Planning Methods Research Articles

A REVIEW STUDY ON ROLE OF CONTRACEPTIVES AND THEIR VARIOUS TYPES.

Contraception is the process used to stop unwanted pregnancy and control birth rate. Contraceptives reduces the chances of pregnancy after sexual intercourse. Contraceptives prevent pregnancies by interfering with the procedure of fertilization. Contraceptives reduces the chances of abortion by preventing unintended pregnancies on their partners, in which 842 million (44%) are modern using modern methods of Contraceptives are accessible in huge varieties and types . Numerous contraceptives are available, 790 million (42%) are traditional method users according the statistical data of 2019. The most common contraceptive techniques that are use of contraceptives are increasing day by day, 922 million of women of reproductive age used worldwide are female sterilization and male condoms, female sterilization are used in 219 million users (24%), male condoms are used in 189 million users (21%) according the data of 2019. The use of traditional methods and IUDs has reduced worldwide since 1994. According to WHO, The only form of birth control is a condom,that can prevent both unintended pregnancies and sexually transmitted diseases. The need of family planning is increased globally up to 77% from 2015 to 2020.. Over the past 20 years, the number of women using family planning methods has grown, rising from 900 million in 2020 to 2000 million. Use of modern contraceptive methods is also increased from 663 million to 851 million with the prevalence rate of 47.7% to 49.0%. Numerous contraceptive methods exist, including hormonal methods like CHC vaginal ring, CHC transdermal patch, and combination hormonal contraceptives. Progestin-only techniques include hormonal male contraceptives, progestin-only pills, DMPA injections, implants, and progestin-only IUDs. The other approach is non-hormonal and consists of vaginal pH modulators, barrier techniques like condoms, and copper IUDs. Traditional methods, such as the LAM method, the fertile cycle method, and the withdrawal approach, comprise the third type of contraception. Herbal contraceptives, which use a variety of herbs and plant preparations, are the fourth technique of birth control.

К совершенствованию технологии планирования транспортных процессов взаимодействия железнодорожных линий различных категорий

Purpose: increasing the efficiency of the transport network based on the developed balanced system of indicators for the interaction of railway lines of various categories. Methods: methods of control theory, system analysis, synthesis and mathematical modeling, theory of transport processes and systems, and transport planning methods are used. Results: a set of indicators that influence the interaction of railway lines of various categories is substantiated, based on a balanced system of indicators, which makes it possible to develop corrective measures to optimize the transportation process. Practical significance the implementation of the proposed solutions allows us to develop and specify a program to increase the efficiency of operation of low-intensity public railway lines and adjust scheduled transportation on these lines.

The Impact of Succession Planning on Enhancing Organizational Citizenship Behavior: A Field Study at Tikrit University

The study aims to determine the extent to which succession planning contributes to enhancing organizational citizenship behavior at Tikrit University. The research hypotheses were the availability of the dimensions of succession planning and the dimensions of organizational citizenship in the university under study, and the existence of significant correlations and influence between each succession planning and organizational citizenship behavior. The research community was identified with the teaching and administrative staff of Tikrit University, consisting of (280) people, and a survey was conducted on a random sample of them, numbering (158) individuals. All distributed questionnaires were retrieved with a recovery rate of 100%, while the questionnaires suitable for analysis were (120), representing (75.9%) of the total questionnaires returned. The data were analyzed and hypotheses were tested using the statistical analysis program SPSS V.26. The study reached a number of results, most notably: There is a high level of application of both succession planning and organizational citizenship behavior at Tikrit University. The results also showed that there is a positive and moderate significant correlation between succession planning and organizational citizenship behavior at the university under study. The results also showed a statistically significant effect of succession planning methods combined in enhancing organizational citizenship behavior at Tikrit University, which explains 29.5% of the changes in the dependent variable. In addition, there was a statistically significant positive effect for all dimensions of succession planning in enhancing organizational citizenship behavior at Tikrit University, where promotion was the most influential on organizational citizenship behavior, followed by job rotation, training, and finally job transfer.

