Auswahl der wissenschaftlichen Literatur zum Thema „Service stacking“

This research aimed to discovered and analyzed those efficiency of logistics costs by hub and spoke system at Cikarang dry port that provides ports which included logistics services with logistics companies and supply chains so it would contributes to reducing logistics costs and dwelling time at Tanjung Priok Port. This research uses Factor Analysis and AHP (Analitycal Hierarchy Process) method as a method to find out all factors which influence most towards logistics performance and how to reduce those logistics costs at Cikarang Dry Port. Factor Analysis result starting from 14 elements into 8 elements which divided into 3 factors such as transportation, administration and inventory costs. The weight of loading and unloading costs is 0.24709, the weight of container costs is 0.20384 and the weighting of stacking fees is 0.14429. So AHP results was obtained from factors and elements of logistics costs Cikarang Dry Port which has most influence are F1 (loading and unloading costs), F6 (custom service fees), F8 (forwarding service costs), F2 (goods inspection service costs), F4 (stacking fees) , F12 (service quality that needs to be improved), F3 (container tariffs), F5 (loading and unloading labor rates).

BackgroundEarly childhood interventions are critical for reducing child health and development inequities. While most research focuses on the efficacy of single interventions, combining multiple evidence-based strategies over the early years of a child’s life may yield greater impact. This study examined the association between exposure to a combination of five evidence-based services from 0 to 5 years on children’s reading at 8–9 years.MethodsData from the nationally representative birth cohort (n=5107) of the Longitudinal Study of Australian Children were utilised. Risk and exposure measures across five services from 0 to 5 years were assessed: antenatal care, nurse home-visiting, early childhood education and care, parenting programme and the early years of school. Children’s reading at 8–9 years was measured using a standardised direct assessment. Linear regression analyses examined the cumulative effect of five services on reading. Interaction terms were examined to determine if the relationship differed as a function of level of disadvantage.ResultsA cumulative benefit effect of participation in more services and a cumulative risk effect when exposed to more risks was found. Each additional service that the child attended was associated with an increase in reading scores (b=9.16, 95% CI=5.58 to 12.75). Conversely, each additional risk that the child was exposed to was associated with a decrease in reading skills (b=−14.03, 95% CI=−16.61 to −11.44). Effects were similar for disadvantaged and non-disadvantaged children.ConclusionThis study supports the potential value of ‘stacking’ early interventions across the early years of a child’s life to maximise impacts on child outcomes.

Abstract. Satellite-based InSAR (Interferometric Synthetic Aperture Radar) provides an effective way to measure large-scale land surface motions. Currently, the atmospheric phase delay is one of the most critical issues in InSAR deformation monitoring. Generic Atmospheric Correction Online Service (GACOS) is a free, globally available and easy-to-implement tool to generate high-resolution zenith total delay maps, which could be used for InSAR atmospheric delay correction. The mean velocity could then be estimated by stacking multiple GACOS-corrected interferograms. We applied the proposed GACOS-corrected InSAR stacking method in the North China Plain and analysed its performance. Within the 549 interferograms, more than 85 % gained positive correction performances. The correlation between the phase-dZTD indicator and the performance reached 0.89, demonstrating a significant relationship. Deformation maps revealed by InSAR stacking with and without GACOS corrections showed that GACOS could mainly remove the topography-related and long wavelength signals.

Today's Internet and enterprise networks are so popular as they can easily provide multimedia and ecommerce services to millions of users over the Internet in our daily lives. Since then, security has been a challenging problem in the Internet's world. That issue is called Cyberwar, in which attackers can aim or raise Distributed Denial of Service (DDoS) to others to take down the operation of enterprises Intranet. Therefore, the need of applying an Intrusion Detection System (IDS) is very important to enterprise networks. In this paper, we propose a smarter solution to detect network anomalies in Cyberwar using Stacking techniques in which we apply three popular machine learning models: k-nearest neighbor algorithm (KNN), Adaptive Boosting (AdaBoost), and Random Decision Forests (RandomForest). Our proposed scheme uses the Logistic Regression method to automatically search for better parameters to the Stacking model. We do the performance evaluation of our proposed scheme on the latest data set NSLKDD 2019 dataset. We also compare the achieved results with individual machine learning models to show that our proposed model achieves much higher accuracy than previous works.

