Optimal Lifetime Research Articles

Balancing Long Lifetime and Satisfying Fairness in WBAN Using a Constrained Markov Decision Process

As an important part of the Internet of Things (IOT) and the special case of device-to-device (D2D) communication, wireless body area network (WBAN) gradually becomes the focus of attention. Since WBAN is a body-centered network, the energy of sensor nodes is strictly restrained since they are supplied by battery with limited power. In each data collection, only one sensor node is scheduled to transmit its measurements directly to the access point (AP) through the fading channel. We formulate the problem of dynamically choosing which sensor should communicate with the AP to maximize network lifetime under the constraint of fairness as a constrained markov decision process (CMDP). The optimal lifetime and optimal policy are obtained by Bellman equation in dynamic programming. The proposed algorithm defines the limiting performance in WBAN lifetime under different degrees of fairness constraints. Due to the defect of large implementation overhead in acquiring global channel state information (CSI), we put forward a distributed scheduling algorithm that adopts local CSI, which saves the network overhead and simplifies the algorithm. It was demonstrated via simulation that this scheduling algorithm can allocate time slot reasonably under different channel conditions to balance the performances of network lifetime and fairness.

Application the Renewal Theory to Determining the Models of the Optimal Lifetime for Conveyor Belts

Belt conveyance belongs to the continual transport systems characteristic with high-level conveying performances. Belt conveyors are of significant importance in the transportation of various types of materials in the industries like engineering, metallurgy and construction. The fundamental and the most expensive component of belt conveyors is the conveyor belt which is, during the operation on the belt conveyor, exposed to number of various loads that evoke the process of conveyor belt wear and damage. Lifetime of conveyor belts, which is the determining parameter for the belt conveyance economy and efficiency, is very important for the practice.Issues regarding the conveyor belt lifetime should be solved applying also the methods of operation analysis, especially the linear programming and the renewal theory that uses the theory of probability and mathematic statistics. The objective of our research was to determine the optimal lifetime (optimal performance duration) of a belt conveyor, applying the renewal theory, whereas the research was based on the cost approach of the renewal process.

Mathematical Model for Determining the Lifetime of Conveyor Belts Depending on some Selected Parameters

In the last years, belt conveyors belong to the most frequently used means of transport in various industries. The most important component of the belt conveyor is the conveyor belt. Therefore, it is necessary to pay more attention also to optimal lifetime of conveyor belts. Conveyor belt lifetime is a very complicated issue. It is affected by plenty of factors, including above all the quality structure of the belt conveyor, optimal construction, production, and properties of the conveyor belt as such, adequate solution of conveyance route shifting, reasonable maintenance, and quality repairs of conveyor belts. The paper deals with the exploring the lifetime of conveyor belts depending from on some selected parameters obtained from the operating records of practice (thickness of paint layer, width and length of the belt, conveyor speed and quantity of transported material) with using appropriate mathematical - statistical methods.

Discrete O2 sensors produced by a spotting method on polyolefin fabric substrates

New solid-state phosphorescent oxygen sensors produced by solvent spotting on hydrophilic polyolefin fabrics are described. The method comprises of a simple spotting of dye solution, followed by a short post-treatment of water washing and baking (<4h), resulting in sensors with uniform distribution of dye molecules in a discrete spot. The resulting sensors exhibited high brightness, optimal lifetime signals (27–31μs at 21kPa and 49–53μs at 0kPa O2), quasi-linear Stern–Volmer plots and temperature dependence. Compared to the commercial O2 sensors (PS coating on the micro porous support), the new polyolefin-based sensors performed well, showing good wettability and fast response time in liquid (3min for wetlaid and 7min for spunbond PP vs. 32min for the reference). The homogeneity of the sensors was confirmed by microscopic analysis using PLIM (phosphorescence lifetime imaging). Both sensors exhibit cross-sensitivity to humidity which is investigated in this paper through the use of confocal microscopy.

