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Characteristics of two types swapping electric vehicles (EVs) are considered, which include private EVs and electric taxis. Then, a time-space load forecasting method for these swapping EVs is proposed. After that, the forecasting results are taken as the load basis for sizing and locating planning of centralized-battery-charging-stations (CBCSs). In addition, based on the life cycle cost (LCC) theory, a double-layer planning model is established. It takes into account the CBCSs’ planning economy and the optimization for battery logistics system. That is, the planning LCC of CBCSs is conducted by the upper layer optimization. And the lower layer planning optimizes the annual transportation cost of the battery logistics company. The calculation example shows that the proposed planning method for CBCSs is feasible and effective.

Autonomous driving systems (ADSs) need to be able to respond quickly to changes in the dynamic traffic scenario. However, regardless of the changes occurring in traffic scenes, the current local path planning frameworks of ADSs are based on the fixed frequency re-planning path (i.e., running their planning algorithms repeatedly). This planning method makes it difficult to provide a reasonable traveling path, agility, and comfort for driverless vehicles in changing traffic scenarios. Therefore, this article performs an in-depth analysis of the problems of traditional planning frameworks which use a fixed frequency to replan the path and proposes a novel path planning framework that is universal based on multiple-models. The proposed framework divides the planning process into several layers, each of which has different functions. With this framework, the ADS can adaptively adjust the planning process according to the changes in traffic scenes and then provide different path planning algorithms to ensure its safety and flexibility in the process of driving. Moreover, the problems caused by the traditional planning framework can be solved. This framework has been applied to the autonomous vehicle ``Pioneer'', which won first place in the 2019 China Intelligent Vehicle Future Challenge (IVFC). The effectiveness and rationality of the integrated framework of local path planning proposed in this article were verified by a large number of tests in real-world traffic scenarios.

In view of the disadvantages of existing planning methods used in CCOS techniques, such as low efficiency and workpieces contain obvious mid-frequency error after polishing, a new tool-path planning method based on improved Prim algorithm was proposed, of which the core idea was consist by following steps: surface data reading, mesh generation, distribution of resident points determining and polishing path generating. After that, comparison of raster path and the path based on improved Prim algorithm was carried out by simulated experiments from aspects of path length and polishing texture. The results indicated that the path based on improved Prim algorithm could shorten path length as well as increase polishing efficiency, moreover, both the texture and mid-frequency errors can be improved by using the path presented. It was concluded that the presented planning method could improve polishing efficiency and machining quality. Then, comparison between raster path and the path based on improved Prim algorithm was carried out by simulated experiments, from two sides of path length and polishing texture. The results indicated that the path based on improved Prim algorithm could shorten path length as well as increase polishing efficiency, moreover, both the texture and mid-frequency errors would be improved by using the presented path. Finally, the validity of presented planning method was proved in machining experiments.

For satisfying the growing demand of parking in urban area and relieving traffic congestion in downtown, under the condition of urban subway park-and-ride (P&R), the methods of site selection and scale calculation of parking lots are studied. Selecting Xi'an Rd. business circle in Dalian as study object, both survey and analysis of parking demand were conducted. Based on the principle of random equilibrium selection, the logit model of P&R demand was constructed. Then the forecasting models of parking demand both in downtown and peripheral zones were proposed respectively. Using the minimum travel distance of vehicles as the objective function, site selection optimization model of P&R station was constructed. The calculation methods of scale for parking lots in both downtown and P&R station were also processed. For the case of Xi'an Rd. business circle, not only the site of P&R station was planned, but the scale of parking berth was calculated. According to the plan and calculation, the total number of parking berth has increased from 3380 to 4011. Among the planned berths, 75.7 % are in the business circle and 24.3 % in P&R stations are outside downtown. Thus, the number of planned berths in the business circle has actually decreased by about 8 %. The research indicates that, for downtown with subway system, by reducing parking berths in downtown and increasing them in P&R stations outside the urban area, this planning method is more beneficial to relieve the problems of parking and traffic congestion in downtown than traditional method.

