Operational Support Research Articles

Visioning channel evolution for river management: Toward a functional decision support framework

AbstractImprovements in simulating and communicating the evolutionary trajectory of river morphology in response to environmental forcing over multi‐decadal timeframes would foreshadow the development of “foresight competency” in river management, whereby resource managers could strategically plan toward the most preferred of several plausible futures. Of the six steps in foresight competency, visioning, which involves translating scientific forecasts into a format useable by resource managers via a user‐friendly and interactive decision support tool that supports transparent decision‐making, is the least well developed. The approach requires converting forecasting model outputs into metrics of channel evolution that highlight transitions either within or between channel morphology states. Here, seven process‐based state transition metrics are proposed covering channel planform, morphological stability, corridor belt width, floodplain connectivity, bank erosion rate, bedform habitat diversity, and ecohydraulic diversity. To aid decision support, the metrics are converted into graphical indicators that are intuitive for management use and assembled into several prototype dashboard‐style graphical user interfaces designed to facilitate interactivity. A proof‐of‐concept illustration is provided and priorities in development toward a fully operational decision support tool are discussed. Such developments are critical in ensuring the practical relevance of geomorphology.

Research on neural network-based fault diagnosis and prediction method for power communication equipment

Abstract In this paper, facing the digital development of the power grid and the status quo of massive power communication equipment access and targeting the demand for highly intelligent operation and maintenance management of the power grid, combined with neural network technology, we propose an intelligent diagnosis model of power communication equipment faults. Adopting BERT as the vector embedding layer to obtain the vector sequence of fault text, designing a fault entity recognition model for power communication equipment based on BERT-BiGRU-CRF, and completing the construction of the relationship set of fault text. The proposed knowledge graph-based power communication equipment fault intelligent diagnosis model combined with the WBLA-based power communication equipment fault severity level recognition algorithm to obtain different severity fault information, from which a TFIDF-COS-based power communication equipment fault intelligent diagnosis algorithm is designed to realize intelligent diagnosis of power communication equipment faults. After testing, the TFIDF-COS algorithm can get the best optimization effect when the number of hidden layers of the selected algorithm is 1, and the initial learning rate is 0.05, and its accuracy rate can be kept above 98%. Compared with the traditional fault diagnosis system, in terms of the order of magnitude 100M, 500M, 1G, and 5G, the running time is reduced by 322s, 1874s, 4617s, and 7467s, and the accuracy rate is increased by 2.33%, 2.6%, 32.02%, and 61.4%, respectively. Therefore, this paper realizes the accurate positioning of power communication equipment faults and provides technical support for intelligent operation and maintenance of the power grid.

Critical station identification and robustness analysis of urban rail transit networks based on comprehensive vote-rank algorithm

Urban rail transit networks have become the most important traffic modal and greatly improve the traffic environment and travel efficiency of metropolis, and the critical station identification and robustness assessment of urban rail transit networks have become more and more important. In this paper, we propose a comprehensive vote-rank (CVR) algorithm to identify the critical stations, and adopt mutual information and k-center clustering algorithm to analyze the similar characteristics of passenger flow on different dates of urban rail transit networks. Meanwhile, Shanghai metro network is chosen as the example and we find that the optimal classification of passenger flow on different dates is 2 categories, and the passenger flows have the significant differences between conventional day and unconventional day. The results show that the critical stations on unconventional day are farther from the city center than the critical stations on conventional day, and some critical stations locate in the suburbs on unconventional day. Moreover, we study the structural and functional robustness characteristics of urban rail transit networks subjected to continuous malicious attacks to the top critical nodes, and the results show that Shanghai metro network has the worse robustness subjected to malicious attacks. Compared with the existed methods, we can declare that the proposed CVR algorithm is the most effective method for critical station identification and robustness assessment among the discussed methods in this paper, and this study will provide theoretical and practical support for the safe operation of urban rail transit networks.

