Reliable Management System Research Articles

Circular–Sustainable–Reliable Waste Management System Design: A Possibilistic Multi-Objective Mixed-Integer Linear Programming Model

Waste management involves the systematic collection, transportation, processing, and treatment of waste materials generated by human activities. It entails a variety of strategies and technologies to diminish environmental impacts, protect public health, and conserve resources. Consequently, providing an effective and comprehensive optimization approach plays a critical role in minimizing waste generation, maximizing recycling and reuse, and safely disposing of waste. This work develops a novel Possibilistic Multi-Objective Mixed-Integer Linear Programming (PMOMILP) model in order to formulate the problem and design a circular–sustainable–reliable waste management network, under uncertainty. The possibility of recycling and recovery are considered across incineration and disposal processes to address the main circular-economy principles. The objectives are to address sustainable development throughout minimizing the total cost, minimizing the environmental impact, and maximizing the reliability of the Waste Management System (WMS). The Lp-metric technique is then implemented into the model to tackle the multi-objectiveness. Several benchmarks are adapted from the literature in order to validate the efficacy of the proposed methodology, and are treated by CPLEX solver/GAMS software in less than 174.70 s, on average. Moreover, a set of sensitivity analyses is performed to appraise different scenarios and explore utilitarian managerial implications and decision aids. It is demonstrated that the configured WMS network is highly sensitive to the specific time period wherein the WMS does not fail.

Advanced Deep Learning Techniques for Battery Thermal Management in New Energy Vehicles

In the current era of energy conservation and emission reduction, the development of electric and other new energy vehicles is booming. With their various attributes, lithium batteries have become the ideal power source for new energy vehicles. However, lithium-ion batteries are highly sensitive to temperature changes. Excessive temperatures, either high or low, can lead to abnormal operation of the batteries, posing a threat to the safety of the entire vehicle. Therefore, developing a reliable and efficient Battery Thermal Management System (BTMS) that can monitor battery status and prevent thermal runaway is becoming increasingly important. In recent years, deep learning has gradually become widely applied in various fields as an efficient method, and it has also been applied to some extent in the development of BTMS. In this work, we discuss the basic principles of deep learning and related optimization principles and elaborate on the algorithmic principles, frameworks, and applications of various advanced deep learning methods in BTMS. We also discuss several emerging deep learning algorithms proposed in recent years, their principles, and their feasibility in BTMS applications. Finally, we discuss the obstacles faced by various deep learning algorithms in the development of BTMS and potential directions for development, proposing some ideas for progress. This paper aims to analyze the advanced deep learning technologies commonly used in BTMS and some emerging deep learning technologies and provide new insights into the current combination of deep learning technology in new energy trams to assist the development of BTMS.

A Bibliometric Analysis of The Term DataOps

This paper aims to analyze research trends of the term DataOps scientifically through bibliometric studies. Initial data were collected from Scopus database from 2018 to 2023 which resulted 34 documents, while in other hands we found more than 1000 documents in the Google Scholar database collected using Publish or Perish. Five years of data is collected because the scientific publications on term DataOps started to increase since 2018. We have deployed ``bibliometrix 3.0'', the r-package, and VOSviewer to analyze key literature aspects. Since the rise of the term DataOps, significant contribution to its definition and practical applications can be observed. DataOps enthusiasts collaborate to create a common principle for uniformly applying the methodology in the various data operation environments. DataOps will continue to evolve into an effective and reliable data management system. The findings in this study will help related researchers recognize the research trends of topics in DataOps research globally and suggest future research directions.

Self-Scheduling Virtual Power Plant for Peak Management

An efficient and reliable management system for a cluster of distributed energy resources (DERs) is essential for the sustainable and cost-effective peak management (PM) operation of the power grid. The virtual power plant (VPP) provides an efficient way to manage a variety of DERs for the PM process. This paper proposes a VPP framework for PM of local distribution companies by optimizing the self-scheduling of available resources, considering uncertainties and constraints. The study examines two separate scenarios and introduces novel algorithms for determining threshold values in each scenario. An approach is suggested for the transaction between VPP and the aggregator models. The proposed technique intends to determine the optimal amount of capacity that aggregators can allocate for the day-ahead PM procedure while accounting for both thermostatically controlled and non-thermostatically controlled loads. The proposed VPP framework shows promising results for reducing demand charges and optimizing energy resources for PM.

