Background: This study aimed to determine the gender of a sample of Iraqi adults using the mesio-distal width of mandibular canines, inter-canine width and standard mandibular canine index, and to determine the percentage of dimorphism as an aid in forensic dentistry. Materials and methods: The sample included 200 sets of study models belong to 200 subjects (100 males and 100 females) with an age ranged between 17-23 years. The mesio-distal crown dimension was measured manually, from the contact points for the mandibular canines (both sides), in addition to the inter-canine width using digital vernier. Descriptive statistics were obtained for the measurements for both genders; paired sample t-test was used to evaluate the side difference of mandibular canines in both genders, independent samples t-test was performed to evaluate the gender difference in addition to the percentage of dimorphism and percentages of correctly classified and misclassified cases using the standard mandibular canine index. Results: The mesio-distal widths of the mandibular canines were non-significantly slightly larger in males than females, while the inter-canine width was larger in males than females with a high significant difference. The accuracy of genders determination using standard mandibular canine index was 32% for males, 59% for females and 45.5% for the combined sample. The percentages of dimorphism were 0.58% for the canine mesio-distal width, 3.99% for the inter-canine width and 3.85 for the mandibular canine index. Conclusions: The mandibular inter-canine width and mandibular canine index gave better percentage of dimorphism than the mesio-distal width of mandibular canines. On the other hand, standard mandibular canine index showed low accuracy for gender determination.
Background: This study aimed to assess the effect of tooth shape ratio on mandibular incisor arrangement. Materials and methods: The sample included dental casts of some dental students and orthodontic patients having Class I dental and skeletal patterns with normal occlusion and severe crowding. The sample was divided into two groups according to the severity of crowding into: group I had Class I normal occlusion with mild or no crowded mandibular dentition and group II had Class I malocclusion with severe crowded mandibular dentition. Each group comprising of 40 subjects (20 males and 20 females). The mesio-distal and facio-lingual crown diameters were measured manually for each cast using modified vernier caliper gauge. Descriptive sta
... Show MoreBackground: The prediction of changes in the mandibular third molar position and eruption is an important clinical concern because third molar retention may be beneficial for orthodontic anchorage. The aims of this study were to assess the mandibular third molar position by using medical CT scan and lateral reconstructed radiograph and evaluate gender differences. Materials and Methods: The sample of present study consisted of 39 patients (18 males and 21 females) with age range 11-15 years who were attending at Al-Suwayra General Hospital/ the Computerized Tomography department. The distance from anterior edge of ramus to distal surface of permanent mandibular second molar and mesio-distal width of developing mandibular third molar were
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a
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