Femoral neck anteversion is the torsion of the femoral head with reference to the distal femur. Conventional methods that use cross-sectional computed tomography (CT), magnetic resonance or ultrasound images to estimate femoral anteversion have met with several problems owing to the complex, three-dimensional (3D) structure of the femur. These problems include not only the difficulty of defining the direction of the femoral neck axis and condylar line but also the dependency upon patient positioning. In particular, the femoral neck axis, the direction of the femoral head, known as the major source of error, is difficult to determine from either a single or several two-dimensional (2D) cross-sectional images. A new method has been devised for the measurement of femoral anteversion using the 3D imaging technique. 3D reconstructed CT images from the femoral head and trochanter to the distal femur are used to measure the anteversion. It is necessary to remove the soft tissue from the CT images and extract just the bone part. Then, the femoral anteversion is measured from a computer-rendered femur image. The 3D imaging method is compared with both the conventional 2D method and the physical method using 20 dried femurs. For the physical method, which is used as a reference value, a special apparatus is devised. The average difference between the results of the physical method and those of the 2D CT method is 5.33 degrees. The average difference between the results of the physical method and those of the 3D imaging method is 0.45 degrees. Seventy-four patients, who suffer from toe-in-gait disease, are tested to compare the 3D imaging method with the conventional 2D CT method. The average difference between the 2D and 3D methods is 8.6 degrees, and the standard is 7.43 degrees. This method provides a very accurate and reliable measurement of femoral anteversion, as it is virtually equivalent to the direct measurement of bisected dried femur in vitro.

Femoral neck anteversion is the torsion of the femoral head with reference to the distal femur. Conventional methods that use cross-sectional computed tomography (CT), magnetic resonance or ultrasound images to estimate femoral anteversion have met with several problems owing to the complex three-dimensional (3D) structure of the femur. A 3D imaging method has been developed that virtually measures femoral anteversion on the 3D computer space with continuous CT slices; this 3D method provides more accurate and reliable results than conventional 2D CT measurements. A 3D modelling method is devised for the measurement of femoral neck anteversion. This method has advantages over the 3D imaging method, such as shorter processing time, reduced number of slices and an objective result compared with the 3D imaging method. The results of the 3D modelling method are compared with the conventional CT methods (2D CT method and 3D imaging method) using 20 dried femurs.

The e-plant chain is an extension of the integration beyond a production site by means of improved distribution management, electronic data interchange and coordination of multiple plants. The present paper proposes an advanced planning and scheduling model for the e-plant chain. The advanced planning and scheduling is the most important function when supporting flexible planning and scheduling in the e-plant chain. The problem is formulated as a mixed integerprogramming model. The model includes the main features of the system including flexible operations' sequences, resource requirements and alternative schedules. Since the problem is NP-hard, an intelligent search approach based on a genetic algorithm is developed. Numerical experiments show the proposed approach is satisfactory in its accuracy and efficiency. IntroductionIn the 1990s, advancements in technology and computing power spawned a new breed of planning concepts called advanced planning and scheduling (APS). APS includes a range of capabilities from finite-capacity planning at the plant floor level through constraint-based planning to the latest applications of advanced logic for supply chain planning and collaboration (Turbide 1998). The manufacturing environment might require resource capacity constraints, disjunctive constraints and precedence constraints. The resource capacity constraint stipulates that at any given time, the quantity of resources required or consumed cannot exceed the available amount. The disjunctive constraint keeps two activities from using the same unary constraint simultaneously. The precedence constraint restricts operations' sequences (Kolisch 2000, Kusiak 2000, Stadtler and Kilger 2002. Recent APS methods tend to take a holistic and collaborative approach to provide global optimization. This new business model is an attempt to optimize not only plant operations, but also all the activities from a supplier to a customer. This collaborative approach brings the idea of extending an e-plant chain beyond a production site. The e-plant chain, therefore, offers new potential to increase capacity flexibility to react timely to market demands and customer due dates (Beamon 1998, Lutz et al. 1999.APS models for the e-plant chain mainly focus on the following issues: (1) how to make a process plan considering the shop-floor status and the precedence constraints; (2) how to make efficient dynamic schedules considering multiplant dynamic situations and the complexity of the resource constraints; and (3) how

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We have investigated the electrical property of InGaN quantum dots (QDs) embedded in GaN layer using capacitance-voltage and deep-level transient spectroscopy (DLTS) measurements. The apparent activation energy was observed 0.43 eV below the conduction band edge of barrier layers in InGaN/GaN QDs system. The capture barrier height of InGaN QDs was measured more than about 0.17 eV, showing the existence of strain between QDs and barrier layers. Thus, the bound state of QDs was estimated as 0.26 eV apart from the conduction band edge of the GaN.