The Development of High Availability Database Infrastructure for OSS Projects with Monitoring Systems in Cloud Computing Environments

This study addressed a critical problem in the Kominfo's Operation Support System (OSS) project, which significantly impacted business operations. The outage of the MongoDB database, a vital component of OSS, resulted in server crashes and data damage. To overcome this issue, the OSS team initiated a project to migrate to PostgreSQL for high availability and improved database performance. The implementation involved the use of HA PostgreSQL technology, with multiple connected servers sharing data in real-time. Through functional and performance testing, the study has demonstrated that the HA PostgreSQL system increased database availability, managed server failures, and facilitated effective cluster administration. The findings of this research can guide the development of the OSS project's IT infrastructure and serve as a reference for similar projects utilizing HA PostgreSQL technology.

Clif Family Foundation grants for operational support

Clif Family Foundation grants for operational support

Shaft Wall Damage to High-Depth Inclined Ore Passes under Impact Wear Behavior

In order to study shaft wall damage resulting from ore drawing in ore passes, a theoretical model for predicting the shaft wall damage to high-depth inclined ore passes is constructed based on field surveys of 25 ore passes in a deep mine in Yunnan, China. The mathematical expression of the total shaft wall damage volume is derived using the contact mechanics theory. Considering the structural characteristics of ore passes, and taking No. 1, 2, 3, and 9 ore passes as examples, combined with numerical simulation and an engineering case, the rationality of the proposed theoretical model is verified with respect to the initial collision position and the damage conditions of the shaft wall. The influence of, and sensitivity to, the ore block size P and the structural parameters of high-depth inclined ore passes on the total shaft wall damage volume Qtol are quantitatively analyzed. The results show that the calculation results of the theoretical model and numerical simulation are in good agreement with the actual engineering situations. Moreover, the ore-pass dip angle θ and the inclined angle of the chute α have a significant impact on the damage to the shaft wall, while the effects of the ore-pass depth H and the shaft diameter D are comparatively minor. With an increase in θ or α, Qtol generally first increases and then decreases. Qtol increases exponentially with P and increases steadily with D. H affects Qtol by influencing the collision frequency between the ore and the shaft wall. Therefore, in the mining design of deep mines, θ and α should be minimized as much as possible or adjusted to approach 90°, thereby reducing damage to the shaft wall. Secondly, ore block size should be strictly controlled to prevent collapses in the shaft wall caused by large ore blocks. This work provides technical support for the long-term safe operation of high-depth inclined ore passes.

Experiment and theoretical analysis of using natural cold source and cold storage in food refrigerated display cabinet

This work attempts to introduce natural cold source to solve the prominent problem of high energy consumption of food refrigerated display cabinets. The characteristics of natural cold source food refrigerated display cabinet was systematically studied with a typical climate type of city. The theory and experimental methods were employed to analyze its operating strategy and refrigeration performance. Five working modes of the system are recommended according to the outdoor temperature. Besides, the studies proposed operational strategies for natural cold source refrigerated display cabinet systems concerning four typical days and throughout year, followed by an analysis of their energy-saving potential. The results of this study reveal that the natural cold source food refrigerated display cabinet could satisfy the cold storage requirement of food and has good energy saving ability. Compared with the traditional refrigeration system, the energy is saved by 25.46 %, 14.50 %, 15.65 %, 41.95 % on four typical days for natural cold source food refrigerated display cabinet, and save energy consumption by 21.08 % throughout the year. This study can provide a technical support for the energy-saving operation of food refrigerated display cabinets.

