Anatomical Assessment of the Inferior Alveolar Canal and Anterior Loop and Measuring its Distance to Mental Foramen in Patients Referred to Radiology Clinics of Shiraz in 2017

Knowledge about inferior alveolar canal (IAC) position is very important in dental surgical procedures of the mandible. It has a close relation to mandibular molar teeth. Anatomic imaging of the mandibular canal prior to surgical procedures, such as implant placement and sagittal split osteotomy, is essential for the best result and minimal complications.Purpose: The aim of this study is to determine normal variations of the mandibular canal and mental foramen in a selected population.Material and methods: A total of 668 high qualities CBCT images of edentulous and dentate patients aged from 15 to 75 were evaluated. CBCT projections were analyzed in different planes (tangential, cross-sectional, and axial). Bifid mandibular canal, presence of anterior loop, the level of cortication and mental foramen variations were identified in cross-sectional and axial views.Result: 668 images, 238 males and 430 females, were evaluated. Statistical analysis did not show a significant correlation between prevalence of bifid mandibular canal, anterior loop and mental foramen in both sides with age and sex (p0.05). A significant relationship was seen between right mandibular canal cortication and age (p=0.003). Anterior loop was detected in 90.5% of cases, and its length was 3.34  while accessory mandibular canal was observed in 4.6% of patients only.Conclusion: This study showed that there are numerous anatomical variations of the mandibular canal, mental foramen and anterior loop. Dentists should be familiar with these variations in order to prevent treatment complications and success of mandibular related dental procedures

A Functional Approach To Enterprise-Based Service Design Integration

This thesis describes and justifies an overall framework for information technology-integrated service design termed Integrated Enterprise-based Service Design Activities (IESDA)

Diffusion and Quantum Well Intermixing

Diffusion or intermixing is the movement of particles through space. It primarily occurs in every form of matter because of thermal motion. Atom diffusion and intermixing can also happen in crystalline semiconductors whereby the atoms that are diffusing and intermixing move from one side of the lattice to the adjacent one in the crystal semiconductor. Atom diffusion, which may also involve defects (including native and dopant), is at the core of processing of semiconductors. The stages involved in semiconductor processing are growth, followed by post-growth, and then the construction stage comes last. The control of every aspect of diffusion is necessary to accomplish the required goals, therefore creating a need for knowing what diffuses at any point in time. This chapter will briefly summarize the techniques that are in existence and are used to create diffused quantum wells (QWs). Also, it will outline the examples of QW semiconductor lasers and light-emitting diode (LED) by the utilization of inter-diffusion techniques and give recent examples

Bankruptcy Prediction using Robust Machine Learning Model

The prediction of bankruptcy is the job of forecasting bankruptcy and different financial crisis measures for businesses. It is an enormous area in business and accounting. The significance of the field is partially attributed to its value for creditors and investors in determining the likelihood of business bankruptcy. A predictive model that combines different economic parameters that enable the financial status of a business to be foreseen is the purpose of predicting financial distress. There were various approaches in this area focused on predictive tests, statistical modeling (e.g. generalized linear models), and in addition, artificial intelligence (e.g. Neural Networks, SVM, Decision Trees). In this work, we record our remarks by designing, experimenting, and evaluating some of the classification models used in most cases i.e. Gradient Boosting, Decision Trees, Balanced Bagging, Random Forests, SVM, and Ada Boost which are applicable to expected bankruptcy. The bankruptcy data is collected from Polish firms, in which synthetic features are used to represent statistics of a higher order. The dataset has outliers and is imbalanced. Synthetic Minority Over-sampling Technique (SMOTE) is used to over-sample minority class labels and tackle the data imbalance issue. The feature selection technique is an important step in the preprocessing in which three techniques were applied i.e. PCA, Select Percentile, and Sequential Feature Selection. To evaluate the models, the results are compared using four matrices i.e. accuracy, F1-score, recall, root-mean-square error (RMSE). The simulation studies reveal that the Ada Boost classifier with SFS as a feature selection method is giving the better result of 98.7% in terms of accuracy

Improving The Service Design Process: Process Integration, Conflict Reduction And Customer Involvement

Service design is the science of creating service experiences based on the customer’s perspective, to make it useful, enjoyable and cost-effective for the customer. Although the field of service design is relatively new, it has been rapidly expanding in research and practice. Most researchers focus on the usefulness of the service, cost efficiency, meeting customers’ needs, or service strategy. However, all service elements can benefit from improving the service design process. Current service design processes are suffering a lack of integration of activities, conflicts in decision-making processes, and exclusion of practitioners’ methods. In prior research, information models were created to integrate the service design process across the enterprise. As an extension, this dissertation introduces Petri Nets to improve the service design process. Petri Nets provide a uniform environment for modeling, analysis, and design of discrete event systems. Petri Nets are used to develop a new service design process that enhances the multidisciplinary approach and includes the practitioner methods. Additionally, this dissertation uses the Lens Model to improve the decision-making mechanism. The Lens Model is to characterize decision-making policy in service design. Research shows that there is a conflict between the designer and the manager in service design decision-making. Single Lens Model systems are designed to capture the decision policy for the service designer and the service manager. A double Lens Model system is used to compare the perspectives. Finally, this research suggests a new role for the customer in the design by applying an Asset-Based approach. Asset-based System Engineering (ABSE) is a recently introduced concept that attempts to synthesize systems around their key assets and strengths. ABSE is developed with as an innovative approach that views customers as a primary asset. Customer integration in the design process is achieved through several new service design tools