Background: To study the application of the mathematical programming method in agricultural machinery operation optimal allocation and scale management, this paper adopts the nonlinear programming method to establish the relevant mathematical model. Methodology: This paper investigates the crop planting area, mechanization level, and agronomic direction requirements, production situation, and technological process of corn planting mode. Results: The structure of agricultural machinery equipment is relatively reasonable, and the production efficiency is high. In the whole process of corn production, 11.195 million yuan of maize production value was optimized. The proper harvest time of corn was 5 days, the planting time of wheat was 26 days, and the harvest time of wheat was 10 days. Conclusion: The optimal allocation quantity of agricultural machinery system is calculated by lingo software, and the mathematical model is established by combining non-linear programming.

This paper proposes a multistage distribution network planning (DNP) method that considers multiple planning alternatives, the active management of distributed generation (DG) units and demand response in the context of active distribution networks (ADNs). Representative days are selected for the consideration of uncertainties related with load demand and renewable power generation, during the planning period. The proposed DNP method aims at minimising the net present value of the total investment and operational cost. The proposed DNP considers multiple planning alternatives, such as the reinforcement of existing substations and existing distribution lines, the installation of new distribution lines, and the installation of capacitors. Furthermore, the proposed DNP method incorporates the control capabilities of DG active and reactive power output and demand response schemes. A 24‐bus distribution network and a 144‐bus real world distribution network are used to validate the performance of the proposed method.

Implant placement necessitates an interdisciplinary approach in which a team of dental implant specialists, including an oral surgeon, prosthodontist, periodontist, and oral radiologist, collaborate on the design, execution, and maintenance of the implants to provide the best possible result. According to the data, the vast majority of the participating dentists provide implant-supported restorations to their patients on a regular basis. Surprisingly, the percentage of dentists who plan implant placement and employ backward planning methods was significantly lower. This finding implies that dentists do not always follow the current scientific consensus that the placement of an implant should be based on prosthetic principles.

Objective: Determination of the minimum time spent by a transit car with processing at the marshalling yard, identification of the optimal car flow in order to optimize the loading of the station’s technical devices. Methods: The description of interoperational downtime is carried out by the theory of queuing, simulation modeling is used to recreate technological processes at the marshalling yard. Results: As a result of the analysis of the average time spent by the car at the station, a model of the marshalling yard was built, taking into account the monthly irregularity of the flow of the processed flow. Practical importance: With the help of the obtained data, it is possible to improve the long-term planning of the work of the sortation system, to determine the optimal load of the station’s technical means. By changing the station’s constant parameters (the number of tracks) and variables (the number of maintenance crews, the number of shunting locomotives), it is possible to respond flexibly to the required development of the car traffic made by the station.

The article substantiates the need to identify trends in the development of processes demographic in individual countries and regions. The analysis of the determination of demographic processes is a necessary condition for the development of an effective demographic policy. The authors studied the dynamics of the population of the planet as whole, Europe, and Russia over the past 50 years. The assessment of the degree of influence of the measures taken in certain countries of the world on the demographic situation is given. The article deals with both methodological issues of studying the determination of demographic processes, and the results of research based on statistical information. Much attention is paid to the issues of determining the birth rate and mortality. An assessment of the impact of material payments on the birth rate is given. At the same time, the issues of determining migration processes and population aging are not left without attention. To analyze the causes of population migration in the region, the experimental planning method was used. The use of this method allowed us to identify the factors that affect migration processes and to assess the degree of influence of each of them on the level of the migration efficiency coefficient. The study showed the possibility of using the planning method in the study of socio-economic processes. The authors consider three variants of the population forecast of the Russian Federation until 2035, proposed by Rosstat, and assessed possible options for their implementation.

Community Service Activities were carried out in Tegal Alur Village, Kalideres District, West Jakarta. The problem faced by partners is the lack of training that can open up profitable business opportunities for them. The implementation method is carried out starting with a site survey, followed by training and ending with activity analysis. The Lean Canvas planning method is used to get to the heart of the idea, putting all the information on one page, helping to define the main information needed, without unnecessary details. As a result of this training activity, housewives, Family Welfare Development mother (PKK), youth organizations and Micro, Small and Medium Enterprises (UMKM) in Tegal Alur Village, West Jakarta, can start a business by taking action step by step, so that their efforts can generate profits as expected. It can be concluded that this training is beneficial for the community and increases the desire to become entrepreneurs.