Optimizing Electric Truck Routing and Charging with Soft Time Windows Using Vehicle-to-Grid Technology

Due to the rapid increase in the use of electric vehicles and instability in energy supply, the application of vehicle-to-grid (V2G) technology has gained attention in the freight transportation sector. V2G has the potential to increase the efficiency of power grid and make additional profits by utilizing surplus power from electric vehicle batteries. This paper proposes an optimization model for electric trucks (ETs) to provide operational decision-making support for the freight transportation sector. The objective of the model is to minimize the total net cost, which includes charging cost, discharging reward, and time penalties, while considering changes in ET charging cost and the system marginal price. Furthermore, we conduct sensitivity analysis in the vehicle routing problem with soft time windows using ETs in the V2G system.

An integrated surrogate model-driven and improved termite life cycle optimizer for damage identification in dams

Structural Damage Identification (SDI) is a crucial branch in the field of structural health monitoring, providing an essential support for the safe operation of structures. In this paper, a novel structural damage identification method based on a surrogate-assisted evolutionary optimization algorithm is proposed. This method incorporates cost-effective surrogate modelling techniques and swarm intelligence optimization algorithms with powerful global optimization capabilities. Three popular surrogate models are fused based on a weighted average strategy to construct an integrated surrogate model with stronger generalization ability and higher accuracy. In addition, the self-designed movement strategy is more suitable for the characteristics of Termite Life Cycle Optimizer (TLCO), allowing the improved TLCO to have stronger robustness and the capability to escape from local optimum. The effectiveness of the proposed method for solving the SDI problem is confirmed in a damaged dam model with different complexities. Some important findings are as follows: (i) Compared with the conventional SDI methods, which directly combines optimization algorithms and finite element models, the proposed method maintains reliable accuracy, while improving computational efficiency by a factor of more than 100. (ii) There is no direct relationship between the accuracy of the surrogate models and the effectiveness of the SDI method based on their combination with ITLCO. The proposed method can serve as a promising tool for damage identification in large-scale structures.

Effect of PNBP Policy on The financial Performance of Cellular Mobile Network Operators

Digital transformation is one of the programs initiated by the Government, which in practice requires the support of healthy mobile network operators through financial performance indicators, to fulfill the development of telecommunications infrastructure in all regions. Mobile network operators require significant capital to provide telecommunications infrastructure, including payment of Non-Tax State Revenue (PNBP) to the government every year, which continues to increase due to frequency allocation and telecommunications activities. The aim of this research is to measure the estimated influence of PNBP policy on the financial performance of mobile network operators in Indonesia, while considering several other control variables such as investment costs (CAPEX), number of subscribers, liabilities, number of base transceiver stations (BTS), and number of mobile network operators. This research uses panel data regression with a fixed effect model approach, covering four mobile network operators from 2010 to 2022. The results show that PNBP, sourced from the obligation to pay Spectrum Frequency Usage Fee, has a significant negative impact on financial performance. These findings are also consistent with the research conducted by Katz and Jung (2023)

DIGITAL PLATFORM ARCHITECTURE FOR ENGINEERING EDUCATION MODEL

Digital platforms have become an essential part of engineering education's innovative transformation as a result of the rapid development of technology and constant changes in the field. This article examines and emphasizes the importance of developing a digital platform to provide resources and operational support for implementing the National Model of Engineering Education. The article describes the architecture of a modular digital platform. A study identifies what services are required, which user categories will use it, and which software components should be implemented. As a result of implementing a digital platform based on the proposed architecture, various categories of users will be able to access the necessary set of engineering profession-related services.

The Role of INTERPOL in the European Integrated Border Management

Aim: The study focuses on how the cooperation between the EU and INTERPOL fits into the European integrated border management system, how it contributes to the effectiveness of external border management, and what challenges it faces.Methodology: The paper examines cooperation from the perspective of European integrated border management, drawing on relevant international and national literature on the topic.Findings: By examining this cooperation, the author demonstrates that the relationship between INTERPOL and the EU border administration is vital to enhancing the EU’s ability to effectively manage its borders. INTERPOL provides valuable intelligence, training and operational support to EU Member States in the fight against terrorism, organised crime and other transnational threats. Cooperation contributes significantly to improving border management practices, strengthening cross-border cooperation and ensuring the safety and security of EU citizens.Value: The study presents the relationship between INTERPOL and the EU border management agencies through the European integrated border management model and highlights the challenges involved.

