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The purpose of this paper is to estimate the effects of onsite restaurant business volume on slot machine gaming volume at a Midwestern racino property. The results provide management with critical estimates for use in determining the overall value of the restaurant space. Additionally, operators are able to examine whether it makes sense to operate restaurants at a loss, based on the notion that the dining outlets are contributing to gaming volumes.

Time series multiple regression analysis is used to analyze daily performance data, providing an estimate of the change in the dollar amount of slot wagers resulting from a one‐unit increase in the dollar value of restaurant sales.

The theoretical model advanced herein explained 81 percent of the variation in the aggregate, daily dollar value of slot wagers. A one‐dollar increase in the variable representing overall restaurant sales produced a $91 increase in slot wagers (or $7.44 in slot win).

Regression analysis does not prove cause and effect. The result was produced from a single data set. Operators are encouraged to examine their own data via the method and model advanced herein.

The results provide management an opportunity to examine whether the slot win associated with the restaurant operations exceeds the operating losses incurred by the restaurants, and, if so, by how much.

This is the first study to examine empirically the relationship between restaurant and gaming business volumes at a racino. Specifically, no published study includes statistically derived estimates of the impact of changes in on‐site restaurant volume on a racino's slot wagering volume.

Recognition of machining features is an essential step in the development of efficient‐automated process plans from solid modeling data. This process represents the effective interpretation of the geometric data in a computer‐aided design (CAD) model to create semantically rich manufacture‐oriented features such as holes, slots, pockets, and others that may be exploited in downstream computer‐aided manufacturing/computer‐aided process planning applications. Most successful approaches towards feature recognition have been based on hint‐based procedures operating on a 3D B‐Rep model. The purpose of this paper is to propose an approach by which features are identified in a solid model that is built mainly using sweep solid modeling operations.

Part geometric model is queried for both 2D and 3D geometric elements. Feature hints are generated by an analysis of sweep operations and their 2D sketches, which are defined prior to building the solid model. These hints are then analyzed and validated by applying a two‐phase approach: 2D validation in the sketch geometry; and 3D validation in the final constructive solid geometry tree of the solid model. Valid hints are the basis for the creation of a machining feature model that can be input to a process planning module. In addition, interaction information for machining features is extracted from both 2D hints and their 3D validation. Feature interaction information is obtained by analysis of face/edge neighborhood and their geometric relations in both 2D and 3D spaces.

This approach provides a benefit of performing the majority of geometric analysis in 2D space which is much simpler and computationally more efficient than corresponding analyses in 3D space. Only minimal portion of the analysis is computed on 3D solid models. The approach is implemented in the Java‐based prototype system and is demonstrated and tested on several real‐world examples.

The initial prototype implementation is limited to prismatic parts and linear sweep. Only hole and slot feature can be recognized due to the fact that pocket recognition appears to be trivial.

Motivation for this approach is in the fact that sweep operations from 2D sketches are very commonly used in the mechanical design process, so the approach may be applicable in practical applications of CAD.

This novel approach provides value to product designers and manufacturing planners since linear (extrusion) and circular (rotation) sweeps are very popular design engineer tools.

Flights are often delayed owing to emergencies. This paper proposes a cooperative slot secondary assignment (CSSA) model based on a collaborative decision-making (CDM) mechanism, and the operation mode of flight waves designs an improved intelligent algorithm to solve the optimal flight plan and minimize the total delay of passenger time.

Taking passenger delays, transfer delays and flight cancellation delays into account comprehensively, the total delay time is minimized as the objective function. The model is verified by a linear solver and compared with the first come first service (FCFS) method to prove the effectiveness of the method. An improved adaptive partheno-genetic algorithm (IAPGA) using hierarchical serial number coding was designed, combining elite and roulette strategies to find pareto solutions.

Comparing and analyzing the experimental results of various scale examples, the optimization model in this paper is greatly optimized compared to the FCFS method in terms of total delay time, and the IAPGA algorithm is better than the algorithm before in terms of solution performance and solution set quality.

Based on the actual situation, this paper considers the operation mode of flight waves. In addition, the flight plan solved by the model can be guaranteed in terms of feasibility and effectiveness, which can provide airlines with reasonable decision-making opinions when reassigning slot resources.

Discusses the 27 papers in ISEF 1999 Proceedings on the subject of electromagnetisms. States the groups of papers cover such subjects within the discipline as: induction machines; reluctance motors; PM motors; transformers and reactors; and special problems and applications. Debates all of these in great detail and itemizes each with greater in‐depth discussion of the various technical applications and areas. Concludes that the recommendations made should be adhered to.