Reliable Examination Management System

Abstract: Faculty and staff members must perform invigilation duties as a prerequisite for conducting examinations, such as exams in universities. The preparation of an invigilation duty list is a laborious task in educational organizations, exam authorities, etc. It becomes more complex when more invigilators are involved for examinations scheduled daily in two or more shifts for a greater number of days. Here, we have discussed the development of a system that can generate an invigilation duty list for any type of examination. This automated system will take some required data, like staff lists, exam dates, and the number of invigilators on the days, as input and produce an invigilation duty list based on fed data. It can be useful with this approach, one may cut down on the time wasted creating the invigilation duty list by hand in any organization, including universities and institutes where exams are held.

Characterization and application of synthesized calcium alginate-graphene oxide for the removal of Cr3+, Cu2+ and Cd2+ ions from tannery effluents

Environmental sustainability has gained acceptance to achieving the goal of a secure ecosystem with a reliable management system. Heavy metal remediation of aqueous streams is of special concern due to the intractability and persistence in the environment. Adsorption is a potential alternative to the existing inefficient conventional technologies for the removal and recovery of metal ions from aqueous solutions and becomes vital to align with the Sustainable Development Goals (SDGs) and mitigate the adverse environmental and social impacts. Calcium Alginate-Graphene oxide (CA-GO) composite has been synthesized for the adsorption of heavy metals including Cr3+, Cu2+, and Cd2+ ions from tannery effluents. Graphene oxide is prepared from commercial graphite powder and reacted with sodium alginate and calcium chloride to form the beads of CA-GO composite. The developed composite was characterized by FTIR, elemental analysis, SEM, XRD analysis, and Raman spectroscopy. Moreover, the effect of pH, adsorbent dosage, contact time, and initial concentration of metal ions on the adsorption capacity were investigated through batch experiments. At a pH>3.0 (pHzpc), the carboxyl group of CA-GO was deprotonated to make the surface negatively charged and facilitate metal adsorption. The optimum pH and maximum adsorption capacity of CA-GO for removal of Cr(III), Cu(II), and Cd(II) were 4.5, 6.0, and 7.0, and 90.58, 108.57, and 134.77 mg g−1, respectively. The kinetics, adsorption isotherms, and thermodynamics were studied to determine the adsorption mechanism. The kinetic of adsorption adopted the second-order model. Thermodynamic parameter were calculated and the adsorption process was determined to be exothermic and spontaneous at room temperature. The developed composite has been efficaciously applied for the removal of metal ions and pollution from real tannery effluents.

Open-Circuit Voltage Variation in LiCoO2 Battery Cycled in Different States of Charge Regions

Open-Circuit Voltage Variation in LiCoO2 Battery Cycled in Different States of Charge Regions

Durable and reliable thermal management system with superior temperature uniformity for sidewall coring tool in extreme thermal environments

The sidewall coring tool (SCT) plays a crucial role in exploring the distribution of oil and gas resources, which needs to operate in a challenging high temperature (205 °C) and vibrating downhole environment for 21 h. However, the internal electronics are unable to withstand such extreme temperatures. Previous investigations on thermal management of downhole electronics have failed to ensure long operational duration and reliability. To solve this issue, a durable and reliable thermal management system (TMS) with superior temperature uniformity was proposed for the SCT in this paper. First, the proposed system adopted heat storage modules (HSMs) with high heat storage density and heat diffusion coefficient to enhance the heat storage rate and extend the operational duration. Second, HSMs were utilized for storing heat from nearby heat sources to improve temperature uniformity. Meanwhile, the reliability of HSMs was verified by high-temperature vibration experimental tests. Finally, through iterative optimization, the system utilized a well-designed configuration of thermal insulators and HSMs to further improve temperature uniformity, thereby extending the operational duration of the system. The performance of the total system was evaluated by thermal simulations. The maximum temperature of the heat sources remained below 150 °C after 21 h, with a maximum temperature difference between any two sources not exceeding 12 °C. Furthermore, the experiment was conducted to validate the simulated results, with the relative error within 5 %. The proposed TMS demonstrates a significantly extended operational duration and improved reliability compared to previous works, which has been successfully applied to downhole operations.