In recent years, the widespread deployment of the Internet of Things (IoT) applications has contributed to the development of smart cities. A smart city utilizes IoT-enabled technologies, communications and applications to maximize operational efficiency and enhance both the service providers’ quality of services and people’s wellbeing and quality of life. With the growth of smart city networks, however, comes the increased risk of cybersecurity threats and attacks. IoT devices within a smart city network are connected to sensors linked to large cloud servers and are exposed to malicious attacks and threats. Thus, it is important to devise approaches to prevent such attacks and protect IoT devices from failure. In this paper, we explore an attack and anomaly detection technique based on machine learning algorithms (LR, SVM, DT, RF, ANN and KNN) to defend against and mitigate IoT cybersecurity threats in a smart city. Contrary to existing works that have focused on single classifiers, we also explore ensemble methods such as bagging, boosting and stacking to enhance the performance of the detection system. Additionally, we consider an integration of feature selection, cross-validation and multi-class classification for the discussed domain, which has not been well considered in the existing literature. Experimental results with the recent attack dataset demonstrate that the proposed technique can effectively identify cyberattacks and the stacking ensemble model outperforms comparable models in terms of accuracy, precision, recall and F1-Score, implying the promise of stacking in this domain.

This paper describes a novel rapid manufacturing and remanufacturing system based on robotic gas metal arc welding. If worn parts are maintainable, this system play a repairer role; if worn parts are unfit to remain in service, this system play a manufacturer role. This system works in ‘modeling - slicing - stacking’ principle. First, Detecting and building three-dimensional models of damaged zone by structured light. Second, Slicing established three-dimensional model in layers with some thickness. Third, planning robotic tool path to get optimumwelding path and parameters. Finally, executing remanufacturing task with robotic GMAW stacking layer by layer. This system remanufactures parts in human - robot interactive way. Take a half cylinder shell as worn part, experiments are conducted. Results show the mean error of surface smoothness is less than 0.5mm.

The single crystal superalloys CMSX-4 and TMS75 were tested for very long times at high temperatures in laboratory creep tests and in service. The microstructure was investigated in TEM and SEM. It was found, that the ’-phase is cut at stresses much below the threshold given in literature. Cutting takes place by <110> screw dislocations. These mobile dislocations can be locked locally by a Giamei-lock. Thus a stacking fault dipole forms between the locked segment and the preceding ones. The dipole consists of two supershockley dislocations with 30° character, which are also stabilized by Giamei locks. The dipole formation is analyzed and discussed in detail.

PT Delta Arta Bahari Nusantara is a regional-owned company owned by the East Java region as a loading and unloading operator for the Probolinggo port trying to improve port operation services, one of the efforts that has been made is building port facilities. There is an increase in loading and unloading activities of superior commodities, it is necessary to increase the quality. Efforts to maintain service quality of a company must analyze and serve data and information accordingly from data and measurements, in this case, product suitability and customer satisfaction levels. The purpose of this research is to measure the service quality of PT Delta Arta Bahari Nusantara uses 5 service quality dimensions, the measurement results (gap) between customer perceptions and expectations are evaluated by the Quality Function Deployment (QFD) method. Furthermore, based on the policy (gap) and QFD, strategies are formulated that must be carried out. The results of the analysis showed that all dimensions resulted in a satisfaction level of "less satisfied" (Gap value between -1.5 to -2.25) which means that in all dimensions of satisfaction, customer service ratings provided by PT Delta Arta Bahari Nusantara is not satisfied with meeting expectations. There are 5 indicators that require immediate improvement. Indicators that require the main priority for improvement are the condition and capacity of the dumping yard as well as the facilities and infrastructure, the layout of the stacking field facilities. Recommendations that can be given by the management are evaluating the maximum capacity with the number of storage for goods to determine the addition of the storage area, making improvements to the layout of the facilities and completing if there are lack of public facilities.

