Management Layer Research Articles

Integrating multiple industry 4.0 approaches and tools in an interoperable platform for manufacturing SMEs

Small and medium-sized enterprises (SMEs) often struggle to optimize their production processes and products due to limited resources and lack of expertise in technological solutions. To address this issue, this research work presents a multi-purpose platform that can be used by SMEs as easy-to use support tool to run what-if analyses to optimize their products and production processes design. The platform fulfills the requirements of interoperability, accessibility, and usability and is built upon a layered infrastructure, consisting of specific modules within its Decision-Making Layer, Data Exchange Layer, and User Management Layer. The platform integrates several software, including Plant Simulation, Autodesk Inventor Nastran, and Autodesk Inventor Nesting, to simulate production processes, to run finite element analysis, and to optimize raw material utilization. The interoperability and data exchange are ensured through the adoption of FIWARE, an open-source framework for IoT platforms, which enables the harmonized representation of data formats and semantics among different applications and software within the platform. The User Management Layer allows SMEs to easily interact with the platform, making it an easy-to-use tool even for those with limited IT competencies. A case study conducted by an SME in the furniture sector demonstrated the platform's effectiveness in achieving optimal design and production of a new bookcase, resulting in increased efficiency, reduced costs, and improved profitability. The modular structure of the platform enables potential future integration of additional modules, such as quality control, supply chain management, etc., further enhancing its capabilities and potential benefits for SMEs. The proposed multi-purpose platform represents a valuable tool for SMEs to optimize their production processes and products and to overcome the limitations due to their limited resources and expertise in technological solutions.

Patterns of bacterial distance decay and community assembly in different land-use types as influenced by tillage management and soil layers

Land use and cover change are major factors driving global change and greatly impact terrestrial organisms, especially soil microbial diversity. Little is known, however, about bacterial diversity, distribution patterns and assembly processes across different land use types. In this study, therefore, we conducted a large-scale field survey of 48 sampling sites, encompassing different land use types in Xuancheng city, China, with different degrees of soil disturbance and different soil horizons. The distance-decay relationships (DDRs), assembly processes and the spatial patterns of soil bacterial communities were investigated based on high-throughput sequencing data. We found that the DDRs might be weakened by anthropogenic disturbances, which were not observed in tilled soils, while a decreasing trend was observed along the soil horizon in untilled soils. The relative importance of environmental factors and geographic distance varied with soil tillage. Specifically, bacterial communities in tilled soils were driven by non-spatially autocorrelated environmental factors, while untilled soils were more susceptible to geographic distance. In addition, the heterogeneity of soil properties, as well as the differences in soil bacterial niche width and niche overlap, determined the assembly processes of the bacterial community, resulting in opposite trends along the soil layers in tilled and untilled soils. These findings expand the current understanding of the biogeography of soil bacterial communities across different land use types.

ElasticNotebook: Enabling Live Migration for Computational Notebooks

Computational notebooks (e.g., Jupyter, Google Colab) are widely used for interactive data science and machine learning. In those frameworks, users can start a session , then execute cells (i.e., a set of statements) to create variables, train models, visualize results, etc. Unfortunately, existing notebook systems do not offer live migration: when a notebook launches on a new machine, it loses its state , preventing users from continuing their tasks from where they had left off. This is because, unlike DBMS, the sessions directly rely on underlying kernels (e.g., Python/R interpreters) without an additional data management layer. Existing techniques for preserving states, such as copying all variables or OS-level checkpointing, are unreliable (often fail), inefficient, and platform-dependent. Also, re-running code from scratch can be highly time-consuming. In this paper, we introduce a new notebook system, Elastic-Notebook, that offers live migration via checkpointing/restoration using a novel mechanism that is reliable, efficient, and platform-independent. Specifically, by observing all cell executions via transparent, lightweight monitoring, ElasticNotebook can find a reliable and efficient way (i.e., replication plan ) for reconstructing the original session state, considering variable-cell dependencies, observed runtime, variable sizes, etc. To this end, our new graph-based optimization problem finds how to reconstruct all variables (efficiently) from a subset of variables that can be transferred across machines. We show that ElasticNotebook reduces end-to-end migration and restoration times by 85%-98% and 94%-99%, respectively, on a variety (i.e., Kaggle, JWST, and Tutorial) of notebooks with negligible runtime and memory overheads of <2.5% and <10%.