State of Health estimation for lithium-ion batteries using Random Forest and Gated Recurrent Unit

Lithium-ion batteries are widely used in electric vehicles, energy storage and other fields, and the State of Health (SOH) estimation of lithium-ion batteries are key to ensure the safe operation of battery systems. In this paper, a method combining Empirical Modal Decomposition (EMD), Random Forest (RF) and Gated Recurrent Unit (GRU) for SOH estimation of lithium-ion batteries was proposed. In this approach, we first extracted the time interval during equal voltage increase and the time interval of equal voltage decrease as health indicators (HIs), and analyzed the correlation between the health indicators and SOH using Pearson's coefficient. After that, the empirical modal decomposition (EMD) was used to decompose the battery SOH data, and the Variance Contribution Ratio (VCR) was introduced to measure the relationship between the intrinsic modal function (imf) component and SOH. Finally, an EMD-VCR-GRU-RF based SOH estimation model was developed. The prediction results show that the EMD-VCR-GRU-RF model has the smallest prediction error and the model computation time is at least 15.84 % less than that of the EMD-VCR-GRU model. Our work effectively applies deep learning and machine learning to battery health management, balancing prediction accuracy and computational efficiency. It provides support and reference for battery health management and smart operation and maintenance.

Exploring a novel reservoir drawdown operation framework for boosting synergies of hydropower generation and drought defense

The seasonal operation of drought-limited water level (DLWL) can efficiently boost the synergies of hydropower production and drought defense. This study proposes a seasonal DLWL operation framework for mimicking reservoir drawdown operation to improve hydropower output and mitigate drought risk. Firstly, three statistical analysis methods were used to divide the drought season into three segments. And then, the simulation model of seasonal DLWL operation was configured to evaluate the effect of reservoir drawdown operation on risk and benefits. Lastly, the combined distance-based assessment method was employed to identify the best scheme of seasonal DLWL operation. The Three Gorges Reservoir sited in the Yangtze River of China constitutes the case study. The results suggested that the proposed framework could facilitate reservoir drawdown operation to achieve 2346.95 million kW·h (7.0% improvement) in annual hydroelectricity production and 3.3% improvement in annual utilization efficiency of water resources, while could reduce 22.2% in drought risk during the dry year, compared with the annual DLWL operation scheme. This study not only can provide scientific and technical support for reservoir drawdown operation benefiting synergies of hydropower generation and drought defense but also can suggest policymakers with various favorable strategies to experience potential risks and benefits of seasonal DLWL operation in the interest of sustainable hydropower development.

Daily exposure to combat-related cues and posttraumatic stress symptoms among veterans: Moderating effects of peri- and postdeployment experiences.

One of the central symptoms of posttraumatic stress disorder (PTSD) is a heightened reactivity to trauma cues. The current study used experience sampling to investigate the associations between exposure to combat-related cues and PTSD symptoms in 93 U.S. veterans who served in support of recent military operations in Afghanistan and Iraq. We also examined the effects of peri- and postdeployment factors, including exposure to combat, unit support during deployment, and postdeployment social support on PTSD. Participants completed eight brief random surveys daily for 2 weeks using palmtop computers. The results indicated that more daytime exposure to trauma cues was associated with experiencing more PTSD symptoms at the within-person level, B = 3.18. At the between-person level, combat exposure, B = 4.20, was associated with more PTSD symptoms, whereas unit support, B = -0.89, was associated with experiencing fewer symptoms. At the cross-level interaction, unit support, B = -0.80, moderated the association between trauma cue exposure and PTSD symptom count. Contrary to our hypothesis, postdeployment social support, B = -0.59, was not associated with PTSD symptoms. These findings suggest a functional association between exposure to trauma cues and PTSD symptoms among recent-era U.S. veterans and underscore the importance of unit support during deployment.