With global climate change as the main driver, there is an increase towards including more variable renewable energy (VRE) sources in the electricity mix. Energy production from utilizing the photovoltaic effect, or PV power, is increasing rapidly and is visioned to cover 5 – 10 % of Sweden’s electricity demand in 2040. In addition to rooftop PV production, large- scale PV production in the form of ground-mounted PV parks is gaining ground. A higher share of VRE in the power system creates new challenges as to uphold the power system stability. For a PV park owner, achieving a preferable economic outcome is also a challenge, as the variable electricity output may not match electricity demand. Therefore, combining a PV park with an energy storage, which can store the PV production energy, is seen as a favorable solution. This way, the variability of the electricity production can be reduced and the stored energy in the battery can be used for services benefitting both the PV park owner and the power grid. This study aims to explore the economic potential of combining a PV park with an energy storage. This is achieved by simulating a lithium-ion (Li-ion) battery storage combined with PV production modeled after a 3.5 MW PV park located in Fyrislund, Uppsala. Five cases with individually differing approaches are simulated, exploring how so-called service stacking can be applied with a battery. The investigated services included in the cases are 1) lowering the cost of connecting the PV park to the power grid, 2) lowering the cost of feeding in energy to the power grid, 3) increasing the revenue of selling electricity on the Nord Pool spot market, 4) increasing the revenue by performing energy arbitrage, 5) increasing the revenue by participating in the primary frequency regulating markets to help stabilize the 50 Hz grid frequency. The cases are evaluated by calculating the net present value (NPV) of the system over 10 years with an annual discount rate of 5 %. Battery capacities ranging from 0.1 MWh/0.1 MW to 8 MWh/2 MW are tested. The system configuration achieving the highest NPV occurs when all services are performed, and a 0.13 MWh/0.1 MW battery is used. This NPV is also higher than the NPV when not including a battery in the system. Conclusions include that the spot price impacts the choice of battery capacity to a high extent and that the battery investment cost motivates using a smaller-sized battery.