Pregnancy outcomes in patients with kidney transplant-A retrospective snapshot

Pregnancy in renal transplantation is a sensitive issue since fertility improves shortly after transplantation and the prevalence of pregnancy-related complications in these patients are more in comparison to non-transplanted matched cohorts. Our study aimed at assessing the outcomes of pregnancy in our transplant patients. Methods: This study was designed as a questionnaire based retrospective cross-sectional study wherein the authors contacted all their patients who underwent kidney transplantation under our care and now being followed with us or 4 other hospitals. Results: Total of 20 females conceived unplanned, out of 130 females of child bearing age who underwent kidney transplant. single pregnancy ended up in elective abortion at 4th month after transplant, rest of the pregnancies were successful and uneventful. Conclusion: Fertility related issues should be included in the counselling of kidney transplant females for planned pregnancy. Successful outcome is quite possible. There is a critical need for comprehensive support systems, including counseling, education, and resources, to empower female kidney transplant recipients in their reproductive journeys and to address the gaps in understanding family planning and contraceptive methods in the post-transplant period.

Simulation-Based Hybrid Energy Storage Composite-Target Planning with Power Quality Improvements for Integrated Energy Systems in Large-Building Microgrids

In this paper, we present an optimization planning method for enhancing power quality in integrated energy systems in large-building microgrids by adjusting the sizing and deployment of hybrid energy storage systems. These integrated energy systems incorporate wind and solar power, natural gas supply, and interactions with electric vehicles and the main power grid. In the optimization planning method developed, the objectives of cost-effective and low-carbon operation, the lifecycle cost of hybrid energy storage, power quality improvements, and renewable energy utilization are targeted and coordinated by using utility fusion theory. Our planning method addresses multiple energy forms—cooling, heating, electricity, natural gas, and renewable energies—which are integrated through a combined cooling, heating, and power system and a natural gas turbine. The hybrid energy storage system incorporates batteries and compressed-air energy storage systems to handle fast and slow variations in power demand, respectively. A sensitivity matrix between the output power of the energy sources and the voltage is modeled by using the power flow method in DistFlow, reflecting the improvements in power quality and the respective constraints. The method proposed is validated by simulating various typical scenarios on the modified IEEE 13-node distribution network topology. The novelty of this paper lies in its focus on the application of integrated energy systems within large buildings and its approach to hybrid energy storage system planning in multiple dimensions, including making co-location and capacity sizing decisions. Other innovative aspects include the coordination of hybrid energy storage combinations, simultaneous siting and sizing decisions, lifecycle cost calculations, and optimization for power quality enhancement. As part of these design considerations, microgrid-related technologies are integrated with cutting-edge nearly zero-energy building designs, representing a pioneering attempt within this field. Our results indicate that this multi-objective, multi-dimensional, utility fusion-based optimization method for hybrid energy storage significantly enhances the economic efficiency and quality of the operation of integrated energy systems in large-building microgrids in building-level energy distribution planning.

Study on the planning and scheduling strategies of the hydrogen supply network for road transportation in deep decarbonization scenarios

As the energy decarbonization continues to advance, hydrogen is gaining momentum. With the increasing demand for hydrogen and the lack of hydrogen infrastructure, it is urgent to solve the problem of hydrogen supply network layout planning. In order to reduce redundant construction of hydrogen supply network infrastructure and increase the rationality of its layout, this paper conducts research on the optimal layout planning of hydrogen supply network infrastructure in the transportation sector. By constructing a two-stage real-time scheduling model of hydrogen supply network, the unit cost composition of hydrogen supply network is more complete and accurate, and the location, technology type and quantity of each link of hydrogen supply network are obtained. The results show that the unit cost of China's hydrogen supply network is 27.8 CNY/kg in 2035 and 19.04 CNY/kg in 2050 under the baseline scenario. Compared with the results of existing literature, the two-stage real-time scheduling model can reduce by 7 % of the hydrogen energy supply network unit cost by decreasing the transportation vehicles and the investment capacity of fixed hydrogen storage equipment. The proposed method of the hydrogen supply network planning can provide policy-makers with the selection of sustainability pathways for dynamic hydrogen infrastructure development planning.

