Balancing Component Research Articles

Physics Informed Machine Learning Approach for Performance Degradation Monitoring of Gas Turbine

The heavy-duty gas turbine is playing an increasingly significant role on power generation due to its lower-emission, higher flexibility and thermo-efficiency. Main subsystems of the gas turbine like compressor, combustor and turbine degrade over the operating time under the harsh environmental conditions, which largely impacts the efficiency and productivity of the system. Therefore, it is critical to develop effective approaches to monitor performance degradation of a heavy-duty gas turbine for system predictive maintenance thus improving the efficiency and productivity of the machine. This paper presents a new physics informed machine learning methodology to predict the degradation of gas turbine by seamlessly integrating thermodynamic heat balancing mechanism, component characteristics, multi-source data and artificial neural network model. The mechanism-based thermodynamic model is established for multiple subsystems considering the balance of flow, mass and energy, and then integrated to a system level for performance simulation of the gas turbine under different conditions. The system model is able to effectively simulate values for those parameters that are not measurable (e.g. GT exhaust flow) or inaccurately measured (e.g. fuel flow). Machine learning based data cleaning approach is employed to preprocess the multivariate raw data of the gas turbine. The difference between design performance data and corrected value obtained from the physics-informed model under ISO conditions is utilized to assess the performance degradation. A Long Short-Term Memory (LSTM) model is established from the fusion of the actual and simulation data to predict the performance degradation of the gas turbine. A comparison study with the classical Nonlinear Autoregressive Network with External Input (NARX) neural network is conducted to demonstrate the advantage of the proposed method. Key Word: Gas Turbine, Thermodynamic Balance, Performance Degradation Predict, Machine Learning, LSTM

Balancing, bandwagoning or hedging: Taiwan’s strategic choices in the era of a rising China

ABSTRACT Small states have three strategic options when they are confronted by a rising power: balancing, bandwagoning, and hedging. With an increasingly powerful and assertive China as its neighbour, Taiwan, as a small state, is in such a conundrum. Employing survey data collected during the past two decades, this study examines how Taipei’s cross-Strait policy has been closely associated with the public’s preferences. Because Taiwan citizens reject a unification under Beijing’s terms, the bandwagoning policy has never been considered as an acceptable strategy. A ‘pure’ balancing policy is also unpalatable due to the enormous costs and associated risks. Instead, the island citizens are generally supportive of setting aside the sovereignty dispute with a rapprochement approach towards China. Hedging has thus become a preferred strategic option for most Taiwan citizens. The public’s support for a hedging policy has shifted recently due to China’s aggressive conduct and America’s supportive policy towards Taiwan. Because Beijing’s assertive behaviour is expected to persist and the Biden administration will remain supportive of Taiwan, Taipei’s strategic choice is likely to have a stronger balancing component. The cold and tense cross-Strait relationship since 2016 is expected to continue beyond the tenure of Taiwan’s pro-independence incumbent government.

Toward Privacy-Aware Task Allocation in Social Sensing-Based Edge Computing Systems

With the advance in mobile computing, Internet of Things, and ubiquitous wireless connectivity, social sensing-based edge computing (SSEC) has emerged as a new computation paradigm where people and their personally owned devices collect sensor measurements from the physical world and process them at the edge of the network. This article focuses on a privacy-aware task allocation problem where the goal is to optimize the computation task allocation in SSEC systems while respecting the users’ customized privacy settings. It introduces a novel game-theoretic privacy-aware task allocation (G-PATA) framework to achieve the goal. G-PATA includes: 1) a bottom-up game-theoretic model to generate the maximum payoffs at end devices while satisfying the end user’s privacy settings and 2) a top-down incentive scheme to adjust the rewards for the tasks to ensure that the task allocation decisions made by end devices meet the Quality-of-Service (QoS) requirements of the applications. Furthermore, the framework incorporates an efficient load balancing and iteration reduction component to adapt to the dynamic changes in status and privacy configurations of end devices. The G-PATA framework was implemented on a real-world edge computing platform that consists of heterogeneous end devices (Jetson TX1 and TK1 boards, and Raspberry Pi3). We compare G-PATA with state-of-the-art task allocation schemes through two real-world social sensing applications. The results show that G-PATA significantly outperforms existing approaches under various privacy settings (our scheme achieved as much as 47% improvements in delay reduction for the application and 15% more payoffs for end devices compared to the baselines).