These Guidelines are one of the results of the four-year research project “Open Online Learning for Digital and Networked Society” (2017-2021). The project objective was to enable university teachers to design open and online learning through open and online learning curriculum and environment applying learning analytics as a metacognitive tool and creating open and online learning assessment and recognition practices, responding to the needs of digital and networked society. The research of the project resulted in 10 scientific publications and 2 studies prepared by Vytautas Magnus university Institute of Innovative Studies research team in collaboration with their international research partners from Germany, Spain and Portugal. The final stage of the research attempted creating open and online learning assessment and recognition practices, responding to the learner needs in contemporary digital and networked society. The need for open learning recognition has been increasing during the recent decade while the developments of open learning related to the Covid 19 pandemics have dramatically increased the need for systematic and high-quality assessment and recognition of learning acquired online. The given time also relates to the increased need to offer micro-credentials to learners, as well as a rising need for universities to prepare for micro-credentialization and issue new digital credentials to learners who are regular students, as well as adult learners joining for single courses. The increased need of all labour - market participants for frequent and fast renewal of competences requires a well working and easy to use system of open learning assessment and recognition. For learners, it is critical that the micro-credentials are well linked to national and European qualification frameworks, as well as European digital credential infrastructures (e.g., Europass and similar). For employers, it is important to receive requested quality information that is encrypted in the metadata of the credential. While for universities, there is the need to properly prepare institutional digital infrastructure, organizational procedures, descriptions of open learning opportunities and virtual learning environments to share, import and export the meta-data easily and seamlessly through European Digital Hub service infrastructures, as well as ensure that academic and administrative staff has digital competencies to design, issue and recognise open learning through digital and micro-credentials. The first chapter of the Guidelines provides a background view of the European Qualification Framework and National Qualification frameworks for the further system of gaining, stacking and modelling further qualifications through open online learning. The second chapter suggests the review of current European policy papers and consultations on the establishment of micro-credentials in European higher education. The findings of the report of micro-credentials higher education consultation group “European Approach to Micro-credentials” is shortly introduced, as well as important policy discussions taking place. Responding to the Rome Bologna Comunique 2020, where the ministers responsible for higher education agreed to support lifelong learning through issuing micro-credentials, a joint endeavour of DG Employment, Social Affairs and Inclusion and DG Research and Innovation resulted in one of the most important political documents highlighting the potential of micro-credentials towards economic, social and education innovations. The consultation group of experts from the Member States defined the approach to micro-credentials to facilitate their validation, recognition and portability, as well as to foster a larger uptake to support individual learning in any subject area and at any stage of life or career. The Consultation Group also suggested further urgent topics to be discussed, including the storage, data exchange, portability, and data standards of micro-credentials and proposed EU Standard of constitutive elements of micro-credentials. The third chapter is devoted to the institutional readiness to issue and to recognize digital and micro-credentials. Universities need strategic decisions and procedures ready to be enacted for assessment of open learning and issuing micro-credentials. The administrative and academic staff needs to be aware and confident to follow these procedures while keeping the quality assurance procedures in place, as well. The process needs to include increasing teacher awareness in the processes of open learning assessment and the role of micro-credentials for the competitiveness of lifelong learners in general. When the strategic documents and procedures to assess open learning are in place and the staff is ready and well aware of the processes, the description of the courses and the virtual learning environment needs to be prepared to provide the necessary metadata for the assessment of open learning and issuing of micro-credentials. Different innovation-driven projects offer solutions: OEPass developed a pilot Learning Passport, based on European Diploma Supplement, MicroHE developed a portal Credentify for displaying, verifying and sharing micro-credential data. Credentify platform is using Blockchain technology and is developed to comply with European Qualifications Framework. Institutions, willing to join Credentify platform, should make strategic discussions to apply micro-credential metadata standards. The ECCOE project building on outcomes of OEPass and MicroHE offers an all-encompassing set of quality descriptors for credentials and the descriptions of learning opportunities in higher education. The third chapter also describes the requirements for university structures to interact with the Europass digital credentials infrastructure. In 2020, European Commission launched a new Europass platform with Digital Credential Infrastructure in place. Higher education institutions issuing micro-credentials linked to Europass digital credentials infrastructure may offer added value for the learners and can increase reliability and fraud-resistant information for the employers. However, before using Europass Digital Credentials, universities should fulfil the necessary preconditions that include obtaining a qualified electronic seal, installing additional software and preparing the necessary data templates. Moreover, the virtual learning environment needs to be prepared to export learning outcomes to a digital credential, maintaining and securing learner authentication. Open learning opportunity descriptions also need to be adjusted to transfer and match information for the credential meta-data. The Fourth chapter illustrates how digital badges as a type of micro-credentials in open online learning assessment may be used in higher education to create added value for the learners and employers. An adequately provided metadata allows using digital badges as a valuable tool for recognition in all learning settings, including formal, non-formal and informal.

AbstractThe need to characterise in-service damage in composite structures is increasingly becoming important as composites find higher utilisation in wind turbines, aerospace, automotive, marine, among others. This paper investigates the feasibility of simplifying the conventional acousto-ultrasonic technique set-up for quick and economic one-sided in-service inspection of composite structures. Acousto-ultrasonic technique refers to the approach of using ultrasonic transducer for local excitation while sensing the material response with an acoustic emission sensor. However, this involves transducers with several auxiliaries. The approach proposed herewith, referred to as vibro-acoustic testing, involves a low level of vibration impact excitation and acoustic emission sensing for damage characterisation. To test the robustness of this approach, first, a quasi-static test was carried out to impute low-velocity impact damage on three groups of test samples with different ply stacking sequences. Next, the vibro-acoustic testing was performed on all test samples with the acoustic emission response for the samples acquired. Using the acoustic emission test sample response for all groups, the stress wave factor was determined using the peak voltage stress wave factor method. The stress wave factor results showed an inverse correlation between the level of impact damage and stress wave factor across all the test sample groups. This corresponds with what has been reported in literature for acousto-ultrasonic technique; thus demonstrating the robustness of the proposed vibro-acoustic set-up. Structural health monitoring, impact damage, acousto-ultrasonic testing, non-destructive testing.