A Classification and Interpretation of Methodological Approaches to Pursue Natural Capital Valuation in Forest Research

This paper reviews natural capital (NC) valuation approaches in the context of woodland, forest, and riparian ecosystems, emphasising the need for participatory methods to take priority over neoclassical economics approaches. Focusing on research carried out in Scotland, the study analyses findings according to a classification of natural capital initiatives that we have developed, building on ideas proposed by the UK ENCA initiative, a guideline proposed to help researchers and practitioners understand NC and take it into account in valuation, decision-making and policy. We have found that landscape-scale initiatives that address the relationships between people and place to inform value and decision-making beyond the economic (monetary) benefits generated by ecosystem services (ES) are becoming popular. For instance, recent methods employed to capture stakeholders’ non-utilitarian preferences include the use of participatory GIS mapping, scenario planning, and other participatory methods to identify, explore and quantify less tangible cultural ecosystem services (CES). The review shows that many studies provide information relevant to the formulation of a place-based NC approach, working towards the integration of contextual and relational values into land management decisions to help formulate management strategies that maximise ES delivery. Conversely, we have not found evidence of the integration of shared values arising from an eco-centric perspective of nature valuation into the more classical, instrumental value lens. Such an approach would help inform broader, overarching aspects of woodland and forest management that may foster more effective conservation and help to manage conflicts.

An iterative learning-based integrated motion planning and control method for autonomous patrolling of unmanned surface vehicles

Abstract The minimization of maritime patrol durations and the optimization of patrol trajectories are still a prevailing challenge for autonomous navigation of unmanned surface vehicles (USVs). In this paper, we propose an integrated trajectory planning and control method to achieve time-optimal autonomous patrol of USVs by a data-efficient iterative learning-based predictive control algorithm. We build the optimization problem of the algorithm by introducing a local cost and a local safe constraint set for closed-loop efficient data-driven learning. To guarantee recursive feasibility, stability and convergence properties of the optimization algorithm at each iteration, the local cost and the local constraint set are designed and update iteratively using the historical vehicle states at previous iterations as a dataset. Different from traditional optimization methods, the proposed method does not require a reference path. The cost function of the optimization method decreases monotonically and converge to obtain a time-optimal control law for trajectory planning and tracking of USVs only after several iterations. The proposed approach is validated on the robotic operation system in typical maritime patrol scenarios. The results show that the proposed method implement a 5% reduction of patrol time, fewer lateral track errors, and smoother trajectories compared to the traditional MPC algorithm under water flow conditions. In addition, Enhancements in patrol operation efficiency of USVs are achieved by the algorithm, even under the constraints of varied patrol paths, attesting to its versatility.

The effect of manganese and carbon on the mechanical properties of the welded layer of the bucket teeth of the Hadfield steel excavator

The paper investigates the effect of the surfacing composition’s chemical structure (the manganese and carbon concentrations’ ratio) on the mechanical properties of the surfacing layer on Hadfield steel for increasing the durability of the products made from it, namely the excavator bucket’s teeth. Two criteria, namely the impact toughness and wear resistance of the coating, were chosen as optimization parameters. The assessment of the impact strength of the deposited coating was carried out on the Sharpie samples on the pendulum copra, and the wear test was carried out according to the Brinly-Haworth scheme in the conditions of samples’ abrasion with quartz sand. Wear resistance of Hadfield steel, containing 1.1% C and 13% Mn, was taken as a unit of wear resistance in these experiments. To determine the optimal coating modes, the active experiment with the application of mathematical planning methods was conducted. The obtained response surfaces and graphs of equal output lines make it possible to establish the level of studied factors’ influence on the optimization parameter. In order to analyze the influence of given factors on the optimization criteria, scatter plots with histograms were constructed, which make it possible to determine the rational values ​​of the selected optimization criteria graphically - impact toughness and wear resistance of the coating

Enhanced Synthesis of Poly(1,4-butanediol itaconate) via Box–Behnken Design Optimization

