Upper limb amputation is a condition that severely limits the amputee’s movement. Patients who have lost the use of one or more of their upper extremities have difficulty performing activities of daily living. To help improve the control of upper limb prosthesis with pattern recognition, non-invasive approaches (EEG and EMG signals) is proposed in this paper and are integrated with machine learning techniques to recognize the upper-limb motions of subjects. EMG and EEG signals are combined, and five features are utilized to classify seven hand movements such as (wrist flexion (WF), outward part of the wrist (WE), hand open (HO), hand close (HC), pronation (PRO), supination (SUP), and rest (RST)). Experiments demonstrate that usin

Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi me

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

Background: The adenomatoid odontogenic tumor is a relatively rare benign epithelial odontogenic tumor. It contains both epithelial and mesenchymal components. Few cases presented as an extrafollicular lesion or involve the mandible or associated with other odontogenic lesions. This paper represents a rare case of an extrafollicular AOT. Case presentation: A 24-year-old female had a painless swelling on the right side of the lower jaw since one-month duration. Intraorally there was a well defined fluctuant-blue swelling in the right alveolar premolar region measuring 1×2 cm obliterating the right lower buccal vestibule. Grade II mobility in the vital 44 and 45 teeth were observed. Panoramic radiographs showed a well-defined pear shaped

Ameloblastic fibroma is a rare benign tumor usually affects the first two decades of life. The neoplasm is more predominant in mandibular molar-premolar region and rarely affects the maxilla. In this report, we present a couple of Ameloblastic fibroma cases, affecting boys at their 1st decade. The lesions were presented as swellings of their maxilla, which is atypical location. Radiographic images showed well-defined radiolucency containing areas of radio-opacities and impacted teeth. Differential diagnosis was established as cystic/neoplastic conditions. The lesions were incised and histopathologically diagnosed as Ameloblastic fibroma, since they were composed of immature odontogenic mesenchymal and epithelial cells showing different c

Texture synthesis using genetic algorithms is one way; proposed in the previous research, to synthesis texture in a fast and easy way. In genetic texture synthesis algorithms ,the chromosome consist of random blocks selected manually by the user .However ,this method of selection is highly dependent on the experience of user .Hence, wrong selection of blocks will greatly affect the synthesized texture result. In this paper a new method is suggested for selecting the blocks automatically without the participation of user .The results show that this method of selection eliminates some blending caused from the previous manual method of selection.

Abstract                                                                                                            

Environmental data (whether pre-emptive or responsive perspect