Scheduling Functions Research Articles

Research and Design of Centralized Control System for Optimizing Microgrids with Renewable Energy Power Generation

The exploitation and utilization of renewable energy, construction of sustainable energy system has gradually become the consensus of the international community, the research of microgrid technology with solar, wind and other renewable energy generation is becoming more and more deeply. According to the needs of the development of microgrid technology, in this paper a better functional architecture system of centralized control system for optimizing microgrids with new energy power generation system is proposed. First, according to the layered and distributed idea, a system of physical architecture which can run in the situations of both coordination control and self-control is designed, the system is mainly divided into physical components layer and the central station layer; and then the paper proposes the functional architecture system, it describes all the function modules and their interactions. Finally emphatically introduces the real-time security and stability control, energy optimization scheduling and other function modules which can improve the utilization ratio of renewable energy. The research of this system will play an important role in improving the absorption capacity of renewable energy; reducing fossil energy consumption and environment pollution.

Research and Implementation of Embedded Linux System Power Optimization

This paper firstly discusses the techniques to optimize power consumption of the embedded operating system, and then optimizes power consumption of embedded Linux by adding DVS (dynamic voltage scaling) module and modifies the scheduling function in the standard Linux kernel. Finally, take a comparison test on arm920 platform. The test results show that: the power optimized Linux can effectively reduce the power consumption of the whole embedded system.

Characterization and Optimization of the Glucan Particle-Based Vaccine Platform

Glucan particles (GPs) are hollow porous Saccharomyces cerevisiae cell walls that are treated so that they are composed primarily of β-1,3-d-glucans. Our previous studies showed that GPs can serve as an effective vaccine platform. Here, we characterize CD4(+) T-cell and antibody responses in immunized mice as a function of antigen (ovalbumin) encapsulation, antigen dose, particle numbers, time, immunization schedule, and trapping methods. Although we found that GPs served as an effective adjuvant when admixed with free antigens for IgG1 antibody production, stronger CD4(+) T-cell and IgG2c antibody responses were stimulated when antigens were encapsulated inside GPs, suggesting that the GP platform acts as both an adjuvant and a delivery system. Vigorous T-cell and antibody responses were stimulated even at submicrogram antigen doses, as long as the number of GPs was kept at 5 × 10(7) particles per immunization. One prime and one boost were sufficient to elicit robust immune responses. In addition, strong antigen-specific antibody and T-cell responses prevailed up to 20 months following the last immunization, including those of gamma interferon (IFN-γ), interleukin 17A (IL-17A), and dual IFN-γ/IL-17A-secreting CD4(+) T cells. Finally, robust immune responses were observed using generally recognized as safe (GRAS) materials (alginate and calcium, with or without chitosan) to trap antigens within GPs. Thus, these studies demonstrate that antigens encapsulated into GPs make an effective vaccine platform that combines adjuvanticity and antigen delivery to elicit strong durable immune responses at relatively low antigen doses using translationally relevant formulations.

Production Scheduling of Batch Processes Based on Adaptive DE Algorithm

Production scheduling problems and traditional differential evolution(DE) are analyzed in this paper. Taking the minimum of total completion time as the objective function of production scheduling, a production scheduling model is established for batch processes in process industry.Considering that the performance of the traditional DE algorithm is sensitive to the parameter settings,an adaptive control evolution strategy is used to control the parameter scale factor F and crossover probability CR to solve the problem of parameter settings. Taking a practical production problem as a scheduling example,the established model and adaptive DE algorithm are applied to implement the production scheduling simulation. The simulation results show that compared with the ant colony system(ACS) algorithm,the adaptive DE algorithm is effective and feasible.

Cross-layer Resource Allocation on Broadband Power Line Based on Novel QoS-priority Scheduling Function in MAC Layer

Traditional resource allocation algorithms use the hierarchical system, which does not apply to the bad channel environment in broadband power line communication system. Introducing the idea of cross-layer can improve the utilization of resources and ensure the QoS of services. This paper proposes a cross-layer resource allocation on broadband power line based on QoS priority scheduling function on MAC layer. Firstly, the algorithm considers both of real-time users’ requirements for delay and non-real-time users’ requirements for queue length. And then user priority function is proposed. Then each user’s scheduled packets number is calculated according to its priority function. The scheduling sequences are based on the utility function. In physical layer, according to the scheduled packets, the algorithm allocates physical resources for packets. The simulation results show that the proposed algorithm give consideration to both latency and throughput of the system with improving users’ QoS.

