Optimum Farm Plan for Higher Net Income in Southern and Eastern Dry Zone of Karnataka

The present study was focused on deriving an optimum farm plan which would enhance the farm income in different farming systems in Southern and Eastern dry zones of Karnataka. Data collected from 240 respondents selected using random sampling technique from two districts viz. Mandya and Kolar. The dominant farming systems identified in the study areas were crop + dairy, crop + sheep rearing, Crop + dairy + sericulture, and crop + dairy + horticulture. Linear programming technique was used to work out the maximum attainable return. In Mandya district, crop + sheep farming system were providing an annual income of ` 92468 per farm with the total expenditure of ` 175400, whereas, an optimal plan can fetch a return of ` 278810 per farm with the similar expenditure. In Kolar district, crop + dairy was giving annual income of ` 168216 per farm with the total expenditure of ` 150000 and through an optimum plan, a farmer could earn ` 327996 per farm. Mandya district In farming system with the component of crop + dairy + sericulture, farmers were realizing an annual income of ` 296433 per farm with the total expenditure of ` 274947, where optimization can provide the farmer an income of ` 640487 per farm with similar expenditure and this system is turned out to be most remunerative among all the farming systems

Dragline Stripping Method Review to Maximize Productivity and Coal Recovery at Major Fault Zone - A Case Study

Strategic mine planning is substantial to ensure maximum coal recovery across severely faulted geological conditions with predicted below water table excavation. An optimum plan would improve multiple engineering constraints to deliver high recovery with safety and best possible efficiency of machineries deployed at the problematic area. One such case is of Southern pit at Sasan coal mine, India with fault throw varying from 3m to 40m through a series of parallel merging faults located closely within strike length of 800m. It has challenged the mine for better coal recovery, machine performance and scheduled pit progression over recent corner strips. This paper describes how the mine has overcome complexities of operating in the fault area with localised consistent water seepage. It discusses new pre-strip parameters adopted to enhance dragline productivity, preparation of stable dragline operating bench under given bottom wet overburden conditions, and coal extraction plan which has been incorporated together with dragline stripping plan to improve recovery at the area of study. Several aspects of process have been highlighted during implementation, such as requirement of early dewatering setup for dragline low-wall stability and coal roof cleaning.

Measuring Outcomes in Healthcare Economics using Artificial Intelligence: with Application to Resource Allocation

The quality of service in healthcare is constantly challengedby outlier events such as pandemics and naturaldisasters. In most cases, such events lead to critical uncertaintiesin decision making, as well as in multiple medicaland economic aspects of a hospital. External (geographical)or internal factors (medical and managerial) at hospitals,lead to shifts in planning, budgeting, and confidencein conventional processes. In some cases, support fromother hospitals becomes inevitable. This manuscript presentsthree intelligent methods that provide data-drivenindicators to help healthcare managers organize their economicsand identify the most optimum plan for resourceallocation and sharing. Using reinforcement learning, geneticalgorithms, traveling salesman, and clustering, weexperimented with different healthcare variables and presentedtools and outcomes that could be applied at healthinstitutes. In this poster, initial experiments are performed;the results are recorded, evaluated, and illustrated.

Measuring outcomes in healthcare economics using Artificial Intelligence: With application to resource management

The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e., Covid-19) and natural disasters (such as hurricanes and earthquakes). In most cases, such events lead to critical uncertainties in decision-making, as well as in multiple medical and economic aspects at a hospital. External (geographic) or internal factors (medical and managerial) lead to shifts in planning and budgeting, but most importantly, reduce confidence in conventional processes. In some cases, support from other hospitals proves necessary, which exacerbates the planning aspect. This paper presents three data-driven methods that provide data-driven indicators to help healthcare managers organize their economics and identify the most optimum plan for resources allocation and sharing. Conventional decision-making methods fall short in recommending validated policies for managers. Using reinforcement learning, genetic algorithms, traveling salesman, and clustering, we experimented with different healthcare variables and presented tools and outcomes that could be applied at health institutes. Experiments are performed; the results are recorded, evaluated, and presented.