Institutional Information Communication Technology Capacity influence on E-Learning Utilization for Instruction in Kenyan Universities

E-Learning is globally recognized as a significant strategy in improving relevancy, efficiency, costeffectiveness, and quality of higher education. The paper presents a discussion of Information Communication Technology (ICT) infrastructure capacity influences on e-Learning utilization in instruction in Kenyan universities, with a view to determining strategies that universities employ to enhance e-Learning utilization. It opines that e-Learning has not been very popular as a method for instruction in universities, due to limited institutional ICT infrastructure capacities to fully implement e-Learning. The study used the mixed methods research design methodology to debate, reflect, critique, and discuss institutional capacities by universities in utilizing e-Learning in instruction. The reviewed different data sources, borrowed and immensely used government publications, e-Learning books, journals and research articles were used in document analysis. The researchers also used own intuitive experience and knowledge in e-Learning utilization in instruction. E-Learning utilization demands for collaborative effort between government, universities, faculty and students, as well us bodies like the Commission for University Education (CUE). It was found that there are several major barriers to institutional capacities of universities in utilizing e-Learning in instruction. First, was the procurement of technology and sourcing of funds. It was seen that the total capitation for funding the programs was as low as 3%. Secondly, internal barriers arising from within individual institutions and faculty. Majority of the universities for a long time have relied on face to face interaction between students and faculty. However, in the wake of the Covid-19 pandemic, all learning institutions including universities, colleges and schools were forced to close down and seek alternative methods of instruction. It was found that most universities have moderate capacities to utilize e-Learning, but are yet to exploit its full potential. The study also established that nearly all the faculty were aware and used e-Learning for instruction but to a limited extent. Findings revealed that faculty prefer blended mode of instruction, but complained of limited bandwidths and poor connectivity for faculty and students far off from the university campuses. To mitigate the challenge, universities must strive to train and retrain the faculty on how to use technology and not about technology. Based on the review carried out in six universities; all the universities have some technologies in place including Computer Based Learning, Virtual Learning, video conferencing, content delivery via networks, use of memory sticks and emails. All have an e-Learning portal, module and platforms used for e-Learning. Majority of the university dons consider bandwidth, networking and a reliable Learning management system (LMS) as critical infrastructure for e-Learning utilization. Development and improved utilization of e-Learning is practically possible with enhanced institutional capacities. Enhanced use implies enhanced information transfer, reduced movement of faculty and students allow adequate time for faculty to invest in innovative teaching; enable faster transfer of information while students actively learn on their own. This would help bridge the gap and reduce pressure on existing resources. E-Learning could be the solution to the problem of increased student enrolment and reduced quality of university education. However, to ease the burden of financing university programs, public- private sector partnerships need to be encouraged. The study established that universities must provide students with affordable internet. To a large extent it delves into possible benefits and opportunities that would arise if universities realize and utilize fully the available institutional infrastructure and e-Learning resources. Demand is made upon the universities to develop and operationalize e-Learning policy and invest more in capacity building, set up infrastructure to deliver instruction online.

Review of battery models and experimental parameter identification for lithium-ion battery equivalent circuit models

The growing use of electric vehicles has led to an ever-increasing demand for efficient and reliable management systems to control the behavior of lithium-ion batteries, especially with respect to heat generation and state-of-charge. Understanding these patterns constitutes a major new challenge for these batteries, as remaining ignorant of their behavior can result in decreased performance, shorter service life and even safety dangers. This review provides an overview of the different modeling techniques applied to simulate battery behavior. Different methods using equivalent electrical circuit models are discussed, covering both simple battery models and more complex equivalent electrical circuit models, with a focus on the 2RC-Thévenin circuit model. In this context, parameter approach methods for these systems are reviewed. In addition, laboratory tests are run to identify the various model parameters for a lithium-ion battery. This comprehensive study is designed to guide scientists and engineers in the selection and use of suitable tools for state-of-charge and battery health studies.