An Exploratory Study Examining the Appropriateness and Potential Benefit of the Nintendo Wii as a Physical Activity Tool in Adults Aged ≥ 55 Years

This study investigates the physical exertion of playing the Nintendo Wii (R) (Wii) and determines the appropriateness and potential benefit of it as a physical activity tool for older adults. Twenty healthy adults (aged 61 +/- 6 years) took part in a single session using a selection of the Wii Sports and Wii Fit games. During the gameplay session, heart rate and perceived exertion were measured. Pre- and post-session, we investigated mood using the Positive and Negative Affect Schedule (PANAS) and cognitive function (i.e. aptitude, abstract reasoning and problem solving) using the test of non-verbal intelligence (TONI-IQ) and trail B tests. We also gathered subjective feedback from participants using semi-structured interviews and questionnaires. Three of the game activities (hula-hoop, rowing squat and leg extension) were identified to reach a moderate level of heart rate intensity, with one activity (jogging) corresponding to a vigorous level. We identified that post-session PANAS-positive subscale scores were greater than pre-session scores (P < 0.01). There was a reduction in the time to complete the TONI-IQ test from pre- to post-session (P < 0.05). Findings from these data identify that some Wii activities were of an intensity required for health benefits; a single Wii activity session can result in positive mood changes and the Wii interface is generally acceptable and appropriate for this older age adult group. Further randomized controlled and longer term intervention trials are needed to determine the effectiveness of exergame activity programmes.

Short-term Distributed Energy Resource Scheduling for a DC Microgrid

A microgrid is associated with a low voltage distribution power network and inherits small modular generation systems and loads that have certain coordinated functions to provide the solution to supply premium power to remote or specific areas. Similar to conventional power systems, the energy management of distributed generation resources (DERs) is carried out to minimize the operation cost and maximize benefit of installation of DERS in a microgrid. This paper presents the process of implementing the short-term DER scheduling function for a dc microgrid. The optimal scheduling results for two operation modes are then reported.

Experimental Evaluation of OpenStack Compute Scheduler

In the Cloud Computing model, the computing resources are provided as a service in an on-demand and dynamic fashion. Efficient and flexible resource management is among the current research issues in the cloud computing context. We present in this paper a study focusing on the dynamic behavior of the scheduling functionality of an IaaS cloud built using OpenStack. Resorting to the principles of Design of Experiment (DOE), we use a screening design applied on a small-scale private Cloud in order to explore OpenStack Compute Scheduler. We present and discuss in this paper the main outcomes of an enhanced two-level fractional factorial balanced design and we outline our future work.

Kernel-Based Spatiotemporal Multimodeling for Nonlinear Distributed Parameter Industrial Processes

Many industrial processes are nonlinear distributed parameter systems (DPS) that have significant spatiotemporal dynamics. Due to different production and working conditions, they often need to work at a large operating range with multiple working points. However, direct global modeling and persistently exciting experiment in a large working region are very costly in many cases. The complex spatiotemporal coupling and infinite-dimensional nature make the problem more difficult. In this study, a kernel-based spatiotemporal multimodeling approach is proposed for the nonlinear DPS with multiple working points. To obtain a reasonable operating space division, an iterative approach is proposed where the operating space division and local modeling are performed iteratively. The working range of the current local model will help to determine the next operating point required for modeling. Utilizing the potential of each local model, the number of regions can be reduced. In the local modeling, the Karhunen–Loève method is used for the space/time separation and dimension reduction, and after that unknown parameters of kernels are estimated. Due to consideration of time-scale properties in the dimension reduction, the modeling approach is particularly suitable for dissipative PDEs, particularly of parabolic type. The multimodeling and space/time separation techniques can largely reduce the complexity of global nonlinear spatiotemporal modeling. Finally, to guarantee a smooth transition between local spatiotemporal models, a scheduling integration method is used to provide a global spatiotemporal model. To design scheduling functions, a two-stage training method is proposed to reduce the design complexity. Compared with direct global modeling, the exciting experiment and modeling for each local region become easier. Compared with one local modeling, the multimodel integration will improve modeling accuracy. The effectiveness of the proposed modeling approach is verified by simulations.

Effect of scheduled monitoring of liver function during anti-Tuberculosis treatment in a retrospective cohort in China

BackgroundData on effect of regular liver function monitoring during anti-TB treatment is limited in China. This study aimed to evaluate the effects of scheduled liver function monitoring on identification of asymptomatic liver damage and anti-TB treatment outcomes during anti-TB treatment.MethodsA retrospective analysis was performed based on a national-level cohort study. A total of 273 patients developing liver dysfunction were divided into two groups, 111 patients who were diagnosed through scheduled liver function test within two months after initiation of anti-TB treatment formed scheduled monitoring group, others who were diagnosed due to developing symptoms formed passive detection group (n = 162). The two groups were compared through clinical features, prognosis of liver dysfunction and impact on anti-TB treatment using propensity score weighting analysis.Results33.3% of 273 patients did not have any clinical symptoms, including 8 with severe hepatotoxicity. 1.8% in scheduled monitoring group and 11.1% in passive detection group required hospitalization (P = 0.004). Regarding the prognosis of liver dysfunction, most patients recovered, no death happened in scheduled monitoring group while 3 died in passive detection group. In terms of impact on anti-TB treatment, 35.1% in scheduled monitoring group and 56.8% in passive detection group changed their anti-TB treatment (P = 0.001).ConclusionsScheduled monitoring is effective in identifying asymptomatic liver damage, reducing hospitalization rate and improving compliance of anti-TB treatment.