Performance Analysis of Load Balancing Algorithms using Microsoft Windows Azure Cloud Platform

As we are living in technology dominating era, the role of cloud computing as one of the rapidly emerging technologies is highly indispensable. This cloud computing holds load distribution concept, which is usually addressed as a challenging phenomenon, to handle multiple requests which are coming from geographically differentiated locations. There are various load balancing mechanisms exits for the effective distribution of the work load. This load balancing mechanism takes the advent of the virtualization approach on resources to optimize the utilization of the resources. In virtualization, the creation of virtual machine and mapping the same to the suitable request makes the cloud computing a prominent technology. This paper work considers various load balancing mechanisms for the allocation of resources and also shows a comparative study on them with the help of an example scenario. These load balancing algorithms are applied on applications like real-time systems and prioritized medical field related data storage system. This research work is implemented in Windows Azure Platform as Cloud Operation System under load balancing component.

Module Stabilizing of Biocarbon Based Electrochemical Capacitor

One of the disadvantages of the electrochemical capacitor (EC) or supercapacitor compared with batteries is its low specific energy. It limits of EC to meet the energy needs of the electrical-electronic devices, such as electric cars. To overcome those limitations, it needs a serial circuit to increase the voltage range, and parallel circuits to increase the storage capacity. Practically, the module that built from 2-6 pieces of 2.5V EC cells will not feasible to make the module with the voltage of 5-15 V. It was found that the voltage of the EC cell could decreases to about 2.0 V, so that the capacitance of the module significantly reduced. This paper reports the basic methods that can be applied to overcome these problems by using a stabilizing or balancing component. The balancing components used in this study were a resistor, a Zener diode, and a Schottky diode. Each component was attached to every EC cell. The influence of the Zener and Schottky diode was observed as a component of a blocking diode. The results showed that the use of a 100-ohm resistor and Zener diode reduces voltage peaks while the use of blocking diode modules leads to increased discharge time. In general, there was no significant change in the charging time, both with and without the balancing and blocking component.

Scheming an Proficient Auto Scaling Technique for Minimizing Response Time in Load Balancing on Amazon AWS Cloud

Cloud computing is one of the developing innovation in the field of data improvement. Because of its huge application, for example, virtualization and dynamic asset portion, the cloud computing ends up being the most encouraging innovation. To give the solid support of the customers with Quality of Service (QOS), the load balancing component with auto scaling methods would be vital in cloud computing conditions. With the end goal to keep the framework from overloading and slamming, a productive calculation must be given by the application and approaching client activity in the cloud computing condition. The proposed Auto Load Distribution (ALD) calculation have been assessed and contrasted and some of existing load balancing algorithm and its effectiveness is vastly improved than the past calculations. To accomplish the previously mentioned issues, we tried our undertakings in Amazon EC2 stage, one of open cloud administrations which give correct qualities. Results have been investigated and limiting the reaction time greater by utilization of auto scaling system through our proposed ALD algorithm.

WebRTC 환경에 데이터 스트리밍 및 사용자 요청에 따른 동적로드 밸런싱 방법

WebRTC has quickly grown to be the world`s advanced real-time communication in several platforms such as web and mobile. In spite of the advantage, the current technology in WebRTC does not handle a big-streaming efficiently between peers and a large amount request of users on the Signaling server. Therefore, in this paper, we put our work to handle the problem by delivering the flow of data with dynamical load balancing algorithms. We analyze the request source users and direct those streaming requests to a load balancing component. More specifically, the component determines an amount of the requested resource and available resource on the response server, then it delivers streaming data to the requesting user parallel or alternately. To show how the method work, we firstly demonstrate the load-balancing algorithm by using a network simulation tool OPENT, then, we seek to implement the method into an Ubuntu server. In addition, we compare the result of our work and the original implementation of WebRTC, it shows that the method performs efficiently and dynamically than the origin.

Comparison of soft tissue balancing, femoral component rotation, and joint line change between the gap balancing and measured resection techniques in primary total knee arthroplasty: A meta-analysis.