Towards a Domain-Neutral Platform for Sustainable Digital Twin Development

In this paper, we propose an abstract domain-neutral architecture for a cognitive digital twin (CDT) and a software platform to develop such CDTs, including machine reasoning capabilities. Sustainable development refers here to an abstract model that enables a holistic view of limiting resources and has an ability to adapt to different application domains while reusing existing resources. The proposed solution allows for a unified abstract representation and the development of a wide range of diverse digital twins, as well as facilitating their interoperability. The abstract architecture consists of a four-layer structure (observation/actuation layer, data management layer, reasoning layer, and simulation layer) with an upper ontology to which the domain ontology of the specific CDT is mapped. The architecture relies on semantic web technologies, including ontology-based reasoning using OWL, and a loosely coupled, component-based service-oriented software architecture. The platform utilizes a microservice architecture that enables separate, loosely coupled services on each layer, message queues to provide asynchronous communication, and possesses cloud technologies to achieve scalability. The proposed approach was validated by implementing a software platform prototype and demonstrating its key features through two dissimilar scenarios. The first scenario demonstrates simple sustainable energy management through IoT systems inside smart buildings, while the second one demonstrates knowledge quality management based on knowledge space theory.

MPC-based energy management strategy for a substation PEDF System

According to the optimal scheduling and balanced utilization of power generation units, energy storage, and flexible loads in the PEDF(photovoltaic, energy storage, direct current and flexibility) system of a substation, and realizing stable operation with different time scales and operation modes, this paper proposes a hierarchical control framework, which includes energy management layer, power conversion layer, stability control layer, and an MPC-based energy management strategy based control. Among them, the energy management system uses the prediction of the absorbed power and current of the distributed generation units and loads, and based on the technology of model predictive control to generate the optimal reference power and decision variables for the system to decide the on/off of the system’s dispatchable generation unit and the operation mode of photovoltaic and battery. Finally, the proposed control architecture and strategy are validated by a substation PEDF system.

A Multilayer Software-Defined System for High-Performance Electric Vehicle Energy Conversion

A multi-layer software-defined architecture is developed based on a type of elementary power module to improve the energy conversion performance of electric vehicle (EV) system. The proposed structure is composed of three layers: (1) application function layer for the interfaces with various types of electrified loads/sources and the corresponding control functions, such as single/three-phase grid, battery, motor, resistor; (2) elementary module layer for providing desired number of basic power module with local functions of variable frequency soft switching (VFSS) and model predictive control (MPC) to increase the efficiency with better transient performance; (3) interconnection management layer for the coordination and interconnection between the application function layer and elementary module layer to construct the complete power converter topology with desired number of elementary power module for the satisfaction of the interfaced load/source. The merits of the designed architecture include the reconfigurability to be suitable for different types of EV applications, all non-isolated topologies with common mode noise attenuation capability, improved efficiency and dynamic performance by VFSS and MPC of the elementary power module, high accuracy and robustness of the multi-layer control without being influenced by the parametric modeling error from various applications. The proposed multi-layer architecture is validated with experimental tests.

A digital twin-based green construction management method for prefabricated buildings

Background: Site pollution in construction can be reduced by using high levels of prefabrication and industrialization. However, the lack of green concepts and methods during the prefabrication assembly process hinders its environmental benefits. Digital twin technology can monitor sites in real-time and provide data visualization for decision support, which has been used in construction management and risk control. Methods: We propose a six-dimensional digital twin framework that includes physical and virtual spaces, project management and service layers, twin data, and component connections. The framework integrates green factors of prefabricated construction into a model evolution framework and mechanism that enables real-time green services throughout the process. Results: The proposed framework, modeling method, and evolution method were tested in prefabrication projects in Tianjin. By applying these methods, inadequate management measures were promptly identified and strengthened. Energy consumption and pollution were reduced by comparing with the plan before construction. In addition, the model evolution method optimized green management measures and improved the level of green construction management on site. Conclusions: The application results demonstrate the effectiveness of our proposed framework, the model building method, and the evolution method in improving the green level of prefabricated construction.