Com a utilização de sensores inteligentes em hospitais, o monitoramento e processamento dos dados é de extrema importância para melhorar serviços médicos. Em particular, esses dispositivos podem auxiliar na tomadas de decisões críticas. Nesse contexto, a qualidade do serviço (QoS) é essencial para garantir a confiabilidade dos dados das aplicações. Dito isso, esse artigo propõem HealthStack, um middleware para salas cirúrgicas com QoS automático e suporte a transmissão de dados em tempo real. O artigo propõe uma estratégia de QoS baseada em neurônios artificiais para seleção dos componentes do middleware com baixa performance. Foi desenvolvido e testado um protótipo do modelo em uma sala de cirurgia real. A avaliação demonstra que a estratégia pode melhorar o jitter médio de aplicações em até 90,3%.

This paper describes the integration of advanced methods such as component zooming and distributed computing, in an object-oriented simulation environment dedicated to gas turbine engine performance modelling. A 1-D compressor stage stacking method is used to demonstrate three approaches for integrating numerical zooming in an engine model. In the first approach a 1-D compressor model produces a compressor map that is then used in the engine model in place of the default one. In the second approach the results of the 1-D analysis are passed to the 0-D component through appropriate ‘zooming’ scalars. In the final approach the 1-D compressor component directly replaces the 0-D one in the engine model. Distributed computing is realized using Web Services technology. The implementation steps for a distributed scenario are presented. The standalone compressor stage stacking method, in the form of a shared library, is placed in a remote site and can be accessed over the internet through a Web Service Operation (server side). An engine simulation is set up containing a 1-D compressor component which acts as the client for the Web Service operation. Future development of the tool’s advanced capabilities is finally discussed.

ABSTRACT In line with an escalation of drilling operations in East Africa, operators and service contractors are increasing their focus on how to make operations more efficient in challenging market. One operation for which a robust, safe, and effective tool was utilized to increase efficiency is the plug and abandonment of deepwater exploration wells in Tanzania and Kenya. Traditional abandonment of a well is accomplished by stacking multiple cement plugs to achieve zonal isolation. The plugs covering reservoir sections are normally independently verified in keeping with best practices applicable to well barriers. By setting longer plugs to cover multiple zones, rig time and operating costs can be significantly reduced. However, there are limitations to cement plug length when set conventionally without significantly increasing the risk of stuck pipe. The Hydraulic Tubing Release Tool (HTRT) was introduced during a deep-water exploration campaign in East Africa. It has been used successfully during the abandonment of five different wells where seven plug and abandonment operations placed long abandonment plugs, ranging from 405m to 1787m, in a single operation. The utilization of the tubing release tool system in well abandonment operations has proved to lower the risks and operational costs through the reduction of necessary cementing operations. With the sacrificial tubing being left in the cement, there is less risk of plug contamination which occurs as a result of pulling out of the plug. It also allows for longer plugs to be set in a single operation as opposed to stacking several cement plugs to get the required length, saving additional time. It has been used successfully on five deepwater wells in East Africa to set long abandonment plugs in open holes ranging from 700m to 1800m MD. The main objective of the disconnect system is to shorten the time taken to perform a well abandonment program as well as reducing the associated risks, thereby saving rig time and money.

Compressor blades experience significant surface degradation with service. Elevated levels of surface roughness reduce compressor efficiency and mass flow rate. This paper presents measurement and a new model of compressor blade performance degradation due to blade surface roughness. Performance tests have been conducted in a low-speed, linear cascade with roughened compressor blades. Equivalent sandgrain roughnesses of 12, 180, 300, 425, and 850 microns have been tested. These roughness values are representative of compressor blade roughnesses found in actual gas turbines in service. Flow angle, flow rate, and loss have been measured. For the tested roughnesses of 180, 300, 425, and 850 microns, the axial velocity ratio decreases by 0.1, 2.1, 2.5, and 5.4%, respectively. For the same cases, the deviation increases by 24, 38, 51, and 70%, respectively. Finally, the loss increases by 12, 44, 132, and 217%, respectively. Thus, among the three parameters, the loss responds most sensitively to changes in compressor blade roughness. Furthermore, a new mean-line model based on the assumption of 50% reaction stages has been developed to estimate the effects of roughness on the performance of a multi-stage compressor. The data from the cascade data are used as input to predict the performance of a single compressor stage. Subsequently, a stage-stacking method is used to enable prediction for a multi-stage compressor. According to the model, the pressure ratio, and mass flow rate are significantly influenced by the blade surface roughness.