Feasibility and optimality of the initial capital stock in the Ramsey vintage capital model

Using a discrete-time version of the Ramsey Vintage Capital Model we provide a characterization of the set of initial capital stocks compatible with a predefined scrapping time, given the rate of technical progress and the level of capital productivity. Each profile of initial capital stock in that set generates a complete infinite horizon feasible capital path. From that characterization, we prove the existence of a minimum value for the scrapping time of the machines compatible with the rate of technological progress. Moreover, for each level of capital productivity, there exists an upper bound for the technological progress which allows the existence of feasible capital paths with full employment. Finally, we transform the infinite horizon dynamic programming problem into one of finite dimension. We use this to find the optimal lifetime for the machines as well as the optimal composition of the initial capital stocks. A numerical example shows that, in accordance with the infinite horizon approach to the problem, the increase in the rate of technological progress leads to a decrease in optimal scrapping time of capital goods.

The optimal lifetime of passenger cars based on minimization of CO2 emission

The paper's objective is to suggest a model for determining optimal lifetime of passenger car based on minimization of CO2 emission. The life cycle was modeled by eight main life cycle sequences. Combining the mathematical interpretations of the itch life cycle sequence is developed an optimization model. In this paper is suggested a new mathematical interpretation of following sequences: use, repair, distribution of passenger car and distribution of passenger car's parts. Comparison of the obtained numerical results was performed on examples for the data of new passenger car fleet from the EU14 countries. Special attention is given to analysis of dependencies between the optimal lifetime of passenger cars and Directive 2000/53/EC, trends of changing car weight, model year, kilometer driven and regulatory limit of the specific CO2 emission. The optimal lifetime in case where petrol car is replaced by diesel car was analyzed too.

Energy efficient networking via dynamic relay node selection in wireless networks

Mobile wireless ad hoc networks need to maximize their network lifetime (defined as the time until the first node runs out of energy). In the broadcast network lifetime problem, all nodes are sending broadcast traffic, and one asks for an assignment of transmit powers to nodes, and for sets of relay nodes so that the network lifetime is maximized. The selection of a dynamic relay set consisting of a single node (the ‘master’), can be regarded as a special case, providing lower bounds to the optimal lifetime in the general setting. This paper provides a preliminary analysis of such a ‘dynamic master selection’ algorithm, comparing relaying to direct routing.

JOINT ALPHARMA-BEEF SPECIES SYMPOSIUM: Considerations on puberty in replacement beef heifers1

Many important changes occur throughout reproductive development in beef heifers, including during the prenatal, early postnatal, and peripubertal periods. Wave-like patterns of follicular development have been observed in heifer calves as early as 2 wk of age. Some dramatic changes occur from about 2 to 5 mo of age, most notably the transient increase in LH secretion. Most components of the hypothalamic-pituitary-ovarian axis are fully competent by approximately 5 to 6 mo of age. Peripubertal changes include increases in LH secretion, estradiol production, follicular development, and reproductive tract size. Eventually, the process reaches the point that the initial ovulation is achieved. Heifers that reach puberty and experience multiple estrous cycles before the onset of their initial breeding season have a greater probability for early conception and optimal lifetime productivity. Attainment of puberty typically occurs at around 12 to 14 mo of age in beef heifers but varies greatly. Genetic differences and environmental factors contribute to this variation. In typical U.S. cow-calf operations, calves are generally weaned at approximately 200 d of age. The impact of postweaning management on age at puberty in heifers has been demonstrated, and there is considerable flexibility in the timing of gain from weaning to breeding. However, even when heifers are grown to the desired BW before the start of breeding, there remains a pronounced variation in the timing of puberty, which impacts pregnancy rates. Less attention has been focused on the impact of preweaning management on age at puberty. Heifer calves with increased growth rates from birth to weaning have reached puberty at earlier ages. Precocious puberty has also been induced in a majority of heifers with early weaning and feeding a high-concentrate diet. Nutritional control during early maturation in heifers exerts a substantial influence on the timing of puberty. Understanding the mechanisms involved in reproductive development increases our ability to effectively manage replacement beef heifers for optimal reproductive performance.