Live demonstration of an SDN-reconfigurable, FPGA-based TxRx for an analog-IFoF/mmWave radio access network in an MNO’s infrastructure

This paper presents the end-to-end integration of a software defined network (SDN) reconfigurable real-time analog-intermediate frequency-over-fiber (A-IFoF)/millimeter wave (mmWave) layout into a real mobile network operator (MNO) infrastructure. The key part of the presented infrastructure is the fully programmable gateway array (FPGA)-based A-IFoF transceiver (TxRx), equipped with active SDN functionalities based on constant monitoring of the transport link. This layout was successfully evaluated in the physical data management and application layer. Regarding the physical layer performance evaluation, error vector magnitude values of 7.3% were achieved for quadrature phase shift keying waveforms, while the uninterrupted operation of real-time services such as augmented reality/virtual reality applications was enabled by the reactive SDN-based capacity reconfiguration capabilities.

A digital life-cycle management framework for sustainable smart manufacturing in energy intensive industries

Energy intensive industries can be classified into those that process metal, glass, ceramics, paper, cement, and bulk chemicals. They are associated with significantly high proportions of carbon emissions, consume a lot of energy and raw materials, and cause energy wastage as a result of heat escaping from furnaces, reheating of products, and rejection of parts. In alignment with UN sustainable development goals of industry, innovation, infrastructure and responsible consumption and production, it is important to ensure that the energy consumption of EIIs are monitored and reduced such that their energy efficiency can be improved. Towards this aim, it is possible to employ the concepts of digitalisation and smart manufacturing to identify the critical areas of improvement and establish enablers that can help improve the energy efficiency. The aim of this research is to review the current state of digitalisation in energy-intensive industries and propose a framework to support the realisation of sustainable smart manufacturing in Energy Intensive Industries (EIIs). The key objectives of the work are (i) the investigation of process mining and simulation modelling to support sustainability, (ii) embedding intelligence in EIIs to improve energy and material efficiency and (iii) proposing a framework to enable the digital transformation of EIIs. The proposed five-layer framework employs data acquisition, process management, simulation & modelling, artificial intelligence, and data visualisation to identify and forecast energy consumption. A detailed description of the various phases of the framework and how they can be used to support sustainability and smart manufacturing is demonstrated using business process data obtained from a machining industry. In the demonstrated case study, the process management layer utilises Disco for process mining, the simulation layer utilises Matlab SimEvent for discrete-event simulation, the artificial intelligence layer utilises Matlab for energy prediction and the visualisation layer utilises grafana to dashboard the e-KPIs. The findings of the research indicate that the proposed digital life-cyle framework helps EIIs realise sustainable smart manufacturing through better understanding of the energy-intensive processes. The study also provided a better understanding of the integration of process mining and simulation & modelling within the context of EIIs.

Research on the integration and development of student management and ideological and political education in universities based on environmental psychology

Abstract To cultivate college students to become new intellectuals with virtue and talent who master modern scientific and cultural knowledge and are physically healthy. This paper constructs a model of college student management and ideological and political education based on environmental psychology. The CIPP evaluation mechanism is used to analyze the appropriateness of the effectiveness of ideological and political education in colleges and universities, calculate the weight values among the indicators according to the priority relationship among environmental psychology indicators, input the evaluation data into the database information management layer for compression processing through multi-level analysis, and pass into the indicator adjustment layer as well as the data mining layer for a comprehensive evaluation of the effectiveness of ideological and political teaching, which proves that it can promote student management and ideological and political education It is proved that it can promote the integration of student management and ideological and political education. In this paper, three classes of universities were selected for the experiment, and it was proved that the average score of the ideology factor increased from 64.42 to 82.96 under the environmental psychology teaching model, and the classroom head-raising rate of students increased by more than 10%. It shows that the application of the environmental psychology teaching model to students’ Civic Education in colleges and universities can significantly improve students’ ideological and political level, can keep up with the changes in the social environment for effective management of students, and promotes the integration development of student management and Civic Education.