Heat dissipation performance research of battery modules based on composite phase change materials cooling and electrochemical thermal coupling model

In order to improve electric vehicle lithium-ion batteries (LIBs) performance and increase cycle life, it is crucial to design a reliable and efficient battery thermal management system (BTMS). Compared with other active battery cooling methods, passive phase change material (PCM) cooling has the advantages of simple structure, good temperature control uniformity, strong reliability, and no additional energy consumption. This article uses a series of experimental procedures to add expanded graphite to traditional paraffin wax PCM and obtain composite phase change materials (CPCM) with different mixing ratios. A control experiment is created to compare the cooling performance of the CPCM cooling with natural convection cooling, research shows that the cooling performance of CPCM can well meet the cooling demand which maximum temperature and maximum temperature difference of battery modules. In addition, to study the performance of thermal properties parameters related to CPCM, a COMSOL numerical calculation model of battery module based on CPCM cooling and electrochemical thermal coupling model is established. The effectiveness and accuracy of the model are verified through heat generation experiments at different rates (0.5 C, 1 C, 1.5 C), with a maximum temperature error of 1.6 K and an error accuracy of less than 0.6%. Subsequently, the performance of phase change temperature, thermal conductivity and phase change latent heat is studied and reasonable value ranges are obtained, which are 312 K∼318 K, 2.5 W /(m·K), and 175 J/g∼200 J/g, respectively.

SSE_CIB: Secure storage and exchange of copyrighted images using blockchain

AbstractThe rise of technology has resulted in the evolution of data generation at a rapid speed. With the high increase in the volume of data, it has become necessary to store it using reliable and scalable data management systems. Blockchain offers a storage structure that ensures the security and reliability of the stored data. Smart contracts further enhance the technology by enforcing more stringent record management activities. In recent times, there has been widespread utilization of IPFS in conjunction with blockchain technology. This utilization facilitates the establishment of decentralized and distributed data storage, as well as the connection of blockchain transactions to external data, thereby enhancing scalability and reducing storage expenses within blockchain applications. This paper introduces an effective collaborative ecosystem called SSE_CIB, where images undergo multiple operations including quantization before getting uploaded to IPFS. The image‐related details are stored in the blockchain to keep track of record entries. In our approach, a watermarking process has also been included to ensure the protection of copyright. Further, the images undergo block‐wise rotation based on a secret key and bit‐wise operation with a key image for enhanced security and protection. The work is implemented and tested using real‐life images in an Ethereum environment incorporated with a smart contract that enables proper execution of transactions.

Uncertainty analysis of dam-break flood risk consequences under the influence of non-structural measures

Climate change is causing an increase in the frequency of extreme disasters, increasing the likelihood of dam failures and floods. At the same time, the concentration of human activities in certain areas has increased the severity of the consequences of dam failures, requiring the establishment of more robust and reliable emergency management systems to protect lives and property. Non-structural measures serve as flexible and adaptable emergency mitigation measures that can be dynamically adjusted during rescue operations and enhance the resilience of urban systems. This article focuses on the consequences of life loss due to dam failure. Taking China's Yuyao City and SMH Reservoir as the research object, it analyzes the emergency response process after the disaster occurred, identifies the factors influencing the life loss, and selects non-structural measures such as disaster identification warnings, urban emergency management responses, evacuation routes, and destination selection as key areas of study. The research examines the impact of non-structural measures on the consequences of life loss and provides recommendations and suggestions. The results indicate that effective non-structural measures can significantly reduce the life loss in flood disasters.

Spar Cap/Shear Web Debonding Under Fatigue Loading Studied On The DTU 12.6m Wind Turbine Blade

Understanding fatigue damage initiation and propagation of composite wind turbine blades is an essential step towards the design of reliable prognostic and health management systems (PHM) and to improve lifetime predictions. This study presents a numerical investigation of the debonding process in the spar cap/shear web region of a full-scale composite wind turbine blade under fatigue loading and presents the manufacturing approach for creating initial debondings. For this purpose, numerical simulations have been performed to design and specify the size and locations of artificial defects to provoke steady, controllable damage growth in the adhesive bondline between the rear shear web and cap region of the DTU 12.6m wind turbine blade under fatigue loading. Subsequently, these artificial defects are embedded into the manufacturing process of the composite wind turbine blade with the help of slip foils and partially perforated slip foils to create regions with no bonding, 30% and 50% bonding of the contact surfaces of the adhesive joint, respectively.The numerical predictions as well as the manufactured and instrumented blade sets the framework to subsequently execute experimental tests of damage growth in the adhesive joint of the bondline in order to compare numerical and experimental data. The experimental demonstration will allow to better understand the complexity of damage growth of composite structures under fatigue loading and the necessity of accurate numerical prediction tools for reliable prognostic health management systems.