The development of new gas and gas condensate fields in a complex external geopolitical environment for the Russian Federation requires the development of methods for selecting the optimal modes for the operation of gas wells. The mathematical apparatus and computational algorithms, which allow, based on accumulated geological and field information, to calculate the long-term dynamics of the flow rates of gas producing wells under the conditions of using potentially possible operating modes are considered. Prediction of long-term dynamics of gas production well rates in practice is necessary for long-term planning of gas production, optimal distribution of productivity between the gas processing unit in the gas gathering network of the enterprise, and the formation of pre-design options for the development of gas deposits. In other words, planning methods based on the accumulated geological and production data of gas well operation modes are needed in order to select from a variety of possible technological modes of operation those that will ensure the optimization of the gas production plan in an unstable economic environment.

Research on planning, method choice, and method substitution in adolescents’ suicide attempts is limited. We conducted in-depth interviews with 20 adolescents following their suicide attempt to learn the extent to which the attempt was planned, why they used the method they did, and whether they would have substituted another method if the one they used had been unavailable. Applied Thematic Analysis was used to identify codes and develop themes. Attempts were largely unplanned, and planned attempts were often haphazard, as urgency to escape immediate pain was a main impetus for the attempt. Method choice was driven by easy access. Half of participants said they would not have attempted suicide if the method they used were inaccessible, but 7 of 20 said they would have, and 3 were unsure. Not all suicide attempts would be prevented by blocking access to methods that adolescent attempters would otherwise use. To understand whether restricting access to low-lethality methods could harm some attempters, future research should examine in-the-moment method substitution.

Resource-based cities generally have "high energy consumption, high carbon emissions, and high pollution". Exploring low-carbon planning of resource-based cities means great significance for promoting the low-carbon transformation and development of resource-based cities and achieving "carbon peak" and "carbon neutrality". Based on the two levels of city region and central city, the paper proposes a low-carbon planning method for resource-based cities from four aspects: industrial transformation, land use, road transportation and ecological environment. At the city region level, it is necessary to reasonably determine urban industrial structure and industrial development scale, and meanwhile, optimize the industrial layout by reasonably planning production, living and ecological space and formulating practical space control measures; coordinating the connection between external traffic and traffic system within the city; constructing a carbon sink network composed of green patches-ecological corridors-peripheral matrix. At the central city level, it is necessary to analyze gradient attributes of carbon emissions from different land types, rationally arrange various types of construction land; optimize the layout of urban residence and employment space; increase systematicness of road planning in central urban areas; give full play to the carbon sink role of ecological corridors. Finally, an empirical study is carried out with the case of Xingtai City. The research can provide theoretical basis and path reference for reducing carbon emissions of resource-based cities through spatial planning.

Generalized equivalent uniform dose (gEUD) -based hybrid objective functions are widely used in intensity modulated radiotherapy (IMRT). To improve its efficiency, a novel fuzzy logic guided inverse planning method was developed for the automatic parameters optimization of the gEUD-based radiotherapy optimization. Simple inference rules were formulated according to the knowledge of the treatment planner. Then they automatically and iteratively guide the parameters modification according to the percentage of deviation between the current dose and the prescribed dose. weighting factors and prescribed dose were automatically adjusted by developed fuzzy inference system (FIS). The performance of the FIS was tested on ten prostate cancer cases. Experimental results indicate that proposed automatic method can yield comparable or better plans than manual method. The fuzzy logic guided automatic inverse planning method of parameters optimization can significantly improve the efficiency of the method of manually adjusting parameters, and contributes to the development of fully automated planning.

State policy in the military sphere, defense and military construction is now aimed at creating modern mobile and combat-ready defense forces that will be respected in society and by foreign partners and international organizations, together with other state institutions will ensure comprehensive defense of Ukraine, protection of its sovereignty and territory integrity and inviolability. Numerous scientific publications substantiate various models and the need to increase the effectiveness of defense management in the current environment of managing defense planning processes, especially security, in order to achieve certain strategic goals of defense reform and bring these processes closer to standards adopted in NATO armies. The purpose of the article is to find effective approaches to the formation of a model for managing defense planning processes, bringing them closer to modern needs and the principles and standards adopted in the armies of developed NATO member states. Defense planning is carried out in order to ensure the state's defense capabilities by determining the priorities and directions of development of defense forces, their capabilities, armaments and military equipment, infrastructure, training of troops (forces), as well as developing appropriate concepts, programs and plans taking into account real and potential threats in military sphere and financial and economic capabilities of the state. It is carried out using the capability-based planning method, which aims to develop them in the long term. The defense planning process includes: capability planning; capacity development programming; budgeting and resource management; implementation of programs and plans. In order to qualitatively prepare and implement effective defense management for the management of defense planning processes, it is expedient to improve the methodology of this work in practice, to bring these processes closer to the principles and standards adopted in the armies of NATO member states.