This meta-analysis was designed to compare the accuracy of soft tissue balancing and femoral component rotation as well as change in joint line positions, between the measured resection and gap balancing techniques in primary total knee arthroplasty. Studies were included in the meta-analysis if they compared soft tissue balancing and/or radiologic outcomes in patients who underwent total knee arthroplasty with the gap balancing and measured resection techniques. Comparisons included differences in flexion/extension, medial/lateral flexion, and medial/lateral extension gaps (LEGs), femoral component rotation, and change in joint line positions. Finally, 8 studies identified via electronic (MEDLINE, EMBASE, and the Cochrane Library) and manual searches were included. All 8 studies showed a low risk of selection bias and provided detailed demographic data. There was some inherent heterogeneity due to uncontrolled bias, because all included studies were observational comparison studies. The pooled mean difference in gap differences between the gap balancing and measured resection techniques did not differ significantly (-0.09 mm, 95% confidence interval [CI]: -0.40 to +0.21 mm; P = 0.55), except that the medial/LEG difference was 0.58 mm greater for measured resection than gap balancing (95% CI: -1.01 to -0.15 mm; P = 0.008). Conversely, the pooled mean difference in femoral component external rotation (0.77°, 95% CI: 0.18° to 1.35°; P = 0.01) and joint line change (1.17 mm, 95% CI: 0.82 to 1.52 mm; P < 0.001) were significantly greater for the gap balancing than the measured resection technique. The gap balancing and measured resection techniques showed similar soft tissue balancing, except for medial/LEG difference. However, the femoral component was more externally rotated and the joint line was more elevated with gap balancing than measured resection. These differences were minimal (around 1 mm or 1°) and therefore may have little effect on the biomechanics of the knee joint. This suggests that the gap balancing and measured resection techniques are not mutually exclusive.

Integrated timetabling and vehicle scheduling with balanced departure times

Sequential planning of public transportation services can lead to inefficient vehicle schedules. Integrating timetabling and vehicle scheduling, the vehicle scheduling problem with time windows (VSP-TW) aims at minimizing costs of public transport operations by allowing small shifts of service trips' departure times. Within the scope of tactical planning, a larger flexibility of departure times following predefined departure time windows may be desirable. However, with increasing degrees of freedom, conventional solution approaches for the VSP-TW become computationally prohibitive. Furthermore, a sole focus on cost minimization might produce timetables of insufficient quality, while public transport agencies expect high-quality timetables with service trips scheduled at times reasonable from a passenger's point of view. Extending the VSP-TW, we propose the vehicle scheduling problem with time windows and balanced departure times (VSP-TW-BT). In addition to the cost-efficiency objective of the VSP-TW, our objective function considers the quality of a timetable from a passenger's point of view. Timetables are generated by balancing consecutive departures on a line according to predefined departure time intervals. We use a weighted sum approach to combine both objectives, namely costs of operation and quality of timetables. Our mathematical model and solution approach are based on efficient techniques known from the area of vehicle routing with time windows. A hybrid metaheuristic framework is proposed, which decomposes the problem into a scheduling and a balancing component. Real-world-inspired instances allow for the evaluation of quality and performance of the solution approach. The proposed solution approach is able to outperform a commercial solver in terms of run time and solution quality.

The Federal Circuit and Inequitable Conduct: An Empirical Assessment

Inequitable conduct is a unique judicially created doctrine designed to punish patent applicants who behave inequitably toward the public in the course of patent acquisition. Its name alone strikes fear into the hearts of patent prosecutors, and justly so – for when successfully asserted, inequitable conduct can have devastating consequences that reach far beyond a patentee’s case. The need for a systematic empirical study of inequitable conduct jurisprudence has become especially pressing now that the Federal Circuit is reviewing inequitable conduct en banc – in terms so broad as to be unprecedented in the history of the doctrine. This Article reports such a study. The study reported here provides evidence, inter alia, that the Federal Circuit applies an inequitable conduct standard stricter than that applied by a substantial number of the tribunals it reviews. The Federal Circuit’s stricter standard manifests primarily through the intent to deceive component of inequitable conduct doctrine. For all intents and purposes the Federal Circuit has no substantive jurisprudence around the balancing component, and the materiality component is comparatively less impactful then intent to deceive. The court appears to have trouble communicating its stricter standard to lower tribunals. We offer some explanations for why this might be so, and offer some modest suggestions that might advance inequitable conduct doctrine.