Fabrication of transparent and hazy cellulosic light-management film for enhancing photon utilization in photocatalytic membrane process

Given the high demand of photocatalytic membrane filtration processes on both mass transport and light-utilization, this work introduces a novel transparent and highly porous cellulose film (P-RCF) that can serve as a light management layer to enhance the photon utilization of photocatalytic membrane processes. The built-in micron-sized pores act not only as channels for mass transport (filtration resistance ∼5 × 1010/m) but also as forward scatterers to endow the film with a high transmission haze (∼77%) without impairing its transmittance (∼90%). A g-C3N4 membrane with attached P-RCF (P-RCF@C3N4) exhibited enhanced photocatalytic activity for both tetracycline (TC) oxidation and Cr(VI) reduction. Moreover, by adjusting the incident light angle from 0° to 50°, the observed TC degradation kinetics on P-RCF@C3N4 became more stable than those on the bare g-C3N4 membrane, exhibiting incident-angle-independent properties. This enhanced photocatalytic performance can be attributed to the synergistic effect of refractive-index matching and light scattering within our transparent film, which reduces light reflection and traps the light inside at the photoactive layer, resulting in extended light propagation and utilization. This study provides a novel and versatile strategy for developing light management techniques for advanced photocatalytic membrane systems.

YARN Schedulers for Hadoop MapReduce Jobs: Design Goals, Issues and Taxonomy

Objective: Big Data processing is a demanding task, and several big data processing frameworks have emerged during recent decades. The performance of these frameworks greatly dependent on resource management models. Methods: YARN is one of such models which acts as a resource management layer and provides computational resources for execution engines (Spark, MapReduce, storm, etc.) through its schedulers. The most important aspect of resource management is job scheduling. Results: In this paper, we first present the design goal of YARN real-life schedulers (FIFO, Capacity, and Fair) for the MapReduce engine. Later, we discuss the scheduling issues of the Hadoop MapReduce cluster. Conclusion: Many efforts have been carried out in the literature to address issues of data locality, heterogeneity, straggling, skew mitigation, stragglers and fairness in Hadoop MapReduce scheduling. Lastly, we present the taxonomy of different scheduling algorithms available in the literature based on some factors like environment, scope, approach, objective and addressed issues.

HIERARCHICAL ENERGY MANAGEMENT STRATEGY BASED ON THE MAXIMUM EFFICIENCY RANGE FOR A MULTI-STACK FUEL CELL HYBRID POWER SYSTEM

A multi-stack fuel cell hybrid power system (MFCHS) consists of multiple sources with various characteristics. The power distribution between different sources influences the performance of the system, which involves many factors. To distribute the power effectively and enhance the efficiency and fuel economy of a single-stack fuel cell system, this study proposed a hierarchical energy management strategy (EMS) for MFCHS. An MFCHS configuration that included three fuel cell systems and a battery was presented. An MFCHS model that incorporated the effect of altitude was constructed, and an efficiency analysis of the multi-stack fuel cell system (MFCS) was performed. The hierarchical EMS of MFCHS was composed of a bottom control layer and a top management layer. The bottom control layer utilized a coordinated optimal distribution strategy based on the maximum efficiency range of MFCS to realize optimal power allocation between the different fuel cells in MFCS. The top management layer used EMS under multiple operating conditions to realize the effective distribution of the demand power between MFCS and the battery. Results demonstrate that the proposed strategy improves the average efficiency of MFCS by up to 5.2% and 8.9% compared with those of the equal distribution and daisy chain strategies, respectively. The proposed strategy also displays good performance in terms of the hydrogen consumption of MFCS, which saved 1% and 3% hydrogen compared with the equal distribution and daisy chain strategies, respectively. The proposed strategy results in promising improvements in the overall performance of the system. This study provides a good reference for developing EMS for MFCHS. Keywords: Fuel cell, Multi-stack fuel cell hybrid power system, Energy management strategy, Coordinated optimal distribution, Maximum efficiency range

Challenges and Opportunities for Conducting Dynamic Risk Assessments in Medical IoT