In recent years, more manufacturing enterprises are building automated flexible production lines (AFPLs) to satisfy the dynamic and diversified demand. Currently, static planning methods can hardly...

This report describes a prosthetically-driven implant planning method, guided by the alignment procedures between the cone beam computed tomography, intraoral digital scans, and digitized maxillary and mandibular interim complete dentures using intraoral composite resin markers as a common reference. The markers were attached to the keratinized oral mucosa of the edentulous ridges using cyanoacrylate and kept in place during the digitizing procedures. The technique provides a simpler and more economical alternative to conventional prosthetically-driven static implant planning methods.

Rural planning plays an important role in rural industrial integration, but there are few researches on the planning methods of rural industrial integration in China at present. Therefore, learning from the successful experience of developed countries and combining with the current situation of rural economic and social development in China is an important means and basic idea to explore the rural planning method of guiding the integration of primary, secondary and tertiary production in rural areas in China.

The article discusses the contributes to the development of a new focus on the use of various mixtures of natural raw materials and waste in the construction materials industry as a strategically important direction for solving the environmental burden and recycling industrial waste with a feasibility study that improves the state of the environment. This problem is particularly relevant in the production of building materials used in environmentally distressed areas of the republic and in conditions of intense corrosion and erosion wear. The production of efficient building materials and products that meet the modern requirements of environmental friendliness, basic physical and mechanical characteristics, availability and cost is an important and not fully solved task in the field of construction and the construction materials industry. Analysis have been conducted on the current state of the local availability of perspective materials for high-quality composite construction materials, their chemical and mineralogical and granulometric properties have been studied, the influence of the granulometric composition of the basic properties of a composite material and features of the structure formation during heat treatment were studies; physical and mechanical properties of the obtained compositions were tested. Optimal compositions and technological schemes for the production of composite materials based on the use of technogenic waste, natural raw materials and their mixtures have been developed to ensure the production of high-quality construction products with specified thermomechanical properties.The optimization of compositions and properties of compositions was carried out using mathematical planning methods, which made it possible to predict changes in the properties of composite materials depending on the number, weight of the components and the size of the filler granules. Experimental batches of at least 3 main types of construction products were obtained.

Centralized methods of planning the use of N devices for the realization of operations on a set of M objects with the scheme of the elementary operation is "one object  k devices" are proposed. Methods include modifications for the following cases: 1) only the described scheme of elementary operation is applied ("rigid" requirement); 2) the named scheme is preferred, but there are possible options of reducing the specified (desired) maximum number k for individual operations ("soft" requirement). Methods suitable for multi-elements dynamic systems in real time of their operation. Under planning conditions, the device system and the set of objects are multi-element. Planning methods belong to the category of "fast" methods, which suitable for dynamic multi-element systems in real time of their operation. The verification of the methods is implemented for the generalized system and for the particular case of the satellite system of observation of orbital objects.

Nowadays, the daily forecast for employee losses becomes a major issue. Staff participation is an important issue for the organization, especially when professional technical staff and key people in the organization come from good positions. This leads to a loss of finances to replace skilled labor. Therefore, we use data from current and former employees to analyze common causes of employee access or influence. To avoid employment, we use several planning methods, namely: Decision Tree, Log-log of Backlog, SVM, KNN, Random Forest, Bayes Naive. To do this, we use the method to select employment information and analyze the results to avoid employee income. Companies need to anticipate employee incentives and contribute to economic growth by reducing manpower.