Contemporary evaluation for medical ultrasound teachers

Modern critical care practice is increasingly making use of ultrasound to improve bedside diagnostics and enhance patient safety. Physician teachers and mentors therefore need access to mechanisms that maintain learning and professional development of ultrasound learners. We present an exploratory assessment of Distance Travelled Analysis, a novel form of continuous cyclical evaluation used in the context of a Fellowship in Critical Care Echocardiography and a practical guide to applying it to your practice. We adapted the qualitative process of ‘Distance Travelled Analysis’ from vocational education to construct the evaluation tool. We used the tool to collect primary data from the Echo Fellow over a five-month period. The quality and trustworthiness of the subjective primary data-set was triangulated using reflective conversations, spontaneous positive storytelling, face-to-face questionnaires and a summative assessment. Distance Travelled Analysis successfully translated onto the study curriculum, offering purposeful and active evaluation. The tool was able to identify a critical incident and alerted stakeholders to negative change allowing contemporaneous rather than post hoc action. An unexpected finding was that the evaluation tool significantly impacted both learner and mentor creating active learning exchange. The study findings expose the importance of reflective conversation as a balancing component of Distance Travelled Analysis. This qualitative work lends weight to the potential for continuous evaluation in high stakes curricula. The process of Distance Travelled Analysis could offer curriculum evaluators an agile alternative to traditional retrospective evaluation methods, preventing evaluation from being too little too late.

Transforming "fairness" as a ground of judicial review in Hong Kong

This paper evaluates the recent development of “fairness” as a ground of judicial review by the courts in Hong Kong. This newly developed ground of fairness is significantly more far-reaching than “procedural fairness” and other existing uses of fairness in judicial review. Key innovations include: (a) the courts’ review of systemic problems with decision-making processes; (b) the extension of the courts’ review of the fairness of such processes beyond the traditional focus on, for example, the right to a hearing; and (c) the introduction of a sliding scale of review with stronger or “anxious” scrutiny of decision-making processes. The paper evaluates the need for these innovations, noting an absence of a conscious internalization of procedural standards in decision making at the executive level. The paper concludes that the ground of fairness, therefore, is a positive development of administrative law. However, in addition to the usual risk of over-judicialization of administrative process, there is a risk that the recently developed ground is too hard-edged as currently formulated. The paper, therefore, proposes the introduction of a justificatory and balancing component to its usage, similar to that used in the context of proportionality. It also proposes a clarification of the kinds of situations that would trigger the use of this stronger ground of fairness.

Research on Direct Power Control of Modular Multi-level Converter for Power Transmission

Control methods for a novel modular multi-level converter are studied and applied to voltage source converter based high-voltage DC for an offshore wind farm. A new method of trigger pulse generation is proposed based on multi-carrier sine pulse-width modulation. The principle of the (2n + 1) level output for the modular multi-level converter is described in detail. The method of capacitor voltage sorting and the strategy of adding a balancing component in the reference signal are combined for control of the voltage of the sub-module to be constant. Meanwhile, the strategy of virtual flux direct power control is applied for a modular multi-level converter, focusing on the power estimation method of this topology. The control method designed in this article is compared with the traditional strategy, and MATLAB (The MathWorks, Natick, Massachusetts, USA) was used for testing under various conditions (including step response and transient); the results show that the designed method is correct and effective.

Early Revision for Component Malrotation in Total Knee Arthroplasty

Component malrotation may result in unsuccessful total knee arthroplasty. We asked whether revision improves function in patients with malrotated total knee arthroplasty components. We retrospectively reviewed 22 revision total knee arthroplasties performed for femoral and/or tibial component malrotation. Revision surgery was performed within 2 years of the primary arthroplasty in 81% of the cases (18 of 22) with the remainder within 5 years. Although all patients had pain, 32% of patients had associated instability and 36% of patients had poor range of motion. Average Knee Society Scores improved from 42 preoperatively to 77 postoperatively. Average Oxford Knee Scores improved from 38 preoperatively to 29 postoperatively. Although clinical and functional improvement was observed, these results are inferior to those for primary knee arthroplasty, and they emphasize the need for proper component rotational positioning during primary total knee arthroplasty. Internal component malrotation leads not only to patellofemoral problems, but also to difficulty in gap balancing and femoral component sizing, which may in turn lead to either poor range of motion or symptoms of knee instability.