Modern medical devices connected to public and private networks require additional layers of communication and management to effectively and securely treat remote patients. Wearable medical devices, for example, can detect position, movement, and vital signs; such data help improve the quality of care for patients, even when they are not close to a medical doctor or caregiver. In healthcare environments, these devices are called Medical Internet-of-Things (MIoT), which have security as a critical requirement. To protect users, traditional risk assessment (RA) methods can be periodically carried out to identify potential security risks. However, such methods are not suitable to manage sophisticated cyber-attacks happening in near real-time. That is the reason why dynamic RA (DRA) approaches are emerging to tackle the inherent risks to patients employing MIoT as wearable devices. This paper presents a systematic literature review of RA in MIoT that analyses the current trends and existing approaches in this field. From our review, we first observe the significant ways to mitigate the impact of unauthorised intrusions and protect end-users from the leakage of personal data and ensure uninterrupted device usage. Second, we identify the important research directions for DRA that must address the challenges posed by dynamic infrastructures and uncertain attack surfaces in order to better protect users and thwart cyber-attacks before they harm personal (e.g., patients’ home) and institutional (e.g., hospital or health clinic) networks.

A review of the different power system architecture at the district level and its analysis

The new power system at the station level is the phased product of the large-scale and high-proportion penetration development of wind and solar new energy. The source network load storage system with the station area as the smallest adjustable unit is constructed by using energy storage +. Different from the traditional substation area system, the architecture of the new power system at the substation area level becomes extremely complex due to the change of access terminal attributes, interaction relationship and various business types. In order to systematically describe the new power system architecture at the station district level, this paper first combs and summarizes the relevant literature at home and abroad, and summarizes the literature related to the current substation District, wind and new energy access and energy storage system regulation. Secondly, from the perspectives of demand differences, common functional requirements and non functional requirements, the requirements of station area level new power system under different application scenarios are classified and analyzed in detail. Then, a new power system for different scenarios is designed, which is divided into local equipment layer, edge control layer, station management layer and centralized control layer from bottom to top, and the functions of each layer are described in detail. Taking Zhangjiajie scenery storage and charging comprehensive energy demonstration project as an example, this paper expounds the ways of terminal data access, transmission and visualization under the framework of Taiwan district level new power system, so as to provide reference for the networking of other similar projects. Finally, the research contents of this paper are summarized, and the contents that need further research in the future are prospected.

Detecting Circular Economy Strategies in the Fourth Sector: Overview of the Chilean Construction Sector as Evidence of a Sustainable Business Model

An essential part of the economic and social system is the existence of sustainable companies worldwide. Despite the fact that the literature has described different kinds of innovations, organizations, and models regarding this topic, there is a need to understand the dynamics that occur within the fourth sector and how strategies and practices are working. In this study, construction companies presenting sustainable projects are identified, and the way in which they serve the community, stakeholders, and consumers is analyzed. The present article presents an epistemological search to recognize the best practices and strategies, which allows an understanding of the new circular economy strategies in the fourth sector. The authors show a conceptual approach regarding these actions and a methodology on the most notable techniques of the Circular Economic Strategy of Chile based on an investigation of documentary and comparative data. Data collection considered perceptions of construction practices regarding the circular economy and the specificity of each situation and reflected the actual production systems. We used simple random sampling to collect data in the scope of the study. The findings show the importance of some relational elements between companies that structure construction projects, supporting the impact of discovering specific variables in the different layers of sustainable management. In addition, results show how those responsible for construction projects understand sustainability as a preference, amplify the role of various factors in the work of the cultural and social ecosystems under consideration. Finally, this article details and analyzes the channeling of innovative business models in the fourth sector.

Can leadership make the difference? A scoping review of leadership and its effects in child and youth care

Child and youth care (CYC) is operating in an unpredictable environment, making leadership in CYC a challenge. Leaders of CYC operate under public and political pressure to reform failed systems, compete for scarce resources, obtain and sustain a highly skilled workforce, and achieve organizational goals and tasks within a complex network. Although many studies underline the importance of leadership in CYC, there is no clear demarcation of the concept of leadership and its associated effects. By conducting a scoping review of the literature, this study aims to improve a conceptual understanding of leadership and provide insight into the influence of leadership on service delivery in CYC.The results show that the majority of the studies within the scope did not use clear definitions of leadership and did not specify the type or level of leadership. Despite this lack of clarity, most studies do discuss the positive effects of leadership behaviors. Leadership behaviors are primarily associated with positive effects on employee commitment and well-being; i.e. creating and communicating a vision, providing trust, safety and respect, inspire, motivate, stimulate and having a cooperative attitude. These leadership behaviors are not exclusively linked to a specific level of leadership and seem effective at all levels. However, the results also show that support from the top of the organization, noticeable in behavior, is a prerequisite for the other layers of management in the organization to be effective.The lack of clarity about type or level of leadership to which the conclusions apply, makes it difficult to develop and recommend targeted leadership interventions. Therefore, future studies should provide a clear definition of leadership, including job title, job content and leadership level.Our findings suggest that these leadership behaviors, can help CYC professionals navigate through their unpredictable environment and improve the quality of care.