Artificial intelligence for improving public transport: a mapping study

The objective of this study is to provide a better understanding of the potential of using Artificial Intelligence (AI) to improve Public Transport (PT), by reviewing research literature. The selection process resulted in 87 scientific publications constituting a sample of how AI has been applied to improve PT. The review shows that the primary aims of using AI are to improve the service quality or to better understand traveller behaviour. Train and bus are the dominant modes of transport investigated. Furthermore, AI is mainly used for three tasks; the most frequent one is prediction, followed by an estimation of the current state, and resource allocation, including planning and scheduling. Only two studies concern automation; all the others provide different kinds of decision support for travellers, PT operators, PT planners, or municipalities. Most of the reviewed AI solutions require significant amounts of data related to the travellers and the PT system. Machine learning is the most frequently used AI technology, with some studies applying reasoning or heuristic search techniques. We conclude that there still remains a great potential of using AI to improve PT waiting to be explored, but that there are also some challenges that need to be considered. They are often related to data, e.g., that large datasets of high quality are needed, that substantial resources and time are needed to pre-process the data, or that the data compromise personal privacy. Further research is needed about how to handle these issues efficiently.

Laporan Akhir Kerja Praktik (KP) Aplikasi Surat Perintah Perjalanan Dinas Di UPTD PPD Medan Utara Bapenda Provsu

The Regional Revenue Agency (BAPEDA) is a government operational support component that carries out financial support tasks in the field of regional income. The author conducted a study of the official travel system while working practically, and at the UPTD PPD North Medan Bapenda PROVSU Medan produced an official travel order application. The author's aim in carrying out this practical work is to support the personnel department in the process of updating employee data including data entry and output. Assist in verifying car number plates and payment of vehicle tax that has just been registered on the e-Samsat application via the website with the branch office. Assist in preparing official travel orders and vehicle transfer reports. After a month of direct practice, the author found many incidents where after discussing with agency superiors, the author discussed the issue of Official Travel Orders (SPPD). The agency will use an inefficient and time-consuming system to handle future cases. because getting permission for official travel requires you to personally navigate a protracted bureaucracy. Therefore, the author used the skills he acquired in college to create an official travel booking system for an agency based on a website, making it easier for the department employees who handle it to obtain permits via the internet only. It can be concluded that students gain new information and experience through practical work that they would not get from face-to-face lectures. A clear picture of the overall scope of activities of an agency is provided through practical work. Additionally, practitioners receive training on how to perform their work with care, diligence, and analysis.

Mindlin cracked plates modelling and implementation in train-track coupled dynamics

Nowadays, the widely constructed ballastless track in high-speed railways will inevitably suffer from localized damage cracks induced by complicate environmental effects, which would change its designed dynamic performance under train dynamic loads and further affect its service life and durability. To this end, a semi-analytical approach of the in-plane and the out of plane forced vibration for Mindlin plates with a side crack are derived, and is further implemented into the train-track coupled dynamic (TTCD) system which comprehensively considering nonlinear wheel-rail contact and 3D spatial flexibility of the cracked track slab. The dynamic partial differential equation of the cracked slab is derived by Hamilton principle and discretized by Galerkin method. Then the eigenvalues and forced vibrations of the cracked slabs for both in-plane and flexural vibrations are tackled utilizing a set of powerful trigonometric modified by special corner function, which can effectively explain the singularity of stress at the crack tip and the discontinuity of deformation on both sides of the crack. The eigenvalue analysis and mode shapes of the cracked plate mode in free boundary condition are compared with the finite element method to verify its accuracy. Meanwhile, the reliability of the proposed dynamics model is verified by comparing with the responses predicted by the co-simulation technology. Finally, the discrepancies of dynamic responses of the track slab with or without a side crack are analyzed, and the effects of various operation speeds and support stiffness on the dynamic behaviour of both slabs are revealed. Results indicates that the track slab with a side crack has significant distinctions on the slab dynamic signals in both time and frequency domains, and the amplitude amplification phenomenon occurs in some specific areas compared with the intact slab; The type-Ⅱ stress intensity factor (SIF) is more sensitive to train speeds, while the support stiffness is highly correlated to all types of SIFs. This work may contribute to the scientific maintenance and health monitoring of high-speed railway tracks.