Protective genes expressed in endothelial cells: a regulatory response to injury

Endothelial cells (ECs) have evolved to guard against insults that incite inflammation. Response to injury is an active process that, if uncontrolled, can progress to EC death (apoptosis). Here Fritz bach and colleagues suggest that ECs have a balancing component to their proinflammatory response: they upregulate a set of protective genes, including anti-apoptetic genes, that serve to limit the activation process and thereby regulate the response to injury.

Noise control in solid-phase immunoassays by use of a matrix coat

This paper describes the matrix coat noise control technique as applied in an ELISA to detect IgG antibody to the semen protein p30 (also known as prostate-specific antigen). Background noise due to non-specific binding of IgG in solid-phase immunoassays has recently been shown to be highly charge dependent. In this technique, the surface antigen (here, p30) is co-coated on the test surface with an anionic macromolecule, the noise reduction matrix component, to reduce non-specific IgG binding. A second matrix component, the noise balancing component, is added if necessary to balance non-specific IgG binding between a detecting well which contains matrix plus antigen and a control well which contains matrix alone. Sample noise can then be measured in the control well and subtracted to yield a noise-corrected signal. This approach both minimizes background noise and then precisely quantitates residual noise. In this study, human α 1-acid glycoprotein (AGP) served as the noise reduction component and bovine serum albumin (BSA) as the noise balancing component. Optimal coating concentrations of AGP and BSA for the matrix were determined by a new technique, the tetrad method of signal and noise analysis. A signal probe (immune serum), a noise probe (non-immune serum) and a set of four test wells are employed to analyze the noise control properties of a given combination of matrix components. For each such tetrad of wells, three ratios are calculated: the sensitivity, signal-to-noise and noise balance ratios, along with a composite index, the matrix index. These can be used to select the combination and concentrations of matrix components which optimize assay noise control and minimize losses of assay sensitivity. When an ELISA using matrix coat noise control (MCNC-ELISA) was compared with ELISAs using standard blocking techniques, the MCNC-ELISA was superior in its ability to control for false positive results due to non-specific IgG binding and binding of the polycation poly- L-lysine. Two subjects (14%) out of a clinic population of sexually active women were found to have significant serum levels of anti-p30 IgG ( P ≦ 0.001) by MCNC-ELISA.

Artemia salina as pabulum for growing Penaeids under laboratory conditions

Growing interest in Artemia salina Leach is supported by its high protein content, the relative ease of its mass production, and its incompletely utilized potential biomass which is found in saltpans all over the world. Experiments involving the catching of adult brine shrimps by means of a 500 μm nylon net located on the main outflow canal were carried out in Margherita di Savoia saltworks in southeastern Italy preliminarily in August 1980. Replicates during May–July 1981 showed it was possible to collect about 250 g min −1 of adult Artemia. According to the figures of the samples taken, it is reasonable to assume a brine shrimp standing crop of at least 50 tonnes (wet weight) over a 1000 ha surface area. The Artemia collected in this way were tested for feeding Penaeids under laboratory conditions, as sole food and as supplement to a dry selfmade diet. Firstly Penaeid growth supported by mussels was tested in comparison with frozen Artemia diet. The latter gave the best results with 30% daily supply of shrimp body (wet weight). Moreover Artemia were tested as a balancing component of a dry diet to correct a deficit of aminoacids and supply missing highly unsaturated fatty acids (HUFA). With this mixed diet it was enough to supply A. salina 2 days per week to achieve promising results which are considered a good compromise between economics and the growth rate of Penaeus japonicus Bate. Consequently, it is suggested that intensive and/or extensive Penaeid cultures be planted near saltpans, utilizing brine shrimp biomass as a food source which could otherwise be wasted.