One cycle of chemotherapy does not eliminate all cancer cells, therefore it takes a repeated cycle (Williams, et al, 2016), so the guarantee the availability of chemotherapy drugs is needed. An effective drug requirement planning is required to ensure the availability of chemotherapy drug. This study was intended to determine the effectiveness of planning the need for chemotherapy drugs using the morbidity method on the availability of chemotherapy drugs in Dr. Ramelan Navy Hospital. This study was an observational study with a cross sectional study design. The instrument used in this study was the data collection sheet with data sources prescription sheets and sheets of chemotherapy drug reconstitution during 2015-2017. Descriptive data analysis and to determine effective planning methods using indicators of drug availability. The results showed that the planning of drug needs with the morbidity method can better guarantee the availability of chemotherapy drugs and can minimize drug shortages compared to the consumption method that has been done so far in Dr. Ramelan Navy Hosptal. So it can be concluded that in this study, the morbidity method is effective in meeting the needs of chemotherapy drugs.

In the Armed Forces of Ukraine, work continues to improve the efficiency of defense planning and management of defense resources. The algorithm of defense planning for the development of the Armed Forces of Ukraine, step by step, uses the results of the analysis of the experience of the leading countries of the world, which have moved from defense planning based on threats to defense planning, focused on the acquisition by troops (forces) of the capabilities necessary to fulfill the tasks assigned to them. The list of tasks of the Armed Forces of Ukraine is determined on the basis of probable scenarios of their use. One of the key points in the effective planning of the use of the Armed Forces according to the corresponding scenario is a real and reasonable determination of the amount of necessary defense resources (human, logistical, financial). At the present stage of transformation of the defense planning system to NATO standards, as well as the application of the planning method based on capabilities in the General Staff of the Armed Forces of Ukraine, it is necessary to improve the existing methodological approaches to determine the needs for defense resources for the use of the Armed Forces of Ukraine according to certain scenarios of their use. Also, an urgent task today is the need to assess the sufficiency of the real economic and temporary capabilities of the state to ensure the use of the Armed Forces for the scenarios of their use determined by it. The general algorithm for assessing the cost of defense resources for the use of the Armed Forces of Ukraine in conflicts of varying intensity should take into account the economic realities of the development of the country's national economy. In the article, the authors proposed their views on improving the existing approaches to calculating the amount of necessary defense resources, the procedure and content of assessing their cost according to the corresponding scenarios for the use of the Armed Forces in order to further assess the economic capabilities of the state to provide them. The main results of the article are the procedure for assessing the cost of fulfilling the tasks assigned to the Armed Forces of Ukraine and the cost of conducting hostilities of varying intensity, as well as the general algorithm for making calculations.

In order to ensure the machining effect, a flexible velocity planning method is generally adopted to make the motion parameters, such as speed, acceleration, and Jerk continuous. The longitudinal c...

This paper presents a phase planning method specially designed for coal deposits with nearly horizontal, bedded coal seams. The geology of this type of deposit is modeled into a column model, instead of a block model, to avoid coal-rock mixing in blocks. A nested pit generation algorithm is developed for producing a series of nested, least-strip ratio pits with a column model as its input. The algorithm completely overcomes the troublesome gap problem. Taking the least-strip ratio pits as possible phase states, a dynamic programming formulation is proposed to simultaneously optimize the number of phases, the phase-pits, and the ultimate pit, with an objective of maximizing the net present value. The merits and capability of the proposed method are demonstrated through a case study on a large coal deposit.

Maila Sari Brebes Nugget Company is one of the companies engaged in the food industry, in that its sales of Nugget products have a fluctuating volume of sales each month due to the lack of application of scientific forecasting planning methods, so forecasting techniques need to be applied by the company. This study aims to optimize the sales plan of Maila Sari Brebes Nugget, do the calculation between the Exponential Smoothing method and the Least Square method of the error value, can be used as an appropriate and effective method in accordance with the real sales data of Maila Sari Brebes. Using the Microsoft Excel 2010 application and POM-QM for Windows 5. Based on the results of the analysis that has been done that the Exponential Smoothing method α = 0.9 has a smaller difference with an average difference of 508.892833 and an average forecast error rate of 3.44% per month, compared to the Least Square method which has an average difference of 6064,772 and an average error rate of forecasters of 41.67% per month

This article presents demand response techniques for the participation of datacenters in smart electricity markets under the smart grid paradigm. The proposed approach includes a datacenter model based on empirical information to determine the power consumption of CPU-intensive and memory-intensive tasks. A negotiation approach between the datacenter and clients and a heuristic planning method for energy reduction optimization are proposed. The experimental evaluation is performed over realistic problem instances modeling different types of clients. Results indicate that the proposed approach is effective to provide appropriate demand response actions according to monetary incentives.