MPI와 OpenMP기반 하이브리드 모델을 이용한 항공 레이저 스캐닝 자료의 병렬 처리

In the present study, a parallel processing method running on a multi-core PC-Cluster is introduced to produce digital surface model (DSM) and digital terrain model (DTM) from huge airborne laser scanning data. A hybrid model using both message passing interface (MPI) and OpenMP was devised by revising a conventional MPI model which utilizes only MPI, and tested on a multi-core PC-Cluster for performance validation. In the results, the hybrid model has not shown better performances in the interpolation process to produce DSM, but the overall performance has turned out to be better by the help of reduced MPI calls. Additionally, scheduling function of OpenMP has revealed its ability to enhance the performance by controlling inequal overloads charged on cores induced by irregular distribution of airborne laser scanning data.

Safety constraints applied to an adaptive Bayesian condition-based maintenance optimization model

A model is described that determines an optimal inspection and maintenance scheme for a deteriorating unit with a stochastic degradation process with independent and stationary increments and for which the parameters are uncertain. This model and resulting maintenance plans offers some distinct benefits compared to prior research because the uncertainty of the degradation process is accommodated by a Bayesian approach and two new safety constraints have been applied to the problem: (1) with a given subjective probability (degree of belief), the limiting relative frequency of one or more failures during a fixed time interval is bounded; or (2) the subjective probability of one or more failures during a fixed time interval is bounded. In the model, the parameter(s) of a condition-based inspection scheduling function and a preventive replacement threshold are jointly optimized upon each replacement and inspection such as to minimize the expected long run cost per unit of time, but also considering one of the specified safety constraints. A numerical example is included to illustrate the effect of imposing each of the two different safety constraints.

Ontological framework for enterprise-wide integrated decision-making at operational level

In the domain of chemical process engineering, there is an increased interest in the integration of the enterprise hierarchical levels for decision-making purposes. At the scheduling level, decisions on the allocation of tasks to resources, sequencing and timing of tasks must be managed. However, such decisions are directly related to other enterprise actions, such as control and planning, but they are difficult to coordinate because they are modeled at different time and space scales, and their goals are not the same. In order to achieve integrated decisions supported by high quality information, there is a need to improve and develop robust computational tools and consistent models. In general, scheduling optimization approaches for decision-making differ depending on problem features, such as physical layout or time representation. Therefore, this work focuses on providing a framework based on a semantic model that captures the diversity in scheduling problem representation. Such semantic model uses the master recipe concept from the ANSI/ISA-88 standard perspective and encapsulates the scheduling decision task features. As a result, by the use of a single representation approach, any scheduling problem can be modeled and solved by its adequate optimization tool. The potential of a general model representation is presented by means of several case studies related to the scheduling function. Such case studies shed light to the model capabilities to represent different kinds and particular scheduling problems, achieving integration at the different decision support levels.

Design and Analysis of AFDX Network Based High-Speed Avionics System of Civil Aircraft

Avionics Full Duplex Switched Ethernet (AFDX) standardized as ARINC 664 is a major upgrade for integrated avionics systems of civil aircraft. It becomes the current communication technology in the context of avionics and provides a backbone network for the civil avionics system. This paper focuses on features of AFDX network protocol. Architecture of AFDX switch based on shared memory is proposed to meet the requirements of avionics real-time system. In addition, frame filtering, traffic policing and frame schedule function are used to eliminate uncertainties in huge traffic flows. End System (ES) host-target architecture is also researched in this paper. Virtual link scheduler, redundancy management, and protocol stack in ES are designed to ensure determinism and reliability of data communication. AFDX switch and ES have been successfully developed, and configuration tool, ARINC 615A loader and simulation tool related to AFDX network are also provided as package solution to support avionics system construction. Finally, AFDX switch and ESes have passed ARINC 664 protocol conformance test and certification, the test results show that our AFDX products meet the requirements of real-time communication, determinism and reliability defined in ARINC 664

Parallelization of sequential programs: distribution of arrays among processors and structurization of communications

Data distribution functions are introduced. They are matched with scheduling functions. The processors and iterations are determined that use an array element at its fixed position in a statement. This makes it possible to obtain the initial data distribution and also information on the data volume for every processor and on the structure of required communications.