We investigate the relationship between airline network structure and airport congestion. More specifically, we study the ways in which airlines adjust capacity to delays depending on the network type they operate. We find some evidence suggesting that airlines operating hub-and-spoke structures react less to delays than airlines operating fully connected configurations. In particular, network airlines have incentives to keep frequency high even if this is at the expense of a greater congestion at their hub airports. We also show that airlines in slot-constrained airports seem to react to higher levels of congestion by using bigger aircraft at lower frequencies; thus, we conclude that conditioning the number of available slots on the levels of delays at the airport seems an effective measure that creates the right incentives for airlines to reduce the congestion they generate.

This study addresses the production optimization of a cellular manufacturing system (CMS) in magnetic production enterprises. Magnetic products and raw materials are more critical to transport than general products because the attraction or repulsion between magnetic poles can easily cause traffic jams. This study needs to address a method to promote the scheduling efficiency of the problem.

To address this problem, this study formulated a mixed-integer linear programming (MILP) model to describe the problem and proposed an auction and negotiation-based approach with a local search to solve it. Auction- and negotiation-based approaches can obtain feasible and high-quality solutions. A local search operator was proposed to optimize the feasible solutions using an improved conjunctive graph model.

Verification tests were performed on a series of numerical examples. The results demonstrated that the proposed auction and negotiation-based approach with a local search operator is better than existing solution methods for the problem identified. Statistical analysis of the experiment results using the Statistical Package for the Social Sciences (SPSS) software demonstrated that the proposed approach is efficient, stable and suitable for solving large-scale numerical instances.

An improved auction and negotiation-based approach was proposed; The conjunctive graph model was also improved to describe the problem of CMS with traffic jam constraint and build the local search operator; The authors’ proposed approach can get better solution than the existing algorithms by testing benchmark instances and real-world instances from enterprises.

Scheduling the airlift of relief supplies into a damaged or small airport during a crisis is complex yet crucial. The volume of cargo and flights can temporarily overwhelm the airport’s capacity and the mix of flights adds complexity. The purpose of this paper is to better characterize airport operations during a crisis, to develop a model that can assess strategies for scheduling flights and to draw implications for decision makers.

First, empirical data are analyzed to characterize airport operations. Previously unreported data from the 2010 Haiti earthquake response in the form of a “flight log” are analyzed to provide new insights and parameters. Alternate scheduling strategies are drawn from review of the literature and After Action Reports. Second, a queuing model is developed to understand operations in past crises and predict the impact of alternate scheduling strategies. Empirical data provide the parameters for airport scenarios evaluated.

Unloading capacity is seen to be the bottleneck but also to not be fully utilized, suggesting that a more aggressive flight schedule is needed. Scheduling flights is shown to be a tradeoff between volume of aid delivered and flights that must be diverted. The proper mix of aircraft and prioritized divert policies also provide benefits. Finally, it is beneficial, though perhaps counterintuitive, to create a parking buffer upstream from the unloading bottleneck.

Analysis of previously unreported data from the Haiti earthquake provides new insights regarding airport parking and unloading operations. A new model of airport scheduling for disaster response is proposed. The model differs from other humanitarian airlift models in that it focuses on aircraft parking and unloading. It differs from commercial aircraft scheduling and gate assignment in the objective used.

The purpose of this paper is to present analysis of an influence of rotor slots opening on self-excitation process, terminal voltage and performance characteristics of the single-phase self-excited induction generator (SPSEIG).

The paper presents field analysis of the self-excitation problem in the SPSEIG and performance characteristics on the base of two-dimensional field-circuit model of the generator.

The carried out field computations of the tested SPSEIG with closed rotor slots showed that only an initial voltage across the excitation capacitor of about nominal value (230 V) causes successful self-excitation of the generator. It was also proved that the suitable opening of the rotor slots, beside remnant flux density in the rotor core, facilitates self-excitation in the generator. Since in working applications initially charging of the capacitor to almost nominal voltage may cause a problem, therefore employment of semi-closed rotor slots in the SPSEIG would be proper solution.

The conducted simulations, validated by laboratory tests showed that not only suitable excitation capacitor capacitance and rotor speed are needed to obtain desired terminal voltage of the generator, but also suitable initial voltage across the capacitor in auxiliary stator winding is very important and necessary for reliable self-excitation of the single-phase induction generator with closed rotor slots. The employment of semi-closed rotor slots in the SPSEIG makes the self-excitation more effective.