Vigorously developing new energy is an important measure to deal with the energy crisis and environmental degradation, but the volatility and randomness of its output have brought great challenges to the new energy consumption. In this paper, the maximum new energy consumption is taken as the objective function, and the power flow constraints, multi-energy source capacity constraints and electrical constraints are taken as the constraints. Based on the complex adaptive system theory, the minimum construction step size of new energy sources is taken as the agent for modeling, focusing on the coordination among multiple sources, adjusting the installed node position and capacities of various types of power sources to obtain the optimal layout of power sources for multi-energy power systems. Based on the actual meteorological and operational data of a regional power grid in Northwest China, the original power system is re-planned. The simulation results verify the effectiveness of the proposed planning method.

Background The aim of the study was to develop and assess a technique for the optimization of breast electronic tissue compensation (ECOMP) treatment plans based on the breast radius and separation. Materials and methods Ten ECOMP plans for 10 breast cancer patients delivered at our institute were collected for this work. Pre-treatment CT-simulation images were anonymized and input to a framework for estimation of the breast radius and separation for each axial slice. Optimal treatment fluence was estimated based on the breast radius and separation, and a total beam fluence map for both medial and lateral fields was generated. These maps were then imported into the Eclipse Treatment Planning System and used to calculate a dose distribution. The distribution was compared to the original treatment hand-optimized by a medical dosimetrist. An additional comparison was performed by generating plans assuming a single tissue penetration depth determined by averaging the breast radius and separation over the entire treatment volume. Comparisons between treatment plans used the dose homogeneity index (HI; lower number is better). Results HI was non-inferior between our algorithm (HI = 12.6) and the dosimetrist plans (HI = 9.9) (p-value > 0.05), and was superior than plans obtained using a single penetration depth (HI = 17.0) (p-value < 0.05) averaged over the 10 collected plans. Our semi-supervised algorithm takes approximately 20 seconds for treatment plan generation and runs with minimal user input, which compares favorably with the dosimetrist plans that can take up to 30 minutes of attention for full optimization. Conclusions This work indicates the potential clinical utility of a technique for the optimization of ECOMP breast treatments.

Рассматривается способ координации настроек локальных систем автоматического регулирования установок компенсации реактивной мощности (РМ) городской системы электроснабжения для достижения оптимального режима работы всей системы по критерию минимума потерь электрической энергии. На основе анализа базы данных автоматизированной системы коммерческого учета электроэнергии МУП «Воронежская горэлектросеть» за пять лет определено, что величина tg φ (коэффициент реактивной мощности) не соответствует нормируемым ГОСТом значениям и требует существенной корректировки для снижения потерь электрической энергии. Оптимальный режим управления рассматриваемой системой электроснабжения по месту подключения и величине реактивной мощности требуемых установок компенсации возможен при правильном соотношении выбранных критериев локальной и системной оптимизации режимов работы ГЭС. Определено, что для получения экономически обоснованного эффекта от оптимизации режима работы ГЭС по критерию достижения tg φ не более 0,35 необходима установка устройств компенсации РМ как минимум на 50% -70% всех параметров реактивной мощности узла нагрузки (РП) энергоемких потребителей. Кроме того, показана целесообразность использования при данном способе компенсации реактивной мощности регрессионного принципа автоматического управления, базирующегося на методе факторного планирования эксперимента. При наличии базы данных параметров городской системы электроснабжения возможно получить серию уравнений регрессии, являющихся основой для настроек локальной системы управления установок компенсации реактивной мощности, которые необходимо установить в основных узловых точках РП МУП «Воронежская горэлектросеть». Установлено, что сформированные на базе уравнений регрессии параметры для системы управления успешно могут быть интегрированы в современные цифровые микропроцессорные регуляторы установок компенсации реактивной мощности сложных систем электроснабжения This article discusses how to coordinate the settings of local automatic control systems of reactive power compensation plants of a city power supply system in order to achieve the optimal mode of operation of the entire system according to the criterion of minimum loss of electric energy. Based on the analysis of the database of the automated system of commercial accounting of electricity of Municipal Unitary Enterprise "Voronezh City Electric Network" for five years, it was determined that the value of tg φ (reactive power factor) does not correspond to the values normalized by GOST and requires significant adjustment to reduce electrical energy losses. The optimal control mode of the considered power supply system at the point of connection and the value of reactive power of the required compensation plants is possible with the correct ratio of the selected criteria of local and system optimization of the hydroelectric power station operation modes. It was determined that in order to obtain an economically justified effect from optimizing the mode of operation of the hydroelectric power station according to the criterion of tg φ reaching a maximum of 0.35, it is necessary to install RM compensation devices at least 50% -70% of all RP energy-intensive consumers. In addition, the utility of using the regression principle of automatic control c based on the factor planning method of the experiment in this reactive power compensation method is shown. At sufficiently low costs for collection, processing of statistical material and optimization calculations, it is possible to obtain a series of regression equations, on which the calculated part of the settings of the control system of reactive power compensation plants, which should be installed in the main nodes of the Voronezh City Electric Network, is based. It was found that the parameters generated on the basis of regression equations for the control system can be successfully integrated into modern digital microprocessor regulators of reactive power compensation plants of complex power supply systems