Distributed Mathematical Model Simulation on a Parallel Architecture

The aim of this article is to discuss the design of distributed mathematical models and suitable parallel architecture of computers. The paper summarises the author’s experience with mathematical modelling of decomposed information systems of a simulator. Conclusions are based on the theory of the design of the computer control systems. The author describes computers that create a distributed computer system of a flight simulator. Modelling of a time precision of mathematical model of the speed of a simulator system is done by describing equations. The qualities of models depend on the architecture of computer systems. Some functions of other sections of POSIX are also analysed including semaphores and scheduling functions. An important part of this article is the implementation of computation speed of aircraft in multicore processor architecture.

Adaptive Uncertainty Resolution in Bayesian Combinatorial Optimization Problems

In several applications such as databases, planning, and sensor networks, parameters such as selectivity, load, or sensed values are known only with some associated uncertainty. The performance of such a system (as captured by some objective function over the parameters) is significantly improved if some of these parameters can be probed or observed. In a resource constrained situation, deciding which parameters to observe in order to optimize system performance, itself becomes an interesting and important optimization problem. This general problem is the focus of this article. One of the most important considerations in this framework is whether adaptivity is required for the observations. Adaptive observations introduce blocking or sequential operations in the system whereas nonadaptive observations can be performed in parallel. One of the important questions in this regard is to characterize the benefit of adaptivity for probes and observation. We present general techniques for designing constant factor approximations to the optimal observation schemes for several widely used scheduling and metric objective functions. We show a unifying technique that relates this optimization problem to the outlier version of the corresponding deterministic optimization. By making this connection, our technique shows constant factor upper bounds for the benefit of adaptivity of the observation schemes. We show that while probing yields significant improvement in the objective function, being adaptive about the probing is not beneficial beyond constant factors.

Multi-objective Optimization of Multi-Agent Elevator Group Control System Based on Real-time Particle Swarm Optimization Algorithm

In order to get a globally optimized solution for the Elevator Group Control System (EGCS) scheduling problem, an algorithm with an overall optimization function is needed. In this study, Real-time Particle Swarm Optimization (RPSO) is proposed to find an optimal solution to the EGCS scheduling problem. Different traffic patterns and controller mechanisms for EGCS are analyzed. This study focuses on up-peak traffic because of its critical importance to modern office buildings. Simulation results show that EGCS based on Multi-Agent Systems (MAS) using RPSO gives good results for up-peak EGCS scheduling problem. Besides, the elevator real-time scheduling and reallocation functions are realized based on RPSO in case new information is available or the elevator becomes busy because it is unavailable or full. This study contributes a new scheduling algorithm for EGCS, and expands the application of PSO.

Research on the Management System and it’s Key Technology for Retail Industry Distribution Center

In this paper, the design scheme for the retail distribution center management system is proposed and analysis of the key technology is given. The systems involve procurement, inspection, storage, repacking, distribution, scheduling, return goods, and other functions. The key technologies for role access control, storage process and workflow are adopted, which ensure the goods supply of the retail enterprise shop, reduce the supply of goods transport costs, and improve the competitiveness of enterprises.

Study on the Water Quality and Quantity Scheduling Scheme in Xinxue River Constructed Wetland of China under the Constraint Condition of Class III of Surface Water Quality

Using Xinxue River Constructed Wetland as the study object, the wetland prediction models based on BP neural network were established through the seasonal division of the wetland, and the maximum influent water load was determined on the constraint condition that effluent water quality achieved class Ⅲ of surface water quality. Then nonlinear functions of water quality and quantity scheduling were constructed by Origin software. The optimal influent load was determined adopting prediction results of the models as constraint conditions of the functions. Thus the water quality and quantity scheduling scheme of the wetland was established. The results show that optimal influent load for Feb. ~ May: the influent water quantity is no more than 8560m3/d, CODCr is 25.47mg/l~26.37mg/l, ammonia nitrogen 0.11mg/l~1.0mg/l, TN 10.28mg/l~10.51mg/l, TP 0.16mg/l; for Jun. ~ Sept.: the water quantity is no more than 31750m3/d, CODCr is 26mg/l~32.36mg/l, or 37.15mg/l~45.37mg/l, ammonia nitrogen 0.48 mg/l~1.78mg/l, TN 5.15mg/l~6.18mg/l, TP 0.07mg/l~0.09mg/l; for Oct. ~ Dec.: the water quantity is no more than 11070m3/d, CODCr is 24.55mg/l~26.91mg/l, ammonia nitrogen no more than 0.75, TN no more than 8.61 mg/l, TP 0.10mg/l~0.12mg/l, or 0.16mg/l~0.17mg/l.