Formalizing the Semantics of DDS QoS Policies for Improved Communications in Distributed Smart Grid Applications

Quality communication is a major challenges in large-scale and distributed smart grid applications. Several protocols and middleware have been proposed to address communication quality issues in those applications. DDS is a standard data-centric middleware for publish/subscribe communication. It has been proposed for smart grid to address both connectivity and communication quality issues. DDS provides multiple quality of service (QoS) policies to address reliability, latency, and data availability. One of the main challenges in adopting the standard in smart grids is the complexity of adopting and tailoring its QoS policies. This is because those policies are described informally introducing ambiguities, which hinders the precise implementation of DDS. To address this, we formalize the descriptions of DDS QoS policies using the object constraint language (OCL). We also clearly defined the design structural relations among DDS entities and QoS policies. In the process, we analyzed the dependencies among QoS policies and we built clear and concise structural relations. We then proposed feature modeling and a management layer to facilitate QoS tuning and to reduce development and configuration complexity. We implemented the proposed approach in a simulated power consumption domain. The results show that the approach improves the development process. They also show that the approach significantly improves the performance of DDS-enabled applications.

Academic Library Succession Planning in the Association of Research Libraries (ARL)

In the last few decades, there have been multiple peer-reviewed articles that suggest academic libraries do not establish appropriate succession plans, nor do they develop the required leadership capacity in their librarians. This article discusses (a) the development of a survey instrument to measure the frequency with which succession planning activities take place in libraries, and (b) the results of a survey study that explored succession planning practices in the Association of Research Libraries (ARL) in the United States. This study utilized a cross-sectional design with a stratified random sample (n = 353) of academic librarians and administrators employed by ARL member libraries. After data analysis, validity and reliability analyses revealed the survey instrument demonstrates acceptable psychometric properties and produced a strong alpha coefficient of .91. Findings also suggest that several factors impact respondents’ knowledge of and/or participation in succession planning activities, including their sexual orientation, primary job duties, layers of management in their library hierarchy, and whether or not managers identify and prepare interims for critical positions in their library.

Synergistic Photon Management and Strain-Induced Band Gap Engineering of Two-Dimensional MoS2 Using Semimetal Composite Nanostructures

2D MoS2 attracts increasing attention for its application in flexible electronics and photonic devices. For 2D material optoelectronic devices, the light absorption of the molecularly thin 2D absorber would be one of the key limiting factors in device efficiency, and conventional photon management techniques are not necessarily compatible with them. In this study, we show two semimetal composite nanostructures deposited on 2D MoS2 for synergistic photon management and strain-induced band gap engineering: (1) the pseudo-periodic Sn nanodots, (2) the conductive SnOx (x < 1) core-shell nanoneedle structures. Without sophisticated nanolithography, both nanostructures are self-assembled from physical vapor deposition. Optical absorption enhancement spans from the visible to the near-infrared regime. 2D MoS2 achieves >8× optical absorption enhancement at λ = 700-940 nm and 3-4× at λ = 500-660 nm under Sn nanodots, and 20-30× at λ = 700-900 nm under SnOx (x < 1) nanoneedles. The enhanced absorption in MoS2 results from strong near-field enhancement and reduced MoS2 band gap due to the tensile strain induced by the Sn nanostructures, as confirmed by Raman and photoluminescence spectroscopy. Especially, we demonstrate that up to 3.5% biaxial tensile strain is introduced to 2D MoS2 using conductive nanoneedle-structured SnOx (x < 1), which reduces the band gap by ∼0.35 eV to further enhance light absorption at longer wavelengths. To the best of our knowledge, this is the first demonstration of a synergistic triple-functional photon management, stressor, and conductive electrode layer on 2D MoS2. Such synergistic photon management and band gap engineering approach for extended spectral response can be further applied to other 2D materials for future 2D photonic devices.