Efficiency optimization is a primary profitability strengthening driver for private companies (Banker et al., 1984). It also is a prerequisite for public organisations that have adopted the New Public Management concept (3Es: Efficiency, Effectiveness, and Economy). Although relative efficiency measurement is important in the strategic planning of an operational unit, a time lag of data availability exists (e.g., level and cost of resources engaged, level of outputs produced, and revenues obtained). For instance, companies’ balance-sheet reports are released a minimum of six months after the end of the fiscal year. Due to this delay, there is a financial and production data drain. This drain delays policymakers from finalising completed economic analyses and strategic plans for their organisation that take into account the decisions of its counterparts. As a result, during the ‘idle time’, only ceteris paribus analyses can be conducted in which the policymakers of just one player make crucial decisions for the operational unit regarding the peer units as inactive.
The SDEANN model applies a hybrid analysis based on the data envelopment analysis (DEA) method and the artificial neural networks (ANNs). The optimization forecasting model is generalized in order to be applicable to the existing sample units and to operational units that are not included in the dataset under evaluation. Generalization is achieved through the transformation of the ‘deterministic’ empirical production frontier, specified by DEA, into a stochastic production frontier by incorporating statistical noise in the dataset. Depending on the orientation of the analysis, different levels of noise added to the target inputs or outputs that are located in the production frontier help us to identify the appropriate level of noise, which is the level that does not distort the attributes of the original dataset (i.e. does not yield unacceptable input and output values).
The University recognizes that there may exist a range of temporary operational disruptions, such as those to public transportation that may interfere with an employee’s shortterm ability to commute to work. The purpose of this document is to outline a number of business contingency options available to Administrator’s in order to ensure that such interruptions minimize the impact to continuity of operations at the University.
For some applications, meso-scale models do not offer a satisfactory representation of the wind resource. Forecasting for wind farm applications, for instance, requires increased horizontal resolution for an adequate characterisation of terrain effects, unless the wind farm is situated in simple, flat terrain . Micro-scale models are therefore utilised to downscale meso-scale models for improved wind speed estimation. The modelling and forecasting of turbine-specific behaviour such as HWSS phenomena, in particular, requires accurate micro-scale wind speed profiles defined at the turbine level. A variety of techniques have been proposed for the downscaling process  - , and a novel methodology is presented in Chapter 3. The proposed downscaling model, however, is formulated as a supervised learning technique where measurements exist for the training of the model. For long termplanning studies such as siting analyses, reanalysis data is typically used as measurement data is not available. An alternative from the proposed model is therefore required for the meso to micro-scale downscaling of wind speed data.
In order to integrate strategies that reduce emissions into their daily operations, companies have begun to provide incentives for low carbon solutions. The most rigorous example of such a scheme is the environmental profit and loss accounting system of Puma Sports. Puma assumes that future green house gas emissions will eventually lead to increased costs of €66 per tonne . As a result, the company has committed to investing in low carbon solutions to the equivalent €66 per tonne of carbon saved. This approach will have a significant impact on the company’s long term strategic planning across sales, logistics and manufacturing. For example, if an innovative new method of working was to save 5,000 tonnes of ghg’s over its lifecycle compared to the current method then Puma have committed to invest €330,000 to implement this new methodology. Marks and Spencers have also confirmed that they have factored a cost of carbon into their future financial planning .
We modify the standard neoclassical growth model in that we allow preferences to exhibit two non-standard features. First, naïve individuals may discount hyperbolically rather than exponentially. They consider their future discount rates to be lower than the present one. However, when future arrives, they realize that their discount rate, then, is higher than planned. That is, hyperbolic discounting introduces time-inconsistency. Second, individuals exhibit a shortplanning horizon. That is, they are not planning from t
Prospective clinical trial to evaluate long-term toxicity and survival is initiated after the analysis presented. In the following study we are planning to investigate short-term and long-term toxicity, 3-year and 5-year survival and predictive value of different biomarkers for the patients treated with salvage HDR brachytherapy in case of local recurrence after primary prostate cancer radio- therapy.
However, despite the considerable contribution of the BSC and the interest it brings to enterprises, its limitations are numerous. The most important ones are: (1) part of BSC is not adapted to the operational level and is intended primarily for senior managers to provide a comprehensive view of performance (Ghalayini and Noble, 1996), (2) absence of a network orientation (Hibber, 2002), (3) it does not consider performance management and measurement within the perspective of the extended enterprise (Bititci et al, 2005).