At present, there are too few organ and tissue donors. Due to the needs of the medical market, scientists are seeking new solutions. Those can be found in tissue engineering by synthesizing synthetic cell scaffolds. We have decided to synthesize a potential UV-crosslinked bio-ink for 3D printing, poly(1,4-butanediol itaconate), in response to emerging needs. Diol polyesters are commonly investigated for their use in tissue engineering. However, itaconic acid makes it possible to post-modify the obtained polymer via UV-crosslinking. This work aims to optimize the synthesis of poly(1,4-butanediol itaconate) in the presence of a catalyst, zinc acetate, without using any toxic reactant. The experiments used itaconic acid and 1,4-butanediol using the Box–Behnken mathematical planning method. The input variables were the amount of the catalyst used, as well as the time and temperature of the synthesis. The optimized output variables were the percentage conversion of carboxyl groups, the percentage of unreacted C=C bonds, and the product’s visual and viscosity analysis. The significance of the varying synthesis parameters was determined in each statistical model. The optimum conditions were as follows: amount of catalyst 0.3%nCOOH, reaction time 4 h, and temperature 150 °C. The temperature had the most significant impact on the product characteristics, mainly due to side reactions. Experimentally developed models of the polymerization process enable the effective synthesis of a polymer “tailor-made” for a specific application.

Research on Public Space Interior Environmental Planning and Design Method Based on BIM Topological Relationships

With the wide application of building information modeling (BIM) technology in the field of architectural design, this study aims to explore the planning and design method of public space internal environment based on BIM topological relationship. Through in-depth analysis of the data structure and spatial topological relationships of BIM models, this study proposes a public space design framework that combines user needs and environmental standards. Collect and convert relevant data of public spaces into BIM models, use BIM technology to establish detailed models of spatial elements and their topological relationships, combine spatial connectivity, line of sight, and flow simulation analysis, and consider key factors such as spatial layout, lighting, and ventilation. Realize the planning and design of indoor environments in public spaces. The experimental results indicate that the method can effectively improve the quality of public space design and promote the sustainable development of the environment. This study not only highlights the application potential of BIM in public space design, but also provides a new design methodology for the internal environmental planning of public space.

Thermal management for the prismatic lithium-ion battery pack by immersion cooling with Fluorinated liquid

This study constructs a novel FS49-based battery thermal management system (BTMS), proposing an optimization method for the system energy density and an indirect control method for the system cooling capacity. The boiling of dielectric refrigerant occurred at the battery surface, which provided strong and uniform cooling for each battery cell. The results show that the peak temperature difference of liquid immersion cooling (LIC) module during 1C rate discharging and charging was reduced by 91.3% and 94.44%, respectively, compared to the natural convection (NC) module. The reduction of temperature nonuniformity greatly reduced the state of charge (SOC) inhomogeneity of different cells within the module. Moreover, the energy density of LIC module can be optimized by reducing the cell spacing and liquid filling ratio. Comparing with 100% filling rate, the module maximum temperature corresponding to 25% filling rate (with wick) during 2C rate discharging is only increased by 1.6℃, however, the module peak temperature difference is reduced by 53.3%, and the energy density is increased by 13.14%. In addition, Equivalent circuit model (ECM) and volume of fluid (VOF) model were used to simulate the LIC module, and the numerical results are in good agreement with the experimental data. This study provides a systematic design plan and numerical method for the engineering application of LIC in the field of BTMS.

Priority of competencies in the professional activities of general practitioners (family doctors)

The functional responsibilities of general practitioners (family doctors) (GPs) have changed significantly over the past decade. The number of GP functions has expanded. Despite the increasingly complex professional activities of GPs, there is no scientific evidence for the qualification characteristics of GPs expressed in knowledge, skills, abilities, and competencies in the theory and practice in training. In this regard, a study was conducted to determine the priority of GP competencies that make up the qualification characteristics of a specialist. Aim. To analyze, generalize and rationale the research results, as well as to develop preliminary guidelines for GP training. Material and methods. The information base for the study was the results of ranking competencies according to their importance in the professional activities of GPs in Russia. It was obtained during the ascertaining experiment, implemented using the Delphi method as a method of expert assessment and strategic planning of training specialists. Conclusion. The analysis of competencies developed and agreed upon by experts showed its compliance with the job functions of GPs, the requirements of the Federal State Educational Standard for the General Medical Practice (Family Medicine) and the WONCA guidelines. A summary of the study results to determine the priority of competence in GP activities showed the following: — all competencies (25) were defined as necessary and constitutive of GP qualification; — 21 competencies were considered significant and highly significant for GPs; — 4 competencies were considered as of moderate significance and below moderate significance. The analysis of the priority of competences revealed insufficient methodological support for GP training in accordance with the social order. The results obtained showed the need to continue the study within the project "Quality Management of Training of General Practitioners (Family Doctors)".