As a kind of flexible manufacturing system, the machining quality of a robotic belt grinding system is related to a variety of factors with strong time variation, which easily leads to process fluctuations and affects the final quality. Therefore, it is a great challenge to control the quality precisely during the whole grinding procedure. Focusing on this problem, an adaptive parameters adjustment and planning method for robotic belt grinding using the modified quality model is proposed in this paper. Firstly, the correlation analysis method of grinding parameters in time domain is presented based on an improved-Mahalanobis distance. The response surface methodology (RSM) is utilized to construct the quality prediction model, and furtherly the parameter sensitivity function, which can characterize the influence degree of different parameters on the grinding quality, is introduced to calculate the Mahalanobis distance for improving the accuracy of the correlation analysis method. Secondly, based on the correlation analysis, a conversion method from the old samples into the new samples space is presented using vector field smoothing algorithm (VFS), then the modified grinding quality model can be re-established adopting the new samples. Furtherly, taking the problem of poor robotic response rate into consideration, a multi-parameters collaborative planning method under the smoothness constraint is developed using particle swarm optimization (PSO) algorithm, which can avoid the parameter mutation and improve the process stability. Finally, belt grinding experiments on a curved surface were carried out based on the robotic grinding platform. The results show that the approach can improve the grinding shape accuracy, which verify the effectiveness of the proposed methods.

Critical interference error can be mostly resulted from illogical tool-path generations in the penetration and retraction segments of internal cylindrical thread helical milling. Therefore, a less interference tool-path planning method is proposed for the quarter revolution penetration and retraction trajectories in internal cylindrical thread helical milling. Firstly, the parametric expression of the complete tool path of internal cylindrical thread helical milling is established; after that, a definition of eccentricity parameter m is given to adjust the radius of the penetration and retraction trajectories, and Z-axis coordinate of any point on the tool path is defined as a function of the θ; thus, the planned penetration and retraction trajectories in internal cylindrical thread helical milling with the m are derived; finally, the proper eccentricity parameter m is decided to improve the machining accuracy of thread by exploring the influence of the m on the interference error. Taking the experimental of milling, an M20 × 1.5 thread using a φ8 × 1.5 cutter as one of the examples that indicate the maximum interference error of the planning method (m = 0.4) can be reduced by 30.93%, compared with the original trajectory, and can dramatically improve the precision of internal cylindrical thread helical milling.

Despite the large amount of research devoted to economic uncertainty, enterprises are still held hostage by unforeseen circumstances. This is facilitated by management focused on forecasting average revenue values, while the most serious consequences are caused by random fluctuations in sales. The focus of this study is a mathematical model of revenue under conditions of uncertainty in demand, which can be used to develop planning methods based on separation, deterministic and random components of sales.