Platform replacement planning for management of product family obsolescence

In our rapidly changing world, existing technologies quickly obsolesce and new technologies continually emerge. While it is desirable that product platforms are designed for long life spans, state-of-the-art products cannot be developed on platforms with obsolete technologies. The purpose of this study is to develop a model to determine the optimal lifetime of platforms trading-off the cost efficiency of platform development and lost sales due to obsolete technologies. In order to predict sales revenue with respect to platform lifetime, a stochastic product introduction model is developed based on a diffusion model. A computational analysis is performed to reveals the influence of platform features and the market situation on the optimal lifetime and profitability of platforms. Furthermore, the economic value of retarding the speed of obsolescence is assessed in order to glean insights into the design of a robust or flexible platform.

Is Addiction a Failure of Rationality?

This note argues that addiction itself can be seen as a form of double failure, specifically the failure to stick to a predetermined optimal lifetime consumption path for an addictive commodity, which failure might be the result of bad luck, and the failure to adjust the level of consumption of the addictive commodity once the consumer is off their optimal path, which might be seen as a failure of judgment.

Risk-Based Approach for Optimum Maintenance of Bridges under Traffic and Earthquake Loads

Structures deteriorate as a result of material aging, aggressive environmental conditions, and increasing loads. During their lifetime, structures are also possibly exposed to some extreme events. The associated consequences of failure caused by progressive deterioration or extreme events can be devastating. Therefore, risk assessment and risk mitigation are necessary to keep structural performance within tolerable levels. This paper proposes an approach for assessing the time-dependent risks caused by traffic and earthquake loads and establishing the optimal preventive and essential maintenance strategies of bridges. The efficiency of the proposed approach is demonstrated using a highway bridge. Socioeconomic and environmental losses are investigated in a consequence-based framework. The vulnerability analysis under traffic loads is performed using time-dependent deterioration and traffic load models. The time-dependent failure probability for given earthquake loads is computed by comparing displacement ductility capacity and demand obtained via nonlinear dynamic analysis. The risks from 196 earthquake scenarios associated with four magnitudes and 49 earthquake strike locations are compared, and the highest one is selected as representative of the seismic risk. Based on the available maintenance options and the associated costs, the optimal lifetime essential/preventive maintenance strategies for total risk mitigation are developed.

On the design of an optimal non-linear tax/pension system with habit formation

We study the optimal tax/pension design in a two-period model where individuals differ in both productivity and discount rates or projection bias and where their utility of the retirement period consumption is not independent of the earlier standard of living. We consider both welfarist and paternalistic social objectives. The paternalistic government attempts to correct the projection bias by using a higher discount factor. We derive general mathematical expressions that characterize optimal tax/pension design (marginal tax/subsidy rates). They suggest that the pattern of marginal labor income taxes depends on habit formation. Negative marginal labor income tax rates are possible. To gain a better understanding, we examine numerically the properties of an optimal lifetime redistribution policy with habit formation. We find support for non-linear tax/pension program in which some types of individuals are taxed while some are subsidized. The effect of changes in the degree of habit formation is explored in the numerical simulations as well as the implications of different degrees of correlation between skill and projection bias.

Towards an optimal lifetime in heterogeneous surveillance wireless sensor networks

In this article, we study the coverage problem for heterogeneous wireless sensor networks where different targets need to be covered (sensed) by different types of wireless sensors running at possibly different sampling rates as well as different initial energy reserve. The objective is to maximize network lifetime while fulfilling diversified coverage constraints, i.e., different targets may require different sensing quality in terms of the number of transducers, sampling rate, sensing data rate, etc. The problem is particularly challenging since we need to consider both connectivity and routing requirements. To conquer this combinational complexity, we formulate a lifetime maximization problem, which is general and allows unprecedented diversity in coverage requirements, sampling rates, transmission energy consumption models, communication ranges, and target sensing ranges. Furthermore, to efficiently solve the optimization problem, we propose a column generation based approach, where a column corresponding to a feasible solution; our idea is to find a column with steepest ascent in lifetime, based on which we iteratively search for the solution of the maximum lifetime problem. To speed up the convergence rate, we generate an initial solution through a novel random selection algorithm. Through extensive simulations, we systematically study the effect of sampling rates, transmission energy consumption models, communication ranges, and sensing ranges on the lifetime. Several interesting insights have been revealed.