Research on Path Planning for Industrial Cleaning Robots in Complex Environments: An Enhanced Immunogenetic Algorithm Approach

As industrial automation advances, cleaning robots in complex environments have demonstrated significant value in enhancing efficiency and reducing labor costs. This paper presents a path planning method based on an improved Immune Genetic Algorithm (IGA) for comprehensive coverage path planning in complex industrial settings. Initially, the Boustrophedon Cellular Decomposition (BCD) method is employed to effectively segment the complex scene, identifying key areas for cleaning tasks. Subsequently, the path planning efficiency and adaptability are enhanced through an optimized genetic algorithm that integrates immune memory, Inver-Over operators, and 3-opt operators to refine the traversal sequence between regions. Moreover, this study incorporates the A* algorithm and the Biologically Inspired Neural Network (BINN) algorithm for efficient inter-regional path transitions and precise intra-regional traversal, respectively. A series of simulation experiments validate the superiority of the proposed algorithm in terms of path length, coverage rate, and computational time. The results demonstrate that this method not only effectively addresses the challenges of path planning in complex industrial environments but also significantly improves cleaning efficiency, offering high practical value and potential for broader application.

AN EXPERIMENTAL INVESTIGATION ON EFFECT OF CONCRETE BY USING PARTIAL REPLACEMENT OF EGG SHELL POWDER IN CEMENT ALONG WITH E-WASTE AS COARSE AGGREGATE

The imagination of a world without concrete isimpossible. It is a soul of infrastructures. Concrete is necessary to gain strength in structures. Conventional concrete, which is the mixture of cement, fine aggregate, coarse aggregate and water, needs curing to achieve strength. Concrete is a counterfeit material in which the totals both fine and coarse are reinforced together by the bond when blended with water. The solid has turned out to be so prominent and essential in view of its natural, concrete acquired an upheaval uses of cement. Concrete has boundless open doors for creative applications, plan and development methods. Its extraordinary adaptability and relative economy in filling extensive variety of necessities has made it is exceptionally focused building material. This project focuses on concrete, keeping importance to this, an attempt has been made to develop strength in concrete incorporating recycling waste. As part of the project cement partially replaced with egg shall powder and e- waste as coarse aggregate Comparative studies were carried out for compressive strength, tensile strength and flexural test for conventional and material concrete mixture introducing new recycling materials

An adaptive operation planning and EBO-BPNN optimization method for decision support systems

Formulating a course of action (COA) before a combat is crucial for operational command. Research in command and control (C2) artificial intelligence is currently focused on using intelligent auxiliary decision-making methods to implement COA. This paper proposes a COA planning method based on line of operation (LOO) and uses planning domain definition language (PDDL) to describe combat scenarios and COA. Following the effect-based optimization (EBO) principle, an effect evaluation model for COA was constructed, and dynamic bayesian networks (DBNs) was used to determine the reasoning and calculate the results of the effect evaluation network. To further improve the execution efficiency of the effect evaluation model in practical applications, the network was optimized through a back propagation neural network (BPNN). Relevant experiments based on the coordinated distributed air defense and anti-missile scenario were carried out using the LOO model to complete the planning of COA. A BPNN evaluation model based on the DBNs evaluation model was built. After training and fine-tuning, it achieved similar evaluation results, with a mean absolute percentage error (MAPE) of less than 0.02%. Compared with the DBNs model, the BPNN model achieved an efficiency improvement of no less than 65%, effectively reducing the consumption of computing resources. This research is the first time to realize the modeled description of COA planning, automatic evaluation, and calculation optimization of COA effects. It can support the development of decision support systems (DSS) and has the potential for practical application.