Reduction the impact of running system of sprinkling machine on the soil

Carried out researches have allowed to establish the optimum plan for the installation of sprinklers for sprinkling machine "Kuban-LK1M" (Cascade) and "CASCADE" in accordance with the applicable running systems and parameters of water conveyance pipeline, load-bearing capacity of the soil and the application rate.

Parameter Optimization for Computer Numerical Controlled Machining Using Fuzzy and Game Theory

Under the strict restrictions of international environmental regulations, how to reduce environmental hazards at the production stage has become an important issue in the practice of automated production. The precision computerized numerical-controlled (CNC) cutting process was chosen as an example of this, while tool wear and cutting noise were chosen as the research objectives of CNC cutting quality. The effects of quality optimizing were verified using the depth of cut, cutting speed, feed rate, and tool nose runoff as control parameters and actual cutting on a CNC lathe was performed. Further, the relationships between Fuzzy theory and control parameters as well as quality objectives were used to define semantic rules to perform fuzzy quantification. The quantified output value was introduced into game theory to carry out the multi-quality bargaining game. Through the statistics of strategic probability, the strategy with the highest total probability was selected to obtain the optimum plan of multi-quality and multi-strategy. Under the multi-quality optimum parameter combination, the tool wear and cutting noise, compared to the parameter combination recommended by the cutting manual, was reduced by 23% and 1%, respectively. This research can indeed ameliorate the multi-quality cutting problem. The results of the research provided the technicians with a set of all-purpose economic prospective parameter analysis methods in the manufacturing process to enhance the international competitiveness of the automated CNC industry.

Study The Influence of The Number of Beams on Radiotherapy Plans for The Hyopfractionated Treatment of Breast Cancer Using Biological Model

Purpose: To evaluate the biologic differences in treatment plans with different number of beams on 3D conformal radiotherapy for breast cancer patients, and compute the percent of probability to tumor control and complication of normal tissue probability using matlap program. Then determine the optimum plan through these values.

Triangular cyclic accelerated degradation zero-failure test plan

Purpose Zero-failure reliability testing aims at demonstrating whether the product has achieved the desired reliability target with zero failure and high confidence level at a given time. Incorporating accelerated degradation testing in zero-failure reliability demonstration test (RDT) facilitates early failure in high reliability items developed within short period of time to be able to survive in fiercely competitive market. The paper aims to discuss these issues. Design/methodology/approach The triangular cyclic stress uses one test chamber thus saving experimental cost. The parameters in model are estimated using maximum likelihood methods. The optimum plan consists in finding out optimum number of cycles, optimum specimens, optimum stress change point(s) and optimum stress rates. Findings The optimum plan consists in finding out optimum number of cycles, optimum specimens, optimum stress change point(s) and optimum stress rates by minimizing asymptotic variance of estimate of quantile of the lifetime distribution at use condition subject to the constraint that total testing or experimental cost does not exceed a pre-specified budget. Confidence intervals of the design parameters have been obtained and sensitivity analysis carried out. The results of sensitivity analysis show that the plan is robust to small deviations from the true values of baseline parameters. Originality/value For some highly reliable products, even accelerated life testing yields little failure data of units in a feasible amount of time. In such cases accelerated degradation testing is carried out, wherein the failure termed as soft failure is defined in terms of performance characteristic of the product exceeding its critical (threshold) value.

Linear Programming Problems: Determination of Optimal Value of Real Life Practical Problems

Nowadays mathematical method are widely applied in planning of natural economy, organization of industry control, business decision, transportation, engineering, telecommunications, elaboration of military operations etc. From the general point of view, the problems of control and planning are usually reduced to a choice of a certain system of numerical parameters or a function ensuring the most effective achievement of the preplanned aim (optimum plan) with the limited possible resources taken into account. To estimate the effectiveness of a plan, introduce the plan quantity index expressed in term of the plan characteristics and attaining the extremism value for an optimal plan. For the large number of practically interesting problems the objective function is expressed linearly in term of plan characteristics, the permissible values of the parameters also obeying linear equalities or inequalities.