Root Canal Anatomy of Maxillary and Mandibular Teeth

It is a common knowledge that a comprehensive understanding of the complexity of the internal anatomy of teeth is imperative to ensure successful root canal treatment. The significance of canal anatomy has been emphasized by studies demonstrating that variations in canal geometry before cleaning, shaping, and obturation procedures had a greater effect on the outcome than the techniques themselves. In recent years, significant technological advances for imaging teeth, such as CBCT and micro-CT, respectively, have been introduced. Their noninvasive nature allows to perform in vivo anatomical studies using large populations to address the influence of several variables such as ethnicity, aging, gender, and others, on the root canal anatomy, as well as to evaluate, quantitatively and/or qualitatively, specific and fine anatomical features of a tooth group. The purpose of this chapter is to summarize the morphological aspects of the root canal anatomy published in the literature of all groups of teeth and illustrate with three-dimensional images acquired from micro-CT technology.info:eu-repo/semantics/publishedVersio

Management Science Letters Solving a mixed-integer linear programming model for a multi-skilled project scheduling problem by simulated annealing

A multi-skilled project scheduling problem (MSPSP) has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP) with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a metaheuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time

Locating workstations in tandem automated guided vehicle systems

This paper presents a new solution framework to locate the workstations in the tandem automated guided vehicle (AGV) systems. So far, the research has focused on minimizing the total flow or minimizing the total AGV transitions in each zone. In this paper, we focus on minimizing total cumulative flow among workstations. This objective allocates workstations to an AGV route such that total waiting time of workstations to be supplied by the AGV is minimized. We develop a property which simplifies the available mathematical formulation of the problem. We also develop a heuristic algorithm for the problem. Computational results show that our heuristic could yield very high-quality solutions and in many cases optimal solutions. © 2010 Springer-Verlag London Limited

Solving a novel multi-skilled project scheduling model by scatter search

A multi-skilled project scheduling problem (MSPSP) has generally been presented to schedule information technology projects in deterministic conditions. The contribution of this model is to consider the resources, called staff members. These members are regarded as valuable, renewable, and discrete resources with different multiple skills. The different skills of staff members, as well as the project networks activity requirement of different skills, cause this problem to become a special type of multi-mode resource-constrained project scheduling problem (MM-RCPSP), with a huge number of modes. Taking into account the importance of this issue and the few studies performed on this problem, a novel mathematical model for the MSPSP is presented. Since the complexity of this problem is NP-hard, an efficient scatter search (SS) algorithm is developed to solve such a difficult problem. This proposed SS is capable of generating optimised solutions in small sizes, and the excellent solutions in large sizes are compared with the solutions reported by a proposed Tabu search (TS) algorithm

Solving a mixed-integer linear programming model for a multi-skilled project scheduling problem by simulated annealing

A multi-skilled project scheduling problem (MSPSP) has been generally presented to schedule a project with staff members as resources. Each activity in project network requires different skills and also staff members have different skills, too. This causes the MSPSP becomes a special type of a multi-mode resource-constrained project scheduling problem (MM-RCPSP) with a huge number of modes. Given the importance of this issue, in this paper, a mixed integer linear programming for the MSPSP is presented. Due to the complexity of the problem, a meta-heuristic algorithm is proposed in order to find near optimal solutions. To validate performance of the algorithm, results are compared against exact solutions solved by the LINGO solver. The results are promising and show that optimal or near-optimal solutions are derived for small instances and good solutions for larger instances in reasonable time

A fuzzy inference- fuzzy analytic hierarchy process-based clinical decision support system for diagnosis of heart diseases

© 2017 Elsevier Ltd Many organizations and institutions are implementing accurate and practical tools to accelerate decision-making process. In this regard, hospitals and healthcare centers are not exceptions, in particular, because they directly impact the health and well-being of the community. When it comes to disease diagnosis, practitioners may have different opinions, which lead to different decisions and actions. On the other hand, the amount of available information, even in a case of a typical disease is so vast that rapid and accurate decision-making may be difficult. For example, practitioners may prescribe several expensive tests in order to diagnose a heart disease whereas many of those tests might not even be required. Accordingly, a Clinical Decision Support System (CDSS) can be very helpful here. In particular, such a CDSS can be developed as an expert system for those patients who have a high likelihood of developing heart diseases. This study develops an expert system based on Fuzzy Analytic Hierarchy Process (AHP) and Fuzzy Inference System in order to evaluate the condition of patients who are being examined for heart diseases. The Fuzzy AHP is used to calculate weights for different criteria that impact developing heart diseases, and the Fuzzy Inference System is used to assess and evaluate the likelihood of developing heart diseases in a patient. The developed system has been implemented in a hospital in Tehran. The outcomes show efficiency and accuracy of the developed approach