Computer modeling and simulation to predict COVID-19 propagation patterns via factual cellular automata

Computer modelling and simulation methods are very important and play a critical role in the mitigation and response to the ongoing COVID-19 pandemic. In this study, we propose a computational modeling technique based on Cellular Automata (CA) with realistic proposed rules. The rules are designed to simulate the propagation of COVID-19 disease through a bounded area. Our proposed CA rules are novel in many respects. For on, the classification of neighbors to nearest neighbors and range of neighbors based on cellular layers is explained. Moreover, the concepts of time generation and access time are deployed for the first time to model the propagation of the disease over time in this work. Further details of the proposed model including the topology of the defined area, the initial states of the cells and four-layer transfer mechanism are explained as well. This work may be considered a criterion of spreading for COVID-19 from point source in a defined population area. The results of the proposed algorithm represent the percentage of the population whose infectious status is described by different cellular state objects after a defined generation time. The results are compared under different circumstances and analyzed equanimity

Monolithically Integrated Wavelength Tunable Laser Diode for Integrated Optic Surface Plasmon Resonance Sensing

In this work, we demonstrate an InGaAsP multiple quantum well tunable laser diode that amalgamates two gain sections with different bandgap energies. This is achieved using selective area intermixing of the multiple quantum wells, and impurity-free vacancy induced disordering. When different current combination is injected into each section, that leads to a laser wavelength peak whose position depends on the relative magnitudes of the two injected currents. The laser wavelength can be fine-tuned from 1538 nm to 1578 nm with relatively constant output power. The free spectral range FSR of the tunable laser found to be 0.25 nm. This tunable laser was launched into an optical surface plasmon resonance sensor head to provide an input light source for the SPR sensor. Using the tunable laser diode, we have demonstrated an optical surface plasmon resonance sensor head that is based on an inverted rib dielectric waveguide, in which the resonance wavelength of the surface plasmon excited at the gold metal-dielectric interface depends on the refractive index of the liquid in contact with it. The inverted-rib waveguide of the SPR sensor head is made of a layer of SU-8 polymer with a refractive index of 1.568. While the lower cladding layer consists of silicon oxynitride (SiOxNy) with a refractive index of 1.526. The top surface is coated with 20 nm of chromium followed by a 50 nm thick layer of gold or with 4 nm of titanium followed by a 25 nm thick layer of gold. The SPR sensor head was designed, to allow monitoring of analyte media with a refractive index, ranging from 1.43 to the 1.52. Using a set of reference liquids representing the analyte medium, the sensitivity of the SPR sensor was measured using the fabricated tunable laser, an optical spectrum analyzer, and a photodiode. It was found that with various calibrated sample liquids in contact with the gold metal, a sharp resonance dip in the transmission spectrum occurred, and its position shifted to a shorter wavelength when the refractive index of the sample liquids was increased. The average sensitivity of the SPR sensor devices was determined to be S = 334 nm/RIU

Improving power theft detection using efficient clustering and ensemble classification

One of the main concerns of power generation systems around the world is power theft. This research proposes a framework that merges clustering and classification together in order to power theft detection. Due to the fact that most datasets do not have abnormal samples or are few, we have added abnormal samples to the original datasets using artificial attacks to create balance in the datasets and increase the correct detection rate. We improved the crow search algorithm (CSA) and used the weight feature of Crows to improve performance of clustering phase. Also, to create balance between diversification and intensification, we calculated the awareness probability parameter (AP) dynamically at iterations of the algorithm. To evaluate the performance, we used the cross validation technique have used the stacking technique in its training phase. The results of extensive experiments on three reference datasets showed high performance to detect power theft. The evaluation results showed that if the data is collected correctly and sufficiently, this framework can effectively detect power theft in any actual power grid. Also, for new attacks, if their patterns can be detected from the data, it is easily possible to implement these types of attacks

High Frequency Battery Impedance Measurements for EMI Prediction

International audienceIn embedded applications which include power converters, the battery that provides the energy is a part of the EMI path. As conducted emissions generated by power converters spread into a large frequency band, the battery characterization should be extended to cover this range of frequencies. In this paper, a method to measure the battery impedance using an impedance analyzer is explained and applied to a cell-phone battery from 1MHz to 100MHz. In this frequency range, measurements show that the battery impedance is unrelated to the battery state of charge and that a model including just inductances and resistances matches very well with the measured behavior. The measured impedance is validated by predicting the frequency spectrum of the battery's voltage when feeding a switched-mode power converter. The converter switches at 1.2MHz and the related harmonics extend beyond 100MHz. The measured and predicted voltages match up to 80MHz

Using IP networks as a deviceless storage for future portable computers

In this paper we propose a generic architecture for a small powerful mobile computer that relies on network and its servers for majority of its activities. Since the network is located in middle of this architecture, we discuss the feasibility and capacity of using the network as a temporary dynamic storage in the form of cache for limited and frequently used data/.control data. However the node delivery and file system design for the proposed network storage is not in the scope of this paper. We show how the routing loop can be utilized to convert the network delay and processing power of the routers to a virtual storage capacity in the network by keeping data in the network in form of floating IP packets. We call this approach Data Storage Technique on IP Networks (DSTN). In satellite and wireless communications this storage can be referred to as deviceless storage. We formulate the potential storage capacity and discuss the parameters that affect the capacity. We validate the technique by comparing the results obtained from the mathematical model with the results obtained from OpNet Modeler simulation tool. Since this paper is a preliminary part of this research, we address the future direction of the research in the last section