Knowledge hierarchy-based dynamic multi-objective optimization method for AUV path planning in cooperative search missions

This study focuses on path planning for Autonomous Underwater Vehicles (AUVs) in underwater cooperative search missions. The complexities of the ocean environment, the uncertainty of target movements, and limited communication capabilities render underwater cooperative search missions dynamic multi-objective optimization challenges. Studies focusing on communication-constrained search strategies still lack reliable metrics for assessing underwater communication quality and do not consider communication dead zones. Addressing these deficiencies, this paper introduces a novel communication optimization strategy utilizing packet error rate as a metric for assessing communication efficacy, complemented by a potential field-based method for navigating out of communication dead zones. To tackle the inherently dynamic nature of cooperative search missions for mobile underwater targets, we propose a dynamic multi-objective optimization algorithm that employs a knowledge hierarchy strategy. This method enhances the NSGA-II algorithm's efficiency by extracting effective gene segments from historical Pareto solution set and generating a new initial population through recombination, hierarchy, and prediction. Distinct from other advanced dynamic multi-objective optimization approaches that are limited to theoretical problems, our approach is directly applicable to practical scenarios. The effectiveness and practicality of the proposed method are validated through a series of simulation experiments considering the impact of underwater acoustic communication. These results demonstrate that this research is not only innovative in theory but also holds significant engineering value and practical prospects in real-world applications.

An improved RRT behavioral planning method for robots based on PTM algorithm

For multi-dimensional high-order nonlinear systems with unstable path quality in parameter and extension terms, we developed a new fast search random tree strategy. First, we established a high-order Lipschitz vector field dynamic system to adapt to high-order systems of multi-degree-of-freedom robots, with the complex obstacle function being one of its key components. Secondly, we designed a classification gap filtering network layer (Classification LSTM) to screen training data models and ensure the global stability of data in path design. Additionally, the visual sensors deployed in the unit area effectively implement the path marking backtracking strategy and dead zone path simplification. Finally, three examples are provided to verify the effectiveness of this design method.

Multi-Robot Path Planning Algorithm for Collaborative Mapping under Communication Constraints

In extensive outdoor collaborative exploration tasks, multiple robots require efficient path planning methods to ensure rapid and comprehensive map construction. However, current collaborative mapping algorithms often integrate poorly with path planning, especially under limited communication conditions. Such conditions can complicate data exchange, leading to inefficiencies and missed areas in real-world environments. This paper introduces a path planning approach specifically designed for distributed collaborative mapping tasks, aimed at enhancing map completeness, mapping efficiency, and communication robustness under communication constraints. We frame the entire task as a k-Chinese Postman Problem (k-CPP) and optimize it using a genetic algorithm (GA). This method fully leverages topology maps to efficiently plan subpaths for multiple robots, ensuring thorough coverage of the mapping area without the need for prior navigation maps. Additionally, we incorporate communication constraints into our path planning to ensure stable data exchange among robots in environments with only short-range communication capabilities. Field experiment results highlight the superior performance of our method in terms of stability, efficiency, and robust inter-robot communication.

A Survey on Penetration Path Planning in Automated Penetration Testing

Penetration Testing (PT) is an effective proactive security technique that simulates hacker attacks to identify vulnerabilities in networks or systems. However, traditional PT relies on specialized experience and costs extraordinary time and effort. With the advancement of artificial intelligence technologies, automated PT has emerged as a promising solution, attracting attention from researchers increasingly. In automated PT, penetration path planning is a core task that involves selecting the optimal attack paths to maximize the overall efficiency and success rate of the testing process. Recent years have seen significant progress in the field of penetration path planning, with diverse methods being proposed. This survey aims to comprehensively examine and summarize the research findings in this domain. Our work first outlines the background and challenges of penetration path planning and establishes the framework for research methods. It then provides a detailed analysis of existing studies from three key aspects: penetration path planning models, penetration path planning methods, and simulation environments. Finally, this survey offers insights into the future development trends of penetration path planning in PT. This paper aims to provide comprehensive references for academia and industry, promoting further research and application of automated PT path planning methods.