Energy substitutability and modernization of energy-consuming technologies

The paper examines long-term strategies of capital modernization under different assumptions about embodied technological change, energy regulation, and substitutability between energy and capital. To describe modernization of physical capital, the authors use a vintage capital model with the constant elasticity of substitution between capital and energy. The models take into account (i) availability of new more energy-efficient equipment under energy-saving technical progress, (ii) possibility of buying new capital with various combinations of energy parameters and prices, (iii) controlled scrapping of obsolete capital, and (iv) energy regulation quotas. The paper analyzes how the elasticity of substitution between capital and energy impacts the capital modernization policy. In particular, it is proven that the optimal lifetime of capital appears to be longer for a larger elasticity.

Innovation Design of Complex Equipment Based on the Multi-Granularity Structures

Innovation design is a process that makes it easily to satisfy individual customer demands. This study is aimed to realize the innovation design of complex equipment with better satisfaction to the individual customer needs. Firstly, the optimization mathematical model of innovation design was established. Secondly, structural repository of multi-granularity was developed to support innovation design. Finally, in the application of the design of hydro cylinder of injection molding equipment, we demonstrated that our method successfully generated new designs with optimal design lifetime.

Estimating Return Parameters with Short Historical Data: The Case of U.S. Treasury Inflation-Protected Securities

Academic research on consumption and portfolio choices over an individual’s life cycle has been flourishing for almost four decades. Since the seminal work of Merton (1969) and Samuelson (1969), economists’ models have supplied many asset allocations that would achieve optimal intertemporal consumption. Additional considerations on one’s labor decisions or unforeseen rare events have substantiated these models’ predictions and encouraged their implementation by industry practitioners. However, applications of even fairly complex models have quickly exposed the limitations and shortcomings of simplistic assumptions. For example, most models restrict the investment opportunity set to stocks and a riskless asset. Bonds, derivatives and housing are seldom included while other categories are dismissed altogether. Although some model specifications could easily allow for more financial alternatives, it is sometimes data availability (or lack thereof) that determines what variables are included. In this respect, Treasury Inflation-Protected Securities (TIPS) are challenging. The U.S. Government’s first issue was in 1997, long after TIPS were introduced in the U.K., Canada, Israel, Turkey and New Zealand. Naturally, data that span over only 15 years are of little use for the study of an individual’s optimal lifetime behavior: oftentimes, the planning horizon is set at age 90 or 100, with retirement starting at 65. Ultimately, the too recent history of TIPS returns has deterred fund managers from offering them as long-term/retirement assets and, in turn, has curbed their market reach. This project develops a rigorous methodology to estimate the real term structure of TIPS between 1970 and 1997. The resulting series is then merged with the actual data to produce a continuous series of real interest rates from 1970 until now. A summary description of our techniques and preliminary results is attached. The goodness of the newly obtained rates is tested by computing historical correlations with: Moody’s Seasoned AAA Corporate Bond Yield, the 30-Year Conventional Mortgage Rate, the OFHEO’s House Pricing Index, the Dow Jones Industrial Average Index and the S&P500 Index. We perform the exercise for all maturities (5, 10, 20 and 30 years). The outcome of this analysis is twofold. First, it provides practitioners with a reliable tool to better measure the risk-return tradeoff of portfolio strategies with TIPS. Second, it helps establishing guidelines that policy makers can use to choose qualified default investment alternatives (QDIA). Both dimensions offer fertile ground to financial experts who have long cheered TIPS as valuable retirement vehicles.

Optimal Division of Effort between Working and Learning Information About the Financial Market

This paper studies the investor's optimal lifetime working and financial-market investing effort-used strategy in a discrete-time consumption and investment model with wage incomes. The financial market contains a risk-free asset and a risky asset whose excess return (compared to risk-free asset) is not known. An investor is endowed with a fixed effort every period which can be used either to work harder to earn higher current and future wages, or to learn a more precise signal of the risky asset's excess return. The results show that the investor's optimal lifetime working effort strategy is hump-shaped: he works harder in the early part of his career life, but exerts more effort on learning information about the financial market later on; and the optimal risky asset investment has a peak near retirement.