This paper presents a methodology for rapidly analyzing the effect of blending damaged compressor blades on structural integrity. Heavy duty gas turbine compressor blades are subjected to damage from numerous sources. Compressor blades are blended in the field to allow continued operation with minimal risk of failure. By constructing analysis models parametrically, blend limits may be rapidly and reliably established for an entire compressor. Erosion from washing or fogging, foreign object impacts, icing, tip rubs, and clash can damage both stator vanes and blades. Replacement of blades and stator vanes is very costly. The blades on some engines cannot be removed without de-stacking the rotor. The high cost of replacement provides an incentive to determine blend limits that do not compromise mechanical integrity. Field service support of compressor hardware includes the evaluation of compressor damage and the determination of whether such damage can be blended out in situ. Compressors on F-class engines have more than 15 stages, so at least 30 different airfoils must be analyzed when stator vanes are included. One must consider damage in the tips as well as leading and trailing edges at numerous radii. The variation in sizes, locations, and combinations of blends coupled with the number of airfoils results in a intense analytical task. Field service must also support multiple design configurations that include original engine manufacturer (OEM) blades as well as more robust aftermarket designs. By setting up parametric analysis models of each blade, PSM has been able to provide its field service support group with accurate blend limits and has created a tool with which nonstandard blends may be evaluated in nearly real-time. This paper presents a methodology which has been applied to an entire compressor. A pre-stressed large-displacement modal analysis was performed which includes contact effects and considers a wide range of operating speeds using the linear perturbation technique. Combinations of parametrically defined blends are analyzed automatically. The effects of the blends on the modal frequencies were evaluated against in-house criterion. Plots of vibratory stress capability were produced to highlight which airfoils and which portions of airfoils are vulnerable in case of damage. The parametric nature of the analysis allows the user to easily change the position size and shape of the blends. With this methodology PSM is able to rapidly evaluate blends of stator vanes and blades for whole compressors and provide reliable and timely guidance to our field service representatives.

Over the service time, the rotating parts of turbine engine vary in their geometry. When aircraft take off or fly through a volcanic ash cloud, the particles are sucked into the engine, impinge the blade and gradually erode the surface. The impinging between particles and blades is responsible for the increase of the surface roughness. Also, during the long-time operation, the function of the blade’s stacking law combined with the centrifugal force could cause deviation of the stagger angle. Moreover, blade tip clearance could vary because of the casing deformation. All the deformation of geometry could severely reduce the engine performance and thus engine life. The work presented in this paper focused on the influence of geometry deformation in a real low-pressure compressor. The investigation is more difficult than most of the previously published researches with a total of five stages being considered. Due to the irregularities in geometry, it is difficult to numerically assess the performance of the compressor. The aim of this study is to give an analysis method that allows an efficient and accurate estimation of the performance for multistage compressor with geometry deformation. In the first step, the geometry models with different deviation in tip clearance, roughness and stagger angle were established respectively. A CFD study was then applied to the compressor with RANS method to calculate the flow field with different types of deformation. The variation of overall performance due to the deformation was finally analyzed to identify the dominant factor on influencing the performance of the compressor among different types of geometry deformation. A method based on polytropic efficiency analysis and flow field analysis was also established to specifically analyze which stage is most sensitive to the geometry deformation. The results show a significant influence of geometric deformation on the efficiency, total pressure rise and flow range of the multistage compressor. The conclusions of this study would provide an important guidance for engine overhaul in the factory.