An Innovative Concept for an Intelligent Organic Waste Collection Bin that Rewards Users in Oman

As urbanization accelerates in Oman, efficient organic waste management becomes a critical challenge. This paper presents the design and development of a novel Smart Organic Waste Collection bin (SOWCB) equipped with an innovative reward system to encourage and incentivize users for responsible waste disposal in Oman. The SOWCB integrates renewable energy and sensor technologies, including RFID, load sensors, and ultrasonic sensors connected to microcontrollers to monitor and optimize the waste collection process. The innovative reward system embedded in the design offers users tangible incentives for their environmentally responsible behaviour. Further, this incentive shall be claimed by the users from the sponsors in exchange for exposure to their business ads displayed through the bin. The development involves a multidisciplinary approach incorporating 2D and 3D design using Autodesk Inventor software, mechanical fabrication, and electronic and software engineering. The paper details the bin's novel technical aspects, scope for implementation and possible outcomes. The research evaluates the effectiveness of the proposed system through pilot studies conducted in selected areas of Oman, providing insights into user acceptance, system reliability and overall organic waste management improvements. This research aligns with Be'ah's vision "to conserve the environment of our beautiful Oman for our future generations".

Exploration on Data Collection and Analysis System Based on Integrated SIFT Algorithm

With the development of applications related to image processing technology, the target requirements of data acquisition and analysis systems are constantly being optimized. Research on data acquisition and analysis based on the integrated SIFT (Scale Invariant Feature Transform) algorithm is becoming increasingly important. The construction of a data collection and analysis system focuses on ensuring efficient and accurate data collection and analysis to provide valuable insights and decision support. Key priorities include determining data requirements and objectives, designing appropriate data collection methods and tools, establishing reliable data storage and management systems, developing effective data analysis algorithms and models, and ensuring data security and privacy protection. This article analyzed the theoretical analysis of feature point extraction algorithm and the process steps and application of integrated SIFT algorithm. With the help of dimensionality reduction processing, the SIFT algorithm was improved and optimized. Combined with the scale space calculation formula, The conclusion is as follows: On the basis of image processing, the data collection and analysis system using the improved integrated SIFT algorithm on the five selected image file samples has improved the accuracy of feature point matching, with a comprehensive average improvement of 7.6%. The efficiency of feature point extraction has also been improved, with a comprehensive average improvement of about 8%. This indicated that the data collection and analysis system based on the improved integrated SIFT algorithm has good practical application results in feature point matching and extraction.

Research on the Path of Economic Management Innovation and Development in the Context of Informatization

Abstract In the context of economic informatization, the traditional economic management model has been unable to fully meet the actual needs of enterprise development. Enterprises should take effective measures to innovate the economic management model, to achieve the informationization and modernization of economic management work. Based on the needs of economic management innovation, this paper constructs a multi-dimensional digital economic management innovation path based on informationization. Then, according to the fuzzy hierarchical analysis method, construct the evaluation index system of economic management informatization, take company H as an example to carry out empirical evaluation, and analyze the influencing factors of the level of economic management informatization by using the two-sample Z-test. Company H's final evaluation score for economic management informatization is 91.23, and the level of informatization is good. The P-value of the top management's attention to informatization, the cultivation of informatization talents, the innovation ability of informatization talents, the ability of the project to meet the demand, the reliable management system of information system maintenance personnel, and the monitoring system of the information system operation is less than 0.01, and the Z-value is greater than 1.96, and the difference of its results from the hypothesis is very significant, which indicates that these six items have the greatest influence on the informatization of economic management in Company H. Empirical cases and strategy suggestions for the informatization path of economic management are presented in this paper.