Bird Watching Tourism in Sustainable and Accessible Destinations: The Case of the Entrepreneurial Venture Explora Caloccita in the Mexican Pacific Coast

Summary Bird watching is an activity that may prompt sustainable tourism development in remote communities. This case study lays out some lessons learned from the entrepreneurship case Explora Caloccita, a young venture offering bird watching to tourists in the Mexican Pacific coast. This case is based on descriptive research, laying out the practitioners’ insights and analysing the supply of experiences related to bird watching. The innovative vision of the entrepreneurs, the financial and logistical backing by the local hotel La Quinta, and the support of residents and local tour operators allow for the conclusion that bird-watching tourism has been, in this particular case, a sustainable economic alternative. Furthermore, the entrepreneurship Explora Caloccita is embedded in a destination that strongly supports accessible tourism, sustainable local development and nature preservation. The venture and the place’s sustainability are both possible thanks to the strong connections among all stakeholders and residents in the area, as locals also support the bird-watching routes and thus contribute to the conservation of the native and migrant bird species. Information © The Authors 2023

Advancing Readiness Through Military Programs: An Evidence-Based Practice Perspective.

Military nurses comprise the largest percentage of military health care providers. In the current military health care system, they have two roles: (1) Patient care in military treatment facilities (MTFs) and (2) patient care during combat operations. Although in MTFs, the military nurse's roles are similar to those of their civilian counterpart, their roles are unique and varied in the combat operational environment. These combined roles lead to questions regarding readiness training to ensure that nurses are proficient in both MTFs and combat operational settings where treatment requirements may differ. The purpose of this paper is to (1) present the current state of educational readiness programs to maintain a ready medical force that entail formal teaching programs, military-civilian partnerships, and joint exercises of combat simulations, and (2) identify gaps as presented in an evidence-based practice educational panel. On March 11, 2022, TriService Nursing Research Program hosted the virtual First Military Evidence-Based Practice Summit from the Uniformed Services University of the Health Sciences in Bethesda, MD. As part of the summit, an evidence-based practice education panel discussed the availability of current evidence-driven military medical readiness programs and identified gaps in the integration of military readiness for nursing personnel into the Defense Health Agency and Armed Services. The panel participants discussed the separate requirements for training within the MTFs and in combat operational settings. The available training programs identified by the panel were primarily those developed in local MTF settings to meet local needs. Although these programs support the MTFs' peacetime mission, competing roles, limited time, and limited funds contributed to limited preparation of nursing personnel in skills associated with combat-related injuries and illnesses. Prolonged casualty care has become an important focus for the Department of Defense as greater considerations are directed to wartime operations in austere expeditionary environments. Although there is some training available that is specific for prolonged casualty care, the focus has been the adaptation of combat casualty care during contingency operations. A keynote here was the concept that combat casualty care training must include both development of individual skills and integration of the team since maximal care can be achieved only when the individual and the team operate as a unit. A key point was the utility of central repositories for storing information related to training a ready medical force at individual and unit levels and that these repositories could also be used to collect and facilitate the accession of current evidence-based information. Optimal patient care at all levels of the military health system requires training that maximizes individual and unit skills specific to the environment at an MTF or in a combat operational setting. Training must be designed to incorporate evidence-driven knowledge in all military settings with guidance that is specific to the environment. Enhanced communication of evidence-based training and knowledge is an important component of maintaining a ready medical force for broader medical support of combat contingency operations.