In this paper, we describe a method and a fully implemented robotic system using conditional planning for generating and executing short-term interactions by a robot deployed in a public environment. To this end, the proposed method inte- grates and extends two components already successfully used for planning in robotics: ROSPlan and Petri Net Plans. The contributions of this paper are the problem deﬁnition of generating short-term interactions as a conditional planning problem and the description of a solution fully implemented on a real robot. The proposed method is based on the integra- tion between a contingent planner in ROSPlan and the Petri Net Plans execution framework, and it has been tested in dif- ferent scenarios where the robot interacted with hundreds of untrained users.
• Reactive planning is an active attempt to turn back the clock to the past. The past, no matter how bad, is preferable to the present. And definitely better than the future will be. The past is romanticized and there is a desire to return to the "good old days." These people seek to undo the change that has created the present, and they fear the future, which they attempt to
TCR’s leasing offer can be summed up in two words – flexibility and reliability. Whether your needs are for shortterm (leasing) or long term (operational leasing), for a single motorized or non-motorized GSE, or for an entire fleet, TCR stands ready to translate your needs quickly and easily into robust solutions.
Cyclic or periodic scheduling is concerned with steady state scheduling problems where the schedule is to be repeated over an infinite planning horizon. Cyclic schedules are typi- cally implemented in repetitive manufacturing environments like assembly lines in mass production where the primary re- quirement rates are sufficiently stable over time. The objec- tive usually consists in finding a cyclic schedule with mini- mum cycle time. The cycle time is equal to the time between the start of the first job in a cycle and the start of this job in the next cycle, and when the schedule is repeated infinitely many times, minimizing the cycle time is equivalent to max- imizing the throughput rate. Compared to an acyclic sched- ule, a cyclic schedule offers the advantage of an easier shop floor control. That is why in practice, cyclic schedules are sometimes even used as baseline schedules in build-to-order production, from which order-dependent acyclic schedules are obtained by allowing minor deviations (see Pinedo 2002, Sect. 16.2). An overview of cyclic scheduling problems and related complexity results is given by McCormick and Rao (1994).
MST has been identified as an evidence-based practice (EBP) for the treatment of youth criminal behavior, substance abuse and emotional disturbance, often preventing out-of-home placement Treatment is offered in the home and community Goals include separating youth from deviant peer units, improving school or vocational attendance and performance and developing natural supports for the family to preserve therapeutic gains Studies of MST programs show the following outcomes: reduced long-term rates of criminal offending in serious juvenile offenders, decreased recidivism, reduced rates of out-of-home placements for serious juvenile offenders, extensive improvements in family functioning, reduction of admissions to acute inpatient hospitals and decreased behavior and mental health problems for serious juvenile offenders In the Lehigh Valley, Community Solutions is the MST provider
Interestingly, however, there are no risky assets in the baseline NK model. The sole asset with which households can transfer wealth over time is a one period government bond, which carries neither default risk nor liquidity risk. 14 Moreover, since the policy rate is assumed to be the same as the government bond rate, government bonds carry no interest rate risk either. Consequently, neither do term premia nor any other form of risk premia appear in the baseline NK model. Evidently, this represents an oversim- plifying conjecture. By extending the model to include (default-free) long-term govern- ment bonds subject to interest rate risk, at least a positive term premium between short- and long-term government bonds should arise: If the future path of short-term interest rates is uncertain, interest rate risk emerges as rising discount rates cause a capital loss to investors whenever their desired investment period diverges from the maturity pro- ﬁle of the bond. By virtue of the Taylor-rule ⟨8.75⟩, short-term rates are indeed uncertain in the NK model, as they inherit the stochastic shocks to output, inﬂation, and mone- tary policy. Therefore, unless utility is linear in consumption, i.e. when E t U
We all want a bright financial future, but day-to-day financial realities can get in the way. Money issues can feel complicated and overwhelming. Important financial milestones may be years away, and truly important tasks such as earning an income, raising a family and pursuing a passion can keep us from thinking about and planning for the long term.
Bulletin C-10 "Derivative Financial Instruments and Hedging Operations" establishes that: "If the critical characteristics of the hedging instrument and of the primary position are equal (the notional amount, reference rates for payment and collection and the related bases, the effective term of the agreement, the date of price determination and payment, the dates of formal designation and liquidation, among others), then the changes in the fair value or in the cash flows attributable to the risk being hedged, these will be compensated completely at the beginning, during and until the expiry of the coverage, for which reason it will not be necessary to evaluate and measure the effectiveness thereof". Due to the foregoing, in the case of the financial derivative instruments for hedging purposes and when said characteristics are met, the effectiveness of said derivatives is not evaluated and measured.