Hearing Loss and its Impact in the Community

Hearing is considered an important sense of the human being. Hearing impairment cannot be visible and hence its effects are not seen by others, so the deaf suffer in silence. Hearing impairment is not only a communication problem but also a community problem. Hearing loss, which is gradual and permanent, can be brought on by congenital or acquired damage to the auditory nerve and cochlear hair cells. It reduces the working ability and performance of an individual, thus diminishing one’s participation. Hearing loss is often associated with loneliness and social isolation which has an impact on cognitive and psychosocial health. Early identification of hearing impairment in a child is vital for effective management. Hearing loss has a detrimental impact on family dynamics and, as a result, the child’s development. The widespread prevalence of deafness necessitated a reliable management system and simple clinical implementation. This public health burden can be managed by raising awareness of hearing impairment. There are plenty of clinical assessment and therapy options in hearing impairment research, but lack of knowledge about it implies that public education or awareness should be prioritized more. This review article discusses the epidemiology, etiopathogenesis, clinical features, impact of hearing impairment, and its impact on the community along with current treatment options.

Control and management of microgrid clusters: development and future research

The paper explores the potential of microgrid clustering technology and its impact on addressing energy and environmental challenges. Over the past decades, there has been a significant interest in using microgrids to ensure stability and reliability in power systems, especially considering the increasing utilization of renewable energy sources. Microgrid clusters coordinate power distribution between microgrids and the main grid, effectively addressing issues such as voltage rise, harmonics, low power factor, power backflows, and deficiencies in protection schemes. However, before implementing microgrid clustering, certain challenges need to be overcome, particularly in terms of design considerations. The paper critically reviews the design challenges of microgrid clustering, highlighting the advantages and challenges that arise during the development of microgrids, especially the problem of inadequate adaptation to large-scale renewable energy sources. The research analyzes various architectures of microgrid clusters and methods of their interaction. The classification of microgrid clustering is based on different architectures according to connection locations. Additionally, a comparison of different power transmission technologies within microgrid clusters, such as alternating current and direct current systems, is conducted with an assessment of the advantages and disadvantages of each technology. Considerable attention is given to the control and management of microgrid clusters, elucidating the possibilities of hierarchical and distributed management structures to ensure optimal power distribution and voltage and frequency regulation. In conclusion, the paper examines promising directions for further research aimed at enhancing the integration of large-scale renewable energy sources, developing intelligent management and energy management systems, as well as establishing reliable control and management systems for microgrid clusters.

Chromium adsorption capacity from tannery wastewater on thermally activated adsorbent derived from kitchen waste biomass

Environmental sustainability has gained greater acceptance as an approach to achieving the objective of a secure ecosystem with a reliable management system. The best strategy for maintaining a healthy ecosystem is waste management. In this present study, chromium (Cr) adsorption capacity from real tannery wastewater on thermally activated adsorbent, equipped from Cucurbita moschata (pumpkin) peel is described. The adsorbent features were investigated by implementing Fourier transform infrared (FTIR) spectroscopy, Scanning Electron Microscopy (SEM), Energy Dispersive X-ray (EDX), and pHpzc (point of zero charges) analysis. The Cr adsorption was identified by EDX analysis. SEM images were analyzed to record surface morphological modifications. The adsorbent has a pHpzc of 8.7. The thermally activated adsorbent is used to treat the wastewater, in a batch experiment with varying parameters including contact time, adsorbent dose, and pH. Under optimal circumstances, 50 mL of wastewater was mixed with 2.5 g of adsorbent, agitated for 10 min, allowed to settle, and then the Cr concentration was evaluated. The Cr level in untreated effluent and in filtrate was 3178.6 mg/L, and 12.1 mg/L, respectively. The capability of Cr adsorption and Cr removal efficiency was 3164.46 mg/g and 99.32%, correspondingly, at a pH of 7.2. The biochemical oxygen demand (BOD), chloride (Cl-), and chemical oxygen demand (COD) showed a decreasing percentage of 96.58%, 55.62%, and 95.01%. The Cr adsorption fitting for pumpkin peel adsorbent follows the Pseudo second-order (PSO) kinetic and Freundlich isotherm model. Thus, this investigation established the efficiency of using pumpkin peel as an adsorbent for Cr tanning effluent treatment.