección acertada de un pro-grama universitario constituye un desafío para ellos, su familia y la sociedad, puesto que el desarrollo personal, el éxito profesional, los valores y el servicio a la comunidad dependen de ella. Considerando que los factores que intervienen en esta elección son variados, el estudio buscó determinar, empíricamente, si el grado de autoestima y moti-vación escolar tiene efecto en la matrícula de un programa universitario, como primera preferencia. La muestra corresponde a los 2626 jóvenes que ingresaron a la Universidad de Concepción, Cam-pus Chillán, en 2016-2021. Se utilizó un modelo pro-bit binario, pues la variable dependiente toma uno de dos valores discretos. El grado de autoestima y motivación se midió a partir de uno de los índices de desarrollo personal y social (IDPS), entregado por la Agencia de Calidad del Ministerio de Educación de Chile para cada establecimiento de egreso de enseñanza media. Se incorporaron variables de control, como las características personales del estudiante y del establecimiento. Los resultados confirman que, cuanto mayor es el índice de autoestima y moti-vación escolar, mayor es la probabilidad de que el estudiante ingrese al programa de su primera preferencia. Este análisis confirma (1) la importancia de este Indicador y (2) que aún faltan avances para fortalecer programas escolares que pongan el énfasis en propiciar condiciones que permitan el desarrollo integral de los estudiantes, destacando las fortalezas por sobre las debilidades.
Pelayanan jasa informasi meteorologi yang cepat, tepat akurat dan mudah dipahami merupakan salah satu tugas Stasiun Meteorologi (STAMET) Kelas I Maritim Serang. Namun berdasarkan wawancara dan observasi yang dilakukan, menunjukan bahwa pelayanan yang dilakukan belum efisien dan praktis karena pengguna jasa harus datang ke kantor untuk memperoleh data yang diinginkan. Selain itu petugas pelayanan masih mencatat transaksi dalam buku yang kemudian diketik kembali pada aplikasi Microsoft Word, dan mengalami kesulitan dalam mencari berkas yang akan diberikan kepada pengguna jasa. Penelitian ini bertujuan untuk membuat sistem yang dapat membantu tugas STAMET untuk meningkatkan pelayanan jasa meteorologi dengan menggunakan pendekatan Customer Relationship Management (CRM). Metode pengembangan yang digunakan yaitu model prototype dengan perancangan diagram Unified Modelling Language (UML). Sistem dibuat menggunakan Framework Codeigniter dengan Bahasa pemograman Hypertext Preprocessing (PHP) sebagai Server side Programing dan MySQL sebagai Database Server. Metode pengujian sistem yang digunakan adalah Blackbox. Hasil akhir yang diharapkan adalah sebuah sistem informasi pelayanan jasa meteorologi berbasis Web, yang dapat membantu pengguna jasa mendapatkan informasi meteorologi, mempermudah petugas dalam memberikan pelayanan jasa, pembuatan jadwal kunjungan atau pertemuan, mengajukan komplain pelayanan jasa, memberikan kritik dan saran serta mengukur kepuasan pengguna jasa terhadap pelayanan yang diberikan oleh petugas STAMET Kelas I Maritim Serang.
Kata Kunci: Customer Relationship Management (CRM), Pelayanan Jasa Meteorologi, Sistem
Objetivo: Diseñar instrumentos de control documental para la Dirección Municipal de Planificación Física de Santo Domingo, provincia Villa Clara, Cuba, para fortalecer dicha gestión de documentos.
Métodos: El estudio se clasifica como descriptivo. Para la obtención de resultados se utilizaron los métodos inducción-deducción, analítico-sintético, análisis documental y la encuesta.
Principales resultados: Se diseñaron dos instrumentos de control documental para la entidad; estos fueron: cuadro de clasificación documental y tabla de retención; se estableció además una Comisión De Valoración Documental.
Conclusiones: Se evidenciaron condiciones desfavorables para la gestión documental en el Archivo Central de la organización. Se identifica la falta de espacio para los documentos, así como la ausencia de sistemas de gestión para automatizar los procesos de transferencia documental y digitalizar las series documentales. Se diseñaron instrumentos de gestión documental que contribuyen a minimizar los riesgos a los que se expone la organización y mejorar su gestión.