Lifetime Maximization Routing Based on Genetic Algorithm for Wireless Sensor Networks

To prolong network lifetime, lifetime maximization routing based on genetic algorithm (GALMR) for wireless sensor networks is proposed. Energy consumption model and node transmission probability are used to calculate the total energy consumption of nodes in a data gathering cycle. Then, lifetime maximization routing is formulated as maximization optimization problem. The select, crosss, and mutation operations in genetic algorithm are used to find the optimal network lifetime and node transmission probability. Simulation results show that GALMR algorithm are convergence and can prolong network lifetime. Under certain conditions, GALMR outperforms PEDAP-PA, LET, Sum-w and Ratio-w algorithms.

Modeling U.S. Mortality and Risk-Cost Optimization on Life Expectancy

Human life expectancy has risen in most developed countries over several decades, causing observed demographic shifts. Many researchers have developed models to determine the expectancy of life at birth. Yet due to the complexity of the real-world mortality data, and recent global economy impacts, there is a great demand to search for new models to accurately predict the life expectancy, especially in the United States. In this paper, we focus on the analysis of mortality rate in the United States over a period of six decades (data from 1946 to 2005) with considerations of the six most common distribution functions in the mortality area. These functions are: Gompertz, Gompertz-Makeham, logistic, log logistic, loglog, and Weibull. Given complex mortality data, we develop models including algorithms to compute the mortality measures such as mortality rate, and then select the best function for predicting the life expectancy in the United States. The modeling results include life expectancy at birth, life expectancy at each age, mortality rate, and forecasting models. We also discuss a new risk-cost function with respect to life expectancy, and determine the optimal threshold lifetime level that maximizes the expected risk cost. Numerical examples are given to illustrate the expected risk-cost results. The proposed risk-cost optimization model, and the optimal lifetime threshold value can help the policy-decision makers of related healthcare organizations including insurance companies to carefully perform the tradeoff between the cost and benefits. This approach can affect both short term and long term related healthcare policies and plans. The results show that the logistic distribution uniquely out performs other distributions based on the mean square error criterion. We find that on average the life expectancy at birth in the United States in 2005 for both sexes, males, and females are 84.0, 81.9, and 84.6 years, respectively. This new result shows that the true life expectancy on average in the U.S. is significantly larger than in existing reports. Life expectancy obviously changes as one will get older. By late adulthood, a person's chances of living longer increase as is reflected by the life expectancy function. For example, although the life expectancy from birth in the United States in 2005 is 84.0 years, those who live to age 65 will have an average of 20.4 additional years left to live, making their life expectancy almost 85.4 years. Similarly, those who live to age 75 will gain an additional few years, making their life expectancy almost 87.6 years. On average, a child who will be born in the US in 2015 can expect to live 85.5 years, and in 2025 a child born can expect to live nearly 87 years.

Theoretical treatment of target coverage in wireless sensor networks

The target coverage is an important yet challenging problem in wireless sensor networks, especially when both coverage and energy constraints should be taken into account. Due to its nonlinear nature, previous studies of this problem have mainly focused on heuristic algorithms; the theoretical bound remains unknown. Moreover, the most popular method used in the previous literature, i.e., discretization of continuous time, has yet to be justified. This paper fills in these gaps with two theoretical results. The first one is a formal justification for the method. We use a simple example to illustrate the procedure of transforming a solution in time domain into a corresponding solution in the pattern domain with the same network lifetime and obtain two key observations. After that, we formally prove these two observations and use them as the basis to justify the method. The second result is an algorithm that can guarantee the network lifetime to be at least (1 - e) of the optimal network lifetime, where e can be made arbitrarily small depending on the required precision. The algorithm is based on the column generation (CG) theory, which decomposes the original problem into two sub-problems and iteratively solves them in a way that approaches the optimal solution. Moreover, we developed several constructive approaches to further optimize the algorithm. Numerical results verify the efficiency of our CG-based algorithm.