Subject. The article investigates the program-targeted planning methodology, which is implemented in the Russian Federation and leading foreign countries, for high-tech industry development. Objectives. The aim is to identify the specifics of program-targeted planning for the development of high-tech industries, to shape programs and plans for innovative development in the Russian Federation and leading foreign countries. Methods. The study employs general scientific methods of systems analysis, including the statistical and logical analysis. Results. I reviewed methods of program-targeted planning, implemented by the world’s leading countries (the Russian Federation, United States of America, France, Great Britain, Netherlands, Norway, Japan, Canada), in the interests of the development of various high-tech sectors of the economy. The study established that the methodology of program-targeted management is an effective tool for resource allocation by various types of economic activities in accordance with national priorities. I developed proposals by priority areas for improving the methodology for program-targeted planning and management in the Russian Federation in modern economic conditions. Conclusions. The findings and presented proposals can be used to improve methods for program-targeted planning to develop high-tech sectors of the economy; to design various long-term programs and plans, reducing the risk of their implementation; to determine the ways and methods of sustainable socio-economic and innovative and technological development of the world's leading economies.

The field of musculoskeletal diagnostics and personalized medicine has undergone a revolutionary transformation due to a deeper understanding of skeletal biomechanics and due to technological advancements. Analogous to this transformation, our understanding of spinopelvic conditions has experienced a paradigm shift in terms of both static and dynamic changes in spinopelvic pathologies and enabled a more accurate delineation of the drivers of disability. The purpose of this review is to describe the standard and state of the art of preoperative diagnostic and planning methods for common spinopelvic pathologies and to discuss both the added clinical value and limitations. The rationale is to accelerate the accurate and timely diagnosis and as well as the efficient and safe preoperative workflow.

Objective To research and assess automatic volumetric modulated arc therapy (VMAT) planning methods for patients with intraocular cancer. Methods The mdaccAutoPlan system was added to the Pinnacle3 treatment planning system as a plug‐in. Automatic VMAT plans were generated for 10 patients diagnosed with intraocular cancer, and evaluated according to standard dose‐volume histogram parameters. Results The planning target volume of enrolled patients ranges from 14.24 to 50.69 cm3. Both planning methods lead to acceptable planning target volume target coverage with a V95 of 97.9 ± 1.4% and 96.4 ± 1.5% for manual and automatic plans (P = 0.03), respectively. Automatic planning lowered the dose delivered to the ipsilateral lens and optical nerves, but increased the dose to the brainstem compared with manual planning. Automatic planning significantly prolonged VMAT planning time (3.25 ± 0.53 h vs. 1.02 ± 0.69 h, P

The careful selection of the feedrate is necessary during the numerical control (NC) machining process, to prevent drive characteristics such as velocity, acceleration, and jerk of each axis from e...

تناول البحث دراسة الإمکانات الطبيعية والمادية للجزر النهرية في مدينة هيت کونها ابرز المظاهر الجيومورفولوجية في نهر الفرات من خلال الدراسة الميدانية والحقلية ، إذ اعتمدت الدراسة المنهجين الوصفي والتحليلي بالاعتماد على الأساليب التخطيطية لوضع سياسات تنموية لتطوير النشاط السياحي وفق مبادئ الاستدامة الحضرية لما تتمتع به منطقة الدراسة من مقومات سياحية مميزة إذا تم استثمارها بشکل علمي مدروس يمکن تحقيق تطور اقتصادي لمحافظة الانبار بشکل عام ولمدينة هيت بشکل خاص . The research dealt with studying the natural and material capabilities of river islands in the city of Heet as it is the most prominent geomorphological aspects in the Euphrates through field and field study, as the study adopted the descriptive and analytical approaches based on planning methods to develop development policies to develop tourism activity in accordance with the principles of urban sustainability for what the study area has Distinctive tourism assets, if invested scientifically, an economic development can be achieved in Anbar Governorate in general and the City of Heet in particular.

In the future integrated energy market, the traditional centralized planning method cannot solve the planning problem for multi-stakeholder integrated energy systems (MSIESs). To cope with this problem, this paper proposes a synchronously decentralized adaptive robust programming (SDARP) model for MSIESs based on the analytical target cascading (ATC) algorithm. In this model, different stakeholders are planned in parallel under the source-load uncertainties, aiming at minimizing the annual investment and operation costs and fully taking into account the interactive heating/cooling power transmitted by the district heating/cooling network. In each stakeholder, the column-and-constraint generation algorithm is used to address the robustness problems in the three-layer adaptive robust programming model. In addition, a tractable alternating optimization procedure is used to solve the non-convex SDARP model with finite convergence. Case studies verify the superiority and effectiveness of the SDARP method in dealing with the planning problem of MSIESs.